Citation

## Material Information

Title:
Chemical engineering education
Alternate Title:
CEE
Abbreviated Title:
Chem. eng. educ.
Creator:
American Society for Engineering Education -- Chemical Engineering Division
Publisher:
Chemical Engineering Division, American Society for Engineering Education
Publication Date:
Frequency:
Quarterly[1962-]
Annual[ FORMER 1960-1961]
Language:
English
Physical Description:
v. : ill. ; 22-28 cm.

## Subjects

Subjects / Keywords:
Chemical engineering -- Study and teaching -- Periodicals ( lcsh )

## Notes

Citation/Reference:
Chemical abstracts
Also issued online.
Dates or Sequential Designation:
1960-June 1964 ; v. 1, no. 1 (Oct. 1965)-
Numbering Peculiarities:
Publication suspended briefly: issue designated v. 1, no. 4 (June 1966) published Nov. 1967.
General Note:
Title from cover.
General Note:
Place of publication varies: Rochester, N.Y., 1965-1967; Gainesville, Fla., 1968-

## Record Information

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University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
01151209 ( OCLC )
70013732 ( LCCN )
0009-2479 ( ISSN )
Classification:
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660/.2/071 ( ddc )

## UFDC Membership

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Chemical Engineering Documents

Full Text

chemical engineering education

VOLUME 40

* NUMBER 4

* FALL 2006

Teaching Entering Graduate Students the Role of Journal Articles in Research (p. 246)
Hill
Biomass as a Sustainable Energy Source: an Illustration of ChE Thermodynamic Concepts (p. 259)
Mohan, May, Assaf -Anid, Castaldi
Multidisciplinary Graduate Curriculum on Integrative Biointerfacial Engineering (p. 251)
Moghe, Roth
Incorporating Computational Chemistry into the ChE Curriculum (p. 268)
Wilcox

... and articles of general interest.

Random Thoughts: What's in a Name? (p. 28 1) .................................... Felder
Biomolecular Modeling in a Process Dynamics and Control Course (p. 297)......................... Gray
Research Proposal in Biochem. and Biolog. Engineering (p. 323) ..... Harrison, Nollert, Schmidtke, Sikavitsas
Using Visualitation and Computation in the Analysis of Separation Processes (p. 313). ....... Joo, Choudhary
An International Comparison of Final-Year Design Project Curricula (p. 275)............. Kentish, Shallcross
Biomedical and Biochemical Engineering for K-12 students (p. 283)..................... Madihally, Maase
Pressure For Fun: IncreasingStudents'Excitemeni and Interest in Mechanical Parts (p. 291) ... Scarbrough, Case
Computer-Facilitated Mathematical Methods in ChE Similarity Solution (p. 307).............. Subramanian

5-Year Index 2002-2006
Page 328

4
.9 .

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44 .

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SSi

V~ .

I

Chemical Engineering Education
Department of Chemical Engineering
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North Carolina State University
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University of Washington
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University of Michigan
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Rowan University.
Donald R. Woods
McMaster University

Chemical Engineering Education
Volume 40 Number 4 Fall 2006

246 Teaching Entering Graduate Students the Role of Journal Articles in
Research
Priscilla J. Hill
251 Multidisciplinary Graduate Curriculum on Integrative Biointerfacial
Engineering
Prabhas V Moghe and Charles M. Roth
259 Biomass as a Sustainable Energy Source: an Illustration of ChE
Thermodynamic Concepts
Marguerite A. Mohan, Nicole May, Nada M. Assaf-Anid,
Marco J. Castaldi
268 Incorporating Computational Chemistry into the ChE Curriculum
Jennifer Wilcox

> CLASSROOM
291 Pressure For Fun: A Course Module for Increasing ChE
Students'Excitement and Interest in Mechanical Parts
Will J. Scarbrough, Jennifer M. Case
323 The Research Proposal in Biochemical and Biological Engineering
Courses
Roger G. Harrison, Matthias U. Nollert, David W Schmidtke,
Vassilios I. Sikavitsas

> RANDOM THOUGHTS
281 What's in a Name?
Richard M. Felder

> OUTREACH
283 Biomedical and Biochemical Engineering for K-12 students
Sundararajan V Madihally, Eric L. Maase

> CURRICULUM
275 An International Comparison of Final-Year Design Project Curricula
Sandra E. Kentish, David C. Shallcross
297 Biomolecular Modeling in a Process Dynamics and Control Course
Jeffrey J. Gray
313 Using Visualization and Computation in the Analysis of Separation
Processes
Yong Lak Joo, Devashish Choudhary

> CLASS AND HOME PROBLEMS
307 Computer-Facilitated Mathematical Methods in ChE: Similarity Solution
Venkat R. Subramanian

327 Teaching Tip
328 5-Year Index: 2002-2006

CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engineering
Division, American Society for Engineering Education, and is edited at the University of Florida. Correspondence regarding
editorial matter, circulation, and changes of address should be sent to CEE, Chemical Engineering Department, University
of Florida, Gainesville. FL 32611-6005. Copyright 2005 by the Chemical Engineering Division, American Society for
Engineering Education. The statements and opinions expressed in this periodical are those of the writers and not necessarily
those of the ChE Division,ASEE, which body assumes no responsibility for them. Defective copies replaced if notified within
120 days of publication. Write for information on subscription costs and for back copy costs and availability. POSTMASTER:
Send address changes to Chemical Engineering Education, Chemical Engineering Department., University of Florida,
Gainesville, FL 32611-6005. Periodicals Postage Paid at Gainesville, Florida and additional post offices (USPS 101900).

Summer 2006

THE ROLE OF JOURNAL ARTICLES

IN RESEARCH

PRISCILLA J. HILL
Mississippi State University Mississippi State, MS 39762

Students entering graduate school have a variety of
backgrounds. While some have actively participated in
research as an undergraduate, many have no research
experience at all. Although they may have read assigned
technical articles, few are in the habit of searching journal
articles for information or reading articles critically. These
skills, however, are essential to being successful as a gradu-
ate student. Liljar" states that good researchers must perform
literature searches to determine what is already known, and to
avoid repeating existing work. Included in this approach is the
need to develop skills to critically evaluate research articles.
Lilja further states that these are skills that must be taught.
Although technical articles have long been used in graduate
courses to convey technical information, they aren't always
used to develop critical-thinking and technical-writing skills.
To develop critical-thinking skills, several educators have
required students to summarize the main points of journal
articles, and critically evaluate the research.'-41 Others have
required undergraduate students to list the sections of a journal
article to develop technical writing skills.'51
A similar view is taken at Michigan Technological Uni-
versity, where chemical engineering graduate students are
required to take a course entitled, "Theory and Methods of
Research."'61 The purpose of this course is to provide formal
training in skills that students need to be successful in graduate

school. This includes a wide range of subjects from how to
present professionally to guidelines on research notebooks.
One major goal of the course is to improve paper writing,
taught through lectures on the subject and writing assign-
ments. These lectures discuss the purpose of journal articles,
types of journal articles, and the journal submission process.
Later in the semester, students are required to review a journal
article of their choice and present their critique.
One chemical engineering textbook on reaction engineering
includes "journal article critiques"'7' as exercises at the end
of selected chapters. These exercises use chapter concepts to
test claims made in selected papers. Each exercise presents
the point being questioned, and gives hints on how to test the
claim. The goal of these exercises is to teach students how to

Priscilla J. Hill is currently an assistant
professor at Mississippi State Univer-
sity. Her research interests include solids
processing, crystallization, and particle
technology. She received her B.S. and
M.S. degrees from Clemson University
and her Ph.D. degree from the University of
Massachusetts at Amherst. She has taught
design and thermodynamics courses at the
on thermodynamics.

Copyright ChE Division of ASEE 2006
Chemical Engineering Education

At the University of Michigan, students in the graduate
chemical reaction engineering course are required to analyze
and critique a related journal article.181 This consists of a de-
tailed analysis in which students are encouraged to critically
evaluate the assumptions, methods, and conclusions in the
article. They are asked to determine if there is another ex-
planation for the paper's results. The students are also given
evaluation guidelines used by reviewers of AIChE Journal and
Transactions of the Institution of Chemical Engineers.
At the University of Massachusetts in
chemical engineering kinetics class91 T
were required to present or discuss as- class di
signed technical articles in class. On
the day of presentation, a student was method
selected at random to summarize the beca
key points of the paper, while the other encouraj
students joined the discussion. At the partici
beginning of the semester, students and re
were given guidelines as to what ques-
The goal is to teach entering graduate iS Z
students the role of journal articles in effectil
research. This includes teaching students active
to search journal articles when looking is invol
for information, to critically evaluate

journal articles, to summarize the key
points of an article, and to evaluate the
applicability of the research. These methods are implemented
by classroom discussion of technical articles.

INSTRUCTIONAL OBJECTIVES
The objective of journal-related instruction is to better
prepare students for research. Meeting this objective consists
of two parts:
1) Giving students a better understanding of the role of
technical articles in research
2) Introducing students to the paper submission and
review process
Although students will learn this information during their
research projects, it is often helpful for students to hear this in-
formation from two different sources. In addition, it begins the
transition from an undergraduate student to a researcher.

IMPLEMENTATION
Throughout the semester, 10 papers are distributed to the
class for reading. At the beginning of the semester, the class
is told that they are expected to read the assigned technical
Fall 2006

articles and be prepared to discuss each paper. An in-class
discussion session of approximately 15 minutes is set aside
for each paper. The instructor moderates the discussion and
asks questions to encourage class participation. This participa-
tion includes a discussion of the paper's technical points and
other issues, such as the type of paper. The class discussion
method is chosen because it encourages active participation,
and research has shown that teaching is more effective when
active learning is involved.'0- ll

This approach was implemented in a
thermodynamics class was chosen because
it is one of the core courses entering students
take during the first semester. During the
fall semesters of 2003 and 2004, there were
10 and 12 students, respectively. Generally,
graduate classes are small enough to allow all
students to participate in the discussion.

Although all papers assigned relate to ther-
modynamics, they are also chosen to provide
students with a sample of various types of
papers and journals. For example, the papers
assigned for the fall 2004 semester are given
in References 12-21. They ranged from tra-
ditional papers on fundamental concepts to
papers on recent developments. While most
of the papers were published within the last
five years, one11" was published in 1914 and

anotheri8l in 1958.
Since most entering graduate students are unsure what to
the following items.
C Fundamental issue addressed: What concerns are the
authors addressing? What problem is being solved?
C Motivation, perspective: Why are the authors writing
this paper? How does this paper fit into other work
in the area? Is there a need jfr this research? Is the
research novel?
C Main ideas: What are the key points? What are the
assumptions, methods used, limitations, and applica-
tions? For example, is the work limited to a certain
pressure range or a certain class of compounds?
C Relation to course: How does this paper fit into the
course?

The discussion is conducted in a manner to elicit volunteer
responses. Since part of the grade depends on discussion, a
record is kept of participation. The discussion is largely guided

he
scussion
is chosen
ruse it
ges active
ipation,
'search
,hown
'aching
nore
ve when
learning
ved.110, 11]

by the questions given above. The purpose of the assignment is
to give students practice reading technical articles, particularly
to aid students in developing the ability to understand the main
points in technical articles outside their research area.

CLASS DISCUSSIONS

At the beginning of the semester, the instructor explains that
graduate students should become more familiar with journal
articles. Students usually agree that their undergraduate work
relied heavily on textbooks and handbooks, and rarely in-
volved searching journal articles for information. The purpose
of the explanation is to help students understand the reason

To aid students in understanding the role of technical papers,
many concepts can be discussed in addition to the items given
in the student guidelines. Topics discussed in class include
the following.
C It is emphasized that the purpose of journal articles
is to disseminate research results in a timely manner,
to bring attention to research needs, or to encour-
age research in certain areas. The paper on applying
thermodynamics to biotechnology"l71 is used to demon-
strate the last two items.
C Discussion of journal types includes journals written
for various audiences. Class examples include scien-
tific periodicals such as Scientific Americani"6 for the
scientific layman, Chemical Engineering Progressfor
the practicing chemical engineer, and other journals,
e.g., Chemical Engineering Science,"' 11 211 Industrial
and Engineering Chemistry,'""and Industrial and
Engineering Chemistry Research2o for researchers.
Other examples include disciplinary journals such as
Chemical Engineering Science2, 15, 211 and Pure and
Applied Chemistry"71 for chemical engineers and
chemists, respectively. Further examples such as Fluid
Phase Equilibria,14' 19 demonstrate journals that are
highly specialized.

C The students are told that research articles can be
categorized as theoretical, computational, experimen-
tal, or as a combination of these types. One paper is
included to show how experimental papers may present
new techniques or devices.212"Discussion also mentions
other types of articles, such as published plenary lec-
tures and review articles. Also discussed is how articles
are categorized by length as letters or full research
articles.

C Classroom discussion on article structure emphasizes
the purpose of each section in the paper, showing how
sections of a paper vary depending on article type.

C The students are told that although acceptance criteria
varies among journals, they share many common
criteria, including determining whether a paper is ap-
propriate for the journal, presents new material, and
is well-written. Each publication has its own specific
submission guidelines.
C The mechanics of journal submission are also dis-
cussed, and students are encouraged to check the
submission and acceptance dates on published articles.

ASSESSMENT AND DISCUSSION

The first time this teaching method was implemented, no
formal assessment was used. In 2004, an anonymous assess-
ment was performed by using brief surveys on the first day of
class and at the end of the semester. The purpose of the first
survey was to determine the students' knowledge entering
the class, while the second survey determined how much the
students learned from class discussions. The final survey had
additional questions to determine the students' perception of
what they had learned through the discussions.

The initial survey at the beginning of the semester followed
the suggestions of Angelo and Cross1221 for a background
knowledge probe and a misconception/preconception check
on the purpose of technical articles and procedure for pub-
lication. Some of the survey questions were drawn from
Chemical Engineering Education

TABLE 1
Question 1 2 3 4 5 Initial Final
Survey Survey
1. What sources do you use books mainly books mainly articles 2.92 3.20
for technical information? only books and articles only
articles
2. What sources do you books mainly books mainly articles 3.83 4.3
use for current technical only books and articles only
information? articles
3. Rank the importance of not slightly useful very crucial 4.75 4.8
reading technical articles neces- useful useful
for conducting research. sary

misconceptions expressed the first time this approach was
taught in 2003. This survey provided a baseline comparison
with the second survey.
As shown in Table 1, the first set of questions addressed the
importance of reading technical articles. The students were
instructed to answer the questions using a rating of one to five,
as defined in the table. The initial and final survey columns
are the average ratings for each question. A comparison of
the final survey results with the initial survey results shows
more students became convinced technical articles are the
main source for current information. Since students were
question showed little change.
to any particular response. The following five questions were
papers? The responses to this question were mostly
the same on initial and final surveys. The response
"to get current information came from at least half
the class. This is probably because most students al-
ready realized that articles are a good source of cur-
rent information. One change between surveys was
that on the initial survey 42% of students responded
"to find out what has been done or "avoid repeating
work," while on the final survey 70% of the students
gave these responses.

2. Why are technical articles published? Most students
responded either "to disseminate research results" or
"to disseminate research results quickly." The main
difference between the two surveys was in the second
response; the number of students citing this reason
increased fiom 25% to 40%.

3. Why is a literature review included in an article?
Most students-more than 50%-already realized that
the literature review is used to provide background. In
the initial survey, 33% of the students stated that the
purpose of the review was to give credit to previous
Fall 2006

researchers, but this response dropped to 10% in the
final survey.
4. What are the criteria for getting a technical article
accepted? The response of "the work being novel
or creative" increased from 17 to 50 percent during
the semester. Also, while one-third of the students re-
sponded "don't know" on the initial survey, only one
student responded "don't know" on the final survey.

5. How long does it take for a journal article to be
reviewed? The initial survey showed that 42% of the
students wrote "don't know" for this question, but
none of the students used this response on the final
survey. In general, on the initial survey most students
thought reviews would be received in less than 6
months, while the times became slightly longer on
second survey.

Student perception of the technical article reading assign-
ment was assessed in the final survey using the questions
shown in Table 2. For these questions, the students were asked
how much they agreed with the statements by rating their
agreement on a scale from I (strongly disagree) to 5 (strongly
agree). In general, students thought the technical reading
assignments and class discussions helped their understand-
ing of how to read technical articles and get a journal article
published. Furthermore, most of the students recommended
this exercise be repeated in future classes.

DISCUSSION AND CONCLUSIONS

Class discussion of journal articles required little additional
time to implement. Faculty members commonly use technical
Although discussing the role of technical papers in research
required some time, it provided graduate students with a bet-
ter understanding of why they should read recent literature.
Having reading assignments and class discussions account
for 10 percent of the course grade motivated the students to
to encourage the students to be prepared.
249

TABLE 2
Students' Perception of the Technical Reading Assignments (Rated fom I-strongly disagree to 5-strongly agree)
Statement Average Rating
1. During this course, my ability to read technical articles improved. 4.22
2. I have a better understanding of the role of technical articles in research. 3.89
3. As a result of the discussions, I have a better understanding of the types of journals and articles. 4.11
4. I have a better understanding of the acceptance criteria and procedure for getting a journal article 3.67
published.
5. I would recommend that the professor repeat the technical article reading assignments and discussions 4.39
the next time the course is taught.

The survey assessment was supplemented by faculty obser-
vation during class discussion. It was clear from the students'
were able to comprehend the main points. They even com-
mented on some differences in the types of articles. Some
of the concepts, however, were new to them. For example,
many of the students had not submitted a paper to a journal
at this time, so they were not aware of the review and publi-
cation timeline. Most students also didn't know that papers
frequently list the date the manuscript was received and the
date it was accepted.

The response from the students was that they liked reading
the papers and discussing them in class. Many of the students
regularly contributed to the discussions. Since this assessment
has only been performed once with a class of 12 students, it
has not been well tested. Future work will include repeating
this technique and its assessment.

ACKNOWLEDGMENTS
Parts of this paper were originally published in the 2005
ASEE Southeastern Section Conference Proceedings.

REFERENCES
1. Lilja, D.J., "Suggestions for Teaching the Engineering Research Pro-
cess," ASEE Annual Conference Proceedings, Session 0575 (1997)
2. Gleichsner, J.A., "Using Journal Articles to Integrate Critical Thinking
with Computer and Writing Skills," NACTA J., 38(3), 12 (1994)
3. Gleichsner, J.A., "Using Journal Articles to Integrate Critical Thinking
with Computer and Writing Skills," NACTA J., 38(4), 34 (1994)
4. Ludlow, D.K., "Using Critical Evaluation and Peer-Review Writing
Assignments in a Chemical Process Safety Course," 2001 ASEEAnnual
Conference Proceedings, Session 3213 (2001)
5. Tilstra, L., "Using Journal Articles to Teach Writing Skills for Labora-

tory Reports in General Chemistry," J. Cliemr. Educ., 78. 762 (2001)
6. Holles, J.H., "Theory and Methods of Research (or, How to Be a Gradu-
ate Student)," 2005 ASEE Annual Conference Proceedings (2005)
7. Fogler, H.S., Elements of Chemical Reaction Engineering, 4th Ed.,
Prentice Hall, PTR, Englewood Cliffs, NJ (2006)
8. Fogler, H.S., Elements of Chemical Reaction Engineering, 1st Ed.,
Prentice Hall, PTR, Englewood Cliffs, NJ (1986)
9. Westmoreland, P.R., personal communication (2003)
10. Felder, R.M., and R. Brent, "FAQs," Chem. Eng. Ed., 33, 32 (1999)
11. Wankat, P.C., The Effective, Efficient Professor: Teaching, Scholarship.
and Service, Allyn and Bacon, Boston (2002)
12. Jaksland, C.A., R. Gani. and K. Lien, "Separation Process Design and
Synthesis Based on Thermodynamic Insights," Chem. Eng. Sci., 50,
511 (1995)
13. Bridgman, P.W., "A Complete Collection of Thermodynamic Formu-
las," Phys. Rev., 3, 273 (1914)
14. Raabe, G., and J. Kohler, "Phase Equilibria in the System Nitrogen-
Ethane and Their Prediction Using Cubic Equations of State with
Different Types of Mixing Rules," Fluid Phase Equil., 222-223, 3-9
(2004)
15. Aslam, N., and A.K. Sunol, "Reliable Computation of Binary Homo-
geneous Azeotropes of Multicomponent Mixtures at Higher Pressures
Through Equations of State," Chem. Eng. Sci., 59, 599 (2004)
16. Barker, J.A., and D. Henderson, "The Fluid Phases of Matter," Sci.
Am., 245, 130 (1981)
17. Prausnitz, J.M., "Molecular Thermodynamics for Some Applications
in Biotechnology," Pure Appl. Chem., 75, 859 (2003)
18. Curl, R.F. Jr., and K.S. Pitzer, "Volumetric and Thermodynamic Proper-
ties of Fluids-Enthalpy, Free Energy, and Entropy," Ind. Eng. Chem.,
50, 265 (1958)
19. Gmehling, J., "Potential of Thermodynamic Tools (Group Contribu-
tion Methods, Factual Data Banks) for the Development of Chemical
Processes," Fluid Phase Equil., 210, 161 (2003)
20. Givand, J., B.-K. Chang, A.S. Teja, and R.W. Rousseau, "Distribution
of Isomorphic Amino Acids Between a Crystal Phase and an Aqueous
Solution," Ind. Eng. Chem. Res., 41, 1873 (2002)
21. Loffelmann, M., and A. Mersmann, "How to Measure Supersaturation,"
Chem. Eng. Sci., 57, 4301 (2002)
22. Angelo,T.A., andK.P. Cross, ClassroomAssessmentTechniques:AHand-
bookfor College Teachers, 2nd Ed., Jossey-Bass, San Francisco (1993) 0

Chemical Engineering Education

250

s__________._______________________^

CURRICULUM ON INTEGRATIVE

BIOINTERFACIAL ENGINEERING

PRABHAS V. MOGHE AND CHARLES M. ROTH
Rutgers University Piscataway, NJ 08854
Biointerfaces arise at contacts between biologically de-
rived systems-living and nonliving-and synthetic
systems, typically comprised of synthetically designed
materials. Many new technologies in cell-based diagnostics
and therapies, tissue engineering, biomolecular therapies,
and biosensors are critically dependent on advances in bio-
interactive surfaces."[ 12 22J Rapid advances have taken place in
identifying new biological molecules and in the initial design
of diverse materials capable of biomimicry and scale-specific
bio-recognition.421 Consequently, the field of biomaterials is
poised for a major impact on our society. In contrast to the
traditional development of the materials and biology fields,
which largely occurred independently, the next generation of
bio-inspired and bio-interactive materials will be systemati-
cally developed through the integration of these disciplines,
structural biochemistry, and nano/microsystems materials
sciences and engineering.'2." "37] To realize these opportunities,
a structured framework is needed for cooperative graduate
learning and research scholarship that cuts across engineer-
ing, physical, and life sciences while focusing on mainstream
"biointerfacial" problems and opportunities. Based on the edu-
cational core of a new National Science Foundation-supported
IGERT initiative at Rutgers, we propose a new Integrative
Fall 2006

CoprTight ChE Division ofASEE 2006

Prabhas V. Moghe received his B.S. and
the University of Bombay and University of
Minnesota, respectively. He is currently an
associate professor in the Departments of
Chemical and Biochemical Engineering
*and Biomedical Engineering at Rutgers Uni-
versity. Dr. Moghe directs the NSF-funded
IGERT training program on biointerfaces
(). His research is
focused on cell-interactive biomaterials and
bioactive nanosystems, with applications
to vascular and skin therapies and tissue
engineering.

Charles M. Roth received his B.S. and Ph.D.
degrees in chemical engineering from the
University of Pennsylvania and University
of Delaware, respectively. He is currently
an associate professor in the Departments
of Chemical and Biochemical Engineering
and Biomedical Engineering at Rutgers.
Dr. Roth is one of the leading core faculty
for the Rutgers IGERT on biointerfaces. His
research is focused on molecular systems
bioengineering, with major emphasis on
nucleic acids technologies and applications
to liver therapies and cancer.

Biointerfacial Engineering (IBE) curriculum that involves
a three-pronged focus on molecular/cellular engineering;
micro/nanoscale biomaterials; and tools to quantitatively
probe biointerfaces (see Figure 1). While such a curriculum
can be best rooted within a bioengineering core (designated
bio-x-engineering), the integrative curriculum is designed to
effectively resonate among a diverse range of nonengineers.
In the following section we review the core curriculum and
the best instructional practices of the IBE curriculum.

TECHNOLOGICAL CONTEXT FOR
CURRICULUM: RESEARCH PROGRAMS
ON BIOINTERFACES
The curriculum on biointerfaces can be designed to ar-
ticulate with the specific areas of research expertise of each
graduate institution. The research thrusts are an important
prerequisite, as they provide the technological context and
research infrastructure for the courses. Three major thrusts
were identified at Rutgers: (1) living cell biointerfaces, i.e.,
engineered cellular/intracellular systems that elucidate/affect

Figure 1. A triad of graduate courses has been designed to cap
approaches related to biointerfacial problems involving living
micro- and nanoscale biofunctional materials; and biosystems
biosensing, and actuation. The schematic backdrop illustrates
in terms of (a) the biointerfacial confluence of cells, biomolecu
disciplinary research thrusts denoted as IRT's. Emerging oppor
scientists to address biointerfacial problems at the nao

biointerfacial phenomena; (2) biologically interactive na-
noscale and microscale interfaces; and (3) systems or devices
built from designed biointerfaces.
Thrust 1 involves studies at the interfaces that occur be-
tween living cells and biomaterials, between living cells
and supported biomolecules ligandss), and intracellular in-
terfaces between cytoskeletal proteins and signaling targets
within living cells. Such interfaces are fundamental to any
cell-based diagnostic, therapeutic, or model systems used to
study stem-cell development, pathology, and bio-inspired
devices. The interpretation and modeling of cellular dynamics
on more complex ligand substrates is also an area that often
falls outside the expertise of cell biologists, but is central to
the integrated curriculum proposed here. A recent report in
the Annals ofBiomedical Engineering describes a curriculum
concentrating on cellular engineering120" that embraces many
of these principles.
Thrust 2 involves investigation of inorganic and polymeric
substrates from micron-sized cell interfaces to nano-sized
peptide/protein interfaces. Such interfaces are widely emerg-
ing in biophotonics,
bioMEMs, single-cell
studies, and therapeutic
Approaches to tissue
Engineered cellularlintracellular regeneration and drug
systems that elucidateleffect delivery. For exam-
bjomterfaclal phenomena b
bnteraca phenomena ple, interfaces created

by micropatterning
proteins on synthetic
polymeric substrates
can be fabricated us-
ing microlithographic
ENGINEE or microcontact print-
u ing technologies, then
analyzed using micro-
scopic, spectroscopic,
and cellular approaches.
The capabilities of mi-
crofabrication-the
ial physicochemical
in characterization-and
biological studies fall
of any single discipline
and, therefore, consti-
ture the synthetic and analytical tute a major area in the
engineered cells on: substrates; integrated training ap-
and processes for cell signaling, preach we envision.
the landscape of the curriculum prach we envision.
les, and materials; and (b) inter- Thrust 3 involves
-tunities allow engineers and life studies of systems or
7o- through microscales. processes involving
Chemical Engineering Education

Molecular & Cellular
Bioengineering

IIRT73
SystemrnsDewce Level
Integration of biointerfaces

LA
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1E==

SBiofncnimal MkrosMale andH
BiRT o] Interfaces

biomaterial substrates designed to elicit systematic responses
from living cells or biomolecular moieties (e.g., oligonucle-
otides, peptides/proteins), called bio-responsive interfaces;
substrates designed to detect and sense biomolecules and cells,
called biosensors; and substrates engineered to be physiologic,
three-dimensional,E191 and/or actuated through the media-
tion of biologic mechanisms or motors. Such interfaces are
fundamental to the development of therapeutic implantable
biomaterials, implantable biosensors, and biomicro-electro-
mechanical systems (BioMEMS).

COURSE LEVEL AND PREREQUISITES
The biointerfacial engineering curriculum is aimed at
second-year or higher graduate students in chemical and
biomolecular engineering, biomedical engineering, allied en-
gineering disciplines (mechanical and materials engineering),
and physical and life sciences. At Rutgers, nearly 60 graduate
students (50% chemical and bio-engineers; 10% mechani-
cal and materials engineers; 25% molecular bioscientists;

and 10% physical scien-
tists) participated in these
2005-6. Because students
enter the curriculum from
diverse backgrounds, pre-
requisites are expressed
topically rather than by
specific course numbers,
and consultation with
course instructors and/or
encouraged. Prerequisites
sciences courses (general
biology, cell biology/bio-
chemistry/molecular biol-
ogy) as well as structured
the physical and quanti-
tative sciences, such as
physical chemistry and
curriculum builds later-
gineering courses such as
transport phenomena, an-
alytical methods in chemi-
cal and bioengineering,
and thermodynamics and
kinetics. The curriculum
Fall 2006

TABLE 1
Course Syllabus for Integrative Biointerfaces Curriculum
Course and underlying Syllabi of course modules
integrative philosophy
IC 1: Molecular and Module 1: Genes-sequence and function technologies and data-
Cellular Bioengineer- bases: gene expression profiling; genetic engineering
ing (integrated across Module 2: Proteins-structure and function; molecular recogni-
scales of bio-organiza- tion; protein adsorption; nanopatterning of proteins; proteomic
tion) technologies
Module 3: Biochemical Networks-gene expression data mining;
metabolic flux analysis; signal transduction and gene network
modeling
Module 4: Cells-growth and differentiation; cell-material
responses; expression-phenotype relationships; actuated cell
responses; stem cells
IC2: Microscale and Module 1: Microlithography and microfabrication
Nanoscale Biointer- Module 2: Nanoscale processing and fabrication
faces (integrated across Module 3: Soft tissue- nanostructures, microstructures, macro-
scales) structures
Module 4: Hard tissue-nanostructures, microstructures, and
functional components
Module 5: Nanostructures and microstructures of biosensors,
bioseparations, implantable devices, bioMEMs
IC3: Biointerfacial Module 1: Chemical surface characterization; electron spectros-
Characterization copy
(integrated across Module 2: Physical surface characterization-topography, surface
biointerfacial phases: energetic, microscopy, spectroscopies (surface Raman; single
chemical, physical, molecule; FTIR); nanoparticle sizing and morphology
biological) Module 3: Biological Surface Characterization -proteins at inter-
faces and protein arrays; cell dynamics at interfaces (adhesion;
migration; endocytosis; growth/differentiation); biofunctional-
ized substrates; gene micro-arrays
Module 4: Integrative design, applications, and case

tives for a Ph.D. degree. For example, the Rutgers Chemical
and Biochemical Engineering graduate program requires 15
elective credits (beyond 15 core credits), for which any or
all of the three integrative courses (IC) described below may
be used. Further, engineering graduate programs that have
recently instituted a life science course requirement can eas-
ily adopt any IC courses. Similarly, biomedical engineering
graduate programs, such as those at Rutgers, require three
bioengineering electives (9 credits), which can be readily met
through the IC courses.

CURRICULUM COMPOSITION
The proposed curriculum involves a triad of courses,
denoted as ICI, IC2, and IC3 (see Table 1). We utilize an
integrative philosophy to develop curricular themes. For
example, we designed courses that integrate biointerfaces
across the range of organization of biological components
of the interfaces (e.g., genes, proteins, cells: see IC1), or size

scales (e.g., nano-micro-macroscales: see IC2), or the two
phases that constitute a typical biointerface (e.g., the gene
element, plus the siliconwafer, that form a class of gene-chips:
see IC3). In the future, other integrative philosophies can be
envisioned as well (e.g., integration across time scales for
dynamic interfaces).

INTEGRATIVE TREATMENT OF
THE CURRICULUM
A variety of fundamental tools and phenomena are in-
troduced in each of the three courses within the context of
significant technological problems. In order to provide a
cohesive framework in the overall curriculum, many key
problems are dissected within all three courses. Naturally,
each course treats the problem differently, as illustrated in
Table 2. For example, the problem of tissue-specific target-
ing of drug nanoparticles is discussed in ICI at the level of
receptor-ligand binding, and in the theory and analysis of
binding affinity; IC2 treats the nanofabrication of particles and
biofunctionalization; while IC3 treats the experimental tools
for nanoparticle characterization. These tools include the use
of dynamic laser scattering and zeta potential measurements to
characterize nanoparticle charge and sizing, and quartz-crystal
microbalance and surface plasmon resonance techniques to
evaluate ligand-receptor affinity. Other cross-cutting topics
are summarized in Table 2.

BEST PRACTICES
In developing the new curriculum, an overarching goal
has been integration of the graduate students' research and
learning experiences, i.e., to help usher the frontiers of bio-
interfacial science and engineering into the classroom. The
instructors have identified several instructional approaches
that have proven to be particularly effective in merging active
learning with emerging scientific advances and technological
applications. These approaches include the selected inclusion
of faculty experts as guest lecturers, extensive incorporation
of readings from current research literature, and demonstra-
tions of techniques and instrumentation at laboratories around
campus. Additionally, mid-course corrections in response to
student feedback have occurred.

Use of the Current Biointerfacial
Research Literature

For all three courses, each major topic was contextualized
through extensive use of recent, leading publications in the
field. The manuscripts were assigned prior to respective lec-
tures, and significant portions of class were allotted to critical
review and discussion. In IC3, following each lecture students
were assigned homework based on the key publication. The
homework involved writing a short essay highlighting key
principles, insights obtained, and shortcomings of biointer-
facial characterization techniques treated in each reading.

Chemical Engineering Education

TABLE 2
Breakdown of Topics Treated Across the Triad of Integrative Courses
CROSS-CUTTING PROBLEMS SPECIFIC TOPICS AND REFERENCES
ICl IC2 IC3
High-Content Living Cell Assays Signal transduction; cell Cell microreactorsl 32 Cell adhesion and motility
cycle and proliferation; characterization['4. n. 45.471
differentiation; metabolic
engineeringI', 30, 4
DNA and Protein Microarrays Applications of microar- Photolithography; Chemical, physical, and
rays; interpretation of surface attachment and functional characteriza-
data3, '231 functionalization125, 341 tioni31.491
Discovery and Applications of Novel Protein molecular recog- Micro/nano-scale or- Single molecule and
Biological Transformations nition and function151 ganic substratesI 311 FRET imaging'21. 3I func-
tion'ls
Targeted Biofunctionalized and Drug Ligand-receptor binding Fabrication of Size; charge; biofunc-
Carriers and intracellular traffick- micro- and nanoscale tional characterization:
ing'291 inorganic and organic fluorescence spectros-
substrates1 '15 17' 221 copy[18 28,33.351
Regenerative Biomaterials Scaffolds Protein adsorption and Fabrication of nano- Molecular modeling;
biocompatability'46' and microporous scaf- conformation; topography
folds and fibers611 241 and microstructure
characterization127 .41431
Multicellular Tissue Assembly Cell-cell and cell-matrix Cell-matrix assembly Cellular phenotypic and
and Engineering communication, 26 391 and patterning 'I signaling within tissue
assemblies"91

Retrospectively, students have reported this exercise was
critical to understanding the key elements of each technique
within an application area. As described below, student feed-
back to the use of scientific literature has been consistently
enthusiastic.
Tracking Student Learning and
Integrative Outcomes
Careful attention has been given to choosing student as-
sessment vehicles that both support the research-centric
and integrative goals of the new curriculum and address the
divergence in student backgrounds and preparation (i.e., the
enrollment across engineering, physical sciences, and life
sciences graduate programs). All three courses used a three-
fold combination of short (homework) assignments, mid-term
and/or final exams, and class projects-thereby providing
students with different ways to demonstrate mastery of the
material. Class projects, in particular, have proven to be a
valuable mechanism for promoting integration of classroom
learning and student research, and promoting cross-disciplin-
ary interactions.
In all three courses, students were assigned one or more
integrative project reports to prepare over the course of the
semester. Students presented their findings orally to the
entire class and also submitted their slides and/or a paper
to the instructor. Students were challenged to select topics
that related to their own thesis research, and to consult the
course instructors should they need help in doing so. Several
strategies were adopted to encourage cross-disciplinary dialog
and learning during the course projects. For example, the IC 1
course projects allowed pairs of students to work on such
reports, with the teams composed of students from different
remote fields were asked to review and comment on student
projects. The instructor for IC3 encouraged each student to
select another student from an orthogonal field to be a con-
sultant on his or her project.
Student Early Assessment and
Curriculum Refinement
Given the diverse backgrounds of students, a first-day sur-
vey administered by the instructors has proven invaluable in
assessing the knowledge base of each student population, and
appropriately customizing the focus of the modules within
each course. For instance, in IC 1, which has now been offered
twice, the student body was further along in research and more
familiar with tissue engineering and other bioengineering top-
ics. The second year's class was, on average, still formulating
research projects and had a preponderance of students with
bioinformatics backgrounds. Mid-course surveys also proved
helpful in refining the course delivery. For example, students

definitions of specific terms and references to foundational
papers. These modifications were readily implemented as
postings on the course Web sites.
Curriculum Assessment
Given the interdisciplinary nature and lack of precedent for
such a curriculum, continuing assessment is necessary to as-
sure that it meets its goals and the needs of constituents. The
ultimate goal of the curriculum is to provide students with
knowledge that will increase the quality and productivity of
their research. While the current curriculum form has been
at Rutgers since 2003, a more comprehensive quantitative
assessment of this outcome will have to wait for curricular
knowledge to be translated to research output. Comments on
course assessments suggest that students feel more knowl-
edgeable and empowered in the areas of this interdisciplinary
curriculum.
The curriculum serves as an effective platform for evalu-
ating the success of students from diverse backgrounds. To
gather additional data on possible differences in student per-
formance, based on disciplinary background and/or IGERT
participation, all students in IC3 were asked to evaluate each
other's oral course project presentations using a structured
questionnaire designed by the instructor. Evaluation criteria
included not only presentation quality (clarity, organization,
etc.), but also the appropriateness of the characterization
methods chosen and the degree to which the chosen re-
search problem was significantly biointerfacial. As rated by
their peers, IGERT Fellows and non-IGERT students fared
comparably, on average, indicating that the student learning
outcomes were not systematically biased by their training
program affiliation. Likewise, engineers, biologists, and
chemists all fared similarly, with some students from each
discipline giving stronger presentations than others from the
same discipline.
An excellent source of data about student feedback on
courses is the "Student Instructional Ratings Survey" (SIRS)
vancement of Teaching. All courses at Rutgers are evaluated
using a standard 10-question survey with a one- to five-point
rating scale. The survey is reproduced, along with actual rat-
ings for the first offering of the three IC courses, as Table 3
(next page). Additionally, three open-ended questions were
posed to acquire qualitative feedback (not shown for brev-
ity). To put the curriculum feedback in context, we calculated
an average "bio-x-eng" response by using the SIRS data for
"mean of responses from all courses this level" from the
biomedical engineering and chemical and biochemical engi-
semesters the IC courses were offered.

Fall 2006

Students complimented the teaching quality of all three
courses, which is consistent with the high numerical scores for
each of the three lead instructors in Questions 1-5. Students
noted the care given to the choice of topics (both breadth and
relevance) and to the organization and delivery of the course
three courses incorporated current research literature into the
course curriculum. Students appreciated the time devoted to
discussion of the papers, and how these discussions, together
with written assignments, helped students develop "alternative
way(s) to look at data and critically review papers." Finally,
students appreciated the attempts to tie course content and
assignments to the biointerfacial aspects of their graduate
dissertation research. The projects/presentations assigned in
all three courses were useful in terms of "covering topics of
interest instead of recycling research or spending too much
time out of research." As expressed by another student, in-
structor and peer feedback from classroom presentations of
final projects "will be important in directing and focusing the
research in a biointerfacial twist."
Student Constructive Criticisms
Students in IC 1, which did not use guest lecturers, expressed
interest in having a few guest lecturers. Conversely, students
in IC2 and IC3 felt that courses might be improved by fewer
guest lecturers and/or better quality control. In IC2, students

were primarily concerned that they sometimes could not
deduce the relevance of a certain lecture, i.e., its relationship
to the overall curriculum. Other constructive criticism and
suggestions of the students focused on not decreasing-and
perhaps increasing-the frequency of short assignments and
other ongoing student assessments. In IC2, there was concern
about the difficulty of knowing what to study and having too
much weight attributed to a final exam. In IC1, there was
input that optional short exercises, calculations, and readings
could be provided to address respective gaps in students'
backgrounds. Finally, some students suggested the creation
of a textbook for IC3, and a more modular organization of
topics as in IC 1.

CURRICULUM EVOLUTION AND
INSTITUTIONALIZATION
The Rutgers curriculum on biointerfacial engineering was
first structured around the core graduate training pathway of
the IGERT program (). We expect
the curriculum to evolve in response to the emerging areas
of biomaterials and biointerfaces. The dynamic participation
of a large number of research-active institutional faculty with
will be integral to ensuring the timely evolution of the cur-
riculum. The biointerfacial engineering area also resonates
particularly well with the field of biomaterials science and

TABLE 3
Rutgers Student Instructional Rating Survey (SIRS)
N=15 N=13 N=16
Questions
ICi IC2 IC3 bio-x-
eng
1. The instructor was prepared for class and 4.75 4.67 4.75 4.32
presented the material in an organized manner
2. The instructor responded effectively to 4.63 4.60 4.67 4.30
3. The instructor generated interest in the 4.44 4.73 4.67 4.09
course material
4. The instructor had a positive attitude toward 4.63 4.53 4.58 4.40
assisting all students in understanding course
material
5. The instructor assigned grades fairly 4.38 4.20 4.38 4.22
6. The instructional methods encouraged 4.31 4.00 4.50 3.98
student learning
7. 1 learned a great deal in this course 4.50 4.27 4.58 3.97
8. I had a strong prior interest in the subject 4.56 4.53 4.42 3.73
matter and wanted to take this course
9. I rate the teaching effectiveness of the 4.44 4.33 4.77 4.10
instructor as
10. I rate the overall quality of the course as 4.25 4.13 4.77 4.08

engineering. Given the close
ties of our IGERT to the New
Jersey Center for Biomateri-
als ( org>), we expect to offer the
IC courses along with core
biomaterials-related courses
as part of a comprehensive
certificate program at Rut-
gers on biointerfaces and
biomaterials. The certificate
program, to be established
fall 2006, indicates success-
ful institutionalization of
the curriculum and will help
sustain an identity for the
curriculum.

CONCLUSIONS
on integrative biointerfacial
engineering was developed.
This curriculum treats the

Chemical Engineering Education

synthesis, analysis, and design of biological interfaces in terms
of the constituent components biologicss, materials, systems),
and with an eye to emerging technological applications such
as tissue engineering, biotechnology, nanobiomaterials, and
biomedicine. Each course within the curriculum is designed
based on a fundamental integrating philosophy. The node
for the curriculum lies within bio-x-engineering, while the
breadth of the curriculum enables life scientists, physical
scientists, and other bio-engineers to participate fully within
the curriculum. Various instructional strategies were adopted
to more fully integrate the multiple disciplines represented
in the field. Based on student perception during early student
assessment, the curriculum is equivalently amenable to stu-
dents from a wide range of disciplines, effectively structured
and rigorous, dynamic in embodying state-of-the-art research
engineers and scientists. Graduate curriculum on integrative
biosciences and bioengineering would resonate well in other
American and international universities, particularly those
with significant research strengths in molecular biosciences,

ACKNOWLEDGMENTS
The authors gratefully acknowledge support from the
National Science Foundation Integrative Graduate Educa-
tion and Research Traineeship (IGERT) DGE 0333196 (PI:
P. Moghe), and from Rutgers University. The authors are
indebted to Professor Kathryn Uhrich for her active participa-
tion and significant contribution to curriculum development.
Dr. Linda J. Anthony provided excellence assistance with the
management of the educational program. P. Moghe expresses
gratitude for the contributions of many faculty colleagues
at Rutgers and UMDNJ including Yves Chabal, David Sh-
reiber, Theodore Madey, Gary Brewer, William Welsh, Jack
Ricci, Adrian Mann, Richard Riman, Sobin Kim, and Edward
Castner, among several others, whose instructional help has
strengthened the quality of the curriculum.

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47. Zaman, M.H., R.D. Kamm, P. Matsudaira, and D.A. Lauffenburger,
"Computational Model for Cell Migration in Three-Dimensional
Matrices," Biophys. J., 89, 1389 (2005)
48. Zhu, H., M. Bilgin, R. Bangham, D. Hall, A. Casamayor, P. Bertone, N.
Lan, R. Jansen, S. Bidlingmaier, T. Houfek, T. Mitchell, P. Miller, R.A.
Dean, M. Gerstein, and M. Synder, "GlobalAnalysis of Protein Activities
Using Proteome Chips," Science, 293, 2101 (2001) J

Chemical Engineering Education

BIOMASS AS

A SUSTAINABLE ENERGY SOURCE:

an Illustration of ChE Thermodynamic Concepts

MARGUERITE A. MOHAN, NICOLE MAY, NADA M. ASSAF-ANID, AND MARCO J. CASTALDI*
Manhattan College Riverdale, NY

A s discussed in an earlier paper,m the overall objective
discussed in an earlier paper the overall objective Nada M. Assaf-Anid is an associate professor and chairperson of the
of the thermodynamics course sequence at Manhat- Chemical Engineering Department at Manhattan College. She earned
tan College is to allow students to become confident her B.S. and M.S. in chemical engineering from the Royal Institute of
about their understanding of theoretical material and familiar Technologyin Stockholm, Sweden, and her Ph.D. in environmental engi-
neering from the University of Michigan in Ann Arbor. Her research and
enough with mathematical manipulations to properly and ac- teaching interests are in separations, biochemical engineering, hazardous
curately set up solutions to problems involving thermodynam- chemicals remediation, thermodynamics, and water purification. She is
director of the ASEE Chemical Engineering Division and director of the
ics. Toward the end of the semester, students have a chance to Environmental Division of AIChE.
explore and propose feasible solutions for what-if scenarios Marguerite A. Mohan is currently working towards her M.S. in chemical
to contemporary problems such as Methyl Tert-Butyl Ether engineering at Manhattan College, where she previously obtained a B.S.
(MTBE) contamination of groundwater,r" biofuels,121 and in chemical engineering. After completing her graduate degree, she will
be employed full time by Merck & Co., Inc., as a staff chemical engineer.
thermodynamics of power plants.[3] The desired outcome is to Marguerite's research interests include chemical thermodynamics and
develop the students' engineering judgment and capabilities nanoscale science.
along with their mathematical skills in solving complicated Nicole May is currently pursuing her M.S. in chemical engineering at
equations with many inputs. This major assignment introduces Manhattan College. She also holds a B.S. in chemical engineering from
Manhattan College. Her interests include engineering education, bioreac-
the students to a practical and current problem they can tackle tion engineering, and environmental conservation.
somewhat intuitively, rather than by a direct application of Marco J. Castaldi is an assistant professor in the Earth and Environmental
formulas as presented by Cengel.t4t The only requirement Engineering Department at Columbia University. He received his B.S. ChE
for a solution is the use of computer programming, possibly from Manhattan College, and M.S. and Ph.D. ChE from the University of
California, Los Angeles. Prior to joining Columbia University, he worked
a spreadsheet, and the thermodynamic principles taught in in industry for seven years researching and developing novel catalytic
class (e.g., phase equilibria, solubility, fugacity). Such an reactors. His teaching interests lie in thermodynamics, combustion phe-
nomena, and reaction engineering. His research is focused on beneficial
open-ended approach is common in engineering education and uses of CO2 in catalytic and combustion environments, waste-to-energy
processes, and novel extraction techniques for methane hydrates.
* Columbia University Earth and Environmental Engineering Department
Copyright ChE Division of ASEE 2006

Fall 2006

has been used in thermodynamics
courses151 because it resembles
problem-solving situations en-
countered in industry.161

The objectives of this paper are Bioreactor
to present an open-ended prob-
lem given as a final project to a
class, describe how one student
tackled it, and demonstrate how it
was a useful addition to the ther-
Liquid
modynamics concepts taught in Draw Off
the class. Portions of the problem
may be suitable in an undergradu-
ate thermodynamics, modeling,[3]
or design class,[71 if presented in
a less open-ended manner or as a Fi
continuing problem integrated in
a series of courses using the approach of Shaeiwitz.11 The
problem given to students, with three references on anaerobic
digestion,19-l1 is shown below. Students were instructed on
literature research methods using online libraries and Internet
sites, such as About.com,1121 to assist them in finding back-
ground information. Topics and information searched ranged
from gasification of biomass for distributed energy production
systems, to physical property data needed to perform calcula-
tions, to ideas for possible solutions.

TABLE 1
Overview of Course Syllabus
(The chapters refer to the class textbook1131)
Week Subject
1 Review of classical thermodynamics
2 Review of classical thermodynamics (cont'd)
3 Ch. 2, prepare for exam #1
4 Ch. 3, exam #1 (classical thermo and Ch. 2)
5 Ch. 4 (parts)
6 Ch. 5 (parts), review exam #1
7 Ch. 6 (parts); computer assignment discussed
8 Ch. 7 (parts)
9 Ch. 7 (parts), exam #2 (Ch. 3, 4, 5, 6)
10 Ch. 8, Ch. 9 (parts)
11 Review exam #2, Ch 9 (parts)
12 Ch. 10 (parts), Ch. 11 (parts), Ch. 12 (parts)
13 Statistical thermodynamics, computer assignment
due, review
14 Final exam

gure 1. Schematic of system components.

PROBLEM STATEMENT
As shown in Table 1, the students had about six weeks to
complete the project and were expected to work indepen-
dently. By the time the computer assignment was issued, the
students were exposed to solution equilibrium theory, which
begins with Chapter 6.
The demand for power, especially electricity, has driven
many engineers to propose possible ways to generate power.
Of course, that power generation must be compatible with
environmental regulations and must be fueled by available
resources. One novel power-generation system uses a bioreac-
tor to decompose various types of biomass anaerobically. The
off-gas from that process will generate methane (CH ), which
can be used as fuel. However, carbon dioxide (CO2) is also
generated. In this gas mixture of CH4 and CO2, the latter is
considered a diluent and effectively lowers the energy content
of the gas stream. One could separate out the CO, from the
stream, but the energy requirements are prohibitively high.

The total power that can be obtained from the system is
governed by volumetric flow rate and energy content. It has
been proposed to accelerate the decomposition of the biomass
to generate more CH4, or at least a higher flow rate of the
CH4/CO2 mixture. One way to do this is to "feed" the bacteria
that is decomposing the biomass a warm stream of CO2 and
hydrogen (H2). In addition, this CO2 can serve as a carbon
source for the bacteria. This allows the bacteria population to
increase and the decomposition of the biomass to occur faster.
The supply of CO2 and H2 is secured by another reactor placed
upstream to convert some of the bioreactor product stream
(CH4 and C02) to H2, carbon monoxide (CO), and CO2. This
second reactor is a catalytic, reforming reaction that uses a
Chemical Engineering Education

small amount of air. Lastly, it is known
that the bacteria will have some waste
byproducts as a result of their digestive
process. Some of those byproducts could
harm the bacteria if they accumulate to
dangerous levels.
As an engineer on this job, you need to
provide a full understanding of the bio-
reactor. That is, what types of byproducts
will be formed by the bacteria and how
will those byproducts distribute them-
selves between liquid and gas phases. In
addition, you also need to determine the
preferred concentrations of carbon in the
bioreactor feed stream as a function of
residence time in the bioreactor, to ensure
that adequate carbon is dissolved in the
liquid phase for the bacteria to access.
In addition to the statement, a concep-
tual schematic (Figure 1) was provided to
show the overall system. Finally, a survey
was distributed to students assessing
how this type of a project impacts their
understanding of the subject and overall
learning experience.

BACKGROUND AND THEORY
Anaerobic digestion, or methane
fermentation, is the process by which
microorganisms convert biomass to
methane in the absence of oxygen. Of-
ten, a water layer serves as a blanket to
exclude oxygen and promote growth of
the appropriate anaerobes. "41 With higher
(gross) heating values ranging from 15.7
to 29.5 MJ/m3(n), the gas produced by
the anaerobic digestion of biomass, called
biogas, is a medium-energy fuel that may
be used for heating and power.E"4'

Methane fermentation is a three-step
process that utilizes three main categories
of bacteria: fermentative, acetogenic, and
methanogenic."41 "I5 In the first step, the
fermentative bacteria convert complex
polysaccharides, proteins, and lipids
present in biomass to lower molecular
weight fragments, such as carbon dioxide
and hydrogen,"4'1 according to the main
reactions shown.1141

Reactions
C6Hl,06 +6H,O -- 6CO, + 12H,
C6H1,06, -> 2CH3COCO; + 2H+ + 2H,

AG '(kJ)
-26 (Rxnl)

-112

C6H,,06 + 2HO- CHCHCO +H + +3CO, + 5H, -192
C6H,06 -> CHCH,CHCO, + H+ + 2CO, + 2H, -264

(Rxn 2)
(Rxn 3)
(Rxn 4)

In the second step, hydrogen-producing acetogenic bacteria catabolize the
longer chain organic compounds formed in the first step to yield acetate, carbon
dioxide, and hydrogen. Also, some carbon dioxide and hydrogen are converted to
acetate by the acetogens, according to the main acetogenic reactions considered
below 141:

Reactions

CH3COCO2 + HO -> CH3CO; +CO, + H,
2CO, +4H, CH3CO; + H+ +2H,O
2HCO- + 4H, +H+ -4 CH3CO, + 4H,O

AG o(kJ)
-52 (Rxn5)
-95 (Rxn6)
-105 (Rxn 7)

C6H1,06 + 4H,0 -> 2CHCO, + 2HCO + 4HW + 4H, -206
C6H,06 + 2HO -> 2CH3CO; + 2HW + 2CO, + 4H, -216
C6HI,06 -> 3CHCO; + 3H -311

(Rxn 8)
(Rxn 9)
(Rxn 10)

In the third and final stage of the fermentation process, methanogenic bacteria
convert acetate to methane and carbon dioxide by decarboxylation, and the latter
to additional methane upon reaction with hydrogen, according to Reference 14:
Reactions AG o(kJ)

CH CO- + H+ -> CH4 + CO,
CO + 4H ---> CH4 + 2H,O
HCO0 + H+ + 4H, CH, + 3H,O

-36 (Rxn 11)

-131
-136

(Rxn 12)
(Rxn 13)

In the three stages described above, CH4, H,, and CO, are in the gaseous state.
In addition, the standard physiological conditions are atmospheric pressure, unit
activity, and a temperature of 25 C at a pH of 7.0."141
As evidenced by the reactions, there are a number of intermediate acids gen-
erated. Since all reactions do not go to completion, a certain amount of these
compounds builds up within the bioreactor, changing the solution pH, poisoning
the bacteria, or inhibiting the digestion rates. Since the bioreactor usually takes
days to digest the initial charge of biomass, an equilibrium is established between
the vapor and liquid phases in which the compounds partition.
The information presented thus far on biochemical reactions taking place in the
bioreactor can now be applied to solve the problem at hand. One unique feature
of this type of problem is the dynamic nature of the system. That is, starting the
system with an initial charge results in changing stream composition while steady
state is achieved. This requires students to develop a solution that is iterative in
nature and exposes them to realistic processes in industry, where thought must be
given to system startup and shutdown, as well as adjustments that must be made
on the way to a targeted operational condition. As was previously discussed, the

Fall 2006

v .___________ __ ___ ________________.________,_____________

problem statement is open-ended; therefore, there are several
possible approaches and solutions.

ONE STUDENT'S SOLUTION
A computer solution was created in Mathematica to perform
the calculations described in the Background and Theory
section, and can be obtained, in Mathematica format, upon
request.
The objective of this project was to determine if it is
possible to increase the total power that may be harnessed
from a traditional bioreactor system. Therefore, the logical
starting point is to calculate the amount of power actually
generated from a traditional system, which consists solely
of a batch bioreactor set to operate in the mesophilic 30 C
- 38 C temperature range, at a pH within the range 6.6 7.4
to maintain the proper alkalinity. Furthermore, a high-rate
digestion is assumed, and an appropriate residence time of
10 days is specified. The volume of the reactor is estimated
using values from the literature,M and it is assumed that ap-
proximately two-thirds of the total volume is charged with an
initial amount of municipal solid waste (MSW). The MSW
is simplified to a 50% (by weight) glucose suspension in
water, and its volume, along with the density of the waste (a
weighted density of water and glucose), allows the calculation
of the total amount of MSW in the reactor or the total amount
of glucose initially charged (So). Once the initial amount of
glucose is calculated, three sets of reactions (Rxn 1-13) are
assumed to occur, and the resulting biogas (vapor product
stream) may be evaluated. Its composition (which is directly
proportional to the power generated) is noted. This will serve
as the control to which all subsequent biogas compositions
will be compared.
Catalytic Reforming Reactor
The next aspect of the solution is the introduction of addi-
tional equipment (the catalytic reforming reactor and the shift
reactor) that, along with the bioreactor, constitute a modified
system that may be used to meet the objective of increasing
the total power harnessed as specified in the problem state-
ment. The product stream from the bioreactor is split: 90%
is sent to a power generation plant, and the remaining 10% is
routed to a catalytic reforming reactor which is brought online
to generate hydrogen that will be fed continuously to the
bioreactor. Hydrogen is used by the bacteria in the bioreactor
as an electron donor for methanogenesis. In most cases, the
hydrogen is the limiting reactant. Therefore, feeding hydrogen
to the bioreactor may help to accelerate the decomposition
of the biomass and generate a higher flow rate of methane
and carbon dioxide. This was one of the major outcomes of
the investigation. That is, once the student developed the
262

computer routine that accurately predicted the performance
of the system, it was discovered that under several scenarios
the hydrogen fed back to the bioreactor was completely
consumed long before the other substrates. This result brings
into question the entire concept of feeding a warm stream of
hydrogen to accelerate the digestion process.
In addition to the 10% split, an air stream is fed to the
catalytic reforming reactor. The air stream provides the
oxygen necessary for a partial oxidation reaction, which will
produce (among other things) the desired hydrogen. In order
to maximize the concentration of hydrogen in the catalytic
reforming reactor's product stream, the equivalence ratio (()
of the system is varied, and the effect on product composition
observed. The equivalence ratio is defined as:

= (F / A)ctual (1)
(F / A)stoichiometric
where
F/A = the fuel (CH4) to air (02,) ratio
After testing various equivalence ratios, an 4 = 3.0 is cho-
sen, and a partial oxidation reaction follows:
4CH, (g) + 2.670, (g) + 10.ON, (g) --- 0.449CO, (g) +
3.55CO(g) + 0.901H20(g) + 7.21H2 (g) + 10.0N2 (g)
(Rxn 14)
The stoichiometry of the above partial oxidation reaction
was obtained through the use of the thermodynamic equilib-
rium software, GasEQ."7I At the adiabatic flame temperature
(1020 K), Rxn (14) has an equilibrium conversion, Xeq of
0.9969.
Shift Reactor
The effluent of the catalytic reforming reactor contains
a significant amount of CO, which is toxic to the bacteria
within the bioreactor. In order to avoid feeding this CO to
the bioreactor, a shift reactor is added to the process after
the catalytic reactor, and before the bioreactor, to convert, or
shift, the CO to CO, according to:

CO(g) + HO : CO, + H,(g)

(Rxn 15)

The benefits of shifting the CO to CO, are two-fold. First,
it removes the entire amount of poisonous CO from the
bioreactor feed stream. Second, it provides the bacteria with
the other species necessary for methane production-carbon
dioxide (the first species being hydrogen).
Modified Bioreactor
The next step in the solution involves returning to the
bioreactor (which will now be referred to as the modified
bioreactor). This bioreactor operates as a semi-batch reactor
since the waste that is decomposed by the bacteria is charged
Chemical Engineering Education

in as necessary (this is dictated by the residence time), while
the stream of hydrogen and carbon dioxide produced from
the other reactors (catalytic reforming and shift) is fed
continuously.
The same assumptions as in the traditional system regard-
ing the MSW are made, and once the total amount of glucose
initially charged is calculated, it is further assumed that at
the end of the charge life all of the glucose will have decom-
posed, reaching a final concentration of S 1 = 0. Assuming
a residence time of 10 days, which is typical for high-rate
anaerobic digestion, and assuming that glucose decomposes
at a constant rate throughout the 10-day period, the rate of
glucose decomposition may be calculated and compared to
the continuous flow of H, and CO2 that is fed to the bioreactor,
since both will be on a time basis.
The initial charge of MSW is allowed to start decompos-
ing before the external H, and CO, stream is fed into the
bioreactor, and for a duration that is sufficient to allow all
of the fermentative and most of the acetogenic reactions to
occur. As this decomposition approaches the end of the ace-
togenic stage and the beginning of the methanogenic stage,
the continuous feed of H, and CO, is introduced. The benefits
of introducing this external feed stream into the bioreactor
are three-fold: first, the H, and CO, provide an immediate
electron and carbon source for the bacteria; second, the gas
stream increases the contact area between the bacteria and
the available food sources; and third, since the external feed
stream is at an elevated temperature, it enhances the digestion
rate within the bioreactor.
As this stream feeds into the bioreactor, the solubilities of its
components in water must be considered. Most of those (N,,
H2, and the acid vapors) are gaseous and insoluble in water.
The solubility of CO, is of particular interest, however, as it is
dictated by the carbonate system. When CO, enters an aqueous
solution, the following dissolution and dissociation occur:
KH K K
CO,(g) CO, (aq) => H,CO3 (aq) HCO3 (aq) (Rxnl6)
The initial concentration of the CO, entering the bioreactor
is used along with Henry's constant, K to find the concentra-
tion of CO,(aq). The latter is then used in combination with
K to find the concentration of carbonic acid H 2CO The
concentration of HCO ,3 along with Ka and the pH of the
system, are used to find the concentration of the bicarbonate
ion HCO,-. Once the concentrations of CO2(aq), H2CO3, and
HCO3 have been calculated, the remaining concentration of
the CO,(g) is tabulated.
Acid Phase Distribution

As the remaining acetogenic and methanogenic reactions
take place, CH4 and CO2 are continually produced, while
Fall 2006

most of the other components are consumed. The exceptions
to this are the acid byproducts-acetic, butyric, and propionic
acids-produced in the fermentation and acetogenic reactions,
and if their levels in the liquid continue to increase, the alkalin-
ity of the bioreactor will change. As a result, the pH may drop
outside of the allowable range for methane fermentation. In
order to find the distribution of acids between the liquid and
vapor phases, chemical thermodynamic concepts are applied
using the assumptions summarized in Table 2 (next page). The
first concept used is the equilibrium criterion:
f. = f\ (2)

The fugacity of component i in a liquid solution is related to
the mole fraction, xi, according to the following equation

f. = xy (T,P,x )f (T, P) (3)
where y, = the activity coefficient

f = the fugacity at some arbitrary condition known as
the standard state

In this solution, the standard state is assumed to be that of
the pure substance and the fugacity of the standard state is
defined as:

V dp
fo(T,P) = P,'"'(T) -e9,at'

The Poynting pressure correction factor and the fugacity
coefficient, are assumed to be negligible (i.e., they equal
unity). Another term in the standard state fugacity is the vapor
pressure for the pure liquid, Pa (T), which can be calculated
using the Antoine Equation. The final term needed for the
liquid phase fugacity is the liquid mole fraction. In this system,
the only nongaseous components formed from the bioreactor
reactions are water and organic acids, which are assumed to
be produced as byproducts in a supernatant layer that is
separate from the sludge. Thus, the original liquid mole frac-
tion is known, and the liquid phase fugacity for each compo-
nent may be calculated.
Once the standard state fugacity is known, the next step in
obtaining the liquid phase fugacity is to calculate the activity
coefficient, y,, which is a function of composition, tempera-
ture, and pressure as seen in Eq. (3). Unless the pressure is
very high, however, its effect on the activity coefficient may
be neglected, as is done in this solution, and the van Laar
equation used to calculate the activity coefficients.
The fugacity of component i in a gas mixture may be related
to the fugacity of pure gaseous i at the same temperature and
pressure by the following relationship,

Figure 2. Flow rates (in ibmol/min) of major components using modified system.
Chemical Engineering Education

TABLE 2
Summary of Thermodynamic Model Assumptions
Liquid Phase Assumptions Justification
1) The Standard State is that of the Pure Substance -
2) Poynting Pressure Correction Accounts for situations where the actual system P pa,'. Since it is an exponential function
of P, it is small at low Ps. The bioreactor is operated at low Ps, therefore the Poynting
-*- V-dP correction factor is assumed to be a negligible term which was confirmed by preliminary
R-T calculations.
Factor = 1 e is negligible
3) The saturation fugacity coefficient q sa,= 1 Corrects for deviations of the saturated vapor from ideal gas behavior. ip' differs con-
siderably from I as T,,ea, is approached. Since the T of the system is not near any of the
components critical Ts, it is assumed that this term equals unity.
4) The activity coefficient, y,, is not a function of P The activity coefficient becomes a function of P at very high pressures. Since the system P
is low, this term is primarily a function of T and composition.
5) The activity coefficient is calculated from the The van Laar equation is typically used for binary systems. When it is employed, however,
van Laar Equation the concentrations of all other components are so small that a binary system can be as-
sumed.
Vapor Phase Assumptions Justification
1) Lewis Fugacity Rule applies (f= y f ) The LFR assumes that at a fixed T and P, the fugacity coefficient of species i is indepen-
dent of the composition of the mixture and is independent of the nature of other compo-
nents in the mixture. The LFR relies on the assumption that Amagat's rule is valid over the
entire range of pressures from 0 system P. The LFR is a good approximation at sufficiently
low Ps where the gas phase is ideal, as is the case in this system.
2) The pure fugacity coefficient, (p re, and mole For a pure, ideal gas, the fugacity is equal to the pressure (i.e., the fugacity coefficient and
fraction, y., = 1 mole fraction are both 1). It is assumed that the system follows ideal-gas behavior because
it is at low pressure, therefore the coefficient is set to unity. The mole fraction is unity
because the species is pure.

6305 m3
T = 86 F O
P = 14.7 psia

Liquid Draw C
FAcids= 1.13

F[=] Ibmol/min

TABLE 3
Mathematica Model: Traditional vs. Modified Bioreactor
Traditional BR Modified BR Single Pass
CH, Produced. Ibmol/min 7.65 8.16
CH, Sacrificed. Ibmol/min -0.765
CH, Sent to Power Plant, 7.65 7.40
Ibmol/min
Biogas CH4/CO, 0.89/1 0.72/1

f" .,(T,P, yi) -
RTIn fM T, P y) o (vi v)dP (5)

To more easily solve for the vapor phase fugacity, either
an equation of state or the principle of corresponding states
with a simplifying assumption such as the Lewis Fugacity
Rule may be used. According to this rule, the fugacity coef-
ficient of i is independent of the composition of the mixture
and of the nature of the other components of the mixture, at
constant temperature and pressure. As a result, the fugacity
of component i in a vapor mixture is expressed as:

fv,(T,P,y,)= y,-fpu,(T,P) = y,-(P-) (6)

where Y = the vapor phase fugacity coefficient of component
i th i t

1 111 6ilL .,U L IlllALUl-.
The pure phase fugacity is determined
of state such as the van der Waals equati
van der Waals equation, shown below, is
trivial equation of state, it provides a reas
of volumetric behavior of the vapor phase:
a, + P 1in I
i = e where =

(7)

In this solution, YO was calculated and w

Once all of the terms in both the liquid
fugacities have been tabulated, the criteria
may be written as:

RT VdP
x, -1. (T, P, x ).P,s' (T)-.- .e Py =

Eq. (8) is used to solve for the compos
phase and allows the calculation of the c
liquid phase in equilibrium with this vapor

RESULTS
While not all students followed the above
results obtained from the students were gen
Fall 2006

in that most of them analyzed the entire system. Figure 2 de-
picts the flow rates (in lbmol/min) of the most important com-
ponents as they move through the modified system in a single
pass, and Table 3 illustrates how the external feed stream
of H, and CO, (i.e., the modified system) affects the power
generated and summarizes the comparison of the traditional
and modified systems. The results shown in Table 3 indicate
that the current modified system does meet the objective of
accelerating the decomposition of the biomass by producing
more methane: 8.16 lbmol/min vs. 7.65 lbmol/min produced
from the modified bioreactor and the traditional bioreactor,
respectively. Although the quantity of the methane produced
increases in the modified system, the quality of the biogas
(defined as CH4 to CO, ratio) decreases from 0.89/1 to 0.72/1
in the traditional and modified system, respectively.

COURSE ASSESSMENT
using an equation Once the projects were submitted, the students were asked
on. Although the to assess the overall success of the assignment. The student
the simplest non- answers to questions 2 and 3 indicate that they overwhelm-
onable estimation ingly found the project to have enhanced their understanding
of thermodynamics (n = 8). In Table 4 (next page), a score
of 5 indicates agreement with the statement, and 1 indicates
-- + b -- disagreement.
P R-T
In addition to the four questions listed in Table 4, students
'as close to unity. answering the question, "What sources (e.g., World Wide
Web, online libraries, handbooks, publications) were useful
and vapor phase in obtaining thermodynamic data, bioreactor information,
>n for equilibrium etc.?," students listed a variety of sources including the Web
(more specifically and Web sites linked to
chemical engineering departments at large universities, e.g.,
Texas A&M). Students also indicated the use of the Manhattan
y, P',I (8) College and Columbia University online libraries, Vapor/Liq-
uid Equilibrium Data handbooks, the research articles handed
ition of the vapor out with the assignment, and microbiology and bioreaction
composition of the engineering textbooks. In their answer to the question, "Did
you program the solution yourself or use a computer program
in your solution? If computer program was used, which one
and why?," students reported using a variety of program-
development, the ming tools including Mathematica (especially for its useful
rally satisfactory, indexing feature and for repetitive and iterative calculations),
265

Excel (for both programming and graphing), and the Pro/II
Simulation Package.

CONCLUSIONS

This paper presented the results of one student's work
for a class-required computer project. Model results valida-
tion- using Pro/II and an experimental anaerobic bioreactor
-is the subject of another study in preparation. The require-
ment given to the students was to only use the thermodynamic
concepts learned during the semester to analyze and propose
a feasible solution to a current environmental or industrially
significant problem. The outcome of such an exercise allows
students to apply sometimes-abstract thermodynamic con-
cepts to an important problem while training them to focus
on the big picture: how to find a solution to the problem.
An additional benefit is that students obtain an appreciation
for what commercially available thermodynamic packages
involve, as well as their capabilities, since students find the
Also, the exercise gives students a sense of accomplishment in
that they applied the principles of thermodynamics to analyze
and propose feasible, realistic solutions to problems they may
encounter during their careers.

Lastly, as the need for renewable energy sources grows,
research and development will require a workforce that is
well educated and trained to develop the technologies neces-
sary for a sustainable future. The example presented in this
paper demonstrates that such training is possible through an
in-depth approach to a societal problem. It also sets the stage
for further development of the chemical engineering curricu-
lum at Manhattan College to include grounding in alternative

energy sources and sustainability following the call of J.W.
Sutherland, et al.,"19 of Michigan Technological University
for the need for "globally aware students."
NOMENCLATURE

M' Fugacity of component, i, in the liquid mixture

fv
M' Fugacity of component, i, in the vapor mixture.

x Liquid phase mole fraction of species, i.
y (T, P, x) Activity coefficient of species, i ,as a function
of temperature, pressure and liquid phase
mole fraction.

f (T,P)

p a, (T)

V
Y,
P
4

Pure component fugacity of, i, in the liquid
phase.

Vapor pressure of species, i, as a function of
temperature.

Fugacity coefficient of the saturated vapor of
species, i.
Molar volume of the liquid (condensed) phase.
Gas phase mole fraction of species, i.
Total pressure of the system.
Fugacity coefficient of species, i.
Equivalence ratio.

REFERENCES
1. Castaldi, M., L. Dorazio, and N. Assaf-Anid, "Relating Abstract
Concepts of Chemical Engineering Thermodynamics to Current, Real
World Problems," Chem. Eng. Ed., 38(4) 268 (2004)
2. Kauser, J., K. Hollar, F. Lau, E. Constans, P. Von Lockette, and L.
ASEE Annual Conference and Exposition: Vive L'ingenieur; 4593-4600
(2002)
Chemical Engineering Education

TABLE 4
Course Assessment
Question 5 4 3 2 1
1. Overall, do you feel that the class lectures 12.5% 75% 12.5% -
and homework provided you with the neces-
sary background for developing a solution to
the computer project?
2. Did the computer project give you a better 12.5% 75% 12.5% --- --
understanding of thermodynamic principles
such as fugacity, solubility, and multi-phase
equilibrium, and how they are used in practi-
cal situations?
3. Was the computer project a relevant, 75% 25% -
practical, and open-ended application of the
principles taught in the class?
4. Did the computer project enhance your 12.5% 12.5% 50.0% 12.5% 12.5%
research skills?

3. Farley, E.T., and D.L. Ernest, "Application of Power Generation Mod-
eling and Simulation to Enhance Student Interest in Thermodynam-
ics," Modeling and Simulation. Proceedings of the Annual Pittsburgh
Conference. 21(3), 1275 (1990)
4. Cengel, Y.A., "Intuitive and Unified Approach to Teaching Thermody-
namics," Proceedings of the ASME Advanced Energy Systems Division,
36,251 (1996)
5. Lombardo, S.. "Open-Ended Estimation Design Project for Thermo-
dynamics Students," Chem. Eng. Ed. 34(2), 154 (2000)
6. Tsatsaronis, G., M. Moran, and A. Bejan. "Education in Thermo-
dynamics and Energy Systems," American Society of Mechanical
Engineers, Advanced Energy Systems Division (Publication) AES, 20
644 (1990)
7. Reistad, G.M., R.A. Gaggioli, A. Bejan, and G. Tsatsaronis, "Ther-
modynamics and Energy Systems-Fundamentals. Education, and
Computer-Aided Analysis," American Society of Mechanical Engi-
neers, Advanced Energy Systems Division (Publication) AES. 24. 103
(1991)
8. Shaeiwitz, J.A.. "Teaching Design by Integration Throughout the
Curriculum and Assessing the Curriculum Using Design Projects,"
International Journal ofEng. Ed., 17, 479 (2001)
9. Garcia-Ochoa, F., V.E. Santos, L. Naval. E. Guardiola, and B. Lopez,
"Kinetic Model for Anaerobic Digestion of Livestock Manure." Enz.vyme
and Microbial Technology, 25. 55 (1999)

10. Jagadish, K.S., H.N. Chanakya, P. Rajabapaiah. and V. Anand, "Plug
Flow Digesters for Biogas Generation from Leaf Biomass." Biomass
and Bioenergy. 14(5/6), 415 (1998)
11. Castelblanque, J., and F. Salimbeni, "Application of Membrane Sys-
tems for COD Removal and Reuse of Waste Water from Anaerobic
Digesters," Desalination, 126, 293 (1999)
12. "Chemical Engineering" section, About.com, com>
13. Prausnitz, J., R.N. Lichtenthaler, and E. Gomes de Azevedo, Molecular
Thernmodynanics of Fluid-Phase Equilibria, Prentice Hall International
Series. Upper Saddle River, NJ (1999)
14. Klass, D.L.. Biomass for Renewable Energy, Fuels, and Chemical,
Academic Press. New York, 452 (1998)
15. Madigan, M.T., J. Martinko, and J. Parker, Brock Biology of Microor-
ganisms, Prentice Hall, Upper Saddle River, NJ (2000)
16. Muller, E.A., "Thermodynamics Problem with Two Conflicting Solu-
tions," Chem. Eng. Ed., 34(4), (2000)
17. Morley. C.,
18. Sutherland, J.W., V. Kumar, J.C. Crittenden, M.H. Durfee, J.K. Gersh-
enson, H. Gorman, D.R. Hokanson, N.J. Hutzler, D.J. Michalek, J.R.
Mihelcic, D.R. Shonnard, B.D. Solomon, and S. Sorby, "An Educa-
tion Program in Support of a Sustainable Future," American Society
of Mechanical Engineers, Manufacturing Engineering Division, 14,
611 (2003) 1

Fall 2006

Incorporating

COMPUTATIONAL CHEMISTRY

into the ChE Curriculum

JENNIFER WILCOX
Worcester Polytechnic Institute Worcester, MA 01609

In many engineering curricula it is difficult to cover the
fundamental concepts that are required to provide all
students with an optimum base for the solution develop-
ment of new problems and applications. Although this task
is daunting, replacing the learning and understanding of
fundamental concepts with starting parameters and a list of
equations to use as tools is not a solution. Such an approach
subsequently limits the capabilities and potential accomplish-
ments of the students.
This trap is easy to fall into, however, since it is nearly im-
possible to cover all of the fundamentals in addition to the ap-
plications. Yet a failure to emphasize these basics could mean
putting emerging chemical engineers at a disadvantage against
chemists or physicists, who may be able to develop new ideas
more readily because their training through education has
taught them to derive the equations they are using. Engineers
are typically admired for their ingenuity and creativity, but
with a curriculum that does not obligate them to derive and
to consistently ask "why" and "from where," engineers will
soon lose the merits for which they are so well known.
Within a graduate-level chemical engineering course, fun-
damental chemical principles combined with computational
chemistry software were used as a tool to bridge the gap that
often exists between chemistry and applications within the
Copyright ChE Division of ASEE 2006

field of chemical engineering. In the case of reactor design
problems in which rate expressions must be known, activa-
tion energies and rate constants are typically provided as
input parameters for a particular design equation. Since more
sophisticated methods for approximating rate constants are
not taught in traditional chemical engineering courses, the
development of a rate expression was chosen as one of the
main objectives of this computational chemistry course. The
theoretical calculation of a rate expression involves many
tasks, including the development of a quantum mechanical-
based potential energy surface (PES) and the understanding
of reaction kinetic tools such as transition state theory. Similar
methodologies have emerged recently in the literature for as-
similation into graduate chemistry coursework.r' 2] The current
methodology, however, is different from its typical inclusion

Chemical Engineering Education

Jennifer Wilcox is an assistant pro-
fessor in the Chemical Engineering
Department at Worcester Polytechnic
Institute. She received her B.S. de-
gree from Wellesley College in math-
ematics and her M.A. and Ph.D. from
the University of Arizona in chemical
engineering.

within a chemistry course since it has been incorporated into
a chemical engineering curriculum, where it serves to couple
fundamental chemical principles to applications in chemical
engineering through a combination of ab initio theory and
reaction kinetics. During the fall 2005 semester this course
was offered for the first time in the Chemical Engineering
Department at Worcester Polytechnic Institute. A six-week
assignment termed, "Learning through a Reaction Example,"
served as the main driving force throughout the course and
was reflected both in lecture material and student exercises.
The course methodology carried out to accomplish the goal
of bridging the gap between fundamental principles in
chemistry to applications in chemical engineering is self-
contained, in that it can be adopted by any instructor wishing
to achieve this goal through offering a similar class within
his/her department.

COURSE OVERVIEW
The course spanned 14 weeks and was held for 1.5 hours
twice a week; homework was assigned on a weekly basis.
The course was divided into the following sections with less
than half taking place outside the computer lab:

> Principles by which ab initio-based methods
and basis sets are comprised. Background of
key features and concepts of quantum mechanics
(QM) were taught. Homework assignments in-
cluded the following: methods used in solving ap-
proximations to the SWE, e.g., variational meth-
ods and perturbation theory; classical problems
from QM, e.g., particle in a 1-D box; harmonic
oscillator; and the hydrogen atom. Homework
assignments throughout this aspect of the course
required a background in calculus and differential
equations. A brief review of complex numbers and
differential-equation solution types was given.
These topics comprised four weeks of the course,
culminating with a closed-book, in-class exam.

> "Learning Through a Reaction Example." This
assignment included five weekly projects and a
take-home exam that required students to compile
the individual components into the form of scien-
tific papers (so that students could gain familiarity
with writing in a scientific manner). An additional
manuscript is being submitted for publication that
describes further details and results of this assign-
ment, purely through the students' perspective.r"
In addition, students reflect on each of these
four sections of the course in detail, determining
which exercises were more beneficial than others
Fall 2006

and why. Throughout the "Learning Through
a Reaction Example" topic, a combination of
lecture and interactive learning through computa-
tional in-class lab exercises was used, i.e., using
the Gaussian98 software package for electronic
energy predictions. Extraction of these energies
combined with reaction kinetic tools such as po-
tential energy surface development and transition
state theory (TST) led to the development of rate
expressions. To ensure mastery of the software, an
in-class, computer-based exam was given seven
weeks into the course, i.e., three weeks after the
software was introduced.

> Final project. During the last four weeks of the
course, students were asked to choose a topic for a
final project. It was required that the final project
relate to a student's research project, i.e., within
their senior thesis, M.S. thesis, or Ph.D. disserta-
tion. The goal of this final project was to apply the
computational and kinetic tools learned through-
out the course to an aspect within their chemical
engineering research. In some cases, the research
area of focus required an advanced background in
molecular modeling that the course was not able
to provide in just 14 weeks, and in these cases the
students gained mastery of the literature available
on the computational chemical aspect of their
research. Additionally, the students used what was
learned from the course to provide insight into the
chemical mechanisms that may play a role in the
explanation of experimentally observed phenom-
ena. The goal of this final exercise was to provide
a way to evaluate students' understanding of the
material, with a measure of the course success
dependent upon whether a student was able to ef-
fectively apply knowledge gained from the course
to their research in a novel way. Some examples
of this application include:
Electrochemical water-gas shift reactions on plati-
num and ruthenium catalysts
Application: fuel cell chemistry
Adsorption mechanisms of MTBE, chloroform, and
1,4-dioxane with cations
Application: separation of contaminants from
groundwater using zeolites
Mechanism development of sulfur's role in poison-
membranes

With regard to several of the student projects -such as the
one involving the application of ab initio theory for modeling
complicated catalytic processes such as those involved in fuel
cell research-the student completed the final project with an
understanding of the computational literature in this field and
a visual interpretation of the mechanisms involved within the
complexities of the process, which will likely benefit him by
providing focused direction when deciding which experiments
to carry out in the lab. This theoretical understanding became
the goal of this student's project since heterogeneous modeling
was outside the scope of the course. With respect to the sec-
ond project listed above, the student used ab initio energetic
predictions along with electrostatic potential and molecular
orbital maps to understand the reactivity between groundwater
contaminants and zeolite exchange ions. This student has since
had a paper accepted and has presented her research at the
International Conference in Engineering Education in Puerto
Rico in July 2006.141 Therefore the measure of success spans
a wide range, whether it is based on the direct inclusion of ab
initio-based calculations in a student's work or based on an
appreciation and understanding of the ab initio language to a
level that allows for material retention from a peer-reviewed
article within the student's specific research area.
If one wished to integrate molecular modeling and compu-
tational chemistry techniques into a graduate curriculum to
supplement the chemical engineering background tradition-
ally acquired, carrying out this reaction assignment would
ensure student mastery of the computational tools necessary
for incorporating a molecular perspective into their graduate
research. Therefore, it is this aspect of the course that will be

COURSE SPECIFICS

In the "Learning Through a Reaction Example" assign-
ment, elementary gas-phase reactions were considered for a
complete thermodynamic and kinetic analysis. The goal was
to produce a high-level potential energy surface based upon
ab initio energetic, and to derive accurate rate expressions for
the reaction using transition state theory. Computational-based
ab initio techniques were employed to solve approximations
to the Schrodinger wave equation (SWE), which describes
the location and energetic associated with the electrons in
a given system. The "level of theory" chosen to investigate
the species within a given reaction requires two components,
i.e., a mathematical method to solve the approximation to the
SWE and a wave function (spatial description of the electrons
in space).

This computational chemistry course was highly techno-
logically based with approximately two-thirds of the classes

involving active learning through the use of computers. Stu-
dents used the software package Gaussian981'1 to calculate
the electronic energies from approximations to the SWE. To
visualize vibrational frequencies, chemical bonding, electron
density maps, and molecular orbital maps, gOpenMol soft-
ware was employed. In a traditional course in introductory
chemistry these topics are covered in detail, but oftentimes
teaching students about them is difficult due to the underlying
abstract quantum chemistry involved. Using the visualiza-
tion software, the students were responsible for developing
electron density and molecular orbital maps to gain under-
standing into the chemical reactivity of various species.
Straightforward molecules such as water and methane were
introduced, and in additional assignments students explored
molecules of increasing interatomic bonding complexity
such as cyclohexane and 1,4-dioxane. For the development
of the quantum mechanical-based potential energy surfaces,
MATLAB software was used. A Sun Microsystems Sun Fire
V20z server with a dual AMD Opteron 64 bit processor and
4 gigabytes of memory with a 73 gigabyte hard disk was
devoted specifically for the course. The software program
WebMO 4.1 was used as an interface to submit jobs to Gauss-
ian98 through the Sun server. Students were able to submit
their calculations to the server such that the local desktop
computers could remain active throughout each class period;
this also provided students with the flexibility to work on
homework assignments and submit jobs from any computer
with Internet capabilities.

DESCRIPTION OF REACTION ASSIGNMENT
One of the following elementary gas phase reactions was
assigned to each pair of students in the class.
H + Cl, HC + H (1)

D2 +C1- DCl+D

H, +F F HF+H

D, + F -DF + D

F, + H HF + F

Two students investigating the same reaction were doing
so for validation of the molecular results generated with each
investigation being performed at a unique level of theory, i.e.,
method and basis set combination.
Step One: Students were asked to retrieve experimentally
based chemical properties of the species within their assigned
reaction in addition to experimental thermochemical and
kinetic data for the total reaction. The chemical properties
included equilibrium bond distances, vibrational frequencies,
Chemical Engineering Education

dipole moments, and rotational constants. Seeking these
experimental data required students to gain familiarity with
standard references such as JANAF'6l tables, the Handbook
of Chemistry and Physics,17' and Herzberg spectroscopy
texts.8E' The experimental thermochemical data included
reaction enthalpies, entropies, Gibbs free energies, and
equilibrium constants using the NIST Chemistry Web-
Book.[91 To locate experimental kinetic data for the reaction,
students were encouraged to perform literature searches
in addition to accessing the data available in the NIST
kinetic database.191
Step Two: Within this step of the assignment students per-
formed geometry optimization and spectroscopic calculations
on their assigned reaction species. They were required to
perform the calculations at varying levels of theory, includ-
ing the density functional method, i.e., Becke-3-parameter-
Yee-Lang-Parr (B3LYP), as well as Hartree-Fock, and the
second order perturbation method-Moller-Plesset (MP2).
Additionally, higher electron-correlated methods such as
quadratic configuration interaction (QCI) and coupled cluster

(CC) techniques were also explored. Both Pople and Dunning
basis sets were considered with each of these calculational
methods. The complexity of the basis sets assigned ranged
from minimal-such as the double-zeta Pople basis set,
6-31G-to more extensive, including both diffuse and po-
larization functions-such as the triple-zeta Pople basis set,
6-311++G**. Students were assigned nine levels of theory
for the energetic and spectroscopic predictions, and asked to
Step Three: Within this step students compared their theoreti-
cal predictions to the experimental data that was compiled in
step one of the assignment. It is this aspect of the assignment
that allows the students to be in control of their learning; they
are able to see how well a chosen level of theory agrees to
experiment. There is flexibility as well since the students are
to those assigned. An example of equilibrium geometry and
spectroscopic predictions for Reaction (2) is shown in Table 1.
Thermochemical predictions, including reaction enthalpies,
entropies, and Gibbs free energies, at varying levels of theory,

TABLE 1
Comparison of Chemical Properties of Species from D2 + Cl DCI + D
Bond Vibrational Dipole Rotational
Theory Length Frequency Moment Constant
(A,) (cm-') (Debye) (cm1')
DCI D, DCI D, DCI DC1 D,
B3LYP/LANL2DZ 1.3149 0.7435 1943 3153 1.80 5.11 30.28
HF/6-31G 1.2953 0.7297 2097 3289 1.87 5.27 31.44
HF/STO-6G 1.3112 0.7105 2097 3886 1.77 5.14 33.16
MP2/6-31G 1.3174 0.7376 1970 3206 1.88 5.10 30.77
MP2/6-311+G 1.3269 0.7376 1943 3149 1.89 5.02 30.77
MP2/6-311+G(d,p) 1.2731 0.7383 2214 3206 1.44 5.46 30.71
MP2/6-31+G* 1.2810 0.7375 2177 3206 1.53 5.39 30.77
MP2/6-311(3df,3pd) 1.272 0.7367 2190 3195 1.17 5.47 30.84
QCISD/6-31G 1.3262 0.7462 1901 3089 1.88 5.03 30.06
QCISD/6-311+G 1.3262 0.7465 1875 3018 1.71 5.03 30.04
QCISD/6-311+G** 1.2758 0.7435 2183 3126 1.33 5.43 30.28
QCISD/6-311++G** 1.2762 0.7435 2181 3126 1.32 5.43 30.29
CCSD/6-31G 1.3261 0.7462 1901 3089 1.88 5.03 30.06
CCSD/6-311+G 1.3365 0.7465 1876 3018 1.89 4.95 30.04
CCSD/cc-pVDZ 1.2905 0.7609 2144 3100 1.16 5.31 28.91
CCSD(T)/6-311G** 1.2772 0.7435 2174 3127 1.46 5.42 30.28
CCD/aug-cc-pVDZ 1.2897 0.7610 2151 3084 1.16 5.32 28.90
CCD/cc-pVTZ 1.2748 0.7421 2172 3127 1.18 5.44 30.39
Experimental' 1.2746 0.7420 2145 3116 5.44 30.44
t RefJ7 141

Fall 2006

are presented for Reaction (5) in Table 2. In most cases, the
students would choose more than three additional levels of
theory for investigation in an effort to obtain a theoretical
prediction with minimal deviation from experiment. Within
this step of the assignment students learned how the addition
of polarization and diffuse functions to a basis set can influ-
ence the theoretical predictions. Of course, lecture material
included a discussion of the details of methods and basis sets;
however, the interactive experience of testing, checking, and

0.7 075 0.8 0.85 0.9 0.95 1
H.H

Figure 1. PES for the reaction H2 + F--- HF + H generated
at the QCISD/6-311 G(3df,3pd) level of theory.

comparing to experiment was far more valuable, allowing
these concepts to sink in to a deeper level of understanding
from the student perspective. Class at this time included dis-
cussions concerning the difference in accuracy of the various
levels of theory and the reasons associated with why some
levels work better than others. Additionally, discussions also
included why at times some levels of theory work, but not
necessarily for the right reasons, i.e., cancellations in error
could provide a reasonable heat of reaction prediction in
one case, but may deviate from experiment in terms of the
predicted equilibrium geometry. The goal of matching the ex-
perimental data provided a motivation for the students to push
forward through obstacles that are typical of a traditional lec-
ture-formatted curriculum. For example, traditional teaching
methods such as Microsoft Office PowerPoint presentations
or conventional rote lectures tend to neglect participation of
the students, consequently allowing their minds to wander,
losing the ability to grasp the material at hand. Providing a
motivated student with an objective and the responsibility
for his or her own learning through a series of interactive
exercises ensures active participation, which undoubtedly
enhances the likelihood of material retention.
Step Four: This step involves the development of a high-
level potential energy surface (PES). For a student to proceed
with this step, two criteria must be met, i.e., students must
first choose a level of theory that accurately predicts the heat
of reaction and equilibrium constant. Once a student obtains
a level of theory which predicts a heat of reaction to within
2 kcal/mol to experiment and an equilibrium constant to

TABLE 2
Thermochemistry Comparison for F + H -HF + F
Theory H S G Keq
(kcal/mol) (cal/mol*K) (kcal/mol)
B3LYP/LANL2DZ -91.61 1.841 -92.16 3.87(+67)
HF/6-31G -121.20 1.904 -121.7 2.01(+89)
MP2/6-31G -82.76 1.677 -83.26 1.16(+61)
MP2/6-311+G -91.99 1.586 -92.46 6.48(+67)
MP2/6-311+G(d,p) -103.8 1.787 -104.3 3.44(+76)
QCISD/6-31G -84.52 1.578 -84.99 2.14(+62)
QCISD/6-311+G -94.24 1.510 -94.69 2.82(+69)
CCSD/6-31G -84.65 1.577 -85.12 2.68(+62)
CCSD/6-311+G -94.44 1.513 -94.89 3.91(+69)
CCSD/aug-cc-pVDZ -104.4 1.798 -104.9 9.08(+76)
CCSD(T)/6-311G** -98.96 1.607 -99.44 8.56(+72)
QCISD(T)/6-311G** -98.92 1.612 -99.40 7.92(+72)
Experimental -98.27 3.596 -99.34 7.20(+72)
tNumbers in parenthesis denote powers of 10.
1 Re [6, 9, 15]

within an order of magnitude of
experiment, he or she can proceed
to develop a PES at this chosen
level of theory. A PES generated
from the class for Reaction (3) at
the QCISD/6-311G(3df,3pd) level
of theory is presented in Figure 1.
The software program MATLAB
was employed for the PES plots.
Most of the surfaces generated
in the class consisted of approxi-
mately 200 single-point energies.
Since the reactions assigned were
all elementary gas-phase reactions
involving, at most, three atoms,
the largest transition structures
were three-atom complexes. It
was assumed that each activated
complex was linear so that two
degrees of freedom could be con-
sidered along two dimensions of the
three-dimensional PES plot, with
Chemical Engineering Education

------I -

the third dimension serving as the potential energy. From-
the PES plots students extracted the relative geometry of
the reaction's activated complex. As a further check that this
activated complex corresponded to a true transition structure,
a frequency calculation was performed to ensure the existence
of one negative frequency along the reaction coordinate.
Oftentimes this additional calculation would provide more
accurate coordinates of the transition structure, ensuring ac-
curacy in the barrier-height calculation.
Step Five: The last step of the assignment involved the cal-
culation of rate expression parameters, i.e., the rate constant,
using the hard-sphere collision model (HSCM) for an upper
bound and transition state theory (TST) for a more accurate
rate prediction. In determining the rate constant for each
reaction, the value predicted by transition state theory,'1" Eq.
(6), was modified with the tunneling correction of WignerE"I
given by Eq. (7), so that the final rate constant value was
given by Eq. (8),

kTST kbT QTs e RT (6)
h QQ,2

k- 1 7hcv )
S 24 kbT

k kTT -kT cm
mol -s

where v represents the single negative frequency value of
the transition structure and the partition function, QTta =
QtransQrotQvibQelec Two lectures and one homework assignment
were dedicated to providing the students with an introductory
background in statistical mechanics so that they could under-
stand the assumptions that are made in Gaussian to obtain the
partition function data. Three to four lectures were dedicated
to reaction kinetics in which the HSCM and TST were taught.
Students were required to work through two
TST problems in a homework assignment
before applying the knowledge to their reac-
tion example. Further details of TST can be
found in standard kinetic texts, which served Temp Range
(K)
as references for the course.112 31 In addition, (K)
the barrier heights required for Eq. (6) were 291-1192
extracted from the previously developed 1000-1500
high-level PES. The barrier height was calcu- 600-1000
lated by taking the energy difference between 200-1000
the thermal-corrected (including zero-point 298.15-2500
energies) transition structure and the sum of
the thermal-corrected reactant species. 298.15-2500
The calculation of the rate constant based in pae
TNumbers in paren
upon the hard-sphere collision model was
Fall 2006

performed using Eq. (9),

kC N 8Te cm3
7k12 mol.s

where the barrier height, E is the same as for kTSI, ,t1 is the
reduced mass, and 12 is the collision diameter. Since Ea is
already known, and t, can be determined with a simple cal-
culation, the only difficulty was in determining the collision
diameter. Here, the lack of experimental data required the
use of estimation techniques to find an approximate value of
o. The primary technique utilized was a traditional approach
based on the critical properties of the species in the reaction as
shown in Eq. (10), in which V and Z are the critical volume
and critical compressibility parameters, respectively.
1 6
0= 0.1866VcjZc A (10)

An example of the predicted reverse rate expressions for
Reaction (1) calculated at the CCSD/6-311G(3df,3pd) level
of theory compared to literature predictions and experiment
is presented in Table 3. Figure 2 (next page) is a graphical
representation of the rate prediction for the forward direction
of Reaction (1), showing that this high level of theory with
a modest kinetic tool such as TST provided a fairly accurate
kinetic prediction.

CONCLUSIONS

A graduate-level chemical engineering course in com-
putational chemistry was developed that served to provide
chemical engineering students with an introduction to a
molecular approach in understanding chemical reactivity.
Often there exists a disconnect between the topics in an ap-
plied engineering discipline and the fundamental chemical
and physical principles on which applications are based. This
course served as a means to provide students with additional

TABLE 3
comparison of Arrhenius Parameters for the Reaction,
HCI + H -- Cl + H2
A' Ea Reference
(cmn/mol*sec) (kcal/mol)
3.114(13) 4.84 Allison, et al.1"7
2.318(13) 4.25 Allison, et al.171
7.94(12) 4.39 Lendvay, et al.u1'
5.015(13) 4.39 Present work (TST)
CCSD/6-311G(3df, 3pd)
6.134(14) 4.67 Present work (HSCM)
thesis denote powers of 10.

... TST {CCSDI6-311G(3df,3pd)}
34 FHSCM {CCSD/6-31 1G(3df,3pd)
3* Allison et al. [17]
32 + Kumaranetal. [19]
*. \ Miller and Gordon [21]
30 X Westenberg and de Hass [22]

) 26 -

S 24

22

20 *
0 0.001 0.002 0.003 0.004
1/T (K"1)

Figure 2. Rate-constant comparison for the reaction,
Cl + H2 HCI + H.

tools to supplement their graduate research projects. This
connection was established through the development of a
reaction assignment which led students through a series of
steps ranging from an introduction to quantum mechanics to
the development of a potential energy surface, from which
barrier heights were extracted for predicted rate expression
calculations. This series of steps ensured students compre-
hension of the concepts covered, which was evident based
upon final projects that required the students to implement
these tools of computational chemistry into their individual
research projects.

ACKNOWLEDGMENTS
The author acknowledges graduate students Erdem Sasmaz,
Nicole Labbe for use of their reaction results in this work. In
script by Caitlin A. Callaghan are appreciated. Finally, WPI s
Unix administrator, Mark Taylor is recognized for assisting in
the administration of the course-designated server.

REFERENCES
1. Leach, A.G., and E. Goldstein, "Energy Contour Plots: Slices through
the Potential Energy Surface That Simplify Quantum Mechanical
Studies of Reacting Systems," J. Chem. Educ., 83, 451 (2006)
2. Galano, A., J.R. Alvarez-Idaboy, and A. Vivier-Bunge, "Computational
Quantum Chemistry: A Reliable Tool in the Understanding of Gas-
Phase Reactions," J. Chem. Educ., 83, 481 (2006)
3. Labbe, N., S. Vilekar, E. Sasmaz, B. Padak, N. Pomerantz, J.-R.
Pascault, P. Vallieres, G. Withington, C. Callaghan, and J. Wilcox,
"The Connection Between Computational Chemistry and Chemical

Engineering: A Students Perspective," in progress
4. Labbe, N., J. Wilcox, and R.W. Thompson, "An ab initio Investigation
of Cyclohexane and Zeolite Interactions," Proceedings of the 2006
International Conference in Engineering Education (2006)
5. Frisch, M.J., G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb,
J.R. Cheeseman, V.G. Zakrzewski, J.A. Montgomery Jr., R.E. Strat-
mann, J.C. Burant, S. Dapprich, J.M. Millam, A.D. Daniels, K.N.
Kudin, M.C. Strain, 0. Farkas, J. Tomasi, V. Barone, M. Cossi, R.
Cammi, B. Mennucci, C. Pomelli, C. Adamo, S. Clifford, J. Ochter-
J.J. Dannenberg, D.K. Malick, A.D. Rabuck, K. Raghavachari, J.B.
Foresman, J. Cioslowski, J.V. Ortiz, A.G. Baboul, B.B. Stefanov, G.
Liu, A. Liashenko, P. Piskorz, I. Komaromi, R. Gomperts, R.L. Martin,
D.J. Fox, T. Keith, M.A. Al-Laham, C.Y. Peng, A. Nanayakkara, M.
Challacombe, P.M.W. Gill, B. Johnson, W. Chen, M.W. Wong, J.L.
Andres, C. Gonzalez, M. Head-Gordon, E.S. Replogle, and J.A. Pople,
Gaussian 98, Gaussian, Inc., Pittsburgh (1998)
6. Chase, M.W. Jr., NIST-JANAF Themochemical Tables, 4th Ed., J. Phys.
Chem. Ref Data, Monograph 9, 1-1951 (1998)
7. CRC Handbook of Chemistry and Physics, 58th Ed. CRC Press,
Cleveland, Ohio (1978)
8. Huber, K.P., and G. Herzberg, Molecular Spectra and Molecular Struc-
ture. IV Constants of Diatomic Molecules, Van Nostrand Reinhold Co.
(1979)
9. NIST Computational Chemistry Comparison and Benchmark Database,
NIST Standard Reference Database Number 101, Release 12, Aug.
2005, Editor: Russell D. Johnson III,
10. Eyring, H., "The Activated Complex in Chemical Reactions," J. Chem.
Phys. 3, 107 (1935)
11. Wigner, E., "Crossing of Potential Thresholds in Chemical Reactions,"
Z. Phys. Chem. B., 19, 203 (1932)
12. Simons, J., An Introduction to Theoretical Chemistry, Cambridge
University Press (2003)
13. Steinfeld, J.I., and J.S. Francisco, Chemical Kinetics and Dynamics,
Prentice Hall (1999)
14. Shimanouchi, T., Tables of Molecular Vibrational Frequencies, Con-
solidated Volume 1, 39 (1972)
15. Cox, J.D., D.D Wagman., and V.A. Medvedev, CODATA Key Values
for Thermodynamics, Hemisphere, New York (1989)
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Study of the H + HCI +-+ H, + Cl Reaction from 298 to 1192 K," J.
Phys. Chem. 97, 1409 (1993)
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proved Potential Energy Surface for the H,CI System and Its Use for
Calculations of Rate Coefficients and Kinetic Isotope Effects," J. Phys.
Chem., 100, 13575 (1996)
18. Lendvay, G., B. Laszlo, and T. Berces, "Theoretical study ofX + H, --
XH + H and Reverse Reactions (X = F, Cl, Br, I) using a new empirical
potential energy surface," Chem. Phys. Lett., 137, 175 (1987)
19. Kumaran, S.S., K.P. Lim, and J.V. Michael, "Thermal Rate Constants
for the CI+H, and Cl+D, Reactions Between 296 and 3000 K," J. Chem.
Phys., 101, 9487 (1994)
20. Westenberg, A.A., and N. de Haas, "Atom-Molecule Kinetics using
ESR Detection. IV. Results for Cl + H, +-* HCI + H in Both Directions,"
J. Chem. Phys., 48, 4405 (1968)
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balance in the Cl+H, reaction," J. Chem. Phys., 75, 5305 (1981) J

Chemical Engineering Education

Bma curriculum

An International Comparison of

FINAL-YEAR

DESIGN PROJECT CURRICULA

SANDRA E. KENTISH AND DAVID C. SHALLCROSS
University of Melbourne Victoria, Australia 3010
The final-year design project has been an essential part
of the chemical engineering undergraduate curriculum David Shallcross is an associate professor
S. in the Department of Chemical and Biomo-
for many decades. Some would argue that the structure lecular Engineering at the University of Mel-
of this subject has changed little.m As will be shown in this bourne. He is founding chair of the Institution
paper, however, there is considerable evidence of a substantial of Chemical Engineers' Education Subject
Group and is editor of the international jour-
shift in the teaching of the design project to better reflect the nal Education for Chemical Engineers. He
demands of both a changing discipline and the wider expecta- is the author of three books and is active in
of future employers. promoting the profession within the second-
tions of future employers. ary-school community.
This paper reviews design project teaching at 15 chemical
engineering departments across Australia, Singapore, and
the United Kingdom. Information on Australian courses was Sandra Kentish (Ph.D.) is a senior lecturer
obtained during a design project workshop organized by the within the Department of Chemical and Bio-
molecular Engineering at the University
Australian-based Education Subject Group of the Institution of Melbourne and the coordinator of their
of Chemical Engineers, and sponsored by Aker Kvaerner Aus- capstone Design Project subject. She joined
the department in 2000, after working within
tralia. The workshop was held Feb. 14-15, 2005. Information the chemical industry for nine years. Her
regarding the courses in Singapore and the UK was obtained research interests are focused in two areas:
during a study tour by one of the authors in July 2005. membrane separations and sonoprocess-
ing (the use of ultrasound in the chemical
Historically, the capstone design project was developed industry). r -
to draw together the design techniques developed during
Copyright ChE Division of ASEE 2006
Fall 2006 27:

the chemical engineering course into a single, integrated
project. Reference to the instructions for the 1974 Institu-
tion of Chemical Engineers design projects21 indicates that
the requirements were for process selection and descrip-
tion, material and energy balances, process and mechanical
design, and costing. There was a requirement to complete a
Hazard and Operability study, but generally the emphasis on
health, safety, and the environment was minimal. The learn-
ing outcomes were clearly intellectual ability and practical
design skills. Transferable skills such as teamwork, oral com-
munication, and open-ended problem-solving ability were
not considered relevant. By 1991,13] the scope of the project
assessment, energy efficiency, and environmental impact.
At this stage, however, there was still no evidence of generic
skill development.
More recently, emphasis within chemical engineering edu-
cation has shifted to focus on learning outcomes beyond only
a technical nature. Transferable skills that will assist graduates
in a range of employment roles are gaining importance.[4-7]
Evidence from the institutions considered here shows that the
final-year design project is evolving as a crucial mechanism for
developing these skills because of its position at the tail end of
the course and the minimal demands for technical knowledge
transfer. Indeed, the design project acts as the "exit transition"
subject at most institutions, bridging the gap from university
study to a real-world position.

The greater computing and
word processing power available
to today's students and the ready
resources has enabled the design
project scope to expand. Larger
and/or more diverse projects
are being undertaken focusing
such as sustainability, process
safety, and the use of design
standards and regulations. Pro-
cess simulation can be practiced
and practical computing skills
developed.
A common feature of chemical
engineering courses considered
here is that they are accredited
by the UK-based professional
body, Institution of Chemical
Engineers (IChemE).171 The
IChemE promotes the concept
of a design portfolio, in which a
number of design exercises are
completed over the curriculum.
There was certainly evidence
276

of a trend in this direction, with many institutions running
product design projects in separate subjects, as well as design
exercises in the earlier years of study. This paper, however,
focuses in particular on the final project at the M.Eng. level,
which is the fourth year of continuous study at almost all in-
stitutions (the fifth year at Scottish universities). The IChemE
accreditation guide'71 indicates that at this M.Eng. level:
.. the course shall include a major design exercise demon-
strating that issues of complexity have been appropriately
addressed. The major project is normally undertaken in
the final year and is normally weighted at 20 credit points
minimum (This equates to 16.6% of the final-year credit).
The major project at M.Eng. level can be up to 50% of the
final-year credit.
Table 1 shows that among the departments considered, the
design project had a credit range between 12.5 and 40% of
the final year. In most cases, the project ran across either a
single semester or the full year. Some English institutions,
however, undertook the design project in the penultimate
year of an M.Eng. course to accommodate B.Eng. students
into a common program.
It should be noted that within the UK system, a degree of
uniformity between departments is provided by the use of
external examiners. All design project briefs, assessments,
and samples of final project submissions are reviewed by a
senior academic from another institution. Within Australia, a

TABLE 1
Chemical Engineering Departments Considered in this Study
and the Format of Their Capstone Design Projects
Country Percent Timing of No. of Written
of Final- Project Submissions
Year
Credit
Curtin University Australia 25.0 Final Semester 12
James Cook University Australia 25.0 Full Final Year 5
Monash University Australia 25.0 Final Semester 1
RMIT University Australia 25.0 Final Semester 4
University of Adelaide Australia 25.0 Final Semester 1
University of Melbourne Australia 18.75 Final Semester 2
University of New South Australia 18.75 Penultimate 7
Wales Semester
University of Newcastle Australia 25.0 Full Final Year 3
University of Queensland Australia 25.0 Final Semester 5
University of Sydney Australia 33.3 Full Final Year 5
National University of Singapore 12.5 Final Semester 3
Singapore
University College London UK 37.5 Full Third Year 8
University of Birmingham UK 40.0 Full Third Year 8
University of Nottingham UK 42.0 Full Year 1
University of Edinburgh UK 33.0 Full Year 1
Chemical Engineering Education

similar degree of uniformity is engendered by the availability
of an Australia-wide design project student prize (the Aker
Kvaerner award) and several regional prizes. For example, the
Aker Kvaemer Prize guidelines currently restrict assessment
components for safety and environmental considerations to
between 10 and 20% of the final grade and process economics
to five to 10% of the total grade.

PROJECT STRUCTURE
Five of the 15 institutions offered only a single project topic
per year, arguing this reduced staff workload. Others offered
a range of project topics. In the "variations on a theme" ap-
proach, a single process was considered, but variations in
things such as raw material purity or plant location were used
to differentiate team projects. This approach was used by
three institutions in order to reduce the opportunity for collu-
sion between classmates, while also limiting staff workload.
Only at the University of Melbourne was plagiarism software
implemented as a tool for monitoring both collusion and
plagiarism from the Internet. When introduced in 2004, this
proved very effective. Substantial plagiarism was detected in
one student's work, and appropriate action was taken.
At virtually all institutions, the students were initially pre-
sented with a design brief of between one and three pages
outlining the design problem. This brief often contained basic

technical and/or costing data. In most cases, the students were
first expected to use this information to complete a feasibility
study; that is, to assess alternate process routes and develop a
process flowsheet to determine market demand and optimum
plant capacity, and to identify potential environmental and
safety issues. This was followed by more detailed equipment
design work, the development of process control strategies,
and a process and instrumentation diagram. At the feasibility
study stage or at the conclusion of more detailed work, an
assessment of the process economics was required. In most
cases, students were expected to argue a business case to
"management" as to whether the facility should proceed.
In all cases, project work was supported by a lecture pro-
gram that provided instruction in design methodology. This
lecture program was often structured to cover subject material
missed in other areas. Thus, for example, it was recognized
that the design of process utilities such as steam and cooling
water systems needed to be covered within this program.
The number of assessable written reports required from
each student or team varied significantly (see Table 1), from
a single submission at the end of a yearlong project to weekly
submissions for a 12-week program.

TEAMWORK AND PEER ASSESSMENT

The design project was conducted as a team exercise at
process issues such as economics,
environmental impact, and health

Capstone Design Project at the Institutions Studied
Class Group Team Team Peer
12-25 5-6 random rotated no
25-35 4-5 by project preference elected by team no
25-40 2-3 and random rotated weekly no
then
10-12
40 5 mix of abilities/gender no no
45 5 by several factors yes yes
50 6 random no
58 5-6 academic merit no yes
60 4 students can exclude no no
others
70 3-4 by academic merit and no yes
project preference
60-70 4-5 random no
70-80 4 self-selection rotated weekly no
80-100 5 random rotated no
100 6-10 mix of abilities/ethnic- no yes
ity/background
80-120 4 self-selection no yes
200-300 7 self-selection elected by team no

Fall 2006

and safety were assessed as team-
remaining an individual activity.
It was common for the individual-
based tasks to equate to slightly
more than 50% of the total grade.
As shown in Table 2, the size of
the teams varied, with typically
four or five students on a team. In
institutions with larger class sizes,
students were allowed to select
their own team members. This was
generally because of the logistics
involved in a central team-selection
process when the number of stu-
dents is large. A significant propor-
tion of design project coordinators
with smaller class sizes, however,
spent considerable effort to develop
team membership. Interestingly,
there was a range of ways to do this.
Some selected students of common
academic ability to be in the same
team, while others deliberately
277

TABLE 2
Basis for Team Assignments in the

ability within one team. The University of Queensland is
considering the use of specific assessment of team skills
from previous years as a basis for team membership in the
final-year project.
Many institutions provided explicit workshops or training
sessions to develop teamwork skills. For example, the Uni-
versity of Sydney had fortnightly sessions on team building
a two-day workshop on effective teamwork a year before
the capstone design project, and followed up with a one-day
refresher course at the project's start. Similarly, many institu-
tions defined a formal role for team leaders. Rotating the posi-
among the majority of students.
teams, which is more representative of
actual industrial environments. For ex-
ample, both the University of Queensland While t
and the National University of Singapore was 4
included an environmental engineering well esi
student in each team, while the Uni- as p
versity of New South Wales included the De
industrial chemists. The University of .
Birmingham had an optional project it was s
that integrated civil engineers, while disapj
Sydney had a multidisciplinary project to the
for highly academic students only that that on.
integrated civil and mechanical engineer- of the in
ing students. used this
While teamwork was clearly well
established as part of the design project,
it was somewhat disappointing to the peer as;
authors that only a third of the institu-
tions used this opportunity to introduce
peer assessment. Between the institutions
that did, a considerable range of methods was used to man-
age the process. In some cases, peer assessment marks were
determined collaboratively by all team members in an open
forum. In others, submission of peer assessment ratings was
anonymous, so that students could not discover how their team
members rated them. The University of New South Wales
presented a relatively sophisticated peer assessment method
designed to improve the consistency of assessors.E8] While
this method would provide high accuracy and a lack of bias,
it could be time consuming in large classes.

INDUSTRIAL INVOLVEMENT

All institutions actively involved engineers with a design or
processing background in the design project curriculum. Some
institutions, notably Melbourne and Birmingham, maintained
part-time adjunct professor-type positions for engineers with
engineering design experience, typically one day a week. In
278

the two cases where the design task was specified by such
design engineers, the hazard analysis was considered at an
earlier stage as a more integral part of the design process than
in other cases. Many other institutions relied on corporate
engineers to assist with setting a valid technical scenario, and
in many cases personnel from these companies provided a
consultant role. In most cases, the academic in charge of the
project also had extensive industrial expertise.

PROCESS SIMULATION AND COMPUTING
TECHNOLOGY
All institutions incorporated the use of simulation packages
such as HYSYS and ASPEN PLUS to assist in design. In most
cases, their use was actively encouraged.
In some cases, the design project brief was
even manipulated to ensure that simulation
work was possible. Others, however, felt that the
use of simulation packages could detract
early from the design exercise because proper
lished implementation required significant time
of input. They also argued that there was a
Project, tendency for students to accept simulation
output without question, and the educa-
ewhat tional value was therefore limited. An em-
nting phasis on proper justification of simulation
thors output was essential, and was usually the
third basis for assessment. Justification by both
tutions shortcut hand calculations and reference
ortunity to literature data was encouraged. The use
of dynamic simulation for process control
ruce and hazard assessment by RMIT University
Sent. was noteworthy.
Also of note was the extensive use of
Web-based learning. A significant pro-
portion maintained subject Web pages as
a major mechanism for relaying information to students.
These subject sites also often used online discussion forums
as a means of bringing common questions into the open and
creating inter-student debate. Electronic library resources
such as Proquest, SciFinder Scholar, and Knovel were also
utilized. A range of smaller, discrete computer programs was
also used to support student learning, such as Microsoft Visio
for engineering drawings.

ORAL PRESENTATION
Now considered an important transferable skill, oral pre-
sentation served as an assessment component in nine of the
15 curricula. In some cases, these presentations were made
directly to engineers and management of the company whose
tations could be individual- or team-based, and sometimes
involved the use of posters to support oral commentary.

Chemical Engineering Education

eat
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TABLE 3
Bio-Based Design Project Topics Used at the Institutions Studied
Enzymatic production of glucose and galactose from cheese whey waste
Lactic acid production
Plasmid DNA-based AIDS vaccine
Bio-ethanol from waste paper
Production of tissue plasminogen activator
Penicillin production

SUSTAINABILITY
The IChemE now prescribes that graduates must "be aware
of the priorities and role of sustainable development." There
was little evidence, however, that sustainability was being
given a focus in the capstone design project. RMIT University
was the only institution formally requiring a sustainability
report as part of the project, relying on the IChemE Sustain-
ability Metrics19] as a template for students. No more than five
other institutions discussed sustainability during the course.
This is clearly an area that could be improved, and many
design teaching staff indicated that they would be enhancing
their approach to this crucial issue in the years to come.

BIO-FOCUSED PROJECTS

Internationally, there is a shift within many chemical
engineering undergraduate degree programs from projects
based on the traditional petrochemical, chemical, and mineral
industries into biomolecular and biochemical engineering
fields. We are currently undergoing such a shift within the
University of Melbourne with a four-year degree in chemical
and biomolecular engineering commencing in February 2005.
It is imperative that the design project can accommodate this
shift to a "bio" focus while retaining the generic skill develop-
ment discussed above.
In many respects, University College London was the
leader in developing a bio-focus with the development of
a biochemical stream alongside their standard course years
ago. This proved so popular, however, that a separate de-
partment had to be formed. This meant that the chemical
engineering department no longer had a need for a bio-based
design project. Birmingham University ran three projects
simultaneously, one of which was a bio-based project. This
project was taken mainly by M.Sc. students, but had IChemE
accreditation. They found that a design team with a mix of
scientists and engineers worked well. They have found some
issues with a full-year bio-based project, however, because
of the limited nature of these processes, and were intend-
ing to move to a series of shorter, more intense campaigns.
Some of these would be focused more on product design
than process design.
Typical bio-based projects that had been undertaken at

Fall 2006

different universities are listed in Table 3. In such bio-based
programs the process volume is much smaller (20kg versus
20,000 tonne per year). The downstream separation processes,
however, can be more complicated, with 10-15 separation
steps being usual. Detailed design tasks can include expanded
bed columns and membrane filtration rigs. Production of mi-
crobiological quality steam or ultra-pure water may also be
required. The regulatory environment of bioprocessing must
also gain an increased focus. Students need to be exposed to
relevant food and drug quality-assurance programs such as
Good Manufacturing Practice (GMP),1101 as well as Hazard
Analysis and Critical Control Point (HACCP)."1 Conversely,
these projects will be more limited in their use of process
simulation packages. There are a number of bioprocess model-
ing computer packages on the market (Aspen Batch Plus and
Intelligen SuperPro), but these can be limited in their ability
to accurately predict unit operation scale-up.['2'

CONCLUSIONS
The design project workshop and subsequent study tour
raised a number of other issues common to many institutions
that cannot be covered in-depth in this analysis. These issues
included the high workload required from teaching staff
to provide a worthwhile design exercise, and the similarly
high workload taken on by some students in completing the
project. Student stress was a significant issue at a number
of institutions, and it was felt that this resulted principally
from the open-ended nature of the design study. Many staff
members also commented on the difficulty of obtaining ac-
curate and up-to-date equipment cost data from the public
domain.
The above discussion, however, shows that institutions
in the United Kingdom, Singapore, and Australia are now
using the capstone design project as a major vehicle for the
teaching of transferable skills such as time management, open-
ended problem solving, teamwork, and oral presentation.
This final-year program has a significant role in "exit transi-
tion," or preparing the student for a role in the workplace.
While the curricula in most cases is very well developed,
the incorporation of more peer assessment and a greater
emphasis on sustainability would enhance further teaching
in this subject.

279

ACKNOWLEDGMENTS

Information was provided by staff at Curtin, James Cook,
Monash, and RMIT Universities, the Universities of Ad-
elaide, New South Wales, Newcastle, Queensland, Sydney,
Birmingham, Nottingham, and Edinburgh, University Col-
lege London, and the National University of Singapore. This
input is gratefully acknowledged. Financial support for travel
to Singapore and the United Kingdom was provided by the
University of Melbourne through a Universitas 21 Fellowship,
and this support is also appreciated.

REFERENCES

1. Murray, K.R., T. Pekdemir, and R. Deighton, "A New Approach to the
Final-Year Design Projects," Proceedings of the 7th World Congress
of Chemical Engineering, Glasgow (July 2005)
2. Austin, D.G., and G. Jeffreys, "The Manufacture Of Methyl Ethyl
Ketone From 2-Butanol: AWorked Solution to a Problem In Chemical
Engineering Design," Institution of Chemical Engineers in association
with G. Godwin Ltd., Rugby, UK (1979)
3. Ray, M.S., and M. Sneesby, Chemical Engineering Design Project:

A Case Study Approach, 2nd Ed., Overseas Publishers Association,
Amsterdam (1998)
4. Changing the Culture: Engineering Education into the Future: The
Institution of Engineers, Australia (1996)
5. Criteria for Accrediting Engineering Programs, ABET Engineering
Accreditation Commission, Accessed from (2004)
6. How Does Chemical Engineering Education Meet the Requirements
of Employment?, World Chemical Engineering Council, Dechema
Frankfurt (2004) Accessed from
7. Accreditation Guide: Undergraduate Study, 2nd Ed., Institution of
Chemical Engineers (2005)
8. Bushell, G., "Moderation of Peer Assessment in Group Projects," Ass.
and Eval. in Higher Ed. (2005)
9. The Sustainability Metrics: Sustainable Development Progress Metrics
Recommendedfor Use in the Process Industries, Institution of Chemical
Engineers,
10. Welbourn, J., "Good Manufacturing Practice in Pharmaceutical Pro-
duction, An Engineering Guide," IChemE, Rugby, UK, Bennett B., G.
Cole (Eds) (2003)
11. Hazard Analysis and Critical Control Point, U.S. Food and Drug
Administration, Center for Food Safety and Applied Nutrition, www.cfsan.fda.gov/~lrd/haccp.html>
12. Shanklin, T., K. Roper, P. Yegneswaran, and M. Marten, "Selection of
Bioprocess Simulation Software for Industrial Applications," Biotech-
nology and Bioengineering, 72(4) 483 (2001) J

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minorities are strongly encouraged to apply.

Chemical Engineering Education

Random Thoughts...

WHAT'S IN A NAME?

RICHARD M. FIELDER
North Carolina State University Raleigh, NC 27695

The monthly Chemical Engineering Department faculty
meeting is in full swing. They spent the usual half hour
di discussing the latest catastrophic budget shortfall and
the urgent need to bring in more grants and more graduate
students with NSF fellowships, and then they moved on to the
upcoming ABET visit. A prolonged argument broke out about
whether teaching students the Gibbs-Duhem equation counts
as preparing them to be ethical and professionally respon-
sible lifelong learners who understand contemporary issues
and can work in multidisciplinary teams to solve global and
societal problems. The argument ended unresolved. Chuck,
the department chair, relayed a message from the department
administrative assistant that unless the professors started
cleaning up their messes in the faculty lounge they could start
making their own coffee. Once the ensuing panic subsided,
the meeting turned to New Business, and the critical issue on
everyone's mind was brought up first.
Chuck: "OK, folks, let's take up Diane's proposition
to change our name to the Department of Chemical
and Biomolecular Engineering. Diane, want to say
Diane: "Sure. Everyone knows that biotech is the
future, and the ones who know it best are the stu-
dents...the freshmen are going more and more for
departments that do biology, and graduate students
all want to work for faculty doing bio research.
Most Chem. E. departments have already put bio-
something in their names and if we don't we're
gonna lose out."

Ch: "Makes sense to me. OK, if no one else has
anything to say, let's vote on it. All in favor of our
becoming the Department of Chemical and Biomo-
lecular Engineering, say..."
Carl: "Hold on, Chuck. If you just say biomolecular
engineering, people will think we're only about
Fall 2006

DNA and all that stuff, which is yesterday's news.
Sam and I do a lot of biocatalysis and biosepara-
tions, which are much sexier than all that gene
stuff, but the students won't know we do those
things here unless we make it explicit."
Ch: "You mean..."

Sam: "Yeah, let's be the Department of Chemical,
Biocatalytic, and Bioseparations Engineering."
D: "Wait just a minute, buster-genes are a whole
lot sexier than enzymes and chromatography, and
we've got twice the grant support you guys do!"

S: "Oh, yeah-well who's got more CAREER
awards, and what's more..."
Ch: "All right, all right-calm down. Tell you
what-we'll just make the tent bigger and call it
the Department of Chemical, Biomolecular, Bio-
catalytic, and Bioseparations Engineering. How's
that?"
C: "Make it Biocatalytic, Biomolecular, Biosepara-
tions, and Chemical -alphabetical order."
D: "That's the dumbest suggestion I ever..."
Ch: "OK, all in favor say..."

Richard M. Felder is Hoechst Celanese
Professor Emeritus of Chemical Engineering
at North Carolina State University. He is co-
author of Elementary Principles of Chemical
Processes (Wiley, 2005) and numerous
articles on chemical process engineering
and engineering and science education,
and regularly presents workshops on ef-
fective college teaching at campuses and
conferences around the world. Many of his
publications can be seen at edulfelder-public>.

Copyright ChE Division of ASEE 2006

Morrie: "Hey, what am I, chopped liver? I don't like
to brag, but have you forgotten that I'm heading
a 3 million artificial organ program with five graduate students..." S: "Can you believe the guy who deals in artificial organs just asked if he's chopped liver?" M: [Glares at Sam] "...five graduate students and two postdocs, and what about our cooperative agreement with St. Swithens Hospital? Biomedi- cal engineering is every bit as important as those other bios around here...besides, we heal people and save lives-let's see somebody here top that for sexy." Ch: "OK, OK.. .I guess we can't include three of our four bio areas and leave out the fourth.. .so, all in favor of renaming ourselves the Department of Biocatalytic, Biomolecular, Bioseparations, Chemical, and Biomedical Engineering say..." M: "Ahem..." Ch: "Right, right-the Department of Biocatalytic, Biomedical, Biomolecular, Bioseparations, and Chemical Engineering..." Ned: "Look, you want to talk about sexy areas, you can't dream of leaving out nanotechnology-it's the hottest field in science.. .you just put nano in your proposal title and you can start looking for your check by return mail-we'll pull the students in here like a vacuum cleaner." Ch: "I see your point-I guess if we don't have nanotechnology in our name Berkeley grads won't look twice at us. OK, so all for the Depart- ment of Biocatalytic, Biomedical, Biomolecular, Bioseparations, Chemical, and Nanotechnological Engineering say..." N: "My mother always said to let the smallest one go first and you don't get much smaller than 10 9 meters, so it should be the Department of Nano- technological..." Ch: "Enough already-don't push your luck! Now, all in favor of..." Ernie: "Whoa, Chuck-have you forgotten Mother Earth?" Ch: "Say what?" E: "Saving lives may be important, but nothing is more important than saving the planet, and the environmental engineering program in this depart- ment is second to none in its dedication to..." Ch: "Yeah, yeah... and what could be sexier than sav- ing Mother Earth?" E: "Just what I was going to say." Ch: "OK, but this is it, gang. My final offer to you is the Department of Biocatalytic, Biomedical, Biomolecular, Bioseparations, Chemical, Environ- mental, and Nanotechnological Engineering -take it or leave it. All in favor say..." D: "You know, that's kind of an awkward name." Ch: "Oh really-I hadn't noticed. So are you offer- ing to drop Biomolecular to help us solve this problem?" D: "Of course not-you can't begin to count the graduate students you'd lose by dropping Bio- molecular. I was thinking, though-nobody here really does anything you could call chemical engineering, do they?" E: "Hey, she's right.. .and we got rid of the last of our unit operations equipment in the undergraduate lab to make room for Ned's scanning electron mi- croscopy experiment and Morrie's heart catheter- ization demo." M: "Besides... students don't seem to have much use for chemical engineering anymore." S: "That's for sure-the latest Roper poll had chemi- cal engineering and pig-lagoon maintenance tied for 247th place in job desirability rankings." Ch: "Well, I guess that settles it. All in favor of be- coming the Department of Biocatalytic, Biomedi- cal, Biomolecular, Bioseparations, Environmental, and Nanotechnological Engineering say aye." All: "Aye!" Ch: "Done! I'll have Patsy order our new letterhead stationery immediately." C: "Hey Chuck, dropping chemical won't cause a problem with ABET, will it?" Ch: "Nah. As long as we can find someplace to slip in the Gibbs-Duhem equation, we're cool." 1 All of the Random Thoughts columns are now available on the World Wide Web at http://www.ncsu.edu/effective_teaching and at http://che.ufl.edu/~cee/ Chemical Engineering Education 1 =1 outreach BIOMEDICAL AND BIOCHEMICAL ENGINEERING FOR K-12 STUDENTS SUNDARARAJAN V. MADIHALLY AND ERIC L. MAASE Oklahoma State University Stillwater, OK 74078 One problem facing the United States is a declining number of students interested in an engineering major.11 Between 1992 and 2002, the percentage of high school students expressing an interest in engineering de- creased significantly.'2' In addition, U.S. students demonstrate a lack of preparedness in math and science.3' To address these issues, a number of programs have been initiated throughout the country in which high school teachers are retrained, or students are exposed to science and engineering through summer outreach programs. [4-7 The College of Engineering, Architecture, and Technology (CEAT) at Oklahoma State University (OSU) has developed a multidisciplinary, weeklong, resident summer academy for high school students called REACH (Reaching Engineer- ing and Architectural Career Heights). The primary goal of REACH is to provide factual, experiential information to all participants, increasing their knowledge in the various fields of engineering, architecture, and technology. Another goal involves increasing the number of students from underrep- resented groups studying these disciplines. The academy is designed to help students make individual career decisions, with the intention of attracting them to engineering careers. Participants are primarily junior or senior high school stu- dents. In the 2005 program, nearly 70% of the 30 students (18 Copyright ChE Division of ASEE 2006 Fall 2006 female and 12 male) were from groups under-represented in engineering, architecture, and technology (such as females, Hispanics, and Native Americans). Each academy begins with a recreational activity such as rock climbing or camping so that participants get to know each other. Afterwards, participants get exposure to engineering Eric L. Maase is an adjunct lecturer of chemical engineering at Oklahoma State University. He received his B.S. in chemi- cal engineering from the University of Maryland, his M.S. in chemical and petro- leum engineering from Colorado School of Mines, and his Ph.D. from Oklahoma State University in 2004. His research interests are teaching methods, computer model- ing, thermodynamics, and bio-related engineering. Sundararajan V. Madihally is an assis- tant professor of chemical engineering at Oklahoma State University. He received his B.E. from Bangalore University, and his Ph.D. from Wayne State University, both in chemical engineering. He held a research fellow position at Massachusetts General Hospital/Harvard Medical School/Shriners Hospital for Children. His research interests include stem-cell-based tissue engineer- .- ing and the development of therapies for traumatic conditions. disciplines including civil and environmental; architectural, electrical, and computer; technology; biosystems and agricultural; mechanical and aerospace; industrial; and chemical and biomedical/biochemical. These disciplines are taught using a modular approach by instructors from each specialty. Hands-on projects are tailored to high school students. During the week participants are also exposed to the engineering industry through a plant tour. At the conclusion of the week, students give a presentation describing their experience at the academy in front of their peers, parents, and teachers. TABLE I Bioengineering Module Schedule Initial Survey 9:00 -10:00 Overview and Introduction 10:00 -11:40 Experimentation 10:20 -10:50 Lab Tour I 10:50 -11:20 Lab Tour II (15 students) 11:45 1:15 Lunch break_ 1:30 1:45 Wrap up the experiment 1:45 2:00 Prepare for the presentation 2:00 2:45 Presentations (5 min each group) 2:45 3:15 Summarize/questions Final Survey 2005 BioModule REACH Pre-S Name: What is your long term c Please provide appropriate replies to each of the following questions. 1. Have you thought of going to medical school? Y 2. Have you thought of becoming an engineer with focus on biotechono 3. What is the confidence in saying you know Basic Biology and Molecu 0 10% 0 30% 0 50% 060% 0 70% 0 90% Courses taken: 4. What is the confidence in saying you know Biochemistry and Biotech 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% Courses taken: 5. What is the confidence in saying you know Humnan Physiology Immu 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% Courses taken 6. What is the confidence in saying you know Fluid Mechanics, Statics, 0 10 0 3% 0 3 0 50% 0 60% 0 70% 0 90% Courses taken 7. How much do you know about the corn syrup added in the many ofth 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 8. How much do you know about enzymes and degradation? O 10% 0 30% 0 50% 0 60% 0 70% 0 909 9. Do you know any prosthetic devices that one of your friends or relate 10. Do youknow anew field calledTissue Engineering? YES or 1 This paper focuses on use of a new module at the 2005 academy, in which students were introduced to biomedical and biochemical engineering. This was the last module in the series. The primary goal was to expose students to various activities in bioengineer- ing. Additional goals included teaching students good research methodology and presentation skills. The activities for the day and scheduled events for the module (Table 1) included an introductory presentation, a laboratory tour, and experimental work. In these ac- tivities, both deductive and inductive learning styles were used8-'-1 to maximize teaching effectiveness and successful completion of the module goals. STUDENT PRE-ASSESSMENT After being informed about the scheduled events for the module and their activities for the day, students survey were asked to complete a one-page sur- vey (Figure 1). Of 10 questions on the career goal? survey, two were about interest in a bio- engineering career or attending medical Fs or NO school. The eight remaining questions required students to self-assess their logy? YES or NO confidence levels of knowledge in vari- ous topics: biological (basic biology and dar Biology? molecular biology); medical (biochem- 0 100% 0 Don't know istry and biotechnology, human physi- ology, immunology, and genetics); and engineering (fluid mechanics, statics, nology7 and electrical circuits). Results of the O 100% 0 Don't know first two questions showed that 19 of the students expressed interest in medical ology, Genetics? school and 10 in a bio-based engineer- S100% 0 Don't know ing. In the self-assessed confidence level in biological, medical, and engineering topics (Figure 2), average values varied andElectrical Circuits? from 36% (25%) to 56% (26%). The 0 100% 0 Don't know only significant difference in confidence levels between male and female students was in the engineering sciences. In the e juices you drnk? more specific bio-related engineering 0 100% 0 Don't know questions on the uses of corn syrup and enzyme-dependent degradation of biopolymers, the average confidence 0 100% ODon'tknow level was 33%. In questions on the yes use List. awareness of prosthetic devices and tissue engineering, 12 students could name vari- NO Ous prosthetic devices and nine had some knowledge of tissue engineering. Figure 1. Pre-assessment survey form. Chemical Engineering Education PRESENTING AN OVERVIEW AND INTRODUCTION TO BIOENGINEERING After completion of the survey, the next event initially ap- peared as an introductory presentation. But its intent instead was as a tool to initiate conversation with the students.1"4 The presentation began with a discussion of five major top- ics in bioengineering, i.e., physiologic systems modeling, prosthetic devices, tissue engineering, drug delivery, and biotechnology. Using an interactive presentation approach, instructors drew attention to practical applications students could have observed in society and asked students to pro- vide their knowledge and awareness of the topics. Further, students were encouraged to ask questions. This approach was beneficial in that instructors were able to make students comfortable while providing new information on biomaterials and bioengineering. The discussion on modeling physiological factors included two examples. The first involved measuring lung volumes and modeling thoracic forces. The example was Lance Armstrong's success in Tour de France competitions, thereby connecting students with a real-life event. The other example involved modeling the dialysis process, and students were informed they would see an entire dialysis unit during the laboratory tour. In discussing prosthetic devices, the need for artificial organs was introduced by a chart describing the deficit of available donors. To encourage participation, students were asked about their knowledge of individuals with artificial limbs, hearing aids, pacemakers, and contact lenses (the most likely device with which an audience member would have direct experi- ence). Further, they were asked, "How do they work?," and "What is the need?" This was done to overcome 100% possible student reluc- 90% tance to participating in a the discussion. The final c 80% - portion on prosthetic de- . U 70% vices dealt with artificial ID heart valves, covering the 60% progression of research 50% and use from mechanical " valves to bioprosthetic 40% - valves, and the difference 30% - with tissue-engineered Q-: valves. a 20% - The basic concepts in W 10% - tissue engineering were < 0% then introduced using examples of currently available artificial skin products and their manu- facturers. After exposing students to other identifiable products, the question posed was: "How do we engineer such products?" In order to show the engineering principles, controlled drug delivery devices were considered. Questions such as: "What happens when a person takes Tylenol?," and "Why does that person need to take pills repeatedly?," served as a basis for pondering better drug-delivery methods. Further, figures of nicotine patches initiated a discussion on the importance of biological factors (half-life, absorption, and metabolism) vs. physiochemical factors (dose, solubility/reactivity/pH, stability) in drug de- livery. In addition, characteristics of traditional oral dosing (cyclic concentrations) and more desirable constant (continu- ous) drug delivery concepts allowed a short discussion of chemical diffusion. Drug delivery served as a link to discussing digestive physiology and enzymes. To introduce this topic, randomly selected students were asked to read the content list on several empty soft drink containers. The most common ingredient, high-fructose corn syrup, was identified on all containers. Stu- dents were asked about the need for corn syrup, creating some discussion on the sweetness, solubility, and production cost of the syrup. This led to discussion on reactor design and the chemical process for obtaining corn syrup. A comprehensive engineering process diagram for complete corn wet milling was presented,151 emphasizing the importance of acid hydro- lysis or enzymatic degradation. The discussion concluded by introducing a specific experiment students would conduct examining enzyme (and acid) degradation of starch. HANDS-ON EXPERIMENT For a hands-on experiment, students were asked to study enzyme-mediated or acid hydrolysis of potato starch. Students Figure 2. Student pre-assessment: science and engineering knowledge by gender. Fall 2006 Figure 3. Different groups pulverizing potatoes. were split into groups of five. Each group was pre-selected to be from differing high schools, and balanced by gender with three females and two males. The low-budget experiment is straightforward, as students either mash cooked potatoes or cut raw potatoes to place in a water bath. Enzyme (a-Amy- lase) or acid is added, and the solution is mixed, maintaining a constant temperature. In presence of the enzyme or acid, starch hydrolyzes to smaller sugars. The presence and amount of starch in a sample can be measured using the iodine-clock reaction-in which the abundant presence of starch is indi- cated by the fast appearance of blue color; reduced presence delays the appearance of blue color; and complete degradation of starch into glucose is indicated by the loss of blue color. Digestion and saliva reactions having already been discussed in the overview, the background consisted of a short (one- slide) presentation on the importance of carbohydrates (e.g., immediate source of energy for the body), and various sources of carbohydrates, including rice, corn, wheat, and potatoes. Other information included types of sugars (granulated sugar, maple sugar, honey, and molasses), and more specifically, simple sugars (fructose and fruit sugar) and double sugars (sugar cane, sugar beet, maltose or malt sugar, and lactose or milk sugar). The experiment was conducted so that students had to take an active role in developing and clarifying experimental pro- cedures.I161 A brief experimental protocol, with instructions regarding volumes of water, directions to use the enzyme or acid, and the solution temperature, was provided to students. 286 The detailed protocols with complete instructions were deliberately not given while critical direc- tions were provided. Furthermore, although each team had the same experimental task, each group was given a unique experimental condition, so that the influence of temperature, mixing, and substrate-size on reaction rate could be discussed. Variables included the amount of potato used, whether it was baked or unbaked, mashed or cut, the temperature (30 C, 50 C, or 70 C), and either enzyme or hydrochloric acid. Potatoes were purchased from a local supermarket, while a-Amylase (enzyme) was purchased from Sigma S Aldrich Co. An iodide-clock reaction kit was from Universe of Science, Inc. Experiments were conducted in 500 mL or 1000 mL conical flasks and each group was equipped with a hotplate/ magnetic stirrer, thermometer, and pH strips. Each group was told to record initial potato weight and solution pH, and to take samples at regular inter- vals to measure starch content. Baked potatoes needed to be mashed, and unbaked potatoes cut into small pieces using a kitchen knife. Students enjoyed this part of the work as an easy means of team participation (Figure 3). Each group had 20 minutes to get experiments under way before laboratory tours began. LABORATORY TOUR Each experimental group was split, with half of the class (15 students) accompanying an instructor on a laboratory tour while the other half stayed to continue experimentation. After the first tour, the students exchanged places. Each laboratory tour was scheduled for 30 minutes. In the laboratory tour, students were taken to an undergradu- ate instructional laboratory containing various unit operations. While emphasis was given to a packed bed reactor containing a resin enzyme, other equipment included a heat exchanger skid, bioreactor assembly, dialysis, absorption column, and a two-phase flow pipe assembly. A demonstration running a two-phase flow of water and air was conducted, including discussion of computer interfaces and control valves. Students liked the demonstrations, and asked a number of questions regarding the computer interface. ORAL PRESENTATIONS After a lunch break, during which experiments continued, the students returned to conclude their experiments. Each group was asked to present the experimental observations/outcomes as a team. They were given 10 minutes preparation time. During this recess, they were told the presentation should be a group effort, all members should be respectful to other Chemical Engineering Education group members, and the audience should ask questions. Each group was allowed five minutes to present its report, including question-and-answer sessions. In the first group, the two male members monopolized the presentation, with the three female members only par- ticipating during the question-and-answer portion. The initial group also provided no introductions of group members or motivation(s) for experimental work. Prior to the beginning of second presentation, instructors gave immediate feedback on presentation strategy and reminded the students about the required equal participation from all group members. This method of immediate feedback to influence presentation be- havior was followed for all presentations. Further, instructors solicited additional critiques from the audience so the entire class could become a source of feedback on presentation style and effectiveness. The instructors ensured their remarks were neither admonishing nor overly negative. Subsequent group presentations continued to improve. The second group correctly followed initial instructions by introducing all team members, and allowing them to actively participate. Presentations from each group improved overall, but students had difficulty adequately reporting experimental results. Furthermore, none of the teams mentioned conclu- sions and recommendations for future investigations. Inter- estingly, one group that performed the experiment similar to another group reported that significantly more starch remained in their solution, but failed to make any comparison with the other team. Neither group initiated any discussion or ques- tions of the results. Instructors had to ask students for possible explanations of the differences between each outcome. EFFECTIVE PRESENTATIONS, EXPERIMENTAL PRACTICE AND PROCEDURE, AND CRITICAL THINKING After the presentations, an overview of what needed to be included in the presentation was discussed. Some of the points addressed included: C Why did you do this experiment? C What was your experimental set-up? C What were your results? C What conclusions can be drawn? C What future plans would you suggest? The students were commended for excellent performance in explaining their setups so the discussion would be viewed positively rather than as criticism. Using the completed experiments as a guide and while their own presentations were still fresh, a discussion on the attributes of an effective presentation was initiated. Using questions stated above, the instructors introduced a general presentation format including introduction, methodology, results, conclusions, and recom- Fall 2006 mendation sections. Although this presentation outline is not robust, it does incorporate many features of an effective presentation.I"7 The students seemed to enjoy participating in a discussion of effective presentations from the unique perspective of devil's advocate, with a recent presentation from which to consider specific needs, individual shortcom- ings, and desirable improvements. The instructors also opened a general discussion on ap- propriate experimental practices and procedures. Specific questions included were: C Why did the pH drop in the experiments where acid was used? C What happened to the pH of the solution? C What happened to the temperature? C Did it take a long time at the end of the experiment? C Did you keep track of time it has been sitting in the container? C Did the viscosity of the slurry create mixing problems? C What happened when you added potatoes to a pre-mea- sured volume of water? C What problems arose? These questions allowed discussion of the criteria neces- sary for good experimental procedures, the problems that may occur in experimental setups, and necessary data to provide adequate and sufficient information for experimental analysis. In addition, there was an opportunity to emphasize the ethical aspect of reporting. One of the teams had forgot- ten to include a magnetic stirring rod, and thus their solution was not well mixed, resulting in less degradation of starch than expected. They were honest about it, and the other teams thought that was a humorous mistake. This allowed a discussion of how no experiment is really a failure, every experiment provides information, and, in this specific case, mixing matters a great deal. Other aspects of the experiment encouraged critical think- ing. Some students spilled excess water from their beakers because they did not account for additional volume when adding potatoes. In other experiments, uniform heat distri- bution was an issue. These complications were built into experimental protocols, and the students needed to identify, overcome, and otherwise consider these issues to accomplish their experimental work. Together with the hands-on experiment, students were shown a 5 liter bioreactor with a jacketed heater and control- lable agitator during the laboratory tour. Explanations were given about how bioreactors work. Reexamining these factors after their experiments emphasized the differences and simi- larities between the two setups, and the need for engineering design of equipment. 287 9 PROBLEMS AND RECOMMENDATIONS g At the end of the module, a general discussion was initiated 7 _asking students to comment on their experiences during the module. Principal comments included: a) Confitsion from switching of operators taking care of 5 experiments 4 b) Need for proper equipment to mash potatoes or cut 3 them into smallpieces 2 ^c) Desire to have an experiment where the product is a 1 take-home substance (not some form of potatoes that 0 are discarded) Medical School Bioengineering d) Better experimental information and more specific experimental protocols Had Not Considered / Encouraged to Pursue e) A prize for the best performance to motivate their work Considered and More Encouraged With each suggestion, the instructors provided immediate Figure 4. Module effect on students' perceptions feedback and an explanation of the current module structure of available career options. in order to elicit further group discussion. For example, team splitting can cause confusion due to lack of communication, but may not necessarily be a problem. It is very common in industrial practice to have three 2005- ioodule REACH Outoe-Sucontinuous shifts, and personnel must effec- Name: What is your long term career goal? tively communicate between shifts. One way Please provide appropriate rep lies to each of the following questions. to promote communication may be to include a 10-minute break between the tours with 1. Didthe module encourage you to conrier attendig medical school? YES or NO specific instructions given to update group members regarding experimental status. 2. Are you more interested in becoming an engineerfocusrig on biotechnology? YES or NO In order to save time, one could use a 3. Whtisyour confidence level insayigyou utmdrstandthe importance of comsyrup? household food processor to mash or chop O 10% O30% O 50% O 60% o O 70% O 90% O 100% O Don't know the potatoes. The incomplete nature of the 4. What isyour levelofunderstandingofthe concepts behindcontrolleddrugdelivery systems? experimental protocols has already been O 10% O o% 0 50% 0606/a 0 70% 0 90% O 100% O Don't know mentioned, and the students were provided some reasoning for the lack of information. 5. What is your confidence level in saying you understand the needforprosthetic devices? Their reactions were noted on this approach O 10% 0 30% 0 50% 06M0 0 70% 090% 0 100% ODon'tknow in future classes. The suggestion of a prize for the best group 6. Whatisyour confidence level in sayigyou undrstanddlhow to properlypresent experimentaldata? was interesting, as the students had been O 10% 030% 0 50% 060% 0 70% O 90% O 100% O Don't know conditioned over the previous week by many of the REACH faculty to expect such forms 7. How much ddyou like the introductory lecture? of praise. While considering the suggestion, 0 10% 030% 0 50% 0 60% 0 70% 0 90% 0 100% O Don'tknow the current module seems best served by not including prizes as a form of reward. Overall, 8 Howmuchdidyouenjoythelaboratorytouranddidyou learn anything? the students enjoyed the desired give-and- O % O 20% 0 40% 0 60% 0 70% O s0% 0 90% 0 10% take interaction encouraged by the instruc- tors, and were open in their suggestions for 9. How much didyou like the experiment? YES or NO improvements. 00% 020%/o 0 40% 0 60% 0 70% O 80% 0 90% O 100% OUTCOME ASSESSMENT 10 Please name the topic you most enjoyedin this module. To understand the effectiveness of the mod- ule on student learning, an outcome assess- Figure 5. Post-assessment survey form. ment was provided (Figure 5), similar to the 88 Chemical Engineering Education pre-assessment survey. To measure the main objectives of the module, i.e., the influence on students' perspectives of careers in bioengineering and medical engineering/science, the first two questions in the pre-assessment were repeated. Out of 30 students, a large number (-2/3) had already expressed interest in attending medical school (pre-assessment data). Therefore, no specific conclusions could be drawn regarding an increase in the student desire, awareness of medical school, or career options (Figure 4). By comparison, an increase in student awareness of bioengineering as a career was observed, as four students indicated a new interest in the bioengineering field. This suggested that the module was successful in introducing bioengineering. Students were also asked to rank their confidence in the importance of corn syrup, for which the overall confidence doubled (Figure 6) with a large group of students indicating more than a 70% confidence level. When asked about their confidence in drug delivery and prosthetic devices, the aver- age was 63% ( 13%) and 76% ( 20%), respec- tively, for each category. Further, students indicated a 74% ( 22%) confidence level in experimental data , presentation. Without a pre-assessment question re- garding their abilities in data presentation, however, Cat the effectiveness of this aspect of the module could Gen not be assessed, although one student did mention Pros that this portion of the module was his/her favorite Arti experience. Exp The final assessment questions gauged overall Lab interest in the introductory presentation materials, No l ft t n ht dA conclusions regarding differences between male and female responses is indeterminate given the small sample population, the overall nature of students' responses indicated both signifi- cant interest and engagement with instructors and presented materials. Further, a larger number of female students than male students indicated the experimental portion was the most enjoyable topic. The trend was opposite the previous response to the specific question, in which male students ranked their enjoyment of the experiment at 54% compared to female students at an average of 47%. SUMMARY The module introduced K-12 students to the field through interactive presentations, discussions, experimental proce- dure (hands-on work), and a tour of working engineering laboratories. The presentation was designed to encourage students' questions while presenting five major aspects of the bioengineering field. Within each primary topic were TABLE 2 What was the topic you most enjoyed?" by category and gender egory M F Total % eral Lecture 2 1 3 10 thetic Devices 2 4 6 20 ficial Organs 4 3 7 23 eriment 2 6 8 27 Tour 1 1 2 7 Response 1 3 4 13 1IUU1 o. l y LUr, -n s11 -lJ on experiment, for which re- sponses were -50% ( 28%). 12 - A follow-up, open-ended ques- tion asked for students' favorite 10 - experience during the day, with responses grouped into six gen- 0 eral categories (Table 2). Sur- c o prisingly, nearly 53% indicated -" the lecture materials as their * favorite events (one student 6 noted that the afternoon lecture o on effective presentations was the most interesting, and said E 4 it included information that Z he/she had never been shown or heard previously). The introductory materials are likely the most interesting, - simply due to the interactive nature of the presentations in relation to identifiable products and aspects of importance in students' lives. While drawing Fig Fall 2006 6Q e e- 8Q e CD CD Cm CD CD C= C- S Mo t RL co Student Response CD CD Co M D lure 6. Student responses to "Importance of Corn Syrup." 289 secondary investigations that delved into both scientific and engineering aspects. All topics incorporated design aspects to draw on personal experiences with bioengineering products, processes, and research. Students enjoyed the presentation style and topics, and were able to connect much of the mate- rial to their own experiences and knowledge. Based on the immediate responses, the overall module was successful in influencing their interest in bio-based engineering. To better understand the effectiveness of the module, however, long- term follow-up studies are needed examining the students' career choices. The assessments also need to be redesigned to more effectively measure module features and goals. ACKNOWLEDGMENTS We would like to thank Oklahoma State Regents for Higher Education, Conoco-Phillips, NASA, and OSU CEAT for financial support and Eileen Nelson for help with the survey analysis and manuscript preparation. REFERENCES 1. The Science and Engineering Workforce: Realizing America's Potential, National Science Board, August (2003) 2. Learning for the Future: Changing the Culture of Math and Science Education to Ensure a Competitive Workforce, Committee for Eco- nomic Development, May (2003) 3. "Bayer Facts of Science Education IX: Americans' Views on the Role of Science and Technology in U.S. National Defense" (2003) 4. Olds, S.A., D.E. Kanter, A. Knudson, and S.B. Mehta, "Designing an Outreach Project that Trains Both Future Faculty and Future Engineers," Proceedings of the American Society for Engineering Education, Nashville (2003) 5. Knight, M., and C. Cunningham, "Draw an Engineer Test (DAET): Development of a Tool to Investigate Students' Ideas about Engineers and Engineering," Proceedings of the American Society for Engineering Education, Salt Lake City (2004) 6. Chandler, J.R., and A. Dean-Fontenot, "TTU College of Engineering Pre-College Engineering Academy Teacher Training Program," Proceedings of the American Society for Engineering Education, Salt Lake City (2004) 7. Douglas, J., E. Iversen, and C. Kalyandurg, "Engineering in the K-12 Classroom: An Analysis of Current Practices & Guidelines for the Future," ASEE Engineering K12 Center, November (2004) 8. Kolb, D.A., Experiential Learning: Experience as the Source of Learn- ing and Development, Prentice-Hall, Englewood Cliffs, NJ (1984) 9. Honey, P., and A. Mumford, "The Manual of Learning Styles," Maid- enhead, Homey (1986) 10. Bransford, J., A. Brown, and R. Cooking, How People Learn: Brain, Mind, Experience, and School, National Academy Press, Washington D.C. (1999) 11. Donovan, M.S., J.D. Bransford, and J.W. Pellegrino, "How People Learn: Bridging Research and Practice," National Research Council (1999) 12. Felder, R., and L. Silverman, "Learning and Teaching Styles In Engi- neering Education," Eng. Ed., 78(7), 674 (1988) 13. Felder. R., and R. Brent, "Understanding Student Differences," J. Engr. Ed., 94(1), 57 (2005) 14. Baker, A., P. Jensen, and D. Kolb, Conversational Learning: An Expe- riential Approach to Knowledge Creation. Quorum Books, Westport, CT (2002) 15. "Chapter 9, Introduction to AP42, Volume I, Stationary Point and Area Sources," US EPA, 5th Ed. (1995) 16. Watai, L., A. Brodersen, and S. Brophy, "Designing Effective Engi- neering Laboratories: Application of Challenge-Based Instruction, Asynchronous Learning Methods, and Computer-Supported Instru- mentation," American Society for Engineering Education Annual Conference & Exposition, Salt Lake City (2004) 17. Hendricks, W., Secrets of Power Presentations, Career Press, Franklin Lakes, NJ (1996) 0 Chemical Engineering Education 290 jfL_ classroom PRESSURE FOR FUN: A Course Module for Increasing ChE Students' Excitement and Interest in Mechanical Parts WILL J. SCARBROUGH AND JENNIFER M. CASE University of Cape Town Rondebosch, South Africa 7701 Chemical engineering as a profession grew in the late 19th century out of collaboration between chemists and mechanical engineers working to develop large- scale industrial processes. To this day chemical engineers working in the process industries are closely involved not only with particular chemical processes and unit operations such as reactors and separators that can accomplish these processes-but also with mechanical devices such as pumps and valves that enable the transport of materials. We have found, however, that skill or even familiarity with mechani- cal components is often undeveloped in first-year chemical engineering students, even though they are often the best and brightest science and mathematics students at the high school level. The first- and second-year curriculum is often theory intensive, and the practical exposure that does take place is more in the traditional science subjects, complemented by some experimental work using basic pilot-scale unit opera- tions. By the time they reach their senior year, we find many students, although academically relatively successful, still struggle to connect reality to theory. In addition, a large seg- ment of the class is relatively intimidated by the prospect of working in a plant environment. In the Department of Chemical Engineering at the Univer- sity of Cape Town (UCT) we have been considering for some time how best to modify our curriculum to afford first-year students better exposure to mechanical aspects of chemical engineering. It was fortuitous that the opportunity arose to design-specifically for chemical engineering students-a five-week module that would form part of the mandatory first-year mechanical drawing course. Previously this part of the course dealt with the interpretation of chemical engineer- ing flow diagrams, but recently it was decided to move this Copyright ChE Division of ASEE 2006 Fall 2006 material to the second year to integrate it more closely with core chemical engineering courses. In discussion among a group of academic staff, we decided that our objectives for this module would not be primarily focused on detailed content knowledge, but rather on changing students' attitudes toward this aspect of chemical engineering. These were the objectives for the new module: > Get students excited about mechanical things. > Develop students' ability and confidence to explain how things work (and the desire to learn more). Will J. Scarbrough is currently a postgradu- ate in the Engineering Education Research Group within the Department of Chemical Engineering at the University of Cape Town. He was appointed as lecturer/course orga- nizer for the duration of this module. Previous experience includes work in inspiration and excitement through the robotics programs of F.I.R.S. T., a nonprofit based in the United States. He received his A.B. in engineering sciences with a minor in education from Dartmouth College in 1998. His research interests include science and technology education, inspiration, and classroom knowledge networks. Jennifer M. Case is a senior lecturer in the Department of Chemical Engineering at the University of Cape Town, with a research focus on educational development. Her early career experience was in teaching high school mathematics and science, and she subsequently completed an M.Ed. in science education at the University of Leeds and a Ph.D. at Monash University. Her research interests are in student learning, with a focus on improving the success of students from nontraditional backgrounds. She lectures in the junior undergraduate program. Help students start building a sense of "mechanical intuition." Provide familiarity with equipment diagrams and hard- ware. Develop students'ability to link the "real world" and theory. This is a rather different set of objectives compared to what chemical engineering lecturers usually design courses around. How do you explicitly design a course module for excitement? This paper describes how we went about meeting this cur- riculum development challenge. The new course module ran for the first time in 2004, and is now an established feature of the first-year B.Sc. (chemical engineering) program at UCT. In this paper we focus on the process of setting up and evaluating the course during its first year. APPROACH TO COURSE DESIGN We found a useful rationale for running this type of course in the classic work by Woolnough"l1 regarding practical work in school science. He argued against the widely held belief that practical work should be done for the sake of theory, and that conceptual understanding will be an automatic outcome of successful practical work. Instead, he suggested that practi- cal work is better understood as having its own end, either to develop skills, to develop the ability to conduct investigations, or to simply get a feel for important physical phenomena. The module we developed fits clearly in the latter category, with the chief aim being to allow students physical interaction with the mechanical aspects of chemical engineering. In recent times a number of innovative courses have been reported on that offer such hands-on experiences to first-year chemical engineering students. For example, Barritt, et al., 121 describes a highly successful multidisciplinary project that involved small groups of students in the design, manufacture, and operation of a pilot-scale water treatment plant. Moor, et al.,[31 also ran a multidisciplinary project for first-year engi- neering students, this time involving the design of a reverse osmosis system, with the collection and interpretation of experimental data from an existing rig. Willey, et al.,[41 de- signed a first-year project that involves experimentation with a sequential batch-processing system. Most of the courses reported in past literature, such as those described here, incorporate relatively sophisticated design projects that run over a long duration. Our aims were more limited as we had a large class and a short period of time. We therefore decided to focus on our primary objectives, which were centered on changing students' attitudes toward working with mechani- cal artifacts. To meet these objectives, we adopted a particular teaching approach that included small class size, group work, and excellently trained facilitation. Additionally, the activities were planned to give students a sense of accomplishment and 292 encourage experiential learning and unsolicited experimen- tation. In traditional terms, this resulted in a combination of practice and some tutorial in one class period, without the use of a lecture period. Assessment was based on a combination of individual and group assignments, and contributed 10% toward the final mark for the mechanical engineering course in which this module was located. By concentrating on the primary objectives of the course, content topics that suited these objectives could be chosen and a rapid movement between topics undertaken if necessary. We chose to use valves, pumps, pressure, and flow regimes in our activities. The intended objectives, however, remained focused on excitement and learning how to explain, rather than on content. Class and Group Size The class of nearly 100 students was split into five groups of approximately 20 students, and each group was allocated a weekly 85-minute session over the duration of the five- week course module. Each session was attended by two or three tutors and the course organizer. Each class made use of student teams ranging in size from two to four members. In most cases students continued with the same team for two successive classes. An introductory chemical engineering course running concurrently had given the students sufficient group-work practice, so this aspect posed no difficulty by the time they began this module in the second semester of their first year. Facilitation by Tutors One vital component of the course was facilitation by tutors. Students were asked to operate unlike they had in any previous school or university situation. Such unfamiliar expectations occasionally caused students to balk at requests. Additionally, with little experience in a potentially intimidating situation, students often had no idea where to begin or how to proceed after achieving a portion of the activity. Our solution was to handpick tutors and train them in facilitation (also known as coaching). The primary role of the tutors was to closely observe student teams and offer guidance when necessary. The tutors were mainly graduate students who were selected based on previous experience with tutoring and an observed ability to patiently facilitate the group process. Tutors were given a short manual on facilitation and practiced a short role- play illustrating typical situations. Detailed tutor notes were provided for each class including a time schedule, jobs for specific tutors, likely problems student teams would encoun- ter, and topic-specific reference material for tutors to use as prompts while facilitating. One example is the specific list of difficulties when taking apart and re-assembling a hand pump. Before each week's class, the tutors met to go over the activity, practice it themselves, and discuss the reference materials for the topic and facilitation tactics for the activity. The environment within the classroom was also an impor- Chemical Engineering Education tant consideration. From the initial description of the module to the manner of facilitation, students were told they had freedom to experiment, try things out, or "fiddle." The class organizer and tutors made a careful effort throughout the module to create an environment "safe" for experimentation, in particular for the students most nervous about physical parts and equipment. THE ACTIVITIES Each week students were presented with a different activity, with the final "challenge" taking place over two weeks. The assessment was integrated throughout the module. Industry Parts The introductory class consisted simply of pairs of students taking apart large-scale components from industry and attempting to intuitively figure out the item's main purpose and interpret the mechanical design. Students were allowed the time to construct their own ideas. An important element was giving each student practical experience with physical parts. Most of the parts were nothing more complicated than valves, yet the novelty of valves weighing 20 kg was clearly demonstrated with an initial com- ment, "This is a pump, right?" After the activity, a handout with information on each type of valve was given. During class we tried not to criticize or correct students' ideas, but instead encour- A'r in ms rsAn -Vo be removec4 kc rejltit sqt-ep c U~clZ until wa ter en+ers -Ve c9 i-cder- Figure 1. Explanation of hand pump by student pair. The illustrated mechanism is an example of a reciprocrating pump, a type that is also used to extract H,O and oil from under the ground. age each pair to complete the line of thinking them- selves. For assessment purposes, each student was required to submit rough notes and a written explanation of how the mechanical part worked. Hand Pump At the start of the sec- ond class each pair of students was given a cheap, transparent pump and bottle: the kind often used for liquid hand soap. Starting with observation, continu- ing with disassembly and reassembly of the pump, and ending with directed experiments, pairs needed to discern the working principles of the pump. Each pair was instructed to create a one-page diagram ex- planation of the physics principles underlying the pump's operation, and how those prin- ciples are utilized by the mechanical parts. This report counted as 30% of the assessment mark for the module. An example of a par- ticularly good student response is reproduced in Figure 1. Fall 2006 DiagrTam ?. Pump Cycle Step 1 Diagram_1: Importacnt Features 4 Ball rYoves up dciue to d Lapkce0-:ent of cvmp-eld c r voave-iopenS Piston compresses sprii-g Cylinder volurne dec r e~ 0 cau,'in9 i-iberr pre&ssurep to rure L eAernol aIbrvQcaph e pressure S-cllrymoves down due to ccoi,-:emS'cn Svolre closes Diagram 4n Pump Cycle step- Diagram 3 Reapply forc.- I Valve Zc-o ;e- - nor"nevw" -flui cian enter +he cjlinimder Figure 3. Students participating in "The Challenge." Within this class and the whole module, students were faced with the need to come up with their own answers. When students asked questions about the pump, tutors-rather than provide the answer immediately-encouraged students to "try it and see what happens." Similar to other activities in this module, free experimentation was required to discover the workings of the mechanism. Creating a detailed explanation of a relatively simple pump allowed students to build confidence by being able to complete 294 Figure 2. "The Challenge" rig setup. a task to a reasonable degree of satisfaction. Only in written feedback afterward were stu- dent misconceptions noted. victor for 10mm tubing Mechanical Drawings 16mm tubing to 1/2" thread In a reverse from previous 10mm tubing to 1/2" thread exercises, the next class began or tubing with sets of mechanical draw- amp ings for six types of pumps. Each group of three or four students had a limited amount of time to work backwards from the drawings for two types of pumps to discover how the pumps operate. The previous hands-on experience with a reciprocating piston pump (the hand pump) provid- ed a base for interpretation of the pump drawings. Partway through the class, students were rearranged into new groups, such that no one in the new group had encountered the same pumps. Then, in a very restricted time, each student was required to explain the pumps they knew to others. THE CHALLENGE The final project was a bit of a competition and a fun way to complete the experience. We named it "The Challenge." For both the fourth and final classes, a custom-designed but inexpensive rig was provided for each team of three to four students. A diagram of the rig is shown in Figure 2. For the first day, students were required to complete a preparation worksheet and then experiment with the rig to demonstrate concepts relating to pressure, head, laminar and turbulent flow, and Reynold's number. For "The Challenge," students worked to control the motion of a bead in a system of pipes using pressure changes (Figure 3). Students had to experiment with the equipment to learn the effect of closing and opening particular valves. The activities were carefully designed to be initially difficult, but easily ac- complished through effort, teamwork, and practice. Many unplanned learning points arose as a result of the physical activities. For example, as dye flowed through the system of pipes, with water and dye flowing from the lower left to the upper left of a "D" shape, a trickle of dye left the Chemical Engineering Education Key 16mm ID clear tubing o o 10mm ID clear reinforced tubing --- 5mm black irrigation tubing adaptor from 5mm tube to large tube Ball, gate or globe valve T connector for 16mm tubing 1 T conne adaptor adaptor clamp fi hose cl ' i -syringe main flow to slowly swirl in the loop on the right of the "D." A student remarked that they had no idea any water would leave the main flow. The final competition was run as a sporting event with team names, an elimination tree structure, stopwatches to record times, and a prize for the winning team. A video cam- era captured the event and projected it onto the big screen behind the two competing teams. The other students cheered as their classmates competed (shown in Figure 4). For as- sessment purposes each team was required to submit a brief report on "The Challenge," and this counted as 30% of the module grade. EVALUATION OF THE MODULE From simple observation of students during the module, it appeared that they had gained both confidence and interest in finding out how mechanical things work. In particular, we noticed students' enthusiasm with the activities and high levels of verbal interaction within student teams as they sought to explain what they had deduced. We needed, however, to find a way to more systematically gauge the success of the activity in meeting its objectives, and therefore administered a short Likert-type survey to all students before and after the module. Five statements were provided, and students were asked to in- dicate their response on a scale of (5) strongly agree, (4) agree, (3) uncertain, (2) disagree, or (1) strongly disagree. Ninety-two completed question- "intuition," began with the greatest "disagree" of all questions at 15%. After the module this was reduced to 3%, although this question retained the largest number of "uncertain" re- sponses, with 27%-indicating students who did not have the confidence to claim mechanical intuition in the other ques- tions. The combined responses "agree" and "strongly agree" to "intuition" moved from 42% to 73%. Student interest in how things work, Question 3, started high and had nowhere to go; this group of students began and remained a curious Figure 4. The winning group celebrates. naires were returned. Table 1 (next page) shows the change in the mode (most frequently reported response) for each statement. A more complete indication of the range of re- sponses is given in Figure 5. The largest change observed was ques- tion 1, "explain"; most students (51%) began not knowing if they could explain how a mechanical object works to some- one else or not. The responses "agree" and "strongly agree" moved from 38% before the module to 97% after the module. Question 2, Fall 2006 Box & Whisker Plot: Response --r ----- _. Before After Question 1 'explain' Before After Question: 2'intutlon' Before After Question: 3'find our stronglyagree - ag ree uncertain dsagree stronglydsagree Median Before After Before After m 25%-75% QuesUtio 4'exmtcd QuOstion: 5'theo M-Max Figure 5. Box and Whisker plot of survey respMin- ax Figure 5. Box and Whisker plot of survey responses, N = 92. bunch. Question 4, "excited," saw only a small decrease (3%) in those "uncertain" about working with mechanical things. Nevertheless, the combined responses "agree" and "strongly agree" moved from 67% to 78%. For the final ques- tion, "theory," the combined responses "agree" and "strongly agree" moved from 64% to 86%. CONCLUSION In this paper we have reported on the development and evaluation of a new module in our chemical engineering undergraduate program, which has the primary objective of getting students excited and confident about working with mechanical artifacts. It has been shown that the module successfully increased students' confidence and perceptions in their ability to work with and explain mechanical things. It was also great fun for the students, tutors, and the course organizer. The module is now fully established in the program, and makes an important contribution to the development of degree outcomes. It was a fairly radical move to design a course module around attitudinal objectives (excitement, etc.) rather than the more conventional content-based design. Even with the current focus on outcomes-based design, this is still often a neglected aspect of curriculum development in chemical engineering. We hope that the descriptions of the activities given in this article will encourage others to try them out with their first-year students. ACKNOWLEDGMENTS The tutor Ryan A. Stevenson was invaluable for his help in brainstorming creative ideas for this module. The support and encouragement of other colleagues in the Department of Chemical Engineering at UCT is also acknowledged. REFERENCES 1. Woolnough, B.E., "Exercises, Investigations, and Experiences," Phy. Ed. 18, 60-63 (1983) 2. Barritt, A., J. Drwiega, R. Carter, D. Mazyck, and A. Chauhan, "A Freshman Design Experience: Multidisciplinary Design of a Potable Water Treatment Plant," Chem. Eng. Ed., 39(4), 296 (2005) 3. Moor, S.S., E.P. Saliklis, S.R. Hummel, and Y.C. Yu, "A Press RO Sys- tem: An Interdisciplinary Project for First-Year Engineering Students," Chem. Eng. Ed., 37(1), 38 (2003) 4. Willey, R.J., J.A. Wilson, W.E. Jones, and J.H. Hills "Sequential Batch Processing Experiment for First-Year Chemical Engineering Students," Chem. Eng. Ed., 33(3), 216 (1999) 0 Chemical Engineering Education TABLE 1 Modal Responses by Students, Before and After Module, N=92 # Question Reference Mode Mode A in text Before After 1 I can explain how a mechanical "explain" uncertain agree T object works to someone else. 2 I have an intuition that allows "intuition" uncertain agree T me to understand mechanical things. 3 I am interested in finding out "find out" strongly strongly o how things work. agree agree 4 I am excited to do a practical "excited" agree strongly T or job that involves mechanical agree things. 5 I can connect chemical engi- "theory" agree agree o neering theory to an image in my mind of what actually happens. Wla curriculum BIOMOLECULAR MODELING in a Process Dynamics and Control Course JEFFREY J. GRAY Johns Hopkins University Baltimore, MD 21218 The field of chemical engineering has always been dynamic and evolving, from the field of applied in- dustrial chemistry at the beginning of the last century, through the revolutionary reformulation of unit operations and engineering science in the 1960s, to the extensive use of computing and the incorporation of biology over the last two decades.11 This latter change is now maturing. Chemical engineering departments around the world are changing their names and refocusing their missions to include the fundamen- tal science of biology. BRINGING IN BIOLOGY There are significant reasons biology is needed in engineer- ing curricula. Most prominently, the human genome was declared finished (at least within a reasonable tolerance) in 2001,[2 3] and thus the full "parts list" of this organism and many others is now available. High-throughput and systems biology tools are extending this "parts list" to provide com- plex views of biological systems at the molecular and cellular level.14.5] Concurrently, the pharmaceutical industry is creating new drugs and products using new biotechnology (cell culture, protein engineering, genetics). These advances rely on tools from the fields of micro- and nanotechnology, and allow us to measure and affect processes on the biological-length scales (Angstroms to microns). Biological systems are complex, robust, specific, and tightly regulated. Many engineers are interested in mimicking these qualities in designed materials, processes, devices, and systems. In addition, we are poised to discover new insights into biology by bringing chemical engineering perspectives to the field. Changes at JHU At Johns Hopkins University (JHU), the Department of Chemical Engineering has long had a significant focus on biologically relevant problems, due in part to the proximity and diffusion of ideas from our prominent medical school and biomedical engineering department. Of our 12 full-time faculty, six have research programs primarily focused on biological problems (protein engineering, cell engineer- ing, drug delivery, etc.), and most of the remaining six have projects with biological implications or applications (nanofluidics and nanodevices, self-assembly). Therefore, as discussions within the chemical engineering community began to suggest that renaming departments could be useful to the field, we immediately implemented such a change at Hopkins. Our department officially became the Department of Chemical and Biomolecular Engineering (ChemBE) in fall 2002. We also recognized that to be a department including biomolecular engineering, it is necessary to train students, both undergraduate and graduate, in this field. In practice, many Hopkins students were already receiving such training, Jeffrey Gray is an assistant professor of chemical and biomolecular engineering at the Johns Hopkins University. He has won a Beckman Young Investigator award and the 2006 Johns Hopkins Alumni Association Excellence in Teaching Award. His research interests are in protein docking, therapeutic antibodies, protein-surface interactions, and allostery. Copyright ChE Diision of ASEE 2006 Fall 2006 as research ideas naturally diffuse into traditional courses and new electives. We resolved to criti- cally examine our undergraduate curriculum and revise course requirements and topics within all core courses to realign the undergraduate cur- riculum with our new mission. The context and purpose for these new courses can best be summed up by the new JHU ChemBE mission statement: Our mission is to define and educate a new archetype of innovative and fundamentally grounded engineer at the undergraduate and graduate levels through the fusion of fundamental chemical engineering prin- ciples and emerging disciplines. We will nurture a passion for technological innova- tion, scientific discovery, and leadership in existing and newly created fields that cuts across traditional boundaries. We will be known for developing lead- ers in our increasingly technological society who are unafraid to explore uncharted engineering, scientific, and medical frontiers that will benefit humanity. The Department of Chemical and Biomolecular Engineering offers courses and training toward a B.S. degree in chemical and biomolecular engineering. This discipline is dedicated to solving problems and generating valuable products from chemical and bio- logical transformations at the molecular scale. The undergraduate program emphasizes the molecular science aspects of biology and chemistry along with engineering concepts essential to developing com- mercial products and processes. By selecting an ap- propriate concentration or by free electives, students can prepare for a professional career path or for further study in chemical, biomolecular, or a related engineering field as well as medical, law, or business school. In the tradition of JHU, many undergraduates are also involved in research-working closely with faculty and graduate students in research groups. Changes in the Needs of a Dynamics and Control Course With the departmental decision to change the undergradu- ate curriculum, I contemplated questions about the process control course. What skills and abilities of "dynamics and control" are also applicable to biomolecular and nanoscale systems? What new skills and abilities must be taught? How are biological dynamical systems similar to and different from traditional chemical process systems? How will our new graduates differ from their predecessors? Similar questions were discussed at a recent series of national workshops.M6' As additional background has been added to the curriculum, some have even suggested that dynamics and control be 298 BOX 1 Specific Course Objectives 1. Create dynamic models for chemical and biological processes, including single-variable and multivariable, linear and nonlinear systems. 2. Integrate dynamic models to determine system behavior over time using Laplace methods, state space methods, or numerical methods. 3. Design control schemes to control system behavior. 4. Analyze dynamics and control with frequency approaches. 5. Analyze nonlinear dynamics with phase portraits and numerical methods. 6. Meet environmental and safety objectives through process control. 7. Use computational tools for system analysis. 8. Operate an industrial control system on a lab-scale process. 9. Collaborate in small working teams on research, analysis, and design. 10. Present work orally and in written reports. BOX 2 Topics Covered 1. Motivation for modeling and control 2. Modeling and system representations 3. State space models and linearization 4. Introduction to MATLAB 5. Pharmacokinetic modeling, biomolecular modeling, and the Central Dogma 6. Laplace transforms 7. Transfer functions 8. First, second, and higher-order systems 9. Poles and zeros, time delay 10. Empirical model formulation 11. Control of gene expression, lac operon 12. Feedback control 13. PID controllers 14. Closed-loop transfer function and stability 15. Large-scale biosimulation (guest lecture) 16. Controller tuning in industry (guest lecture) 17. Frequency response 18. Bode and Nyquist approaches, robustness 19. Introduction to nonlinear dynamics 20. Lotka-Volterra model, limit cycles, chaos 21. Current topics in the literature eliminated.171 The specialty, however, is important in biology because biological processes are dynamic, nonequilibrium, and tightly integrated and regulated as a system.7]' There are several main ways in which biological systems differ from traditional chemical process systems. First, chemi- cal process systems are human-created with known parts and components. Biological systems evolve without human design, and they involve many parts and components that we are still discovering. Indeed, the fact that we are rapidly dis- Chemical Engineering Education In traditional process dynamics and control courses, students learn about sensors, transducers, and actuators. In the new ChemBE curriculum, students must also examine the structures of biomolecular control components. covering these parts and their functions now (via the genome project and various micro- and nanoscale analyses) is one of the main reasons this topic is important today. In the study of dynamics of biological systems, the task is often to reverse engineer the workings of the system, whereas in a chemical process the task is to build a model from the components and parts of a known process.1l' Secondly, biological systems are almost always nonlinear. Enzymatic reactions and active transport channels follow Michaelis-Menten kinetics, allosteric proteins have multistate behavior, and intracellular and tissue transport can be super- or sub-diffusive due to the structured environment. Biological systems are often complex, involving multiple length scales from the atomic and molecular through the tissue, organ- ism, and even ecosystem level. The range of time scales is equally broad, from the fluctuations of protein molecules over nanoseconds to ecological changes over decades. Biological systems incorporate multiple regulatory loops including feed- back, feedforward, and more complex control schemes. These issues are not limited to biological systems: real chemical processes also exhibit the challenges of interplay between multiple length and time scales, nonlinear underly- ing equations, and multiple interacting control loops. Newer textbooks treat these subjects judiciously in later chapters."-" The utility of these topics to both biological and chemical process systems provides additional motivation to include these ideas in a new dynamics and control class. Recent chemical engineering textbooks have begun to include biological problems and examples. For example, Bequette's text includes modules on a biochemical reactor and pharmacokinetic models for diabetic patients.'9J Ogunnaike and Ray also include problems from pharmacokinetics, bio- technology, tissue engineering, and physiology (see problems in chapter 6 on dynamics of higher-order systems). 110 Seborg, Edgar, and Mellichamp now include a section on fed-batch bioreactors.11I In this article, I detail the ways in which I have modified the traditional process dynamics and control course to create a new course, "Modeling, Dynamics, and Control of Chemi- cal and Biological Processes." The course is semester long, (13 weeks) with two 1.5-hour lectures and one hour-long discussion per week. It is typically taken during the senior year. It is required for ChemBE majors, and typically 25% of the students are nonmajors or part-time students from local industry. Below, I discuss the changing nature of students Fall 2006 observed in the new chemical and biomolecular engineering program, and detail the revisions in the syllabus, the new modules in the course, and the modifications of traditional modules. Student learning in the course is assessed through homework, exams, and a short presentation. The usefulness of course changes is assessed through a survey of alumni. I conclude with my opinions on the material that remains omit- ted and prospects for the future of this course in the chemical engineering curriculum. STUDENTS The chemical and biomolecular engineering students at JHU reflect the changing interests of the new generation entering the field, perhaps to an extreme given Hopkins' reputation in life sciences. These interests are reflected in previous courses taken by the students. Figure 1 (next page) shows the percentage of students enrolled in the dynamics class who had taken biology subjects. ChemBE majors are listed separately (nonmajors include biomedical engineering stu- dents who have taken an engineering "Molecules and Cells" course). Biochemistry became a mandatory course for the graduating class of 2007, but the classes before that showed interest in the subject, and in 2005 77% of the students had taken biochemistry. This background allows me to move more quickly through the Central Dogma of Biology and assume some knowledge from the students about the role of DNA, RNA, and proteins in the cell. Hopkins students are highly involved in research. In fall 2005, 65% of students participated in research at some time during their tenure at Hopkins and, of those, 55% were involved in biologically related research. This background elevated the level of discussion on current engineering topics as well as on the basic elements of biological systems, and what those components do. In applying these course modifications at other schools, it may be necessary to take into account the background of the students. SYLLABUS AND OBJECTIVES Boxes 1 and 2 show the course objectives and the list of topics covered in the course from the syllabus. In a broad sense, the course is structured similarly to a traditional process control course: the first third of the course covers dynamics, and the second third feedback control. Both of these parts are infused with biological examples and systems, includ- ing a couple of special lectures. The last third of the course includes a new section on nonlinear dynamics, and a week 299 to review current modeling and control literature. Students are graded on the traditional tests and homework, and in ad- dition they perform an experimental lab exercise and present a literature article to the class. Box 3 shows the biologically related learning objectives and those from the novel nonlinear dynamics segment. Traditional components Many portions of a traditional chemical process control course have been retained. In particular, the philosophies of model building, Laplace approaches, transfer functions, block diagrams, feedback control, and frequency response methods are essential. Many traditional concepts can be reinforced through biological examples from recent literature, e.g., Mark Marten's lab has recently characterized experimental fre- quency responses of fungal cell cultures.""2' Some of the more advanced and specialized treatments for process analysis, however, have been trimmed to make additional time for new concepts. Topics now minimized include in-depth treatments of model identification, discrete control, control methodologies such as ratio control and cascade control, and, regretfully, modem control approaches such as model-based controllers. MAJOR REVISIONS The major subject material additions to the course are as follows. Central Dogma The Central Dogma of Biology concerns the flow of infor- mation in a cell. Deoxyribonucleic acid (DNA) is transcribed by the polymerase into ribonucleic acid (RNA), and RNA is translated by the ribosome into protein. Proteins perform functions within the cell. Therefore, control in a cell can be exerted at any of these levels-interfering with transcription, translation, or the protein function directly. These systems can be modeled as a set of chemical reactions in a cascade, for ex- ample, r rantlaon(t) = k ranslationC oee(t-0)C nRNA(t-6) expresses the rate of translation of mRNA into protein, given the concentra- tion of the polymerase and the mRNA transcript, and assuming a transcription time delay of 0. These concepts are accessible to students with training in kinetics and reactor design. Pharmacokinetic and Pharmacodynamic Approaches Organism models have been built using so-called phar- macokinetic approaches. In this approach, each tissue in the body (e.g., brain, liver, muscle) is modeled as a one-, two-, or three-compartment chamber. The compartments are assumed to be either diffusion-limited or reaction-limited, and are modeled accordingly as an ideal system. The bloodstream is modeled as a single (or double) well-mixed compartment that connects the other organs together. The set of compartments can be distilled into a system of coupled ordinary differential equations. These models are most often used to characterize the movement of a drug or specific set of molecules around the body.113141 300 Population Balances Molecular, cellular, and ecological systems can be con- sidered by writing population balances, or balances on the number of cells, molecules, or organisms in the system: dN/dt = bN-dN+F, where N is the number of units in the system, b and d are birth and death rates, and F represents additional fluxes in or out of the system. These types of models can describe the number of molecules inside a cellular organ- elle, the number of cells in a culture or tissue, or the number of organisms in an ecosystem, for example. Such equations are intuitive for a chemical engineering student with training in mass and energy balances, and they quickly allow the student to work problems with these applications. An example study in literature is the measurement of leukocyte birth and death rates using tracing with the BrdU label.151 Control of Gene Expression One of the most fundamental ways in which a cell exhibits control is by changing which genes are expressed, thus what proteins exist to carry out function.1"6' Gene expression is controlled by transcription factors -proteins that bind to the DNA and either recruit the polymerase or prevent the poly- merase from initiating a transcript. The transcription factors themselves are often switches activated by the presence of a small molecule or a covalent modification. For example, the bacterial lac operon system regulates cell metabolism to use either glucose or lactose as a carbon source."61 When lactose is present, allolactose (a lactose derivative) binds the lac re- pressor, which can then dissociate from the DNA, allowing transcription of the genes encoding the proteins necessary for metabolizing lactose. In the presence of the more efficient glucose feed, however, additional proteins are regulated via the level of cyclic AMP to ensure metabolic energy is not wasted producing lactose-metabolizing machinery. Keasling's group has constructed a straightforward dynamic model of the system,"7' and their article makes an excellent demonstration of a nonlinear, multivariable system that can be simulated using concepts, skills, and tools that students learn in the first third of a dynamics and control course. Furthermore, this segment allows me to introduce a descrip- tion of the biomolecules involved in the process. In traditional process dynamics and control courses, students learn about sensors, transducers, and actuators. In the new ChemBE cur- riculum, students must also examine the structures of biomo- lecular control components. PowerPoint slides available from publisher W.H. Freeman8IJ (Chapter 31) show the structures of molecules involved in control loops in both prokaryotic and eukaryotic cells, from the small molecule effectors, to allosteric proteins and transcription factors, to the ribosome, polymerase, and histones. With this biomolecular background, students were challenged in a homework assignment to imag- ine other nanoscopic implementations of a control scheme. In addition, they could predict the effect of perturbations to the existing biological system (see Box 4, page 304). Chemical Engineering Education Large-Scale Biosimulation The scope and impact of biosimulation is demonstrated by examining recent simulations by a biotechnology startup com- pany that has published details on its models. Entelos (Daly City, CA) employs chemical engineers along with biologists, biochemists, and computer scientists to create realistic disease models. We review the idea of taking a model to the extreme using a case study of Entelos arthritis model that simulates a rheumatoid joint. The model has hundreds of state variables and captures cell population dynamics, biochemical mediator production, cell contact of synovial fibroblasts, macrophages, T-cells, and chondrocytes. Ultimately, the model predicts cartilage degradation."9' With this example, we can discuss issues of numerical accuracy, 100% experimental validation, and uncertainty. Additional Dynamical Analysis Topics 90% - Several fundamental skills underlie biologi- 80% - cal dynamics problems and need extra empha- sis in our course. Fortunately, some of these 70% - same concepts, such as state-space representa- tion, multivariable systems, and treatment of 60%- coupled nonlinear evolution equations, have 50% - Figure 1: Biology-course background of 40% students in the dynamics and control class (ChemBE 409) and for ChemBE majors 30% - only. The number of students surveyed in the course each year was 21, 29, and 31 20% - in Fall 2003, 2004, and 2005, respectively. The number of ChemBE graduates was 12, 10%- 15, 14, 20, and 15 for the classes of 2002- 2006. Students were not surveyed about 0% - their academic background in Spring 2002-2003, and data for majors are from student transcripts. Fall 2006 become more important in industrial process control and are more emphasized in recent textbook treatments. While Laplace approaches create elegant analytic treatments, tools such as MATLAB and Mathematica make it easy to represent vectors and create state-space representations. In particular, Bequette s recent textbook'91 incorporates the state-space viewpoint from the beginning, introducing eigenvalue/eigen- vector treatments immediately and later developing Laplace treatments. With computational tools it is a straightforward generalization to include multiple variables for inputs and outputs in a dynamic model. These approaches culminate in a unit on nonlinear dynamics at the end of the semester. BOX 3 Nontraditional Learning Objectives Basics of Modeling: 1. Derive population model equations for cells, molecules, or organisms. 2. Describe the approach of pharmacokinetic modeling. 3. Derive dynamic equations for compartment-based models of living organisms. Biomolecular Control Systems: 4. Describe the lac operon as a model biomolecular control system, using standard biochemical terms properly (operator, inducer, repressor, promoter, gene, constitutive, induced). 5. Identify standard control features in biomolecular control systems. 6. Describe post-translational control strategies and eukaryotic strategies such as chromatin packing. 7. Describe the Central Dogma of Biology and identify steps where control can be achieved. 8. Imagine new complex control arrangements using biomolecular components. 9. Create complex dynamic models for biomolecular systems. Introduction to Nonlinear Dynamics: 10. Analytically solve for a trajectory given initial conditions and a linear system. 11. Sketch a phase portrait for a linear system or for some nonlinear systems. 12. Identify attractors, repellors, centers, and saddles from the eigenvalues of a system near a fixed point. 13. Identify or define limit cycles and describe qualitative features of chaotic trajectories. 14. Integrate a nonlinear system using a numerical tool. BOX 4 Sample Homework and Exam Problems in (passive diffusion of metabolite) Biomolecular Modeling and Control Population balances and compartment models M M, Develop a very simple dynamic model for an E. coli cell consuming (receptor a metabolite. Ultimately, we would like to know the instantaneous detects Mo M P rate of hydrolysis of the metabolite in response to dynamic changes and signals -E in the metabolite concentration outside of the cell. The hydrolysis production occurs via an enzyme that is itself regulated (through molecular of E) mechanisms in the cell) by the external metabolite concentration. Assume the concentration of the metabolite outside of the cell, M,,, can be manipulated dynamically. The metabolite diffuses passive- ly into the cell. Inside the cell, an enzyme hydrolyzes the metabolite (concentration M) into a product. The enzyme (concentration E) is expressed in response to the presence of the metabolite: a receptor on the outside of the cell detects the external concentration of metabolite and signals this information to the transcription and translation machinery; for simplicity, ignore those intermediate steps and assume that the rate of enzyme production in the cell is instantaneously proportional to the concentration of the metabolite out- side the cell. The enzyme cannot diffuse through the cell membrane and it degrades naturally with a rate of r, = kdE. The metabolite kME hydrolysis obeys Michaelis-Menten kinetics, r = --- . Km,+M a. Identify the state variable(s). input and output variable(s), and parameterss. b. Derive model differential equations to describe this system. Define any physical parameters you need as necessary. c. Put your model in deviation variable form and linearize if necessary. You might want to replace combinations of constants with new parameters (ca, P, etc.) to make your mathematics convenient, particularly as you proceed to (d). d. Find a transfer function from the input to output variable(s). Pharmacokinetics a. Sketch a process flow diagram for a pharmacokinetic model that includes a one-compartment pancreas and a two-compart- ment brain, connected by the bloodstream. b. Formulate model equations for the concentrations of a molecule in the brain. Assume the flux between the two compartments is membrane-limited and passive, i.e., n = -h(C,-C,,/R). Also, assume the molecule is degraded in the inner compartment with first-order rate constant kd'. c. Identify input and output variables and parameters for the most general model. Is your system under-, over-, or exactly deter- mined? Control of gene expression (adapted from Berg"6") A common genetic manipulation employed by cell biologists is to delete a particular gene. What would be the effect of deleting the following genes in the lac repressor system? a. lacY b. lacZ c. lad Nonlinear dynamics (adapted from Beltrami210,3U) Consider this coupled system of ODEs: x, =9x, 1- 2x,x, 9, 2 =6x, 1 X xx, This model captures the dynamics of two competing populations of bacteria. The two state variables represent the population densi- ties of each species, the terms in parentheses cap the growth due to limitations in the environment, and the xx, terms represent the negative effects of competition between the species. a. Show that the point [ 5 2 ]' is a fixed point. b. Linearize the system around [ 5 2 i] and find the eigenvalues and eigenvectors. Is this point stable or unstable? Is the local behavior oscillatory? c. Sketch the phase portrait for this system, including the four fixed points, nullclines, and representative trajectories. Note that since the variables represent population densities, values less than zero are not meaningful and can be omitted from the dia- gram. d. Briefly interpret the physical meaning of the phase portrait. 302 Chemical Engineering Education BOX 5 Selected Literature Articles, Including Biological Dynai Suitable for Review in an Undergraduate Course "Robust control of initiation of prokaryotic chromosome replication: essential for a minimal cell," S.T. Browning, M. Castellanos, and M.L. Shuler. Biotech 575 (2004) "Containing pandemic influenza at the source." I.M. Longini Jr.. et al., Scien (2005) "A computational study of feedback effects on signal dynamics in a mitogen- kinase (MAPK) pathway model," A.R. Asthagiri and D.A. Lauffenburger, Bi 17, 227, (2001) "A mathematical model of caspase function in apoptosis." M. Fussenegger, J. Varner, Nat. Biotechnol.. 18, 768 (2000) "Robust perfect adaptation in bacterial chemotaxis through integral feedback Y. Huang, M.I. Simon and J. Doyle. Proc. Nat. Acad. Sci.. 97(9), 4649 (2000 Nonlinear Dynamics Since biological systems are often highly nonlinear and can exhibit multiple steady-state and non-steady-state be- havior, I have incorporated a unit on nonlinear dynamics. We begin with a set of nonlinear, multivariable, dynamic equa- tions, such as x, =x,;x, =-x, -sinx, which represents large motions of a forced pendulum. Approaches to these problems are covered in Beltrami's short treatise120" and in a later chapter in Coughanowr's text."211 We discuss the idea of multiple steady states and how a complete analysis must capture a system's behavior throughout the phase space. We then discuss fixed points (steady states), eigenvalues (poles), and eigenvectors, relating them to concepts introduced in the Laplace framework. We proceed to sketching phase portraits of attractors, repellors, saddles, and centers. Finally, we dis- cuss means of constructing a complete nonlinear phase portrait using nullclines and linear analysis of all fixed points. 201 The Lotka-Volterra problem,1221 which is usually associated with predator-prey ecological phenomena but was, in fact, first derived to analyze chemical kinetics, provides an excellent and tractable in-class problem for students to work in small groups. Discussion leads naturally to concepts of robustness (or the lack thereof in the Lotka-Volterra system) and the idea of a limit cycle. In discussing limit cycles, we review oscil- lating chemical systems such as the Belousov-Zhabotinsky reaction,123.241 for which chemical kinetic models have been constructed."251 Finally, in a homework assignment, students integrate the Lorenz equations to plot trajectories for a strange attractor based on the Rayleigh instability of a liquid heated from below.1261 In the final class discussion we contrast this system's dynamics with that of less strange attractors, and we identify the defining characteristics of chaos (i.e., sensitivity to initial conditions, trajectory returning infinitely often albeit erratically to the neighborhood of each point on the attrac- tor, fractal microstructure, and noisy power spectra). With a background in dynamics developed throughout the semester, students have an appreciation for the oddities of a chaotic system and a strange attractor, and are able to speculate how Fall 2006 a chaotic dynamical system might be controlled. mics, Literature Review l considerations Student understanding of modeling, i. Bioeng.. 88(5). dynamics, and control concepts in the application to biological systems can be immediately assessed by an oral literature activated protein review. In small groups of two to three otechnol. Prog.. people, students review a current paper in scientific literature on the subject of mod- E. Bailey and J. eling, dynamics, and control of a chemi- control," T.M. Yi. cal or biological process. The goals are: ) (1) to apply knowledge of modeling and control to current applications, particularly in biomolecular and cellular applications for which the course has relatively few homework problems during the semester; (2) to gain experience extracting relevant information from primary literature; (3) to synthesize the topics covered during the semester; and (4) to practice oral presentation skills. Talks present the basic concepts of the article, particularly the modeling and control aspects. Stu- dents need to rephrase the work into standard control terms (control objective, inputs, outputs, state variables, feedback, feedforward, stability, robustness, etc.). Short presentations and written summaries include basic background of the ap- Class discussion, however, often clarified points and helped students recognize the motivations and strategies employed by each paper's authors. plication, some details on the model or controller formulation, and some of the results. The ambitious groups replicate some of the work, a simplified model, or a simple extension using MATLAB. I provide the students a list of articles in literature (see Box 5), but students are allowed to chose articles that interest them, and occasionally they contribute something from a lab where they work. Overall, students demonstrate ease in explaining the biological context of the problems and the dynamic behavior or control systems studied. Occasion- ally students needed help identifying proper state variables and system inputs and outputs, and some complex models in the literature were challenging for undergraduates to fully appreciate. Class discussion, however, often clarified points and helped students recognize the motivations and strategies employed by each paper's authors. Students complete peer- assessments of the members of their team,t271 and I evaluate their talks, focusing on how well students learn the concepts of dynamics and control (see Box 6). Guest Lectures To further broaden the perspectives heard in-class, I typi- cally include two guest lectures per semester. One is given by Red Bradley and Lochlann Kehoe of GSE Systems, a local control systems company. These engineers give an industrial perspective on the challenges and complexities of modeling and controlling real chemical process systems. The second guest lecture is given by someone involved in biological modeling, and differs each year. Two recent speakers were Prof. Kenneth Kauffman of the University of California at Davis who discussed optimal control in cellular systems,i281 and Dr. Saroja Ramanujan of Entelos, Inc., who discussed large-scale biosimulation of arthritis.l191 Guest lectures include a question-and-answer period, and student comprehension of the main topics is evaluated through short-answer, closed- book exam questions. ASSESSMENT Students complete a mid-semester survey and an end-of- semester course evaluation, both of which include questions about the usefulness of the biological content in the course. Opinions are mixed, as some students enjoy the new perspec- tives while others are clearly uncomfortable with the biologi- cal topics (data not shown). Resistance has decreased in recent years, probably due to a combination of changed expectations and improved teaching of the material due to past feedback. To assess the long-term effectiveness of the class, alumni from the first three offerings of the course were surveyed online. Respondents included students from the graduating classes of 2003 through 2005 currently in industry, graduate school in ChE or ChemBE, graduate school in other fields, or professional school. The survey and responses are shown in Box 7. Overwhelmingly, the alumni felt that the addition of biological material helped make the course more practical, and prepared them for their future careers. They also felt that the course did not suffer from lack of traditional content; this view was shared by an alum working in the process control industry and another in a graduate process control research group. Anecdotally, one alumnus reported that he had vigor- ously opposed the integration of biology into the curriculum in his end-of-semester course evaluation and senior exit interview, but that he had experienced a complete change of heart and now is thankful for his biologically related training. Another alumnus, now a graduate student in biological and environmental engineering, noted that the study of the lac operon was specifically useful to converse with biologists and understand gene regulation. Interestingly, 62% reported that knowledge of biology is essential to their current positions, and only one respondent reported that biology is not at all needed in his or her current position. OUTSTANDING TOPICS Much of dynamic biological phenomena requires math- ematical treatments that are significantly different from traditional, lumped-parameter, continuous, or deterministic treatments. In particular, many molecular systems are known to be stochastic and require treatments such as Fokker-Planck and Langevin equations.1291 Recently, one institution has developed a Web module to teach stochas- tic modeling using batch reactor models and oscillating reactions.13t1 I have, so far, been unable to introduce this material, but perhaps as students enter with more biology background the time devoted to introducing biological concepts can be redirected toward these novel treatments. One possibility to free up additional time might be teach- ing dynamics entirely in state-space form and removing BOX 6 Literature Review Evaluation of Team Oral Presentations Assessment Questions (50%) Have the students demonstrated understanding of the major concepts of modeling, dynamics and control (modeling, solution of dynamic equations, nonlinearities, control, feedback, stability, robustness, validation, phase behavior, etc. as appropriate for the article)? (10%) Have the students demonstrated an understanding of computational tools? (20%) Have the students demonstrated excellent communication skills? (10%) Have the students demonstrated an ability to work together in teams? (10%) Are the students aware of contemporary issues, the impact of the work, and any professional or ethical responsibilities? Components Technical Content (65%): Introduction (15%): Problem and goals explained clearly to audience Model description (15%): Origin of model explained and significant assumptions detailed, model explained clearly to audience Results (15%): Most significant results shared clearly, results teach something to the audience, control schemes are useful Other Design Criteria / Broader Impacts (5%): Safety, environmental, economic, biological criteria; relate work to current knowledge in field Reasonable responses to questions (15%) Presentation (35%, roughly 5 points each): Overall flow and pace, organized presentation, clear and interesting slides, time limit met, reasonable energy level, participation by all group members, creativity, clear one-page summary sheet Chemical Engineering Education Laplace treatments, but this could prove challenging with the absence of appropriate textbooks. CONCLUSIONS This paper surveys a radical revision of a chemical engineer- ing process control course to include new material appropriate for chemical and biomolecular engineers. The revised cur- riculum has excited students and provided strong preparation for graduate school, professional school, or industry. I hope this description of our remolded dynamics and control class will be useful, inspiring, and perhaps help others to determine the next step in the chemical engineering curricular evolution. Brown has remarked that the transformation of a curriculum can take a decade.I 61 The shift in the chemical engineering curriculum has just begun, and we will see more changes in the next few years. ACKNOWLEDGMENTS The teaching assistants for this course over the last several years, Tom Mansell, Aroop Sircar, Jullian Jones, and Robert Plemons, added their perspective on biomolecular engineering to help formulate problems and topics. I also thank former department chair Michael Betenbaugh for encouraging me to experiment with the content of this course. Kenneth Kauffman generously provided insightful comments on the manuscript and guidance on course assessment. BOX 7 Assessment Results From Alumni Survey Sixteen alumni responded (out of 55). Respondents came from the classes of 2003 (5), 2004 (7). and 2005 (3). Largest responses indicated in bold. "Rate your agreement with the following state- N/A 1-strongly 2-dis- 3-neutral 4-agree 5-strongly Response ments." disagree agree agree Average 1. I am comfortable with my process dynam- 0% (0) 0% (0) 6% (1) 12% (2) 50% (8) 31% (5) 4.06 ics, modeling, and control background from the Chemical & Biomolecular Engineering Depart- ment at JHU. 2. I1 feel this course has prepared me for the chal- 6% (1) 0% (0) 6% (1) 19% (3) 38% (6) 31% (5) 4.00 lenges I have encountered with modeling, dynam- ics, and control after leaving JHU. 3. I1 feel this course shortchanged me by omitting 19% (3) 19% (3) 44% (7) 6% (1) 12% (2) 0% (0) 2.15 key concepts from classical dynamics and control. 4. The integration of biology helped to make the 6%(1) 0% (0) 6%(1) 12% (2) 31%(5) 44% (7) 4.20 concepts of the course more practical. 5. The integration of biology helped to make the 6% (1) 0% (0) 12% (2) 12% (2) 44% (7) 25% (4) 3.87 concepts of the course more intuitive. 6. The integration of biology helped prepare 6% (1) 6%(1) 0%(0) 12%(2) 31%(5) 44% (7) 4.13 me for my career or education after my B.S. in ChemBE. 7. I1 have developed an appreciation for the 6% (1) 0% (0) 6% (1) 0% (01 62% (10) 25% (4) 4.13 challenges of analyzing complex dynamics and regulation in biological and chemical systems. 8. I1 feel I lack a sufficient foundation from JHU in 6% (1) 25% (4) 38% (6) 6% (1) 19% (3) 6% (1) 2.40 dynamics, modeling, and control to be successful at the types of tasks required of me in my current position. 8 12. 7 6- What is your current position? 10 How important is biology 2 6- 1 4- 0 t I I . Industry Graduate Graduate Professional Other 2 . school in ChE school in school or ChemBE other field (medical, 0 business, Not at all Peripherally Routine Essential law, etc) relevant Fall 2006 30. Additional course material can be accessed at edu/courses/540.409>. REFERENCES 1. Kim, I., "A Rich and Diverse History," Chem. Eng. Prog., 98, 2S-9S (2002) 2. Lander, E.S., L.M. Linton, B. Birren, C. Nusbaum, M.C. Zody, and J. Baldwin, et al., "Initial Sequencing and Analysis of the Human Genome," Nature, 409, 860 (2001) 3. Venter, J.C., M.D. Adams, E.W. Myers, P.W. Li, R.J. Mural, and G.G. Sutton, et al., "The Sequence of the Human Genome," Science, 291, 1304 (2001) 4. Henry, C.M., "Systems Biology," Chem. and Eng. News, 81, 45 (2003) 5. Kitano, H., "Systems Biology: A Brief Overview," Science, 295, 1662 (2002) 6. Brown, R.A., "Frontiers in Chemical Engineering Education" (Web site), (2002-2006) 7. Edgar, T.F, "ChE Curriculum of the Future: Re-Evaluating the Process Control Course," Chem. Eng. Ed., 37, inside cover (2003) 8. Csete, M.E., and J.C. Doyle, "Reverse Engineering of Biological Complexity," Science, 295, 1664 (2002) 9. Bequette, W.B., Process Control: Modeling, Design, and Simulation, Prentice Hall PTR, Upper Saddle River, NJ (2003) 10. Ogunnaike, B.A., and W.H. Ray, Process Dynamics, Modeling, and Control, Oxford University Press, New York (1994) 11. Seborg, D.E., T.F. Edgar, and D.A. Mellichamp, Process Dynamics and Control, 2nd Ed., Wiley (2004) 12. Bhargava, S., K.S. Wenger, K. Rane, V. Rising, and M.R. Marten, "Effect of Cycle Time on Fungal Morphology, Broth Rheology, and Recombinant Enzyme Productivity during Pulsed Addition of Limiting Carbon Source," Biotech. Bioeng., 89, 524 (2005) 13. Gerlowski, L.E., and R.K. Jain, "Physiologically Based Pharmacokinetic Modeling: Principles and Applications," J. Pharm Sci, 72, 1103 (1983) 14. Saltzman, W.M., Drug Delivery: Engineering Principles for Drug Therapy, Oxford University Press, New York (2001) 15. Mohri, H., S. Bonhoeffer, S. Monard, A.S. Perelson, and D.D. Ho, "Rapid Turnover ofT Lymphocytes in SIV-infected Rhesus Macaques," Science. 279, 1223 (1998) 16. Berg, J.M., J.L. Tymoczko, and L. Stryer, Biochemistry, 5th Ed., W.H. Freeman, New York (2002) 17. Wong, P., S. Gladney, and J.D. Keasling, "Mathematical Model of the lac operon: Inducer Exclusion, Catabolite Repression, and Diauxic Growth on Glucose and Lactose," Biotechnol Prog, 13, 132 (1997) 18. Clarke, N.D., J.M. Berg, J.L. Tymoczko, and L. Stryer, Web Content to Accompany Biochemistry, 5th Ed. (Web site), com/biochem5> (2002) 19. Rullmann, J.A., C. H. Struemper, N.A. Defranoux, S. Ramanujan, C.M.L. Meeuwisse, and A.V. Elsas, "Systems Biology for Battling Rheumatoid Arthritis: Application of the Entelos PhysioLab Platform," IEE Proceedings-Systems Biology, 152, 256 (2005) 20. Beltrami, E.J., Mathematics for Dynamic Modeling, 2nd Ed., Academic Press, Boston (1998) 21. Coughanowr, D.R., Process Systems Analysis and Control, 2nd Ed., McGraw Hill, Boston (1991) 22. Krebs, C.J., Ecology, 5th Ed., Pearson, Boston (2002) 23. Belousov, B.P., "The Oscillating Reaction and its Mechanism," Khimiya i Zhizn, 7, 65 (1982) 24. Zaikin, A.N., and A.M. Zhabotinsky, "Concentration Wave Propagation in Two-Dimensional Liquid-Phase Self-Oscillating System," Nature, 225, 535 (1970) 25. Field, R.J., and R.M. Noyes, "Oscillations in Chemical Systems IV. Limit Cycle Behavior in a Model of a Real Chemical Reaction," J. Chem. Phys., 60, 1877 (1973) 26. Lorenz, E.N., "Deterministic Nonperiodic Flow," J. Atmos. Sci., 20, 130 (1963) 27. Kaufman, D.B., R.M. Felder, and H. Fuller, "Accounting for Indi- vidual Effort in Cooperative Learning Teams," J. of Eng. Ed., 89, 133 (2000) 28. Kauffman, K.J., E.M. Pridgen, F.J. Doyle III, P.S. Dhurjati, and A.S. Robinson, "Decreased Protein Expression and Intermittent Recoveries in BiP Levels Result from Cellular Stress During Heterologous Protein Expression in Saccharomyces Cerevisiae," Biotech. Prog., 18, 942 (2002) 29. Rao, C.V., D.M. Wolf, and A.P. Arkin, "Control, Exploitation, and Tolerance of Intracellular Noise," Nature, 231(7), 420 (2002) 30. Kraft, M., S. Mosbach, and W. Wanger, "Teaching Stochastic Model- ing to Chemical Engineers Using a Web Module," Chem. Eng. Ed., 39 (2005) 31. Beltrami, E.J., Mathematical Models for Society and Biology, Academic Press, San Diego (2002) Li Chemical Engineering Education [M] B class and home problems Computer-Facilitated Mathematical Methods in ChE SIMILARITY SOLUTION VENKAT R. SUBRAMANIAN Tennessee Technological University Cookeville, TN 38505 High-performance computers coupled with highly ef- ficient numerical schemes and user-friendly software packages have helped instructors teach numerical solutions and analysis of various nonlinear models more efficiently in the classroom. One of the main objectives of a model is to provide insight about a system of interest. Ana- lytical solutions provide very good physical insight, as they are explicit in the system parameters. Having taught applied math to both senior undergraduate and first-year graduate students for five years, this author feels that students do not appreciate the value of analytical solutions because (1) they wrongly believe numerical methods are best used to solve complex problems with high-speed computers, and (2) they are not comfortable or confident doing the complicated integrals, rigorous algebra, and transformations involved in obtaining analytical solutions. Such solutions, however, can be gained using various computer techniques. For example, computer algebra systems such as Maple,11' Mathematica,j21 MATLAB,'3' and REDUCE,I4' can be used to perform the tedious algebra, manipulations, complicated integrals, vari- able transformations, and differentiations, etc., involved in applying mathematical methods. The goal of this paper is to show how Maple can be used to facilitate similarity transformation techniques for solv- ing chemical engineering problems. The utility of Maple in performing the math, solving the equations, and plotting the results will be demonstrated. For an understanding of the physics in the problems solved, readers are advised to refer to the cited references. For the sake of readers not familiar with Maple, a brief introduction about Maple is given. Venkat Subramanian is an assistant professor in the Department of Chemical Engineering at Tennessee Technological University. He received a B.S. degree in chemical and electrochemical engineering from Central Electrochemical Research Institute in India, and his Ph.D. in chemical engineering from the University of South Carolina. His research interests include modeling, control and simulation of electro- chemical systems including batteries, fuel cells, hybrids, and multiscale simulation. He is the principal investigator of the Modeling, Analysis, and Process-Control Laboratory for Electrochemical Systems (MAPLE lab, ). CoprTight ChE Division of ASEE 2006 Fall 2006 The object of this column is to enhance our readers' collections of interesting and novel prob- lems in chemical engineering. Problems of the type that can be used to motivate the student by presenting a particular principle in class, or in a new light, or that can be assigned as a novel home problem, are requested, as well as those that are more traditional in nature and that elucidate dif- ficult concepts. Manuscripts should not exceed 14 double-spaced pages and should be accompanied by the originals of any figures or photographs. Please submit them to Professor James 0. Wilkes (e-mail: wilkes@umich.edu), Chemical Engineering Department, University of Michigan, Ann Arbor, MI 48109-2136. MAPLE Maple"i is a computer-algebra system capable of perform- ing symbolic calculations. Although Maple can be used for performing number crunching or numerical calculations just like FORTRAN, the main advantage of Maple is its symbolic capability and user-friendly graphical interface. In a Maple program, commands are entered after a ">". Maple prints the results if a ";" is used at the end of the statement. This helps in fixing mistakes in the program after a particular step, as the results are shown after every step or command. For brevity, in this paper most of the Maple commands are ended with a colon (:). In general, while Maple is very useful in doing transformations, the user might have to manipulate resulting expressions from a Maple command to obtain the equation in the simplest or desired form. Often, these manipulations can be done in Maple itself by "seeing" the resulting expres- sions. Hence, first-time users should use a ";" instead of a ":" at the end of each statement to view the results after each command/statement. Many of the mistakes made by students are identified and rectified easily if they replace ":" with ";" in all of the statements. Maple can be used to perform all steps from setting up an equation to analyzing the final plots on the same sheet. All the mathematical steps and manipulations involved can be performed in the same program or file. For clarity between the Maple commands and output, all the text describing the process or Maple commands is given within brackets, "[ ]". SIMILARITY TRANSFORMATION FOR PARTIAL DIFFERENTIAL EQUATIONS Similarity transformation is a powerful technique for treating partial differential equations arising from heat, mass, momentum transfer, or other phenomena, because it reduces the order of the governing differential equation (from partial to ordinary). Depending on the governing equation, boundary conditions, domain, and complexity, the similarity transformation technique might yield a closed-form solu- tion, a series solution, or a numerical solution. One of the major difficulties students encounter is that they find it very difficult to convert the governing equation from the original independent variables to a similarity variable. The following examples illustrate the use of computers and software in teaching/obtaining similarity solutions for various chemi- cal engineering problems. D Example 1 Diffusion/Heat Transfer in Semi-infinite Domains Consider the transient heat-conduction problem in a slab.',21] The governing equation and initial/boundary conditions are expressed in Eq. (1). Ou 02U at ~ x2 u(x,0) 0 (1) u(0, t) = 1 and u(oo, t) = 0 where u is the temperature, x is the distance from the surface of the slab, t is the time, and a is the thermal diffusivity. Eq. (1) is solved by using the transformation = x / (2, Vt). The origi- nal partial differential equation is converted to an ordinary differential equation in the similarity variable, q. The bound- ary conditions for U (u in the similarity variable), are: U(0) = 1 U(oo) = 0 (2) The steps involved in the similarity transformation method are illustrated below: Typically, Maple programs are started with a "restart" com- mand to clear all the variables. Next, the "with(student)" package is called to facilitate variable transformations: >restart: with(student): >eq:=diff(u(x,t),t)-alpha*diff(u(x,t),x2);

eq:= u(x, t) -a 9u(x, t)
at Cx

[First, u(x,t) is transformed to U(Tq(x,t)). Then, the governing
equation is converted to the similarity variable:]
>eq1 :=changevar(u(x,t)=U(eta(x,t)),eq):eq2:=expand
(simplify(subs(eta(x,t)=x/2/(alpha*t)A(1 /2),eq 1))):
eq2:=expand(eq2*t):eq2:=subs (x=eta*2*(alpha*t)A(1 /
2),eq2):eq2:=convert(eq2,diff):
[The final form of the governing equation is:]
>eq2:=expand(-2*eq2);

eq2:= dU() q+I- U (q)
di| 2 d7
[The given boundary conditions are used to solve the govern-
ing equation:]
>bcl:=U(0)=1l
bcl: =U(0)=1
>bc2:=U(infinity)=0;
bc2: =U(o) = 0
>U:=rhs(dsolve({eq2,bcl ,bc2},U(eta))):
>U:=convert(U,erfc);
U: = erfc (TI)
>u:=subs(eta=x/2/(alpha*t)^(1/2),U);
u := erfc 2 o

[The solution is plotted in Figure 1, which shows how the
temperature, u, penetrates to progressively greater distances
as the time, t, increases:]
>plot3d(subs(alpha=0.001 ,u),x=1 ..0,t=500..O,axes=bo
xed,labels=[x, t,"u"],orientation=[-60,60]);
Chemical Engineering Education

Figure 1. Dimensionless temperature distribution
in a semi-infinite domain.

Example 2
Plane Flow Past a Flat Plate-Blasius Equation

The velocity distribution in the boundary layer of a plane laminar
flow past a flat plate is given by Eq. (3):
+u v 0
Ox -y
0x Dy

Ou u OU 02u
U----V-=---
Ox Oy 9y2
u(0,y) = 1
u(x,0)= 0 and u(x,cc)= 1
v(x,0)= 0
For this problem, first the velocities, u and v, should be convey
stream functions defined by u = O9 / Dy and v = -Dp / Ox
stream function, by default, satisfies the continuity equation
1). The second equation yields the governing equation fi
stream function, p. Next, the stream function is express
S=x f (rq), where T = y/Vx is the similarity variable
boundary conditions for u and v yield the boundary conditions
and finally for f(rl). Once the function f(TI) is obtained (numerii
both stream functions and velocity expressions can be express
terms of f and i|. The steps involved in this example are more t(
compared to the previous example. All the complicated steps in,
can be facilitated using Maple:
>restart:with(student):with(plots):
Warning, the name changecoords has been redefined
[The governing equation is entered:]
>eq:=u(x,y)*diff(u(x,y),x)+v(x,y)*diff(u(x,y),y)- diff(u(x,y)

eq:= u(x,y) u (x,y) + v(x, y) u (x, y) u (xy)
Fall 20y 06
Fall 2006

08-6
06
u
04

(12

1 f()- D(f)(T)Tq

(3) 2
> u(eta):= d iff(p si(x ,y),y):
u(eta):=changevar(psi(x,y)=x^A(l/2)*f(et
a(x,y)),u(eta)): u(eta):=expand(s u bs(eta(x,y)=
y/x^A(1/2),u(eta))): u(eta):=subs(y=eta*x^A(1/
rted to 2),u(eta));
. The u():= D(f)(q)
n (Eq.
or the [D(f)(T) in Maple represents the derivative of f with
;ed as respect to rT. Next, the boundary conditions are ex-
*. The pressed in terms of f:]
for p, >bcl :=subs(eta=0,v(eta))=0;
allyy, bcl 1 f(0)
bcl:sed 0
sed in 2 F

>bcl:=-bcl *2*xA(1/2);

>bc2:=subs(eta=0,u(eta))=0;

bcl := f(0)= 0

bc2:= D(f)(0)= 0

>bc3:=subs(eta=infinity,u(eta))=1;
bc3:= D(f)(oo)= 1
[The length of the domain is taken to be five (to replace
infinity). This number is found by trial and error. Increas-

[Next, Stream functions
(u = 9l / 9y and v = -Oi / Ox)
are introduced]
>va rs:={u(x,y)=d iff(psi(x,y),y),v(x,y)=-
diff(psi(x,y),x)}: eq:=subs(vars,eq);

eq:= a '(xy) 92-^(xy)
9y Ox 9y

x,y) (x,y2 (x,y)

[Next, the transformation
S= Txf(), where q = y /
is used to obtain the equation for f:]
>eq:=changevar(psi(x,y)=xA(1 /2)*f(eta(x,y)),eq):
eq 1:=(simplify(subs(eta(x,y)=y/xA(1/2),eq))):
eq 1 :=subs(y=eta*x^A(1/2),eq 1 ):eq 1 :=si
mplify(eq 1*x):eq2:=convert(-eq1 ,diff);

eq2 := I (d ) f() + d f (T)
2 dri' d41
[Next, the velocity variables, u and v (i.e., derivatives
of the stream function), are expressed in terms of f and
the similarity variable i:]
>v(eta):=-
diff(psi(x,y),x):v(eta):=changevar(psi(x,y)=x^A(1 /
2)*f(eta(x,y)), v(eta)):v(eta):=expand(subs(eta(x
,y)=y/x^A(1/2),v(eta))):v(eta):= subs(y=eta*x^A(1 /
2),v(eta)):v(eta): =facto r(v(eta));

ing the length beyond five does not change the results.]
>bc3:=subs(infinity=5,bc3);
bc3:= D(f)(5)= I
[For this problem, analytical solutions are not possible (al-
though approximate solutions are possible). For this example,
numerical solution for the Blasius equation is obtained as:]
>sol:=dsolve({eq2,bcl ,bc2,bc3},f(eta),type=numeric);
sol:= proc (x bvp) ... end proc
[The solution is plotted in Figure 2, which shows how the
function, f (related to the stream function), varies with the
similarity variable, TI, from zero to five]
>odeplot(sol,[eta,f(eta)],0..5,thickness=3,axes=boxed);
[Next, velocity profiles are obtained:]
>u(eta):=convert(u(eta),diff);v(eta):=convert(v(eta),diff);
d
u(q):= f( Tl)

( 1 d:=
2 Vx
[Figure 3 shows how the x component of velocity increases
from zero, at the wall, and levels off at its main stream value
for larger values of Tj from zero to five]
>odeplot(sol,[eta,u(eta)],0..5,thickness=3,axes=boxed
,labels=[eta ,u]);
[Since v is a function of x, v*x!/2 is plotted. Figure 4 shows
the y component of velocity (multiplied by x1/2) increases
from zero at the wall, and levels off at its main stream value
for larger values of iT from zero to five]
>odeplot(sol,[eta,v(eta)*x (1 /
2)],0..5 ,th ickness=3 ,axes=boxed,lab
els=[eta,"v*xA(1/2)"]);
[The solution at T) = 0 is obtained as:]
>sol(0);
d d
vT=0.,f(Tj)=0., df(l)=0., df( ()=0.336152378983949952
dil dq2

[Stress is related to the Reynolds number (re) and the velocity
>S:=re*diff(u(x,y),y);

S := re u (x, y)
y )9y
[The velocity gradient in terms of the stream function is:]
>subs(u(x,y)=diff(psi(x,y),y),S);

re 2 (x,y)

[The second derivative of the stream function (d) is expressed
in terms of f and q:]
>d:=diff(psi(x,y),y$2):d:=changevar(psi(x,y)=xA(1 / 2)*f(eta(x,y)), d):d:=expand(subs(eta(x,y)=y/x^A(1 /2),d)): d:=subs(y=eta*x^A(1 /2),d ):d:=convert(d,diff); d 2 ) d: >S:=re*d: [The second derivative of f is found from the numerical solution:] >eqd3:=sol(0)[4]; eqd3:= d 2 f(r) = 0.336152378983949952 [Hence, the stress-Reynolds number relationship becomes:] >S:=subs(diff(f(eta),'$ '(eta,2))=rhs(eqd3),S);
S 0.336152378983949952 re

( Example 3
Graetz Problem in Rectangular Coordinates
Consider the Graetz problem in rectangular coordinates (to
simplify the mathematical complexity involved with cylindri-
cal geometry).'' The governing equation and initial/boundary
conditions are:
0u 02U
(1-x 2) --
9z 9x\
u(x,0) = 1 (4)

u(0, z)=0 and u(, z) = 0
Ox
For this problem, a similarity transformation cannot be used
to reduce the partial differential equation to one ordinary dif-
ferential equation (boundary value problem in rT). To obtain
solutions very close to z = 0, Eq. (4) is converted to the new
coordinates defined by T = x / (2z) and z = z (note, some
textbooks use z = z, as the second coordinate, but for simplic-
ity it is left as z in this paper). In the new coordinates, q and
z, u is obtained using a perturbation technique by expressing
Chemical Engineering Education

Figure 2. Function f as a function of the similarity variable, 9.
310

1

0-8
-

06-

0.4-

02-

0-

0 1 2 3 4

Figure 3. The x-component velocity as a
function of the similarity variable, 11.

0.0-
0-fi
06

V",1,2) 04.

02

0

0 1 2 3 4 5

Figure 4. The y-component velocity as a
function of the similarity variable, q.
k
u as u ZI Zkf (f). The boundary conditions for f (in the
similarity variable Tr ) are:
fo (0) = 1; fk (0) = 1, k = 1, 2, 3...
fo (oc)= 0;f, (ooc) 0, k = 1,2,3... (5)
The steps involved in the similarity transformation method
are performed in Maple.
>restart:with(student):
>eq:=(1 -xA2)*diff(u(x,z),z)-diff(u(x,z),x$2); eq:= (1 X u(x,z) u(x,z) [First, the governing equation is converted to similarity variables (1 and z):] >eq1 :=changevar(u(x,z)=U(eta(x,z),z),eq): eq2:=expand(simplify(subs(eta(x,z)=x/2/(z)A(1 / 2),eq 1 ))):eq2:=expand(eq2*z):eq2:=subs(x=e ta*2*(z)A(1/2),eq2):eq2 :=convert(eq2,diff): eq2:=expand(-4*eq2); Fall 2006 eq2:= 2 VU(q,z) T-4z (U(nz) -8zn3 0U(Tz)] 9r Oz 98O +16z 2 U(,z) 2 U(,z) [For illustration, only terms up to z2 are considered in the perturbation series:] >N:=2;vars:={U(eta,z)=sum(zAk*f[k](eta), k=0..N)}; N:= 2 vars := {U (, z) = fo (i) + zf, (r) + z2f2 ()} [The governing equations for the dependent variables are obtained as:] >eq3:=expand(subs(vars,eq2)):for i from 0 to 2 do Eq[i]:=coeff(eq3,z,i);od; Eq: 2 d fo(l)+ 2fo(,) d2 Eq2:=2i f2(d) -8f2( n)-8p- fl(3f) +1612f1 ()+ [ d 2 f2 (l) [The first three terms are obtained by solving these differential equations with the given boundary conditions (note that the boundary condition at x = 1 is solved approximately as U = 0 at i] = -j:] >sol[0]:=dsolve({Eq[0],f[0](0)=0,f[0](infinity)=1 });assign (sol[0] ): solo: = fo(q) = erf(qi) >sol[1 ]:=dsolve({Eq[1 ]}); sol, :=.f, (T)=(1 + 2rT)_C2 e+ 1 32T'4 fd Cl+- 1)e(-1 ) +(+2 (1+2T12)2 3 ) [The constants have to be zero to satisfy the boundary condi- tions:] >assign(sol[1 ]):_C1 :=0:_C2:=0:f[1 ](eta):=eval(f[1 ](eta)); 1 (-3T- 4 )e( 3 is ne [Similarly, f, is obtained:] >sol[2]:=dsolve(Eq[2]):assign(sol[2]):_C3:=0:_C4:=0: f[2](eta):=eval(f[2](eta)); 1 (-285 570]3 -384<5 -160q7 )e () 180 [Once the functions (the f's) are obtained, the Sherwood number can be obtained:141] >u:=subs(vars,U(eta,z)):u:=subs(eta=x/2/sqrt(z),u); fxz 1 2l 2 z32) u := erf, +- 2z 3 V 2 285x z 1 280 285x3 4z(3/2) 12x' 5x7 e-z Z(5/2) 4z(7/2) e [The dimensionless temperature distribution is plotted in Figure 5, which shows that temperature increases from the center of the slab to the surface value along the x-coordinate. The increase in temperature is more rapid at the entrance and temperature increases are more gradual for higher values of z from 0 to 0.05, the distance along the flow.] >plot3d(u,x=1 ..0,z=0.05..0,axes=boxed,labels=[x,z, "u"],orientatio n=[1 20,60]); SUMMARY This paper illustrates that mathematical methods for nontrivial problems in chemical engineering can be taught efficiently in a class using computers and user-friendly software. The similarity solution approach is a very powerful tech- nique for obtaining closed-form solutions for problems in heat, mass, momentum transfer, and other disciplines in chemical engineering. A traditional approach to teaching this technique would involve complicated variable transformations and integrals done by hand. In this paper, it was shown how an analytical technique could be facilitated using computers and software. While Maple has been used in this paper, Math- ematica, MATLAB, REDUCE, or other symbolic software packages can be used to obtain similar results. In addition to teaching numerical simulation, computers and software pack- ages can be used to teach traditional mathematical methods for a wide variety of problems. Mathematical methods, such as separation of variables, Laplace transform, perturbation, conformal mapping, Green's function, analytical method of lines, and series solutions for nonlinear problems (multiple steady states) can be facilitated using Maple. Readers can contact the author for further details or copies of related Maple programs. Some of these methods are illustrated in a book to be published in the future.191 REFERENCES 1. 2. 3. 4. 5. Carslaw, H.S., and J.C. Jaeger, Conduction of Heat in Solids, Oxford University Press, London (1973) 6. Crank, J.. Mathematics of Diffusion, Oxford University Press, New York (1975) 7. Slattery, J., Advanced Transport Phenomena, Cambridge University Press, New York (1999) 8. Villedsen, J., and M.L. Michelsen, Solution of Differential Equation Models by Polynomial Approximation, Prentice-Hall, Englewood Cliffs, NJ (1978) 9. White, R.E., and V.R. Subramanian, Computational Methods in Chemical Engineering with Maple Applications, Springer-Verlag (to be submitted in 2006). 0 Figure 5. Dimensionless temperature distribution in rectangular coordinates, governed by the Graetz equation. Chemical Engineering Education S=I curriculum USING VISUALIZATION AND COMPUTATION in the Analysis of Separation Processes YONG LAK JOO AND DEVASHISH CHOUDHARY Cornell University Ithaca, NY 14853 ATLABI11 is best described as easy-to-use math- ematical software that allows powerful graphical presentation and numerical analysis. At Cornell University, MATLAB has been used intensively as a teaching aid in undergraduate courses. For example, every engineering freshman is required to take a computer programming course (COMS100) that includes basic programming concepts and problem analysis using MATLAB. Students in chemical engi- neering take an engineering distribution course on computers and programming (ENGRD211), which deals extensively with MS Excel and MATLAB. They also develop user-friendly computer programs using MATLAB to solve homework in many chemical engineering core courses, including heat and mass transfer. This early integration of MATLAB provides an excellent background for use in the second semester of the junior year, allowing these students to be comfortable with MATLAB in the separations course. In addition, MATLAB can be a very useful teaching aid in a separations course, as its powerful graphical presentation and numerical analysis tools can be utilized both in an interactive, step-by-step, graphical display of conventional methods, and also in solving systems of equations for complex separation processes. The ability to integrate powerful computer software into the course rests on the availability of appropriate computing equipment. Our department's undergraduate computing laboratory is an excellent facility for such activities, and is equipped with 42 Windows-based PCs with a site license for MATLAB. THE COURSE Although typical chemical engineering curricula recognize the importance of recent trends in emerging technologies, it is always a challenge to convey them without sacrificing Fall 2006 fundamentals.1'2 ChemE332 at Cornell is a three-credit course for chemical engineering juniors covering separation methods. The emphasis of the course had formerly been placed on traditional, equilibrium-based methods that involve using manual graphical techniques, including McCabe-Thiele, Ponchon-Savarit, and Hunter-Nash.[3-1 As computers became readily available, however, the graphical approaches were supplemented with assignments to write Fortran code and/or use spreadsheets for distillation columns?"i Modem tools, Yong Lak Joo has been an assistant pro- fessor of chemical and biomolecular engi- neenng at Cornell University since 2001. He received his B.S. in chemical engineering from Seoul National University in Korea, and his M.S. and Ph.D. in chemical engineer- ing from Stanford University. His research interests are in the area of non-Newtonian fluid mechanics and advanced materials processing, with particular emphasis on molecular modeling and complex flow simulation of polymeric liquids. Devashish Choudhary was born in New Delhi, India. He majored in chemical engineering at the Indian Institute of Tech- nology, Bombay. In 2004, he received his Ph.D. from the School of Chemical and Biomolecular Engineering at Cornell University. During his Ph.D., he worked on order-property relationships in semi- conducting materials. Currently, he works at Inte/l Corp. Copyright ChE Division ofASEE 2006 such as the easy-to-use mathematical software MATLABi1' and Mathematica,1121 can be used to write simple codes that allow undergraduates to calculate and display accurate graphi- cal solutions interactively, and thus make learning graphical methods more enjoyable and effective. We introduced in- class visualization of conventional graphical methods using a simple MATLAB code. The interactive nature of MATLAB allowed "what if" analysesrll' in which the effect of changing parameter values such as relative volatility, reflux ratio, feed condition, and stage efficiency are graphically displayed. By spending less time on the details of solving problems graphi- cally or by trial and error, we can spend more time discussing the conceptual and quantitative descriptions of processes, recent trends, and design aspects. With condensed lectures on equilibrium-based processes, ChemE332 in spring 2001 was reconstructed to reinforce rate-based processes such as membrane and sorption separations. Furthermore, emerging processes in bioseparations, such as electrophoresis and is- sues in choosing and designing separation processes, were integrated in the course without sacrificing conventional separations. More than half of the total lectures in ChemE332 are currently spent on rate-based methods, bioseparations, and the design of separation processes. Obtain equilibrium data SThermodynamic Input---------------- Constant relative volatility/ Raoult's law/ Actual data --.-----------------------.------------------------------- Step 1: Display y vs. x diagram (eq. curve) -----... Design Input ........ Reflux ratio & feed condition or S Reflux ratio & boilup ratio or Boilup ratio & feed condition .. ... ------------------------------- ------- Step 2: Display operating lines and feed line Step 3: Determine theoretical equilibrium stages, N, Horizontal line to equilibrium curve Vertical drop to operating line -------------I Design Input ------------ Murphree vapor efficiency,_ m . *_ Step 4: Display new stepping based on Emv Determine actual stages N. and overall efficiency Eo Figure 1. Flowchart of Example 1: McCabe-Thiele method for binary distillation. Despite the advantage of helping students visualize the separation, graphical methods no longer represent the mod- em practice of chemical engineering.171 Modem practice for designing and simulating separations involves commercial process simulators such as AspenPlus, ChemCad, Hysys, and Prosim."41 To be prepared for commercial practice, stu- dents need experience simulating and designing separation processes using these methods. Unfortunately, students often treat these commercial simulators as black boxes, and tend to believe the results they obtain without further checking.i, 14J The exact methods used in these simulators involve solving systems of nonlinear equations and large matrices. Although there is a limit for complicated systems, these exact methods are now tractable due to user-friendly routines and software for numerical analysis. To avoid the potential creation of yet another "black box" using MATLAB, students can be asked to implement specific parts of the code such as a thermodynamic model, matrix solving, and time integration scheme. In this paper we demonstrate that using easy-to-develop mathematical solutions for visualization and numerical computation can make conventional graphical approaches more enjoyable and effective, providing students better un- derstanding of more complex problems. Visualization and interactive display of graphical methods in distillation, solution procedures for complex processes such as mul- ticomponent distillation, and thermal swing adsorption can promote understanding of how these separation processes work. Although we present the examples in distillation and adsorption, this approach can also be extended to many other separation processes such as absorption, stripping, and extraction. We present four examples used in the separations course. In the first two examples, the step-by-step, interactive display of conventional graphical methods for binary distillation were facilitated by MATLAB, while systems of nonlin- ear equations were rigorously solved using MATLAB in the last two examples on multicomponent distillation and adsorption. Example 1 Visualization of McCabe-Thiele Method and Stage Efficiency in Binary Distillation We used MATLAB to visualize the McCabe-Thiele graphical equilibrium-stage method and estimation of stage efficiency in a distillation process for a binary mix- ture of A and B. As described in Table 1, the code consists of (i) constructing and displaying the equilibrium curve, (ii) drawing operating lines and feed line, (iii) displaying the equilibrium stages, and (iv) illustrating stage and over- all efficiency. We use the commands "plot" and "movie" in MATLABrIl to visualize and animate the diagrams (see Table 1). The code was used for interactive display of the method in lectures and homework assignments. Chemical Engineering Education Interactive Display in Lectures Before the McCabe-Thiele graphical method was dem- onstrated by step-by-step display, a lecture was given on the concept and a handout on the detailed description of the options and functions of the MATLAB code for the method was distributed. In-class visualization of the graphical method and stage efficiency consists of four steps, and the overall flowchart of the example is illustrated in Figure 1. Step 1. We show how the equilibrium curves can be constructed. Three ways of determining the equilibrium re- lationship between liquid and vapor phases are implemented in the code: using (i) a constant volatility for mixtures with a similar heat of vaporization, (ii) a simple thermodynamic model such as Raoult's law4' in which the Antoine equation is used to provide the vapor pressure information, and (iii) actual data. For the Antoine equation, the function "fzero" in MATLAB'll is used to find a temperature at which the sum of partial pressures of two components equals the total pres- sure (i.e., P." + P," = Po, ) for a liquid composition xA and xB (see Table 1). Step 2. We show how to draw operating lines. Once any two of three parameters (e.g., the reflux ratio, R; boilup ratio, VB; and feed condition, q) are specified, the operating lines and the feed line are uniquely determined. We also explain the relation between the slope of the q-line and the state of the feed (subcooled, saturated liquid, partially vaporized, saturated vapor, and superheated). while x >= x- ynew=y Step 3. We demonstrate how to determine if iflag==0 theoretical stages. Once the equilibrium curve, xnew=yni operating lines, and feed line are drawn, the elseififlag- t=fzero('a equilibrium composition at each stage is deter- xnew=yni mined by the McCabe-Thiele method. Starting else from the distillate xD (or bottoms product x,), xnew=int drawing a horizontal line from (xD, xD) on the e([xxne' y = x line to the equilibrium curve, followed by hold on dropping a vertical line to the operating line, is Frames(:.i): repeated until x reaches xB. When actual data is pause used for the equilibrium curve, the MATLAB i=i+l; x=xnew interpolation function called "interp 1" is used if x >= x_c to find the intersection points along the equi- %if x >= z librium curve (see Table 1).11 The transfer in y=LoverV the operating line from the rectifying section elover to stripping section is typically made when the end liquid composition, x, passes the intersection plot([xnew, of the two operating lines and feed line. The hold on interactive nature of MATLAB allows "what Frames(:,i) pause if" analysest'9, in which parameter values such if x >= x_B as relative volatility, reflux ratio, and feed con- nstage=n edition may be changed, and their effects on the else distillation column are graphically displayed nstage=n during the presentation. end Step 4. The actual stages, based on the Murphree vapor efficiency, EMv, for each stage, are displayed on top of theoreti- cal stages to demonstrate the effect of stage efficiency on the actual number of stages. In the current example, we note that a single Murphree vapor efficiency, EMV, is used throughout the entire distillation column for simplicity and symmetry in the feed stage. The overall efficiency, Eo, is then determined by the ratio of the number of the theoretical equilibrium stages to that of the actual stages, i.e., Eo= Nt/N,. Some snapshots of the McCabe-Thiele method and stage efficiency for distillation of acetone and toluene that are displayed in class are shown in Figure 2 (page 318). Homework Assignments After the graphical method by MATLAB code was in- troduced, a couple of problems associated with using and modifying the MATLAB code were given as homework. For example, students were asked to determine various feed condi- tions such as subcooled, partially vaporized, and superheated using the thermodynamic properties of benzene and toluene, and then determine the number of equilibrium stages and boilup ratio at a given feed composition and reflux ratio (see Table 2, page 318). The effect of feed conditions on column performance is demonstrated by entering different q values TABLE 1 Portion of a MATLAB Code for Example 1 315 % using constant alpha for eq. relation ew/(a-ynew*(a-l)): :=1 % using Antoine Eq. (2) for eq. relation ntoine2'.tmid,optimset('disp'.'iter'),ynew,al,b l,c l.a2,b2,c2,Ptotal); ew*Ptotal/pvapor(al .bl .cl,t); % using actual data for eq. relation erp 1 (ydata.xdata.ynew): w],[y,ynew],'r','LineWidth',2) % a. Draw a horizontal line to the eq. curve =getframe; /_D*x+x D/(R+I) % using the op. line for rectifying section % using the op. line for stripping section /_B*x-x B/V B x],[ynew,y],'r','LineWidth',2) % b. Draw a vertical line to the op. line =getframe; % calculating # of stages stage+1 stage+x/x_B % c. Repeat a and b until x reaches x_B B c loop for stepping Fall 2006 S ...in the MATLAB code and dis- playing the stage-stepping inter- 09- 9 a actively. In the second problem, o8 o 08 ,' students were asked to modify 0 and extend the MATLAB code to determine the actual number 0 /of stages based on the stage ef- o5s /-' o5 ficiency. This was demonstrated 04 0.4 and displayed in the lecture, but this time the students were asked 0 3 to reconstruct what they had 0D2 02 seen in class and use it to solve 0 a homework problem. About 85% of the students were able o 01 02 0.3 04 05 0.6 0.7 08 09 1 0 01 02 03 0.4 0.5 06 07 08 09 1 to modify the code correctly to (c x determine the actual number 08 of stages. 08 08 0.7 0-7 0.7 _7 Figure 2. Snapshots of graphi- 0o6 0 6 cal output in Example 1: Mc- S0.5 Cabe-Thiele method for binary S,' distillation of acetone and tolu- 04 04 / ene: a) equilibrium curve from 03 Raoult's law; b) operating lines 0 2 and feed line for zA = 0.5, xD 0.2 02 0.95, x, = 0.05, q = 0.5, R = 2; c) o oi' theoretical equilibrium stages; and d) actual stages (shown in 0 o.1 02 03 4 0o5 06 0.7 0.8 0-9 1 0 01 0o2 03 04 0o5 06 07 08 09 dashed line) with E =0.7 for the entire distillation column. TABLE 2 An Example of MATLAB Homework Problem To Link the Effect of Feed Conditions to the Number of Theoretical Stages and Boilup Ratio 4. A mixture of 50 mol% benzene and toluene is to be separated by distillation at atmospheric pressure into products of 95% purity using a reflux ratio L/D=3.0 in the rectifying section. The feed has a boiling point of 92 C and a dew point of 98 C at a pressure of I atm. Determine the q value if (i) the feed is vapor at 150 C; (ii) the feed is liquid and at 20 C; (iii) if the feed is a mixture of two-thirds vapor and one-third liquid. Component AH'"P (cal/g mol) C (cal/g mol C) Liquid Vapor Benzene 7,360 33 23 Toluene 7,960 40 33 Assume a relative volatility of 2.5 and use a simple MATLAB code (feed.m) that is available at the ChemE 332 Web page to determine the number of theoretical stages and the boilup ratio in the stripping section for three different feed conditions. Submit the printouts (graphs). Each graph should have your name and the output (number of stages and boilup ratio) printed on the upper left comer. To do this, the MATLAB code has the following gtext command that writes the specified string at a location clicked with the mouse in the graphics window: gtext({'number of stages:,' num2str(nstage)}) gtext({'boilup ratio:,' num2str(V_B)}) gtext({'run by,' yourname}) First, the code asks you your name and input conditions including the q value. After running the code, go to the graph and click a location (total three times) to print out the number of stages, boilup ratio, and your name on the graph. 316 Chemical Engineering Education Example 2 Visualization of Enthalpy Method in Binary Distillation[6] The McCabe-Thiele method uses an energy balance only at the feed tray, whereas the Ponchon-Savarit graph- ical method uses a rigorous energy balance throughout the distillation column.'4-6] Although the Ponchon-Savarit method for distillation has largely been supplemented by rigorous computer-aided methods, the concept of using a diagram for the separating agent (heat in distillation) and difference points is very important and useful in un- derstanding similar graphical approaches in other separa- tion processes, such as the Maloney-Schubert graphical method[4' in extraction that uses the analogous Janecke diagram for the separating agent (the solvent). We used recitation sessions as well as lectures to in- troduce and demonstrate the Ponchon-Savarit graphical method. A handout on the method using the MATLAB code was distributed first, and the graphical method was demonstrated using step-by-step display. The visualiza- tion of the Ponchon-Savarit method consists of determin- ing difference points and displaying rays and equilibrium tie lines on the enthalpy diagram. ( The flowchart of the Ponchon-Sa- 20 - varit method for binary distillation is shown in Figure 3. We again used 15000- the commands "plot" and "mov- ie" in MATLAB to visualize and graphically display the diagrams,"' 10000 and some snapshots of the method = for distillation of acetone and water S5000r mixtures are shown in Figure 4, right, as well as in Figure 5 (next page). The operating lines obtained 0",, under the assumption of constant molal overflow are shown by the dashed lines in the y vs. x diagram 0 01 02 0 for comparison in the figure. The students were asked to run the same 20000 code as the lecture to solve similar homework problems by varying de- sign inputs such as feed conditions. 1500 In the future, we will ask students to modify the MATLAB code for the Ponchon-Savarit method for a Figure 4. Graphical output for 00ooo Example 2: a) enthalpy-composi- tion diagram from enthalpy data; and b) difference points (open 0 -..... circles) and feed line for z, = 0.5, xD= 0.90, xB= 0.0216, q = 0.5, 5 and R = 0.288. The y-x composi- 0 01 02 0 tion diagram is also shown at the Fall 2006 Obtain equilibrium and enthalpy data ------ Thermodynamic Input Actual equilibrium & enthalpy data \t L------ ------- ----------------------------- Step 1: Display y vs. x and enthalpy .Design Input ........... Reflux ratio & feed condition Distillate, bottoms compositions < t L~----.--------------------------------------- ___ Step 2: Determine and display difference and feed points On enthalpy diagram Display rays that pass difference point and liquid (vapor) composition Display equilibrium tie line to determine the corresponding vapor (liquid) composition. Step 3: Determine the number of equilibrium stages Figure 3. Flowchart of Example 2: Ponchon-Savarit method for binary distillation. Ponchon-Savar Method vs x dagram 09 'F _^ / 3 04 05 06 07 08 09 1 Composrion x or y Ponrhon-Savantr Method 01 02 03 04 0.5 06 07 X 01 3 0,4 05 06 07 08 09 1 0 01 02 03 04 05 06 07 08 09 1 Composition, x or y x distillation such that the extraction process can be solved, analyzed, and displayed interactively. Example 3 Direct Solving Exact Methods for Multicomponent Distillation['41 Despite its practical importance, multicomponent distil- lation has not been thoroughly discussed in first courses on separations. This is mainly because analysis of multi- component separations requires solving material balances, enthalpy balances, and equilibrium relations at each stage, and solution procedures can be difficult and tedious. Hence, only an approximate method commonly referred to as Fen- ske-Underwood-Gilliland (FUG) has been used to make preliminary designs and optimize simple distillation.[41 Al- ternatively, commercial simulators have been introduced to solve multicomponent separations in detail, but students often treat these commercial process simulators as black boxes.7141 a Ponchon- We used MATLAB to solve the 20000 nonlinear algebraic equations for multicomponent distillation in 15000 this example. More specifically, user-friendly routines in MAT- LAB were used to employ the 1 equation-tearing, bubble-point method in solving the governing 5000 equations. This numerical method consists of calculating equilibrium compositions and enthalpies, -__------- solving the modified material balance equations, and updating -5000 solutions using Newton's method 0 01 02 03 04 ( Compo (see Table 3). As indicated in the ) flowchart of the procedure in 20000 Ponchon- Figure 6 (page 322), the system of equations was solved for composi- tions at each stage by the matrix ,1000 solver "sparse" in MATLAB.,"' The Newton's method was used to 10000 update the guess of tearing vari- ables, temperature, and vapor rate j ,' ". at each stage. A function "froot.m" o 0 ,' was created which solves nonlin- - ear equations using a Newton's 0 - method to update the temperature and vapor rate at each stage. Once temperature, enthalpy, and com- -o0 01 0 0.1 02 03 0.4 positions are obtained, the heat Compos duties can be determined. Figure 5. Snapshots o Homework Assignments binary distillation of ace Using the developed MATLAB in the rectifying section; code, students were asked to solve The operating lines ob shown by the dashed 318 a multicomponent distillation of hydrocarbons and compare the results with those obtained from the commercial pro- cess simulator, AspenPlus (see Table 4, page 322). Again, a handout that describes the method used in the code was distributed and explained in a recitation session before the homework was distributed. As depicted in Figure 7 (page 323), a simple thermodynamic model (Raoult's law in which the Antoine equation has been used to provide the vapor pres- sure information) overpredicts the volatility of "light non-key (LNK)" component (ethane) and underpredicts that of "heavy non-key (HNK)" components (pentane and hexane) in the multicomponent distillation of hydrocarbons. As a result, the compositions of the "light key (LK)" component (propane) in the distillate and the "heavy key (HK)" component (butane) in the bottoms are slightly lower than the values obtained from Aspen simulation with more accurate thermodynamics models such as Soave-Redlich-Kwong equation. 05 06 07 08 09 1 0 01 02 0,3 04 05 06 07 08 09 1 ition, x or y f graphical output of Example 2: Pochon-Savarit method for tone and water: a) rays (solid) and equilibrium lines (dashed) and b) rays and equilibrium tie lines in the rectifying section. trainedd under the assumption of constant molal overflow are 'd lines in the y vs. x diagram at the right for comparison. Chemical Engineering Education / i , ' Example 4 Direct Time Integration of Thermal Swing Adsorption[41 Adsorption is one of the most difficult separation processes to teach since it is rate-based, which requires a mass transfer analysis, and is usually operated as a time dependent process. As a result, adsorption with very simple isotherms, such as an irreversible isotherm, has been analyzed in most separa- tion texts.13 41 After we introduced the concept of adsorption isotherms and a breakthrough curve in fixed-bed adsorption, we used MATLAB to develop a numerical model for rate- based, time-dependent adsorption processes such as thermal swing adsorption. In thermal swing adsorption, one bed is adsorbing the solute at ambient temperature, while the other bed is desorbing the adsorbate at a higher temperature. A numerical solution for the regeneration (desorption) step can be obtained using a procedure discussed by Wong and NiedzwieckiP'l (see Figure 8, page 324). Again, a handout that describes the method used in the MATLAB code was distributed in the lecture. In the absence of axial dispersion and a constant fluid velocity, the partial differential equations can be solved using the five-point, biased upwind, finite dif- ference approximation derived from Taylor's series expan- sion. The time integration of the sets of ordinary differential equations was carried out using a simple Euler method with a small step size. Regeneration-loading profiles in thermal swing adsorption at two different regeneration air interstitial velocities, v = 30 m/min and v = 60 m/min, are shown in Figure 9 (page 324), and the effect of air flow on the heating TABLE 3 Portion of a MATLAB Tutorial Handout for Example 3 If we assume that phase equilibrium is achieved at each stage. the governing equations for a distillation process for n components consisting of N stages can be written as4i L,x, V y, Fz -(L +Uj)x (V, +W )y,0 (1) y K ,x, (2: x, 1 y, -1 (3 L,b,h-,+V H1 ,H +F,hr,-(L-+U,)h -(V +W,)H -Q 0 (4 where L,. V. F. U, and W are liquid. vapor, feed. liquid side stream. and vapor side stream rates at stage j. respectively. h, H and Q, are liquid and vapor enthalpies, and heat transfer at stage j, respectively. We utilize the equation-tearing, bubble-point method in solving the governing Eq. (1 )-(4) which consists of: i) calculating equilibrium compositions and enthalpy: ii) solving the modified material balance equations; and iii) updating solutions using the Newton's method. i) Equilibrinum Compositions and Enthalpy Calculations For simplicity, the Antoine equation is used to evaluate K-values and enthalpy of each component. One of tear variables, temperature is assumed and the volatility of each component is determined by K = y/x, = P '/P Meanwhile, the enthalpy of each species can be determined from'4' h,., h,' + AH"' T 4 where the ideal gas species molar enthalpy h, = C:, dT a I(T T' )/k and C,, a, +a.,T+ aT'- + a, T' is the heat capacity at constant pressure. At low pressures, the enthalpy of vaporization is given in terms of vapor pressure by classical thermodynamics 14 d In P,' B .AH -. RT d RT (5 dT (T-C ) ii) Modified Material Balance Equations By rearranging the governing equations Eq. (1)-(3) for each stage, the following systems of equations for component i at stage j are obtained:'4 B C 0 ... 0 x, D A, B, C, : x, D, 0 A. 0 = (6 B"_, C",B x, D,_ 0 ... 0 A, B, x, D\ where x =[x, x,. x, .. x. ] is the liquid composition vector at stage j. and the components of the tridiagonal matrix in each stage are AV,-+ (F,,, +W+U,)-V. 2 B =- -V + (F,-W,- U) -V UI +(V,+W )K I j C, V ,,IK , and the right-hand-side vector at each stage D = -F,z,. l I < j The system of equations Eq. (6) is solved for x, by the sparse matrix solver "sparse" in MATLABI'1 ... [instructions continue]. Fall 2006 31 TABLE 4 An Example of MATLAB Homework Problem Paired With a Problem Using Aspen Plus to Solve a Multicomponent Distillation of Hydrocarbons. 1. Multicomponent Distillation using Aspen Plus Distillation column specifications are given as below: Feed (saturated liquid at 250 psia and 213 F) Component Lbmol/h Ethane 3.0 Propane 20.0 n-Butane 37.0 n-Pentane 35.0 n-Hexane 5.0 Column pressure = 250 psia Partial condenser and partial reboiler Distillate rate = 23.0 lbmol/h Reflux rate = 150.0 lbmol/h Number of equilibrium plates (exclusive of condenser and reboiler) = 15 Feed is sent to middle stage E-mail the following to the TA: 1) a printout of your Aspen process with your NetID as the column name as well as a stream table showing the results using the conditions described in the exercise including stage temperatures, vapor and liquid flow rates, and reboiler and condenser duties. 2) a graph of liquid composition of each component vs. stage number 3) a graph of vapor composition of each component vs. stage number 2. Multicomponent Distillation using MATLAB Repeat Problem 1 using simple MATLAB codes (problem2.m and froot.m) available at the ChemE 332 Web site. The code utilizes the equa- tion-tearing, bubble-point method in solving the MESH equations as described in the handout. For simplicity, the Antoine equation is used to evaluate K-values and enthalpy of each component. The file froot.m is a function routine which solves nonlinear equations using a Newton's method. See the handout for details. When the code is run, you are asked to input the conditions described in the problem. Submit the follow- ing printouts 1) a graph of liquid composition of each component vs. stage number 2) a graph of vapor composition of each component vs. stage number Compare your results with those obtained in Problem 1. Initial guesses for tear variables, T, and V, TABLE 5 ------- ........... Design Input Responses of the Students Antoine equation : Reflux ratio & feed stage Responses to: Enthalpy equation Distillate, bottoms compositions "How valuable were the lectures and homework assignments based -- -- -- -- -- on MATLAB?" Calculate enthalpy (h,, H,) and volatility (K,,) % responses -------------------------- 1 = taught me little 3.0 Sparse matrix solver- 2 = taught me some 4.2 3 = educational 16.3 4 = very educational 57.7 Solve tri-diagonal matrix for x, 5 = extremely educational 17.8 Newton's method Some comments from the students "The mix of conventional method and animation helps us to under- Compute new T,, Q,, V, and L, stand the concept from the front." "I like how much of it is graphic. This makes the learning more intuitive." Converging criteria "I hate graphical methods, but using MATLAB is okay." "Some MATLAB homework problems were too easy because I just Iterate until T, is converged punched in numbers" "No more MATLAB, please. 4 Figure 6. Flowchart of Example 3: multicomponent distil- Display vapor and liquid composition profiles nation. 20 Chemical Engineering Education and cooling cycle in thermal swing adsorption was discussed in detail. Students were asked to use the MATLAB code to determine the regeneration characteristics in thermal swing adsorption at various operating conditions, such as air flow. In the future, the students will be asked to extend the code to solve similar rate-based sorption processes such as ion exchange and chromatography. PEDAGOGICAL ASPECTS OF STUDENT ACTIVITIES AND RESPONSES OF STUDENTS The pedagogical aspects of student activities have evolved over the years. The incorporation of interactive display of graphical methods was done in lectures to effectively dem- onstrate the effect of design parameters on the distillation column. Then, students were asked to run the same code used in lecture to solve similar problems by varying design inputs such as feed conditions. We started asking the students to modify the MATLAB codes to extend its capabilities and analyze the results. A tutorial on how to develop a MAT- LAB code was instituted in the recitation sessions to make this transition smoother. We conducted a survey on using MATLAB in lectures and homework assignments as a part of mid-term evaluation, and results are summarized in Table 5. The wording of questions and responses in the table is taken verbatim from the survey. The survey also provided a space for written comments. As indicated in Table 5, the use of MATLAB was generally accepted as a useful aid in teaching separations. In the future, we would like to allow the students to play more active roles in solving various separation problems using MATLAB. In particular, students will be asked to modify the tom MATLAB codes and extend them to work out many other separation processes such as absorption, strip- ping, and extraction. \ CONCLUSIONS We have demonstrated that simple mathemati- cC2 cal software, MATLAB, can be integrated into a C3 C4 separations course as a useful and effective teaching C6 aid for visualization and numerical computation of many separation processes. The benefits of using MATLAB are the following: Step-by-step and interactive display can make conventional graphical approaches more enjoy- able to students and more effective in classroom. Visualization of the graphical methods has been further extended to the study of packed-column 18 analysis. By spending less time on the details of solving problems graphically and by trial-and-error, bottom we were able to spend more time discussing the conceptual and quantitative description of pro- cesses, and incorporate recent trends and design aspects in the separations course. User-friendly routines of MATLAB can be used to solve systems of nonlinear equations and perform numerical time integration, which, in -X-c03 turn, provides students with a better understand- -+-c4 ing of complex separation processes such as C5s multicomponent distillation and thermal swing C6 adsorption. /. Figure 7. Vapor composition of each compo- nent at each stage in Example 3: multicompo- nent distillation of hydrocarbons, a) obtained using direct matrix solver in MATLAB with a simple thermodynamic model (Raoult's law), 18 and b) obtained from Aspen Plus with the Soave-Redlich-Kwong model. Operating condi- tions are listed in Table 4. Fall 2006 SDesign & Thermodynamic Input 1E Specification of fixed-bed adsorber Breakthrough curve Discretize the spatial derivatives Explicit Euler Method Perform Numerical Time Integration Obtain Loading and Concentration Profiles Display Loading and Concentration Figure 8. Flowchart of Example 4: Thermal Swing Adsorption. 2 3 4 5 6 Distance through the bed, z 2 3 4 Distance through the bed, z 5 6 Obtain Initial Loading and Concentration REFERENCES 1. Pratap, R., Getting Started with MATLAB, A Quick Introduction for Scientists and Engineers, Oxford University Press (2002) 2. Chickering, A.W., and Z.F. Gamson, "Appendix A: Seven Principles for Good Practice in Undergraduate Education, New Directions for Teaching and Learning," 47, 63 (1991) 3. McCabe, W. L., J.C. Smith, and P. Harriott, Unit Operations of Chemi- cal Engineering, 6th Ed., McGraw Hill (2001) 4. Seader, J.D., and E.J. Henley, Separation Process Principles, John Wiley & Sons (1998) 5. Humphrey, J.L., and G.E. Keller II, Separation Process Technology, McGraw-Hill, New York (1997) 6. King, C.J., Separation Processes, McGraw Hill (1980) 7. Wankat, P.C., "Teaching Separations: Why, What, When, and How," Chem. Eng. Ed., 35, 168 (2001) 8. Golnaraghi, M., P. Clancy, and K.E. Gubbins, "Improvements in the Teaching of Staged Operations," Chem. Eng. Ed., 19, 132 (1985) 9. Jolls, K.R., M. Nelson, and D. Lumba, "Teaching Staged-Process Design Through Interactive Computer Graphics," Chem. Eng. Ed., 28, 110(1994) 10. Burns, M.A., and J.C. Sung, "Design of Separation Units Using Spreadsheets," Chem. Eng. Ed., 30, 62 (1996) 11. Hinestroza, J.P., and K. Papadopoulos, "Using Spreadsheets and Visual Basic Applications," Chem. Eng. Ed., 37, 316 (2003) 12. Dorgan, J.R., and J.T. McKinon, "Mathematica in the ChE Curriculum," Chem. Eng. Ed., 30, 136 (1996) 13. Rives, C., and D. Lacks, "Teaching Process Control with a Numerical Approach Based on Spreadsheets," Chem. Eng. Ed., 36, 242 (2002) 14. Wankat, P.C., "Integrating the Use of Commercial Simulators into Lecture Courses," J. Eng. Ed., 91, 19 (2002) 15. Wong, YW., and J.L. Niedzwiecki, "Simplified Model For Multicomponent Fixed Bed Adsorption," AlChE Symposium Series, 78, 120-127 (1982) 0 Figure 9. Regeneration loading profiles in Example 4: Thermal Swing Adsorption with regeneration air interstitial velocity a) v = 30 m/min, and b) v = 60 m/min. Chemical Engineering Education * 5 point, biased upwind Finite Difference Both display of conventional graphical methods and solving of complex systems of nonlinear equations can be achieved using MATLAB, which eliminates the requirement of multiple nu- merical tools in the course such as spreadsheet, for graphical methods, and computer languages, for numerical computation. The aforementioned integration of graphical dis- play and computational approaches into various sepa- ration processes together with the implementation of emerging separation technologies and design aspects can provide students with the ability to choose an appropriate separation technology for a particular ap- plication, and to analyze the performance of modem separation processes. The MATLAB source codes and handouts for the examples can be downloaded from the home page of the Analysis of Separation Processes Course, Chemical Engineering 332 at Cornell University ( edu/courses/cheme332>). ACKNOWLEDGMENTS The authors thank the students and teaching assis- tants of ChemE332 for their feedback on the methods described in this paper. We also thank Professor T. Michael Duncan for insightful suggestions. j c = classroom THE RESEARCH PROPOSAL in Biochemical and Biological Engineering Courses ROGER G. HARRISON, MATTHIAS U. NOLLERT, DAVID W. SCHMIDTKE, AND VASSILIOS I. SIKAVITSAS University of Oklahoma Norman, OK 73019-1004 T he advancement of the U.S. economy is critically de- pendent on new developments in science and engineer- Roger G. Harrison is an associate professor in the School of Chemical, ing technology. Undergraduate students in engineering Biological, and Materials Engineering at the University of Oklahoma. His research focuses on the expression and purification of recombinant are typically well trained in solving well-defined problems. proteins, and the design of proteins for oncologic and cardiovascu- They receive very little training past reading a textbook, lar applications. He is the lead author, with three coauthors, of the textbook Bioseparations Science and Engineering (Oxford University however, in the creative activities involved in development Press, 2003). He received his B.S. in chemical engineering from the of new technology. University of Oklahoma and his M.S. and Ph.D. from the University of Wisconsin-Madison. After his Ph.D., he also worked in R&D at Upjohn One way to help students think creatively about develop- Company and Phillips Petroleum Company. ing new technology is to incorporate a research proposal MatthiasU. Nollert is an associate professor in the School of Chemical, into the coursework. Although numerous efforts have been Biological, and Materials Engineering at the University of Oklahoma. made to incorporate more writing into engineering and sci- His research in the area of biomedical engineering seeks to understand the role of fluid mechanics in modulating the biology of blood cells and ence courses,"1-4 little has been reported about using research the cells of the blood vessel wall. He received his B.S. in chemical proposals in undergraduate courses. In an undergraduate engineering from the University of Virginia and his Ph.D. from Cornell course for chemistry majors at Brooklyn College entitled University. He was a postdoctoral fellow at Rice University. "Introduction to Research," students were required to select David W. Schmidtke is an assistant professor in the School of a research project provided by the instructor.151 Students then Chemical, Biological, and Materials Engineering at the University of Oklahoma. His research interests are in the areas of biosensors and wrote a rough draft of the proposal. After receiving feedback cell adhesion. He received his B.S. in chemical engineering from the from the instructor, they wrote a final draft. In a Youngstown University of Wisconsin-Madison and his M.S. and Ph.D. from the University of Texas at Austin. He was a postdoctoral fellow at the State University course entitled "Chemistry Research," stu- University of Pennsylvania. dents were required to select a research proposal topic, write a rough draft of the proposal, and then write a final draft after Vassilios I. Sikavitsas is an assistant professor in the School of a rough draft of the proposal, and then write a final draft after Chemical, Biological, and Materials Engineering at the University of receiving feedback from the professor.161 For both proposals, Oklahoma. His research interests include the use of molecular and cell the time allotted for writing (five weeks at Brooklyn College biology approaches together with engineering principles in developing cellular and tissue engineering strategies for organ regeneration and and three weeks at Youngstown State) seems too short for assessment of human health risk. He received his B.S. in chemical undergraduates, given the challenging nature of writing a engineering from Aristotle University of Thessaloniki, Greece, and his M.S. and Ph.D. from the State University of New York at Buffalo. He research proposal, was a postdoctoral fellow at Rice University. This paper presents our experiences incorporating a research proposal in four biochemical or biological engineering courses O CopTright ChE Division of ASEE 2006 Fall 2006 32 for graduate students and upper-level undergraduates at the University of Oklahoma (OU). Biochemical and biological engineering are broad fields undergoing rapid development and have many opportunities for students to write research proposals on the advancement of science and engineering. We found that the great majority of students could write proposals on biochemical and bioengineering topics without major problems. Writing the proposal in stages over at least half the semester-with feedback provided by the instructor after each stage-was helpful to the students. Our findings are supported by our own observations and an anonymous survey of the students. RESEARCH PROPOSAL A research proposal was required in each of the following courses, with the number of students indicated in parentheses: Biochemical Engineering (25), Biosensors (9), Cellular As- pects in Tissue Regeneration (9), and Tissue Engineering (15). Each of these courses is an upper-level engineering course for juniors, seniors, and graduate students. Students devoted at least half the semester to developing their research proposals in these courses. While the requirement to do a research paper did not cause a reduction in course material covered in lecture, there was a reduction in homework required compared to what it would have been had a research proposal not been required, especially near deadlines for the research proposal. The proposals ranged from a series of graded writing assign- ments (objectives, rough or first draft, and final draft in Bio- chemical Engineering and in Tissue Engineering; objectives and final draft in Biosensors), to one writing assignment for the entire proposal (Cellular Aspects in Tissue Regeneration). For one of the proposals (Cellular Aspects in Tissue Regenera- tion), the students were required to give a presentation, and feedback from that presentation was incorporated into the final written proposal. A sample outline of requirements and the general grading guidelines for the research proposal in Biochemical Engi- neering are given in the Appendix. The selection of the research topic and development of the objectives and significance by each student were very important to success- ful proposals. Exam- ples of statements of objectives and sig- nificance from our own research were handed out to students as guides. Students were allowed to choose a proposal topic in which they had an interest, based on their own research and/or prior courses in the biological sciences or bioengineering. (Nearly all of the students in the courses were either graduate students in the area of bioen- gineering or were undergraduates who were in one of the bio elective patterns-biotechnology or pre-med.) In some cases, students read ahead in the textbook about topics of interest. Each student met with the instructor to discuss the appropriateness of his or her chosen topic. It was sometimes necessary for a topic to be modified based on the instructor's experience and knowledge of the topic. Students were given guidance about how to search the lit- erature. In one course, Biochemical Engineering, a university librarian came to class and gave a presentation on the various resources available for searching literature, including the use of search programs and interlibrary loan. OBSERVATIONS AND OUTCOMES Our main observations were the following: 1. Writing a research proposal was a challenge for students in these four courses. It was the first time any of them had been required to write a proposal, with the exception of a few students who had written a proposal in one of the four courses in a prior semester. For many of them, it was the first time that they had been required to do reading outside of the assigned text- books. In addition, we observed that students tended to underestimate the difficulty of writing a proposal, especially in coming up with new ideas to research. 2. What separates this assignment from a traditional term paper is that, besides needing to understand the lit- erature, the student also has to develop his or her new ideas for research. Challenging students to develop new ideas and to express them in writing is what we see as the major reason to use this assignment. Chemical Engineering Education TABLE 1 Summary of an Anonymous Survey of Students About the Research Proposal in Bioengineering Courses Percent of Respondents Statement Strongly Agree Disagree Strongly Agree Disagree The research proposal was a good way to learn 64 29 7 0 about a topic in bioengineering in depth. The research proposal involved more creativity 21 43 36 0 than any other assignment I have had while at OU. The research proposal gave me a better apprecia- 14 58 21 7 tion about how new technology is created. The research proposal was one of the most chal- 21 43 29 7 lenging assignments I have had at OU. Writing a research proposal in this course helped with another course/courses taken afterwards 36 64 0 0 and/or a research project. 3. Breaking the requirements down into segments (such as a sunmmnary with specific aims, a rough draft, and a final draft) due on different dates helped make the assignment more manageable for the students. Giving students written or oral feedback about each segment helped students improve on the next segment due. By the final draft, a great majority of students were able to produce a proposal without major problems. We found that roughly one-fifth of the students wrote proposals that presented new and unusual ideas, were well explained, and could serve as the basis of a proposal to a federal granting agency. Undergraduate students performed about the same as graduate students on the proposals. Our observations, based on talking to students about their proposals and reading students' proposals, were confirmed by an anonymous survey of the participating students. Sur- vey results are summarized in Table 1 and selected student comments are given in Table 2. By a large margin, students thought that the research proposal was a good way to learn about a topic in depth. A majority of the students either agreed or strongly agreed that the research proposal involved more creativity than any other assignment they had completed at OU, gave them a better appreciation of how new technology is created, and was one of the most challenging assignments they had at OU. All of the students either agreed or strongly agreed that writing a research proposal in the course helped with another course taken afterward and/or helped with a research project. The student comments shown in Table 2 reinforce the survey results in Table 1. A couple of the com- ments support breaking down the assignments into segments; these comments were given in response to a final question in the survey about ways students thought the research proposal assignment could be improved. The writing of research proposals by students addresses ABET criterion 3(i): "... a recognition of the need for and ability to engage in lifelong learning." Writing a research proposal helps students to learn in a structured way how to create new technology, which will serve them in the future as they are confronted with new problems and challenges. Besides being used as part of a biochemical or biological engineering course, a research proposal could be used as the requirement to fulfill an undergraduate research course (for example at OU, the courses Honors Research, Undergraduate Research Experience, or Senior Research). A research pro- posal could also be required in other upper-level engineering courses on topics where technology is advancing rapidly. CONCLUSIONS We conclude that requiring a research proposal provides an excellent learning experience for upper-level undergraduates and graduate students in biochemical and biological engineer- ing courses, especially when the proposal writing is divided into stages over at least half the semester. Writing a research proposal requires a higher level of thinking than a normal term paper, where the student is typically required to review the technical literature on a given topic. By proposing new research, the student is required to think more about existing research and consider how to advance science and technol- ogy in the field. TABLE 2 Selected Comments From an Anonymous Survey of Students About the Research Proposal in Bioengineering Courses "The proposal requires background research that enhances and reinforces the concepts being conveyed in the coursework." "It increased my knowledge about the subject. and it was stimulating trying to produce something 'new' from the course." "The research proposal helped us learn things that were beyond what could be covered in class. It was a good opportunity to see how the general concepts of bioengineering apply to different areas." "Having to plan and design experiments was very challenging in terms of creativity. The research proposals were out of our area of research; thus, we had to be very creative in developing concepts and ideas for the project." "I had to pull knowledge from quite a few areas and tie them together. It gave a stronger appreciation for those areas in which my knowledge is weak, and forced me to do a fair amount of literature review for those areas." "I would say it is the most challenging assignment I had at OU after the capstone project." "It helped me in writing my thesis." "The assignment helped me formulate cohesive scientific thoughts, and helped me learn to focus my arguments for my dissertation writing. The most important aspect of the assignment was the focus on taking a scientific idea through the research design paradigm. Learning to write clearly, concisely, and scientifically is an essential skill and should always be practiced." "It has helped me in writing research proposals in my own research and for my general examination." "I strongly believe that a complete and full workup of a rough draft (i.e., what a student 'thinks' is a final version of the paper) should be turned in at least three to four weeks prior to the end of the semester. This way the professor can be critical of the writing, and the student would still have time to learn about what was written incorrectly and how to remedy that. The specific aims should be submitted within four weeks of the beginning of the course, in my opinion." "Actually, I thought that it was a great experience. While doing it, I thought that it was more time consuming than it was worth. However, in retrospect I think that it was extremely valuable." "I like the way there were several deadlines along the way before the final proposal was due." Fall 2006 REFERENCES 1. Plumb. C., and C. Scott, "Outcomes Assessment of Engineering Writing at the University of Washington," J. Eng. Ed.. 91. 333 (2002) 2. Boyd, G., and M.F. Hassett, "Developing Critical Writing Skills in Engineering and Technology Students," J. Eng. Ed., 89, 409 (2000) 3. Newell, J.A., D.K. Ludlow, and P.K. Sternberg, "Development of Oral and Written Communication Skills Across an Integrated Laboratory Sequence," Chem. Eng. Ed., 31, 116 (1997) 4. VanOrden, N., "Is Writing an Effective Way to Learn Chemical Con- cepts?" J. Chem. Ed., 67, 583 (1990) 5. Williams, E.T., and Bramwell, F.B., "Introduction to Research," J. Chem. Ed., 66, 565 (1989) 6. Schildcrout, S.M., "Learning Chemistry Research Outside the Labora- tory: Novel Graduate and Undergraduate Courses in Research Meth- odology," J. Chem. Educ., 79, 1340 (2002) APPENDIX Sample Outline of Requirements for the Research Proposal in Biochemical Engineering Each student is required to write a research proposal on a topic associated with the production and processing of bioproducts. Specific topics include, but are not limited to, fundamental studies of: Molecular and Cellular Engineering. This expanding area of engineering research encompasses pure and mixed culture processes, modeling, optimization, and control of cell and metabolite production, development of new biochemical reac- tors, biocatalysis, and conversion of synthetic gas and other chemical feedstocks to value-added products via biological means. New techniques in the monitoring and control of molecular and cellular engineering are also of interest. Downstream Processing. The capability to purify bioprod- ucts in a cost-effective manner on a commercial scale is an important technical goal in bioprocessing of substances of biological origin. New processes and a major enhancement of existing processes are needed to accomplish necessary purification. Guidelines 1. Objectives and significance: Write one to two pages giving the objectives of your proposal and the expected significance. Innovative or original aspects of the objec- tives should be discussed. Also, on a separate page, give the complete citations, including the titles, of five or six literature references that relate to your proposal. 2. Each proposal (initial draft and final draft) must include: A. Project Summary limit one page B. Project Description limit 10 pages C. References no page limit 3. The project description should be a clear statement of the work to be undertaken and should include the following: ob- jectives for the period of the proposed work and expected significance and relation to the present state of knowl- edge in the field. The statement should outline the general plan of work, including the broad design of activities to be undertaken, and an adequate description of experi- mental methods and procedures. Typical section headings of the project description are as follows: Objectives, Significance, and Impact; Background; General Plan of Work; and Experimental Methods and Procedures. 4. Specifications for margins, spacing and font size: 2.5 cm margins on top, bottom, and on each side; double spaced; and 12-pointfont size. 5. Web site references should be limited to business and government Web sites only. All other reference citations should be to peer-reviewed articles in published journals. 6. For the revised proposal, any changes made to the initial proposal should be underlined or highlighted. Grading/Schedule The grade for the research proposal will be based on the following criteria: 1. Approach. Are the conceptual fi-amework, design, meth- ods, and analyses adequately developed, well-integrated, and appropriate to the objectives of the project? 2. Innovation. Does the project employ novel concepts, ap- proaches, or methods? Are the objectives original and in- novative? Does the project challenge existing paradigms or develop new methodologies or technologies? 3. Utility or relevance of the research. This criterion is used to assess the likelihood that the research can con- tribute to the achievement of a goal that is extrinsic or in addition to that of the research field itself and thereby serve as the basis for new or improved technology or as- sist in the solution of societal problems. Grade Credit and Schedule: Selection of proposal topic (due after three weeks) 0% Objectives and significance (due after six weeks) 5% Initial draft (due after 10 weeks) 20% Revised draft (due after 15 weeks) 15% Total for the proposal 40% General Grading Guidelines for the Research Proposal in Biochemical Engineering The one- to two-page statement of objectives and signifi- cance was graded based on the degree to which the objectives were specifically stated. The statement of significance should describe what is innovative about the proposal. The initial and revised drafts of the proposal were graded based on a careful reading by the instructor, with comments and questions written where appropriate in the margins. The questions and/or problems about the proposal led to a rating of the proposal into one of three categories: minor, moderate, or major questions/problems. In addition, the objectives and significance section of the proposal was checked to see if any deficiencies noted in the earlier objectives and significance assignment were corrected. Numerical grades were assigned based on the degree to which questions and/or problems were minimal and the objectives and significance were well stated. 1 Chemical Engineering Education B teaching tips This one-page column will present practical teaching tips in sufficient detail that ChE educators can adopt the tip. The focus should be on the teaching method, not content. With no tables or figures the column should be approximately 450 words. If graphics are included, the length needs to be reduced. Tips that are too long will be edited to fit on one page. Please submit a Word file to Phil Wankat , subject: CEE Teaching Tip. MAKE YOUR TEACHING ASSISTANT A CO-INSTRUCTOR BARATH BABURAo, SARAVANAN SWAMINATHAN, AND DONALD P. Visco, JR. Tennessee Technological University Cookeville, TN 38505 Most engineering graduate students across the country are not trained in teaching. When training occurs, one of three models is normally usedt: 1) Enrollment in formal degree or certificate engineering education programs 2) Formalized future faculty preparatory programs such as the Preparing Future Faculty (PFF) program 3) Informal (share a course with a graduate student) or formal (with course credit) training in pedagogy The Department of Chemical Engineering at Tennessee Technological University recently adopted a procedure similar to the third type that fully integrates a teaching assis- tant (TA) into a senior-level Process Dynamics and Control course. Training occurs throughout the semester and the TA is involved in a meaningful way in all aspects of the course. Implementation was done with two graduate students as co- instructors (CI) supervised by a full-time faculty member (FM). In presenting this model below, however, we use just a single CI for clarity. PROCEDURE The CI was chosen based on interest in an academic career and past experience with the course material. Prior to the beginning of the semester, the FM discussed the CI's in- volvement with the course from developing the syllabus and delivering the material, to preparing and grading homework and examinations. The FM also provided reading materials on important pedagogy tentatively planned for the class, such as active learning or team-based approaches. A weekly meeting was arranged to discuss all relevant aspects of the course, such as feedback on the previous week's class, plans for the upcoming week, etc. In addition, the FM and the CI met 10 minutes prior to each class in order to briefly review Fall 2006 the day's plan as well as discuss any unforeseen issues that have arisen. During the first few class periods the FM provided a course overview and discussed the role of the CI. The CI was trained to design the teaching methods, homework questions, quiz- zes, laboratory, examinations, and the evaluation of the final project and presentation. The CI was given the freedom to use the previous year's course material or design new mate- rial. When the CI taught the class (which happened more than half the time), the FM observed the CI's performance and vice-versa. RESULTS An individual assessment form for the CI was developed under the supervision of the FM. This 18-question form covered six areas: lectures, labs, organization, student inter- action, in-class activities, and assignments/testing. Overall, the students rated the CI as "above average." The best area was "Student Interaction." Student comments indicated that it was easier to approach a graduate student than a faculty member. Additionally, graduate students are likely to keep similar hours to that of undergraduate students, making them more accessible. Overall, the CI's involvement in every aspect of the course proved to be effective training. The FM often had an advisory role. Based on the feedback, the students generally agreed that the CI's involvement was a positive experience for all involved. REFERENCE 1. Wankat, P.C., and F.S. Oreovicz, "Teaching Prospective Engineering Faculty How To Teach," Intl. J. Engr. Educ., 21(5), 925 (2005) 0 Copyright ChE Division ofASEE 2006 Volumes 36 through 40 (Note: Author Index begins on page 338) TITLE INDEX Note: Titles in italics are books reviews. A Active Learning and Critical Thinking, Using Small Blocks of Tim es for ................................................. 38(2),150 Active Learning That Addresses Four Types of Student Motivation, Survivor Classroom: A Method of.......... 39(3),228 Adsorption Laboratory Experiment, A Fluidized Bed....... 38(1),14 Agitation and Aeration: an Automated Didactic Experiment................................................ 38(2),100 Agitation Experiment with Multiple Aspects, An............ 40(3),159 Analogies: Those Little Tricks That Help Students to Understand Basic Concepts in Chemical Engineering 39(4)302 Applied Probability and Statistics, An Undergraduate C ourse in .......................................... ..................... 36(2),170 ASEE Annual Meeting Program, 2002......................... 36(2),128 ASEE Annual Meeting Program, 2003......................... 37(2),120 Aspects of Engineering Practice Examining Value and Behaviors in Organizations...................................... 36(4),316 Aspen Plus in the ChE Curriculum: Suitable Course Content and Teaching Methodology.......................... 39(1),68 Assessing the Incorporation of Green Engineering into a Design-Oriented Heat Transfer Course................. 39(4),320 Assessing Learning Outcomes, Rubric Development and Inter-Rater Reliability Issues in................................ 36(3),212 Assessment of a Simple Viscosity Experiment for High School Science Classes, Demonstration and........... 40(3),211 Assessment of Teaching and Learning, Using Test R results for................................................................ 36(3),188 Assessment of Undergraduate Research Evaluating Multidisciplinary Team Projects, Rubric D evelopm ent for......................................................... 38(1),68 Automated Distillation Column for the Unit Operations Laboratory, An ......................................................... 39(2),104 Automotive Applications, Design of a Fuel Processor System for Generating Hydrogen for...................... 40(3),239 Award Lectures Equations (of Change), Don't Change, The: But the Profession of Engineering Does .................... 37(4),242 Membrane Science and Technology in the 21st C century ................................. ................................ 38(2),94 Future Directions in ChE Education: A New Path to G lory .......................................................... 37(4),284 Azeotropic System in a Laboratorial Distillation Column, Validating The Equilibrium Stage Model for an......... 40(3),195 B Batch Fermentation Experiment for L-Lysine Production in the Senior Laboratory, A................... 37(4),262 (BLEVE), Boiling-Liquid Expanding-Vapor Explosion: An Introduction to Consequence and Vulnerability A analysis ................................................................... 36(3),206 Beer, Teaching Product Design Through the Investigation of Commercial ................................... 36(2),108 Binary Molecular Diffusion Experiments, Inexpensive and Sim ple............................................. 36(1),68 Biochemical and Biological Engineering Courses, The Research Proposal in ............. ............................... 40(4),323 Biochemical Engineering Taught in the Context of Drug Discovery to Manufacturing........................... 39(3).208 Biodiesel Production Using Acid-Catalyzed Transesterification of Yellow Grease, Plant D esign Project: ........................................................ 40(3),215 Biointerfacial Engineering, Multidisciplinary Graduate Curriculum on Integrative ....................................... 40(4),251 Biological Systems in the Process Dynamics and Control Curriculum, Integrating ........................... 40(3),181 Biology and ChE at the Lower Levels, Integrating ......... 38(2),108 Biomass as a Sustainable Energy Source: An Illustration of ChE Thermodynamic Concepts.......................... 40(4),259 Biomedical and Biochemical Engineering for K-12 Students ................................................................... 40(4),283 Biomolecular Modeling in a Process Dynamics and C control C ourse......................................................... 40(4),297 Bioprocess Engineering, A Course In: Engaging the Imagination of Students Using Experiences Outside the C classroom ........................................................... 37(3),180 Bioreactor, Mass Transfer and Cell Growth Kinetics in a .......................................................................... 36 (3),2 16 Block-Scheduled Curriculum, Pillars of Chemical Engineering, A ......................................................... 38(4),292 Brine-Water Mixing Tank Experiment, Teaching Semiphysical Modeling to ChE Students Using a...... 39(4),308 Building Molecular Biology Laboratory Skills in C hE Students ........................................................... 39(2),134 Building Multivariable Process Control Intuition Using Control Station" ..................... ................... 37(2),100 Carbon Cycle, Earth's: Chemical Engineering Course M aterial..................................................................... 36(4),296 Career, Factors Influencing the Selection of Chemical Engineering as a....................................................... 37(4),268 Cars Accelerate Learning, Fast: High-Performance E engines ..................................... ........................... 37(3),208 Catalytic Reactor, Experiments with a Fixed-Bed............. 36(1),34 Cell Growth Kinetics in a Bioreactor, Mass Transfer and ............... ................................................ 36(3),216 Chemical Engineering Education Cellular Biology into a ChE Degree Program. Incorporating M olecular and.................................... 39(2), 124 CFD Tools, Teaching Nonideal Reactors with.............. 38(2),154 ChE Principles, A Respiration Experiment to Introduce 38(3),182 Chem-E-Car Competition, Engineering Analysis in the....40(1),66 Chem-E-Car Down Under ............................................ 36(4),288 Chemical Product Engineering. A Graduate-Level- Equivalent Curriculum in ......................................... 39(4).264 Chemical Reaction Engineering Lab Experiment. A n Integrated ........................................................... 38(3),228 Chemical Thermodynamic Concepts to Real-World Problems, Relating Abstract.................................... 38(4),268 Chemistry into the ChE Curriculum, Incorporating Com putational ......................................................... 40(4),268 Classroom Demonstration of Natural Convection, A Sim ple .................................................................. 39(2),138 Choosing and Evaluating Equations of State for Thermophysical Properties...................................... 37(3),236 Coffee on Demand: A Two-Hour Design Problem............ 36(1 ),54 Coherence in Technical Writing, Improving................. 38(2),116 Collaborative Learning and Cyber-Cooperation in M ultidisciplinary Projects........................................ 37(2), 114 Combining Modern Learning Pedagogies in Fluid Mechanics and Heat Transfer .................................. 39(4),280 Combustion Principles for Engineering Freshman, The Potato Cannon: Determination of..................... 39(2).156 Commercial Simulator to Teach Sorption Separations. U sing A ...................................... .............................. 40(3),165 Common Plumbing and Control Errors in Plantwide Flow Sheets............................................. 39(3),202 Community-Based Presentations in the Unit Ops L laboratory ............................................................... 39(2),160 Communication Skills in Engineering Students, An Innovative Method For Developing ........................ 38(4),302 Compact Heat Exchangers, A Project to Design and B uild ..................................................................... 39 (1 ),38 Compendium of Open-Ended Membrane Problems in the Curriculum A .................................................. 37(1 ).46 Compressible Flow Analysis Discharging Vessels .......... 38(3),190 Computation in the Analysis of Separation Processes, Using Visualization and........................................... 40(4),313 Computational Fluid Dynamics, Incorporating Nonideal Reactors in a Junior-Level Course........................... 38(2),136 Computer Evaluation of Exchange Factors in Therm al Radiation ............................................... 38(2),126 Computer-Facilitated Mathematical Methods in ChE Sim ilarity Solution..................................................... 40(4),307 Computer Programming to Teach Numerical Methods, Increasing Time Spent on Course Objectives by U sing ........................................................................ 37(3),2 14 Computer Science or Spreadsheet Engineering: An Excel/VBA-Based Programming and Problem- Solving C ourse ........................................................ 39(2),142 Computing Experience, Enhancing the Undergraduate... 40(3),231 ConcepTests and Instant Feedback in Thermodynamics, U se o f........................................ ..... ............................ 3 8 (1 ),64 Conceptual Understanding in Chemical Engineering........ 36(1),42 Condensation, Solvent Recovery by: An Application of Phase Equilibrium and Sensitivity Analysis............ 38(3),216 Conducting the Engineer s Approach to Problem Solving, Fall 2006 Discussion of the Method: ....................................... 38(3),203 Consequence and Vulnerability Analysis, Boiling-Liquid Expanding-Vapor Explosion (BLEVE) ................... 36(3),206 Construction and Visualization of VLE Envelopes in M athcad ................................................ .................. 37(1),20 Consulting, The Vagaries of ............................................. 36(l),74 Control Station". Building Multivariable Process Control Intuition U sing ...................................................... 37(2),100 Cooking Potatoes: Experimentation and Mathematical M odeling .................................... ................................ 36(1),26 Cooperative Work That Gets Sophomores on Board.......39(2),128 Copper Rotating-Disc Electrode, Reduction of D issolved Oxygen at a................................................ 39(1),14 Coupled Transport and Rate Processes, Teaching ........... 38(4),254 Course-Level Strategy for Continuous Improvement, A. 39(3),186 Course Project, Partnering With Industry for a M eaningful................................................................ 40(1),32 Cross-Disciplinary Projects in a ChE Undergraduate Curriculum, Development of.................................... 38(4),296 Curriculum: Suitable Course Content and Teaching Methodology, Aspen Plus in the ChE........................ 39(1),68 Cyber-Cooperation in Multidisciplinary Projects, Collaborative Learning and ..................................... 37(2),114 Class and Home Problems A Simple Open-Ended Vapor Diffusion Experiment.. 38(2),122 An Open-Ended Mass Balance Problem................... 39(1),22 Boiling-Liquid Expanding-Vapor Explosion (BLEVE) An Introducton to Consequence and Vulnerability Analysis ........................................... 36(3),206 Computer-Facilitated Mathematical Methods in ChE Similarity Solution........................................ 40(4),309 Cooperative Work That Gets Sophomores on Board.. 39(2),128 Data Analysis Made Easy With DataFit .................... 40(1),60 Fuel Processor System for Generating Hydrogen for Automotive Applications ...................................... 40(3),239 Gas Permeation Computations with Mathematica .....40(2),140 'Greening' a Design-Oriented Heat Transfer Course. 39(3),216 Incorporating Green Engineering into a Material and Energy Balance Course..................................... 38(1),48 Scaled Sketches for Visualizing Surface Tension....... 39(4),328 Solvent Recovery by Condensation: An Application of Phase Equilibrium and Sensitivity Analysis............ 38(3),216 The Sherry Solera: An Application of Partial Difference Equations .................... ....................... 36(1),48 D Data Analysis Made Easy With Datafit........................... 40(1),60 Decision Analysis for Equipment Selection ................. 39(2),100 Demonstration and Assessment of a Simple Viscosity Experiment for High School Science Classes ............ 40(3),211 Design Experience: Multidisciplinary Design of a Potable Water Treatment Plant, A Freshman ........... 39(4),296 Design in Chemical Engineering at Rose-Hulman Institute of Technology, Freshman .......................... 38(3),222 Design of a Fuel Processor System for Generating Hydrogen for Automotive Applications .................. 40(3),239 Design Problem, A Two-Hour: Coffee on Demand ........... 36(1),54 Design Project: Biodiesel Production Using Acid- Catalyzed Transesterification of Yellow Grease, P lant ........................................ ................................. 40 (3),2 15 Design Project Curricula, An International Comparison of Final-Year.............................. ........................ 40(4),275 Design Projects of the Future.......................................... 40(2),88 Design Projects, Web-Based Delivery of ChE...............39(3),194 Design Through the Investigation of Commercial Beer, Teaching Product............................................ 36(2),108 Determining Self-Similarity Transient Heat Transfer with Constant Flux, A Method for............................. 39(1),42 Determining the Flow Characteristics of a Power L aw L iquid ................................................................ 36(4),304 Developing Metacognitive Engineering Teams............ 38(4),316 Development and Implementation of an Educational Sim ulator: Glucosim ................................................ 37(4),300 Development of Cross-Disciplinary Projects In a ChE Undergraduate Curriculum.............................. 38(4),296 Differential Equations, Scaling of: "Analysis of the Fourth K ind,"........................................................... 36(3),232 Diffusion Experiments, Inexpensive and Simple Binary M olecular....................................................... 36(1),68 Diffusivities in the Classroom, Using Molecular-Level Simulations to Determine........................................ 37(2), 156 Discharging Vessels, Compressible Flow Analysis ......... 38(3),190 Discussion of the Method: Conducting the Engineer's Approach to Problem Solving................ 38(3),203 Dissolved Oxygen at a Copper Rotating-Disc Electrode, Reduction of ............................................. 39(1),14 Distillation Case Study, Using Mathematica to Teach Process U nits, A ....................................................... 39(2),116 Division Program, Chemical Engineering.....................36(2), 128 Departmental Articles California Berkeley, University of............................37(3),162 Colum bia University....................... ........................ 40(1),8 Illinois Institute of Technology..................................... 39(1),2 Kansas State U niversity................................................ 36(1),2 Maryland Baltimore County, University of ............... 37(2),82 Oklahoma, University of......................................... 38(3),162 Rice U niversity............................ ......................... 38(2),88 Rowan University........................ ........................ 39(2),82 Sherbrooke, University of........................................ 40(3),146 Tulane University ....................................... 36(2),88;40(2),80 Vanderbilt University........................... ..................... 37(1),2 W ashington University ............................................ 39(3),170 Doctoral Student's Perspective, Teaching and Mentoring Training Programs at Michigan State U university: A ............................................................ 38(4),250 Drawing the Connections Between Engineering Science and Engineering Practice............................ 39(2),110 Drug Delivery for Chemical Engineers, An Introduction to ......................................................... 36(3), 198 Drug Discovery to Manufacturing, Biochemical Engineering Taught in the Context of...................... 39(3),208 Durbin-Watson Statistics to Time-Series-Based Regression Models, On the Application of................ 38(1),22 Dust Explosion Apparatus Suitable for Use in Lecture Dem onstrations, A ................................................... 38(3),188 Dynamic Simulation to Converge Complex Process Flow Sheets, Use of.....................................38(2),142 E Earth's Carbon Cycle Chemical Engineering Course M material, T he............................................................. 36(4),296 Economic Risk Analysis: Using Analytical and Monte Carlo Techniques ....................................................... 36(2),94 Economics and Business Strategies, A Lesson in Engineering: Gas Station Pricing Game.................. 36(4),278 Educator Articles Davis, Robert H.; University of Colorado................. 37(2),88 Doherty, Mike; UC Santa Barbara............................ 38(3)168 Doraiswamy, L.K.; Iowa State University............... 36(3),178 Eckert, Chuck; Georgia Institute of Technology ............ 38(1),2 Gast, Alice; Massachusetts Institute of Technology .....39(2),88 Hesketh, Robert; Rowan University.............................37(1),8 King, C. Judson; UC Berkeley ................................ 39(3),178 LeBlanc, Steve; University of Toledo ....................... 36(2),82 Montgomery, Susan; University of Michigan ............ 40(3),154 Rhinehart, R. Russell; Oklahoma State University ........ 39(1),8 Seider, Warren; University of Pennsylvania................ 36(1),8 Shuler, Michael L.; Cornell University ..................... 38(2),82 Schulz, Kirk; Mississippi State University.................. 40(1),2 Stuve, Eric M.; University of Washington................. 40(2),74 Electrochemical Method, Metal Recovery from W astew ater w ith an.................................................. 36(2),144 Electrodialysis, Exploring the Potential of ......................37(1),52 Electrolyte Thermodynamics, Teaching .............................38(1),26 Energy Balances on the Human Body: A Hands-On Exploration of Heat, Work, and Power.......................39(1),30 Energy Consumption vs. Energy Requirement............. 40(2),132 Energy Source: An Illustration of ChE Thermodynamic Concepts, Biomass as a Sustainable.........................40(4),259 Enhancing the Undergraduate Computing Experience....40(3),231 Engineering Analysis in the Chem-E-Car Competition.....40(1 ),66 Engineering Science and Engineering Practice, Drawing the Connections Between ........................................ 39(2),110 Engines, High-Performance: Fast Cars Accelerate Learning .................................................................. 37(3),208 Environmental Engineers Through Development of a New Course, Introducing Molecular Biology to........ 36(4),258 Environmental Impact Assessment: Teaching the Principles and Practices by Means of a Role-Playing C ase Study ................................................................. 39(1),76 Equations (of Change) Don't Change, But the Profession of Engineering Does.............................. 37(4),242 Equations of State at the Graduate Level, M olecular-Based...................................................... 39(4),250 Equations of State for Thermophysical Properties, Choosing and Evaluating......................................... 37(3),236 Equilibrium Stage Model for an Azeotropic Systems in an Laboratorial Distillation Column, Validating th e ......................................... .......... ......................... 4 0 (3 ),19 5 Equipment Selection, Decision Analysis for ................ 39(2),100 Evolutionary Operation Method to Optimize Gas Absorber Operation, Using the: A Statistical Method for Process Improvement ........................... 38(3),204 Examining Value and Behaviors in Organizations: Aspects of Engineering Practice...............................36(4),316 Excel/VBA-Based Programming and Problem Solving Chemical Engineering Education Course, Computer Science or Spreadsheet Engineering: A n................................ .................. 39(2),142 Exceptions to the Le Chatelier Principle ...................... 37(4),290 Excitement and Interest in Mechanical Parts, Pressure for Fun: A Course Module for Increasing ChE Students' ...................................... ......................... 40(4),29 1 Exercise for Practicing Programming in the ChE Curriculum Calculation of Thermodynamic Properties Using the Redlich-Kwong Equation of State ................................................. .................... 37(2),14 8 Experiment, Agitation and Aeration an Autom ated Didactic ............................................ 38(2),100 Experiment, A Nonlinear, Multi-Input, Multi-Output Process Control Laboratory......................................... 40(1)54 Experiment, A Quadruple-Tank Process Control............. 38(3),174 Experiment, A Simple Open-Ended Vapor Diffusion...... 38(2),122 Experiment for Transport Phenomena, An Easy Heat and M ass Transfer.................................... 36(1),56 Experiment with Multiple Aspects, An Agitation............ 40(3),159 Experimental Air-Pressure Tank Systems for Process Control Education...................................................... 40(1),24 Experimental Design, Personalized, Interactive, Take-Home Examinations for Students Studying....... 37(2).136 Experimental Design into the Unit Operations Laboratory, Incorporating..................... ................ 37(3), 196 Experimental Investigation and Process Design in a Senior Laboratory Experiment ................................ 40(3),225 Experimental Projects for the Process Control L laboratory ............................................................... 36(3),182 Experimentation and Mathematical Modeling: C cooking Potatoes......................................................... 36(1 ),56 Experiments Across the Atlantic, Performing Process C control ...................................... ............................. 39(3),232 Experiments, Inexpensive and Simple Binary M olecular D iffusion................................................. 36(1 ),68 Experiments and Other Learning Activities Using Natural Dye M aterials................................... 38(2),132 Experiments with a Fixed-Bed Catalytic Reactor.............. 36(1),34 Explicit Models, Sensitivity Analysis in ChE Education: Part 1. Introduction and Application to ................... 37(3),222 F Factors Influencing the Selection of Chemical Engineering as a Career............................................ 37(4).268 First-Semester Course Focusing on Connection, Communication, and Preparation, A Successful Introduction to ChE".......................... .................. 39(3),222 Fixed-Bed Catalytic Reactor, Experiments with a.............36(1),34 Flexible Pilot-Scale Setup for Real-Time Studies in Process Systems Engineering, A................................ 40(1),40 Flow Characteristics of a Power Law Liquid, D eterm ining the ....................................................... 36(4).304 Fluid Mechanics, Water Day: An Experiential L ecture for ............................................................... 37(3), 170 Fluid-Mixing Laboratory for ChE Undergraduates......... 37(4),296 Fluidized Bed Adsorption Laboratory Experiment............ 38(1),14 Fluidized Bed Polymer Coating Experiment................ 36(2), 138 For the Sake of Argument: If the Conventional Lecture Is Dead Why is it Alive and Thriving............................. 40(2) Free Convection, A Computational Model for Teaching. 38(4),272 Fall 2006 French Fry-Shaped Potatoes, Optimum Cooking of: A Classroom Study of Heat and Mass Transfer ............. 37(2),142 Freshman Design Experience: Multidisciplinary Design of a Potable Water Treatment Plant, A ........... 39(4),296 Freshman Design in Chemical Engineering at Rose- Hulman Institute of Technology .............................. 38(3),222 Frontiers of Chemical Engineering: a Chemical Engineering Freshman Seminar................................. 37(1),24 FTIR Spectroscopy: An Experiment for the Undergraduate Laboratory, Kinetics of Hydrolysis of Acetic Anhydride by In-Situ.................................. 39(1),56 Fuel Processor System for Generating Hydrogen for Automotive Applications. Design of a .................... 40(3),239 Fuel Cell: An Ideal ChE Undergraduate Experiment......... 38(1),38 Future Directions in ChE Education: A New Path to G lory ................... ................................................ 37(4),284 Gas Permeation Computations with Mathematica...........40(2),140 Gas Separation Membrane Experiments, A Simple A analysis for................................................................ 37(1),74 Gas Separation Using Polymers, Tools for Teaching.........37(1),60 Gas Station Pricing Game: A Lesson in Engineering Economics and Business Strategies......................... 36(4),278 Gasification Senior Design Project That Integrates Laboratory Experiments and Computer Simulation, A T ire ...................................................................... 40(3),203 Gene Subcloning for Chemical Engineering Students, Laboratory Experiment on....................................... 38(3),212 Gibbs Energy Considerations Reduce the Role of Rachford-Rice Analysis, Computing Phase Equilibria: 36(1 ),76 Gillespie Algorithm and MATLAB. Introducing the Stochastic Simulation of Chemical Reactions U sing the.................................................................... 37(1),14 Glucosim: Development and Implementation of an Educational Sim ulator ............................................ 37(4),300 Graduate Course on Multi-Scale Modeling of Soft M atter. A ...................................................... 38(4),242 Graduate Courses, Reflections on Project-Based L earning in............................................................... 38(4),262 Graduate Curriculum on Integrative Biointerfacial Engineering, M ultidisciplinary ................................. 40(4),251 Graduate Education: A Novel Approach for Describing Micromixing Effects in Homogeneous Reactors........ 36(4),250 Graduate Education: Introducing Molecular Biology to Environmental Engineers Through Development of a New Course................................ 36(4),258 Graduate-Level Course in Tissue Engineering, Teaching A ...................................... ...................... 39(4),272 Graduate-Level-Equivalent Curriculum in Chemical Product Engineering, A............................................ 39(4),264 Graduate Level, Molecular-Based Equations of State at the ........................................................................ 39(4 ),250 Graduate Programs, Productivity and Quality Indicators for Highly Ranked ChE ............................................. 37(2),94 Graduate Students the Role of Journal Articles in Research, Teaching Entering................................... 40(4),246 Graduate Thermodynamics Course in Chemical Engineering Departments Across the United States, A Survey of the.......................... ........................ 39(4),258 331 "Greening" a Design-Oriented Heat Transfer Course ..... 39(3),216 Green Engineering into a Design-Oriented Heat Transfer Course, Assessing the Incorporation of........ 39(4),320 Green Engineering into a Material and Energy Balance Course, Incorporating ................................................ 38(1),48 Group Learning, Introduction to Synthesis, Resourcefulness, and Effective Communication in Biochemical Engineering ....................................... 37(3),174 Group Work, Teaching Engineering in a Modern Classroom Setting: Making Room for .................... 39(2),164 Hands-On Laboratory in the Fundamentals of Semiconductor Manufacturing, A.... .............. .... 36(1),14 Heat Transfer Visualization Tools, Java-Based............. 38(4),282 Heat and Mass Transfer Experiment for Transport Phenomena, An Easy......................... .............. 36(1),56 Heat and Mass Transfer, Optimum Cooking of French Fry-Shaped Potatoes: A Classroom Study of ...............................37(2),142 Heat Transfer Analysis and the Path Forward in a Student Project on the Splenda Sucralose Process..... 39(4),316 Heat Transfer Course, Assessing the Incorporation of Green Engineering into a Design-Oriented ............. 39(4),320 Heat Transfer Course, "Greening" a Design-Oriented .... 39(3),216 Heat Transfer Problems, Spreadsheet Solutions to Two-Dimensional .... ................................. 36(2),160 Heat, Work, and Power; Energy Balances on the Human Body: A Hands-On Exploration of ........................... 39(1),30 High School Science Classes, Demonstration and Assessment of a Simple Viscosity Experiment for..... 40(3),211 High-Performance Engines: Fast Cars Accelerate Learning..................................... ........... 37(3),208 High-Performance Learning Environments............ .... 38(4),286 High School Outreach into ChE Courses, Incorporating. 37(3),184 Holistic Unit Operations Laboratory, A................... 36(2),150 Homogeneous Reactors, A Novel Approach for Describing Micromixing Effects in......................... 36(4),250 Hydrogen for Automotive Applications, Design of a Fuel Processor System for Generating .................... 40(3),239 Hydrolysis of Acetic Anhydride by In-Situ FTIR Spectroscopy: An Experiment for the Undergraduate Laboratory, Kinetics of ......................39(1),56 Hyper-TVT: Development and Implementation of an Interactive Learning Environment........................... 40(3),175 I Improving Coherence in Technical Writing................... 38(2)116 Improving "Thought with Hands", On ......................... 36(4),292 Incorporating Computational Chemistry into the ChE C urriculum ................................................................ 40(4),268 Incorporating Experimental Design into the Unit Operations Laboratory............................................. 37(3), 196 Incorporating Green Engineering into a Material and Energy Balance Course.............................................. 38(1),48 Incorporating High School Outreach into ChE Courses.. 37(3),184 Incorporating Molecular and Cellular Biology into a ChE Degree Program ............................................. 39(2),124 Incorporating Nonideal Reactors in a Junior-Level Course Using Computational Fluid Dynamics...........38(2),136 Industrial Training in Chemical Engineering Education, 332 T he R ole of............................................................... 40(3),189 Industry for a Meaningful Course Project, Partnering W ith ................................................. ...................... 40(1),32 Innovative, Can We Teach Our Students to be.............. 36(2),116 Innovative Method for Developing Communication Skills in Engineering Students, An.......................... 38(4),302 Instant Messaging: Expanding Your Office Hours .......... 39(3),183 Integrating Biological Systems in the Process Dynamics and Control Curriculum.......................... 40(3),181 Integrating Biology and ChE at the Lower Levels .......... 38(2),108 Integrated Chemical Reaction Engineering Lab Experim ent, A n........................................................ 38(3),228 Integrating Kinetics Characterization and Materials Processing in the Lab Experience............................ 36(3),226 Integration Technique to Trace Phase Equilibria Curves, U se of an..................................................... 36(2),134 Interactive Learning Environment, Hyper-TVT: Development and Implementation of an ................. 40(3),175 International Comparison of Final-Year Design Project C urricula, A n ............................................................ 40(4),275 Internet Resources for Chemical Engineers.................. 36(2),100 Inter-Rater Reliability Issue in Assessing Learning Outcomes, Rubric Development and ...................... 36(3),212 Introducing the Stochastic Simulation of Chemical Reactions Using the Gillespie Algorithm and M A T L A B ................................................. ................... 37(1),14 "Introduction to ChE" First-Semester Course Focusing on Connection, Communication, and Preparation, A Successful ............................................................ 39(3),222 Introduction to Drug Delivery for Chemical Engineers, A n........................................................... 36(3),198 Introductory ChE Courses, Portfolio Assessment in........ 36(4),310 Introductory Chemical Reaction Engineering Course, Micromixing Experiments in the............................... 39(2),94 Investigation into the Propagation of Baker's Yeast: A Laboratory Experiment in Biochemical Engineering. 38(3),196 I Java-Based Heat Transfer Visualization Tools.............. 38(4),282 Journal Articles in Research, Teaching Entering Graduate Students the Role of................................. 40(4),246 K K-12 Students, Biomedical and Biochemical Engineering fo r.......................................... .............. ..................... 4 0 (4 ),2 83 Kinetics and Reactor Design, Modeling of Chemical........37(1),44 Kinetics Experiment for the Unit Operations Laboratory, A .............................................................................. 39 (3),238 Kinetics of Hydrolysis of Acetic Anhydride by In-Situ FTIR Spectroscopy: An Experiment for the Undergraduate Laboratory....................................... 39(1)56 L L-Lysine Production in the Senior Laboratory, A Batch Fermentation Experiment for................................... 37(4),262 Lab-Based Unit Ops in Microelectronics Processing......37(3),188 Laboratory Exercise, Using a Commercial Movie for an Educational Experience; Alternative: ... 37(2),154 Lab Experience, Integrating Kinetics Characterization and Chemical Engineering Education M materials Processing in the...................................... 36(3),226 Lab Experiment, An Integrated Chemical Reaction Engineering.............................................................. 38(3),228 Laboratory, A Batch Fermentation Experiment for L-Lysine Production in the Senior........................... 37(4),262 Laboratory Experiment, Experimental Investigation and Process Design in a Senior ....................................... 40(3),225 Laboratory in the Fundamentals of Semiconductor M manufacturing, A Hands-On...................................... 36(1),14 Laboratory Experiment on Gene Subcloning for Chemical Engineering Students............................... 38(3),212 Laboratory Experiment, Pem Fuel-Cell Test Station and 38(3),236 Laboratory Skills in ChE Students, Building M olecular Biology................................................... 39(2), 134 Laboratory to Supplement Courses in Process Control, A. 36(1),20 Laboratory Structure Encouraging Realistic Communication and Creative Experiment Planning.......................... 37(3),202 Learning Environments, High-Performance................. 38(4),286 Learning Pedagogies in Fluid Mechanics and Heat Transfer, Com bining................................................. 39(4),280 Learning Through Simulation: Student Engagement.......39(4),288 Lecture Demonstrations, A Dust Explosion Apparatus Suitable for U se in ...................... ....................... 38(3), 188 Letters to the Editor............. 36(1),59;37(1),45;(2),124;(3),207 Le Chatelier Principle, Exceptions to the ..................... 37(4).290 Liquid Diffusion Coefficients, Mass Transfer Experiment: Determination of..................................36(2),156 Lower Levels, Integrating Biology and ChE at the ..........38(2)108 M Making Room for Group Work: Teaching Engineering in a Modern Classroom Setting ............................ 39(2),164 Manufacturing, Biochemical Engineering Taught in the Context of Drug Discovery and............................... 39(3),208 Mathematica, Gas Permeation Computations with.......... 40(2),140 Mass Balance Problem, An Open-Ended........................ 39(1),22 Mass Transfer and Cell Growth Kinetics in a B ioreactor .................................. .............................. 36(3),2 16 Mass Transfer Experiment: Determination of Liquid Diffusion Coefficients.............................................. 36(2).156 Mass Transfer Experiment for Transport Phenomena, A n E asy H eat and ........................................................ 36(1),56 Materials Processing in the Lab Experience, Integrating Kinetics Characterization and.................................. 36(3),226 MathCad, Construction and Visualization of VLE E nvelopes in ............................................................... 37(1),20 MathCad in Undergraduate Reaction Engineering, Numerical Problem Solving Using.........................40(1),14 Mathematica to Teach Process Units: A Distillation C ase Study, U sing.................................................... 39(2),116 Mathematical Methods in ChE Similarity Solution, Com puter-Facilitated.................... ........................ 40(4),307 Mathematical Modeling: Cooking Potatoes, Experimentation and.................................. 36(1),26 Mathematical Modeling and Process Control of Distributed Parameter Systems: The One-Dimensional Heated Rod ................................ 37(2), 126 MATLAB, Introducing the Stochastic Simulation of Fall 2006 Chem. Reactions Using the Gillespie Algorithm and... 37(1),14 McCabe-Thiele Modeling Specific Roles in the Learning Process, Process Simulation and ..............................37(2),132 Mechanical Testing of Common-Use Polymeric Materials with an In-House-Built Apparatus............. 40(1),46 Membrane Science and Technology in the 21st Century... 38(2),94 Mentoring Training Programs at Michigan State University: A Doctoral Student's Perspective, Teaching and............................................................ 38(4),250 Metacognitive Engineering Teams, Developing........... 38(4),316 Micromixing Experiments in the Introductory Chemical Reaction Engineering Course.................... 39(2),94 Mixing Writing with First-Year Engineering: An U nstable Solution .................................................... 37(4),248 Mechanical Parts, Pressure for Fun: A Course Module for Increasing ChE Students' Excitement and Interest in ................... ............................................ 40(4),291 Membranes in ChE Education Analysis of Membrane Processes in the Introduction- to-C hE C ourse........................................................ 37(1),33 Compendium of Open-Ended Membrane Problems in the Curriculum .................................................. 37(1),46 Exploring the Potential of Electrodialysis................. 37(1),52 Membrane Projects with an Industrial Focus in the C urriculum ............................................................ 37(1),68 Press Ro System: An Interdisciplinary Reverse Osmosis Project for First-Year Engineering Students ............ 37(1),38 Simple Analysis for Gas Separation Membrane Experim ents, A ...................................................... 37(1),74 Tools for Teaching Gas Separation Using Polymers .... 37(1),60 Membrane Science and Technology in the 21st C century ............................................. ..................... 38(2),94 Membrane Problems in the Curriculum, A Compendium of Open-Ended.................................... 37(1),46 Metal Recovery from Wastewater with an Electrochemical M ethod.......................................... 36(2),144 Method for Determining Self-Similarity Transient Heat Transfer with Constant Flux, A......................... 39(1),42 Micromixing Effects in Homogeneous Reactors, A Novel Approach for Describing ......................................... 36(4),250 Modeling of Chemical Kinetics and Reaction Design ....... 37(1 ),44 Modeling in a Process Dynamics and Control Course, B iom olecular ............................................................ 40(4),297 Modern Classroom Setting, Making Room for Group Work: Teaching Engineering in a ............................ 39(2),164 Mole Balances Systematically, Put Your Intuition to R est: W rite ........................................ .................... 38(4),308 Molecular and Cellular Biology into a ChE Degree Program Incorporating............................................. 39(2),124 Molecular-Based Equations of State at the G graduate Level ......................................................... 39(4),250 Molecular Diffusion Experiments, Inexpensive and Sim ple B inary ............................................................. 36(1),68 Molecular-Level Simulations to Determine Diffusivities in the Classroom Using............................................ 37(2),156 Molecular Biology to Environmental Engineers Through Development of a New Course, Introducing........... 36(4),258 Monte Carlo Techniques: 333 Economic Risk Analysis, Using Analytical and........... 36(2),94 Movie for an Educational Experience: An Alternative Laboratory Exercise, Using a Commercial................................ 37(2),154 Multidisciplinary Design of a Potable Water Treatment Plant, A Freshman Design Experience: ................... 39(4),296 Multidisciplinary Graduate Curriculum on Integrative Biointerfacial Engineering....................................... 40(4),251 Multidisciplinary Projects, Collaborative Learning and Cyber-Cooperation in........................................ 37(2),114 Multidisciplinary Team Projects, Evaluating: Rubric Development for Assessment of Undergraduate R esearch............................................ ...................... 38(1),68 Multi-Scale Modeling of Soft Matter, A Graduate Course on ...................... ........................ 38(4),242 N Nanostructured Materials Synthesis of Zeolites............. 38(1),34 Natural Convection, A Simple Classroom D em onstration of .......................................................... 39(2),138 Natural Dye Materials, Experiments and Other Learning A activities ....................... ........................ 38(2),132 Next Millennium in Chemical Engineering Crystal Engineering: From Molecules To Products.... 40(2),116 Different Chemical Industry, A................................ 40(2),114 Inside the Cell: A New Paradigm for Unit Operations and U nit Processes ............................................. 40(2),126 Next Millennium in Chemical Engineering, The ......... 40(2),99 Teaching Engineering in the 21st Century with a 12th- Century Teaching Model: How Bright is That...... 40(2),110 Vision of the Curriculum of the Future, A............... 40(2),104 Nonideal Reactors in a Junior-Level Course Using Computational Fluid Dynamics, Incorporating .......... 38(2),136 Nonlinear, Multi-Input, Multi-Output Process Control Laboratory Experiment, A ......................................... 40(1 ),54 Numerical Methods, Increasing Time Spent on Course Objectives by Using Computer Programming to Teach ........................................................................ 37(3),2 14 Numerical Problem Solving Using MathCad in Undergraduate Reaction Engineering........................ 40(1),14 Numerical Problems, A Separation Processes Course Using Written-Answer Questions to Complement.....36(2), 130 Office Hours, Instant Messaging: Expanding Your ......... 39(3),183 On Improving "Thought with Hands"........................... 36(4),292 On the Application of Durbin-Watson Statistics to Time-Series-Based Regression Models..................... 38(1),22 One-Dimensional Heated Rod: Mathematical Modeling and Process Control of Distributed Parameter System s ............................................... 37(2),126 Open-Ended Mass Balance Problem, An........................ 39(1),22 Optimum Cooking of French Fry-Shaped Potatoes: A Classroom Study of Heat and Mass Transfer.............37(2),142 P Paradox of Papermaking, The....................................... 39(2),146 Partial Difference Equations, The Sherry Solera: An Application of .............................. 36(1),48 Particle Demonstrations for the Classroom and Lab ...... 37(4),274 Particle Technology, Novel Concepts for Teaching......... 36(4),272 Partnering with Industry for a Meaningful Course Project............................................................ 40(1),32 Performing Process Control Experiments Across the A tlantic................................................................ 39(3),232 Pem Fuel-Cell Test Station and Laboratory Experiment. 38(3),236 Personalized, Interactive, Take-Home Examinations for Students Studying Experimental Design ........... 37(2),136 Plantwide Flow Sheets, Common Plumbing and Control Errors in...................................................... 39(3),202 Potato Cannon: Determination of Combustion Principles for Engineering Freshman, The.............. 39(2),156 Product Design Through the Investigation of Commercial Beer, Teaching..................................... 36(2),108 Phase Equilibria, How Gibbs Energy Considerations Reduce the Role of Rachford-Rice Analysis: Computing:........................ 36(1),76 Phase Equilibria Curves, Use of an Integration Technique to Trace................................................... 36(2),134 Phase Equilibrium and Sensitivity Analysis, Solvent Recovery by Condensation: An Application of .......... 38(3),216 Phase Equilibrium More User-Friendly, Making............. 36(4),284 Pillars of Chemical Engineering: A Block-Scheduled Curriculum.................................. 38(4),292 Pilot-Scale Setup for Real-Time Studies in Process Systems Engineering, A Flexible............................... 40(1),40 Plant Design Project: Biodiesel Production Using Acid- Catalyzed Transesterification of Yellow Grease......... 40(3),215 Polymer Coating Experiment, Fluidized Bed............... 36(2),138 Polymeric Materials with an In-House-Built Apparatus, Mechanical Testing of Common-Use........................ 40(1 ),46 Portfolio Assessment in Introductory ChE Courses......... 36(4),310 Potable Water Treatment Plant, A Freshman Design Experience: Multidisciplinary Design of a.............. 39(4),296 Power, Energy Balances on the Human Body: A Hands-On Exploration of Heat, Work, and................ 39(1 ),30 Power Law Liquid, Determining the Flow Characteristics of a .................................................. 36(4),304 Press RO System: An Interdisciplinary Reverse Osmosis Project for First-Year Engineering Students...............37(1),38 Pressure for Fun: A Course Module for Increasing ChE Students' Excitement and Interest in Mechanical P arts ..................................................... ..................... 40 (4 ),29 1 Problem, And Open-Ended Mass Balance...................... 39(1),22 Problem-Solving Skills, Assessing: Part 2.......................36(1),60 Process Control of Distributed Parameter Systems Case Study: The One-Dimensional Heated Rod, Mathematical Modeling and.................................... 37(2),126 Process Control Education, Experimental Air- Pressure Tank Systems for.......................................... 40(1),24 Process Control Experiment, A Quadruple-Tank............. 38(3),174 Process Control, A Laboratory to Supplement Courses in. 36(1),20 Process Control Intuition Using Control Stations, Building M ultivariable ........................................... 37(2),100 Process Control Laboratory Experience, Simulation and Experiment in an Introductory................................. 37(4),306 Process Control Laboratory Experiment, A Nonlinear, M ulti-Input, M ulti-Output ......................................... 40(1 ),54 Process Control Laboratory, Experimental Projects Chemical Engineering Education for the...................................................................... 36(3),182 Process Control with a Numerical Approach Based on Spreadsheets, Teaching............................................. 36(3),242 Process Design in a Senior Laboratory Experiment, Experimental Investigation and............................... 40(3),225 Process Dynamics and Control Course, Biomolecular M odeling in a............................................................ 40(4),297 Process Dynamics and Control Curriculum, Integrating Biological System s in the ........................................ 40(3),181 Process Flow Sheets, Use of Dynamic Simulation to Converge Complex........................................... 38(2),142 Process Security in ChE Education................................. 39(1),48 Process Simulation and McCabe-Thiele: Modeling Specific Roles in the Learning Process.................... 37(2),132 Process Simulation Used Effectively in ChE C ourses?, Is............................................................... 36(3),192 Process Systems Engineering, A Flexible Pilot-Scale Setup for Real-Time Studies in.................................. 40(1 ),40 Productivity and Quality Indicators for Highly Ranked ChE Graduate Programs............................................ 37(2),94 Profession of Engineering Does, Equations (of Change) Don't Change but the.......................... .................. 37(4),242 Professor, Returning as a .............................................. 37(4),310 Project-Based Learning in Graduate Courses, R elections on .......................................................... 38(4),262 Project to Design and Build Compact Heat Exchangers, A ............................ ............................ 39(1),38 Project on the Splenda Sucralose Process, Heat Transfer Analysis and the Path Forward in a Student ........... 39(4),316 Project, VCM Process Design: An ABET 2000 Fully C om pliant ............................... ............................... 39(1),62 Propagation of Baker's Yeast: A Laboratory Experiment in Biochemical Engineering, Investigation into the ....... 38(3),196 Put Your Intuition to Rest: Write Mole Balances Systematically ......... ............................. 38(4),308 Q Quadruple-Tank Process Control Experiment, A............. 38(3),174 R Rachford-Rice Analysis, Computing Phase Equilibria: How Gibbs Energy Considerations Reduce the Role of ................36(1),76 Rate Processes, Teaching Coupled Transport and ........... 38(4),254 Reaction Engineering, Numerical Problem Solving Using MathCad in Undergraduate............................. 40(1),14 Reactor Design, Modeling of Chemical Kinetics............ 37(1),44 Real-Time Studies in Process Systems Engineering, A Flexible Pilot-Scale Setup for.................................... 40(1),40 Real-World Problems, Relating Abstract Chemical Thermodynamic Concepts to................................... 38(4),268 Recommendation Letters, Value of Good..................... 37(2), 122 Redlich-Kwong Equation of State: An Exercise for Practicing Proramming in the ChE Curriculum, Calculation of Thermodynamic Properties Using the ................ 37(2),148 Reduction of Dissolved Oxygen at a Copper Rotating-Disc Electrode ............................................ 39(1),14 Reflections on Project-Based Learning in Graduate Courses........... .......................... .......... 38(4),262 Regression Models, On the Applications of Durbin-Watson Fall 2006 Statistics to Times-Series-Based................................ 38(1),22 Relating Abstract Chemical Thermodynamic Concepts to Real-World Problems .......................................... 38(4),268 Research Proposal in Biochemical and Biological Engineering Courses, The.................... 40(4),323 Research, Teaching Entering Graduate Students the Role of Journal Articles in................................................ 40(4),246 Respiration Experiment to Introduce ChE Principles, A. 38(3), 182 Returning as a Professor ............................................... 37(4),310 Reverse Osmosis Project for First-Year Engineering Students, Press RO System :........................................ 37(1),38 Risk Analysis: Using Analytical and Monte Carlo Techniques, Economic......................................36(2),94 Role of Industrial Training in Chemical Engineering Education, The......................................................... 40(3),189 Role-Playing Case Study, Environmental Impact Assessment: Teaching the Principles and Practices by M means of a ..................... ..................................... 39(1)76 Rose-Hulman Institute of Technology, Freshman Design in Chemical Engineering at......................... 38(3),222 Rubric Development and Inter-Rater Reliability Issues in Assessing Learning Outcomes............................. 36(3),212 Rubric Development for Assessment of Undergraduate Research Evaluating Multidisciplinary Team P projects ................................... ................................ 38(1),68 Random Thoughts Changing Times and Paradigms................................ 38(1),32 Death By PowerPoint .................... ...................... 39(1),28 Educator For All Seasons, An.................................. 38(4),280 Effective, Efficient Professor, The........................... 36(2),114 FAQs. V. Designing Fair Tests................................. 36(3),204 FAQs. VI. Evaluating Teaching and Converting the M asses .......................................................... 37(2),106 Fond Farewell, A................................. .................. 39(4),279 How to Evaluate Teaching........................................38(3),200 How to Survive Engineering School......................... 37(1),30 How to Teach (Almost) Anybody (Almost) A anything ............................................................... 40(3)173 Incontrovertible Logic of the Academy, The.............. 37(3),220 Learning By Doing .................................................. 37(4),282 Screens Down, Everyone: Effective Uses of Portable Computers in Lecture Classes ............................ 39(3),200 So You Want to Win a CAREER Award.................... 36(1),32 Speaking of Education-III....................................... 36(4),282 Speaking of Everything-II.......................................... 39(2),93 The W ay to Bet .......................................................... 40(1),32 We Hold These Truths To Be Self-Evident.............. 38(2),114 W hat's in a N am e .................................................. 40(4),281 Whole New Mind For a Flat World, A ...................... 40(2),96 S Scaled Sketches for Visualizing Surface Tension............ 39(4),328 Scaling of Differential Equations: "Analysis of the Fourth K ind"................ .............................. ......... 36(3),232 Self-Similarity Transient Heat Transfer with Constant Flux, A Method for Determining............................... 39(1),42 Semiconductor Manufacturing, A Hands-On Laboratory in the Fundam entals of .............................................. 36(1),14 Semiphysical Modeling to ChE Students Using a 335 Brine-Water Mixing Tank Experiment, Teaching.......39(4),308 Sensitivity Analysis in ChE Education: Part 1. Intro. and Application to Explicit M odels................................ 37(3),111 Sensitivity Analysis in ChE Education: Part 2. Application to Implicit Models................................ 37(4),254 Sensitivity Analysis, Solvent Recovery by Condensation: An Application of Phase Equilibrium and................38(3),216 Separation Processes Course: Using Written-Answer Questions to Complement Numerical Problems ........ 36(2),130 Separation Processes, Using Visualization and Computation in the Analysis of ................................40(4),313 Senior Design Project That Integrates Laboratory Experiments and Computer Simulation, A Tire G asification.............................................................. 40(3),203 Sherry Solera: An Application of Partial Difference Equations, The ........................................................... 36(1),48 Similarity Solution, Computer-Facilitated Mathematical M ethods in ChE ....................................................... 40(4),307 Simple Classroom Demonstration of Natural Convection, A .......................................................... 39(2),138 Simple Open-Ended Vapor Diffusion Experiment, A...... 38(2),122 Simulation and Experiment in an Introductory Process Control Laboratory Experience............................... 37(4),306 Simulation: Student Engagement, Learning Through...... 39(4),288 Soft Matter, A Graduate Course on Multi-Scale M odeling of .............................................................. 38(4),242 Software Tools for ChE Education Students' Evaluations, U se of.................................................. 36(3),236 Solids Product Engineering Design Project, A............. 37(2),108 Solvent Recovery by Condensation: An Application of Phase Equilibrium and Sensitivity Analysis...........38(3),216 Sorption Separations, Using a Commercial Simulator to Teach .................................................................... 40(3),165 Splenda Sucralose Process, Heat Transfer Analysis and the Path Forward in a Student Project on the ............. 39(4),316 Spreadsheet Engineering, An Excel/VBA-Based Programming and Problem Solving Course: Com puter Science or ................................................ 39(2),142 Spreadsheet Solutions to Two-Dimensional Heat Transfer Problem s.................................................... 36(2),160 Spreadsheets, Teaching Process Control with a Numerical Approach Based on.................................................. 36(3),242 Spreadsheets and Visual Basic Applications as Teaching Aids for a Unit Ops Course, Using.......................... 37(4),316 Statistics, An Undergraduate Course in Applied Probability and......................................................... 36(2),170 Stochastic Modeling of Thermal Death Kinetics of a Cell Population Revisited........................................ 37(3),228 Stochastic Modeling, Using a Web Module to Teach...... 39(3),244 Stochastic Simulation of Chemical Reactions Using the Gillespie Algorithm and MATLAB, Introducing the.... 37(1),14 Student Motivation, Survivor Classroom: A Method of Active Learning That Addresses Four Types of ......... 39(3),228 Students, Teaching ChE to Business and Science............ 36(3),222 Students' Evaluations, Use of Software Tools for ChE E education ................................................................. 36(3),236 Successful "Introduction to ChE" First-Semester Course Focusing on Connection, Communication, and Preparation, A...................... ......................... 39(3),222 Summer School Course in Bioprocess Engineering Engaging the Imagination of Students Using Experiences Outside the Classroom, A................................... 37(3),180 Incorporating Experimental Design into the Unit Operations Laboratory........................................ 37(3),196 Incorporating High School Outreach into ChE C ourses ............................................................... 37(3), 184 Increasing Time Spent on Course Objectives by Using Computer Programming to Teach Numerical M ethods............................................ 37(3),214 Introduction to Biochemical Engineering: Synthesis, Resourcefulness, and Effective Communication in Group Learning.............................................. 37(3),174 Lab-Based Unit Operations in Microelectronics Processing........................................................... 37(3),188 Passing it On: A Laboratory Structure Encouraging Realistic Communication and Creative Experiment Planning.......................................... 37(3),202 Water Day: An Experiential Lecture for Fluid M echanics............................. ........................ 37(3),170 Survivor Classroom: A Method of Active Learning That Addresses Four Types of Student Motivation .... 39(3),228 Survey of the Graduate Thermodynamics Course in Chemical Engineering Departments Across the United States, A ......................... ........................ 39(4),258 I Tank Systems for Process Control Education, Experimental Air-Pressure......................................... 40(1),24 Teach Our Students to be Innovative? Can We............. 36(2),116 Teaching ChE to Business and Science Students............. 36(3),222 Teaching Coupled Transport and Rate Processes ............ 38(4),254 Teaching Electrolyte Thermodynamics .......................... 38(1),26 Teaching Engineering Courses with Workbooks............ 38(1),74 Teaching Entering Graduate Students the Role of Journal Articles in Research................................................. 40(4),246 Teaching Free Convection, a Computational Model for.. 38(4),272 Teaching a Graduate-Level Course in Tissue E ngineering............................................................... 39(4),272 Teaching and Mentoring Training Programs at Michigan State University: A Doctoral Student's Perspective............................................... 38(4),250 Teaching Nonideal Reactors with CFD Tools............... 38(2),154 Teaching Particle Technology, Novel Concepts for......... 36(4),272 Teaching Process Control with a Numerical Approach Based on Spreadsheets............................................. 36(3),242 Teaching Semiphysical Modeling to ChE Students Using a Brine-Water Mixing Tank Experiment..........39(4),308 Teaching Tips: Elevator Talks.............................................. 40(3) Teaching Tips............................................... 38(2),121 40(4),327 Teaching Turbulent Thermal Convection, A New A approach to .............................................................. 36(4),264 Technical Writing, Improving Coherence in................. 38(2),116 Technical Writing, Top Ten Ways to Improve ................ 38(1),54 Test Results for Assessment of Teaching and Learning, U sing .......................................................................... 36(3),188 Test Station and Laboratory Experiment, Pem Fuel-Cell 38(3),236 Thermal Convection, A New Approach to Teaching Chemical Engineering Education Turbulent......................................... ...................... 36(4),264 Thermal Death Kinetics of a Cell Population Revisited, Stochastic M odeling of........................................... 37(3),228 Thermal Radiation, Computer Evaluation of Exchange Factors ................................................ 38(2),126 Thermodynamic Concepts, Biomass as a Sustainable Energy Source: An Illustration of ChE.................... 40(4),259 Thermodynamic Properties Using the Redlich-Kwong Eq. of State, An Exercise for Practicing Programming in ChE Curriculum Calculation of ............................... 37(2),148 Thermodynamics Course in Chemical Engineering Departments Across the United States, A Survey of the G graduate ................................. .................... 39(4),258 Thermodynamics, Teaching Electrolyte .... .................. 38(1),26 Thermodynamics, Use of ConcepTests and Instant Feedback in..................................... ........................ 38(1),64 Thermophysical Properties, Choosing and Evaluating Equations of State for.............................................. 37(3),236 Tire Gasification Senior Design Project That Integrates Laboratory Experiments and Computer Sim ulation, A ........................................................... 40(3),203 Tissue Engineering, Teaching a Graduate-Level C ourse in ................................................................... 39(4 ),272 Tools for Teaching Gas Separation Using Polymers.......... 37(1 ),60 Top Ten Ways to Improve Technical Writing ................. 38(1 ),54 Transesterification of Yellow Grease, Plant Design Project: Biodiesel Production Using Acid-Catalyzed. 40(3),215 Transport Phenomena, An Easy Heat and Mass Transfer Experiment for ........................................ 36(1),56 Troubleshooting Skills in the Unit Operations Laboratory, Developing........................................... 36(2),122 Two-Dimensional Heat Transfer Problems, Spreadsheet Solutions to............................................. 36(2).160 uI Undergraduate Curriculum, Development of Cross- Disciplinary Projects in a ChE.............................. 38(4),296 Unit Ops Course, Using Spreadsheets and Visual Basic Applications as Teaching Aids for a.... ................. 37(4),316 Unit Operations Laboratory, A Holistic ......... ............ 36(2),150 Unit Operations Laboratory, A Kinetics Experiment for the................................... ................................. 39(3),238 Unit Operations Laboratory, A Virtual..... .................. 36(2),166 Unit Operations Laboratory, An Automated Distillation C olum n for the............................................................ 39(2),104 Unit Operations Laboratory, Developing Troubleshooting Skills in the....... ......................... 36(2),122 Unit Operations Laboratory, Incorporating Experimental D esign into the......................................................... 37(3),196 Unit Ops in Microelectronics Processing, Lab-Based.....37(3),188 Unit Ops Laboratory, Community-Based Presentations in the ........................................................................ 39 (2 ),160 UOP-Chulalongkorn University Industrial-University Joint Program ...................................... .................... 38(1),60 Use of ConcepTests and Instant Feedback in Therm odynam ics ....................................................... 38(1),64 Using a Commercial Simulator to Teach Sorption Separations................................................................ 40(3),165 Using a Web Module to Teach Stochastic Modeling.......39(3),244 Using Mathematica to Teach Process Units: A Fall 2006 D istillation Case Study ............................................ 39(2),116 Using Small Blocks of Time for Active Learning and Critical Thinking............................. ...............38(2),150 Using Spreadsheets and Visual Basic Applications as Teaching Aids for a Unit Ops Course...................... 37(4),316 Using Test Results for Assessment of Teaching and Learning ............................................................. 36(3),188 Using the Evolutionary Operation Method to Optimize Gas Absorber Operation: A Statistical Method for Process Improvement ............................................... 38(3),204 Using Visualization and Computation in the Analysis of Separation Processes ........................................... 40(4),313 Validating The Equilibrium Stage Model for an Azeotropic System in a Laboratorial Distillation C olum n ............................................... ..................... 40(3),195 Value of Good Recommendation Letters...................... 37(2),122 Vapor Diffusion Experiment, A Simple Open-Ended......38(2),122 VCM Process Design: An ABET 2000 Fully C om pliant Project................................................... 39(1),62 Virtual Laboratory, Web-Based VR-Form.................... 36(2),102 Virtual Unit Operations Laboratory, A.......................... 36(2),166 Viscosity Experiment for High School Science Classes, Demonstration and Assessment of a Simple............ 40(3),211 Visual Basic Applications as Teaching Aids for a Unit Ops Course, Using Spreadsheets and...................... 37(4),316 Visualizing Surface Tension.......................................... 39(4),328 Visualization Tools, Java-Based Heat Transfer............. 38(4),282 VLE Envelopes in Mathcad, Construction and V isualization of.......................................................... 37(1),20 Vulnerability Analysis, (BLEVE) Boiling-Liquid Expanding-Vapor Explosion: An Introduction to Consequence and ........................ ....................... 36(3),206 w Wastewater with an Electrochemical Method, Metal Recovery from ......................................................... 36(2),144 Water Day: An Experiential Lecture for Fluid Mech.......37(3),170 Web-Based Delivery of ChE Design Projects............... 39(3),194 Web-Based VR-Form Virtual Laboratory.......... ........ 36(2),102 Web Module to Teach Stochastic Modeling, Using a......39(3),244 Work, and Power, Energy Balances on the Human Body: A Hands-On Exploration of Heat .............................. 39(1),30 Writing with First-Year Engineering: An Unstable Solution, M ixing...................................................... 37(4),248 Written-Answer Questions to Complement Numerical Problems Case Study: A Separation Processes C ourse ................... ................................................ 36(2),130 Y Yellow Grease, Plant Design Project: Biodiesel Production Using Acid-Catalyzed Transesterification of ..................... ....................... 40(3),215 z Zeolites, Nanostructured Materials Synthesis of............... 38(1),34 Author Index A Abbas, Abderrahim .................. 36(3),236 Abraham, Martin A. ................. 34(2),272 Abu-Khalaf, Aziz M................. 36(2),122 Adhangale, Parag ..................... 37(2),156 Akers, William H. ..................... 39(4),316 Albarran, Carlos Ponce de Leon.... 39(1)14 Al-Bastaki, Nader .................... 36(3),236 Almeida, Paulo Ignacio F ........... 38(2),100 Alves, Manuel A. ...................... 38(2),154 Ang, Siong ............................... 36(3),182 April, G .C..................................... 38(1),8 Ang, Siong ............................... 38(3),174 Arce, Pedro E........................... 38(4),286 Armstrong, Robert C................ 40(2),104 Arnold, D.W ................................. 38(1),8 Ascanio, Gabriel ...................... 37(4),296 Assaf-Anid, Nada M.. 38(4),268;40(4),259 B Baber, Tylisha M...................... 38(4),250 Badino Jr., Alberto C................ 38(2),100 Balakotaiah, Vemuri................. 36(4),250 Balcarcel, R. Robert................... 37(1),24 Barna, Bruce A........................... 36(2),94 Barritt, Amber M...................... 39(4),296 Bayles, Taryn ................ 37(2),82;(3),184 Beene, Jason D......................... 38(2),136 Bennewitz, Marlene Roeckel von38(4),302 Benyahia, Farid.......................... 39(1),62 Bernardo, Fernando P.............. 39(2),116 Besser, Ronald S. ...................... 36(2),160 BeviA, Francisco Ruiz.............. 36(2),156 Bhatia, Surita R ........................ 36(4),310 Biernacki, Joseph J................... 39(3),186 Binous, Housam....................... 40(2),140 Birol, Gulnur............................ 37(4),300 Blau, Gary................................ 37(4),310 Blaylock, Wayne ...................... 38(2),122 Bonet, Josep............................. 36(2),150 Bowman, Christopher ................ 37(2),88 Bowman, Frank M ..................... 37(1),24 Braatz, Richard D........ 36(3),182;38(3)174 Brauner, Neima........................ 37(2),148 Brazel, C .S. ................................... 38(1),8 Brenner, James R. ........................ 40(1)60 Brent, Rebecca.......... 36(3),204;37(2),106; ......(4),282;38(3),200;39(1),28;(3),200; ............................... ......... 40(3),173; Briedis, Daina .......................... 38(4),250 Brown, Gary............................. 39(4),280 Bruce, David A............ 39(2),104;(3),238 Bullard, Lisa G......................... 39(3),194 Burkey, Daniel ......................... 39(3),183 Burmester, Jeffrey A. ................ 40(3),211 Burrows, Veronica.................... 38(2),132 Butler, Justin T. ......................... 39(2),104 C Caicedo, A. Argoti.................... 37(3),228 Carmona, Ximena Garcia............ 38(4),302 Carney, Michael ... ............... 36(2),18 Carter. Rufus ...... ................... 39(4),296 Case, Jennifer M ........ 36(1),42;39(4),288; ............................................... 4 0(4 ),29 1 Caspary, David W..................... 37(4),262 Castaldi, Marco J ..... 38(4),268;40(3),203; ................................................... (4 ),2 5 9 Cecchi, Joseph L ........... ........ 37(3),208 Center, Alfred M. ...................... 36(4),278 Chakraborty, Saikat.... 36(4),250;37(3),162 Chang, Chih-Hung ................... 37(3),188 Chang, Jane P. ........................... 36(1),14 Chauhan, Anuj.......................... 39(4),296 Chen, Bei.................................... 38(1),34 Chen, Wei-Yin................ 37(1),20;(3)228 Chen, Xiao Dong ......... 36(1),26;38(3),196 Chi, Yawu................................... 38(1),34 Chin, Der-Tau........................... 36(2),144 Chou, S.T .................................. 37(3),228 Choudhary, Devashish ............. 40(4),313 Chuang, Steven S.C. ................... 38(1),34 Churchill, Stuart W...... 36(2), 116;36(4),264 Cilliers, Jan .............................. 39(2),100 Qinar, A li.................................. 37(4),300 Ciric, Am y................................ 39(2),164 Cohen, Claude............................ 38(2),82 Coker, A. Kayode....................... 37(1 ),44 Coker, David T ........................... 37(1),60 Colina, Coray M......... 37(3),236;39(4),250 Colton, Clark K ........................ 39(3),232 Cooper, Douglas J .................... 37(2),100 Coronell, Dan........................... 39(2),142 Corti, David S. .......................... 37(4),290 Crittenden, Barry........................ 39(1),76 Crowe, Cameron M............ 36(1),48;(1),60 Cruz, Antonio J.G. .................... 38(2),100 Cussler, Edward L.................... 40(2),114 Cutlip, Michael B..................... 37(2),148 D da Silva, Dulce Cristina Martins. 40(3),195 Dahm, Kevin D ........... 36(3),192;(3)212; .........37(1),68;(2),132;38(1),68;(4),316 .......................... ................... 39 (2),94 Dale, Frances F......................... 40(3),211 Davis, Richard A............. 37(1),74;39(1)38 Demirel, Yasar............... 38(1),74;(4),254 Detamore, Michael................... 39(4),272 DiBiasio, David........................ 37(4),248 Dickson, James M...................... 36(1),60 Dickson, Jasper L....................... 37(1),20 Doherty, Mike .............38(4),308;40(2),116 Donoso, Carmen Gloria........... 38(4),302 Dorazio, Lucas ......................... 38(4),268 Doskocil, Eric J ........................ 37(3),196 Dougherty, Danielle ................. 37(2),100 Doyle III, Francis J. .................. 40(3),181 Dranoff, Joshua S..................... 36(3),216 Drwiega, Jack........................... 39(4),296 Duarte, Belmiro........................ 40(3),195 Dube, Sanjay K ........................ 39(4),258 Dueben, Rebecca...................... 39(4),280 Durand, Alain........................... 39(4),264 E Edgar, Thomas F. ..................... 40(3),231 England, Richard........................ 39(1),76 Erkey, Can.................................. 39(1),56 Erzen, Fetanet Ceylan.............. 37(4),300 Espino, Ramon L. ..................... 36(4),316 Evans, Geoffery M................... 38(3),190 F Fahidy, Thomas Z ....... 36(2),170;38(1),22 Falconer, John L......................... 38(1),64 Fan, L.T.................................... 40(2),132 Farrell, Stephanie.......... 36(2),108;(2),138; ..(3),198;37(1),52,68;38(2),108;(3),182 ................................................. 3 9 (1),30 Farriol, Xavier.......................... 36(2),150 Favre, Eric................................ 39(4),264 Felder, Richard M .......... 36(1),32;(2),114; ..........(3),204;(4),282;37(1),30;(2),106; ..........(3),220;(4),282;38(1),32;(2),114; .............(3),200;(4),280;39(1)28;(2),82; ............(3),200;(4),279;40(1),38;(2),96; ......................... (2),110;(3),173;(4)281 Fenton, James M ........................ 38(1),38 Fenton, Suzanne S...................... 38(1),38 Fernmindez-Torres, Maria J .......... 39(4)302 Ferri, James K .......................... 37(3),202 Fisher, David W ........................ 37(4),262 Fleming, Patrick J. .................... 36(2),166 Fletcher, Nathan W..................... 40(1),40 Floyd-Smith, Tamara M........... 40(3),211 Flynn, Ann Marie........... 39(3),216;(4),316 Fogler, H. Scott.......................... 40(2),99 Font, Josep ............................... 36(2),150 Ford, Laura P............................ 37(3),170 Forrester, Stephanie E .............. 38(3),190 Foutch, Gary L ......................... 37(2),122 Fowler, Michael ....................... 38(3),236 Franks, George V...................... 37(4),274 Franses, Elias I......................... 37(4),290 Fraser, Duncan M......... 36(1),42;39(4),288 Franzen, Stefan ........................ 38(4),242 Freeman, Benny D ..................... 37(1),60 Frey, Douglas ............................. 37(2),82 Friedly, John C. ........................... 38(1 ),54 Chemical Engineering Education G Gadewar, Sagar B. .................... 38(4),308 Gatzke, Edward P ...................... 40(1),24 Ghannam, Mamdouh................ 40(3),189 Glasser, Benjamin L................... 38(1),14 Glennon, Brian......................... 38(4),296 Gray, Jeffrey J. .......................... 40(4),297 Goldstein, Aaron S ................... 38(4),272 Goiter, Paul .............................. 39(4),280 GonzAilez-Fernmndez, Camino....... 37(1),14 Good, Theresa............................ 37(2),82 Gooding, Charles H. ...... 39(2),104;(2),128 Goodson, Mike......................... 39(3),232 Gorowara, Rajeev L................. 36(3),226 Gubbins, Keith E........ 37(3),236;38(4),242 ................................ ......... 39(4),250 Gupta, Santosh K ..................... 36(4),304 H Haji, Shaker................................ 39(1),56 Han, Sang M. .............................37(3),208 Hardin, Matt............................. 38(3),196 Harrison, Roger G.................... 40(4),323 Hart, John A. IV ......................... 37(1),20 Harvey, Roberta ....................... 38(4),316 H ayati, I.................................... 37(2),108 Hecht, Gregory B ..................... 38(2),108 Henda, Redhouane................... 38(2),126 Henderson, Tom....................... 39(4),280 Henson, Michael A................... 40(3),181 Hernandez, Rafael.................... 40(3),215 Hesketh, Robert P.......... 36(2),138;(3),192; .36(3),198;37(1),52:37(1),68;38(3),182 ..................... 38(1),48;39(1)30;(2),94 Hickner, Michael A .................... 36(2),94 Hill, Priscilla J.......................... 40(4),246 Hillier, James R........................ 36(4),304 Hile, Lloyd ............................... 38(2),121 Hinestroza, Juan P. ................... 37(4),316 Holland, Charles E ..................... 40(1),24 Hollar, Kathryn A..................... 38(2),108 Hounslow, M.J. ......................... 37(2),108 Howe-Grant, Mary E. ............... 38(3),168 Hrenya, Christine M................... 40(2),99 Huang, Yinlun............................ 39(1),48 Hubbe, Marty ........................... 39(2),146 Hudson, Mary Beth.................... 40(1),32 Hummel, Scott R........................ 37(1),38 Hung, Francisco....................... 38(4),242 I Ibrahim, Tableb H. ...................... 36(1),68 Iveson, Simon M........ 36(2),130;37(4),274 J Jacoby, William A .................... 37(2),136 Jeffreys, Trent........................... 40(3),215 Jennings, G. Kane ...................... 37(1),24 Jim6nez, Laureano ................... 36(2),150 Johnston, Barry S..................... 39(3),232 Jones, Paul................................ 40(3),211 Joo, Yong Lak .......................... 40(4),313 Joseph, Babu .............................. 36(1),20 K Kear, G areth............................... 39(1),14 Keffer, D .J................................ 37(2),156 Keith, Jason.............................. 38(4),282 Kentish, Sandra E..................... 40(4),275 Khilar, K .C............................... 36(4),292 Kim ura, Sho............................. 37(3),188 Koch, Margaret ........................ 36(4),304 Kolavennu, Panini K................ 40(3),239 Komives, Claire ........ ............ 38(3),212 Kopplin, Lisa L ........................ 36(4),304 Koretsky, Milo D. ..................... 37(3),188 Kourti, Theodora........................ 36(1),60 Kraft, Markus.............. 39(3),232;(3),244 Krantz, William B ...................... 38(2),94 Kuhnell, David R. ..................... 39(3),238 Kulprathipanja, Ann....................38(l),60 Kulprathipanja, Santi ................. 38(1),60 Kunz, H. Russell.........................38(1),38 Kwon, Kyung C ........... 36(1),68;40(3),211 L Labadie, Joseph A .......................36(1),76 Lacks, Daniel J......................... 36(3),242 LaClair, Darcy.......................... 37(3),180 Lam, Alfred .............................. 38(3),236 Lane, A .M .................................... 38(1),8 Law, Victor J. ............................ 39(2),160 Lawrence, Benjamin J............... 38(2)136 Lebduska, Lisa ......................... 37(4),248 Lee-Desautels, Rhonda .............. 40(1 ),32 Lee-Parsons, Carolyn W.T. ......... 39(3),208 Legros, Robert.......................... 37(4),296 LeVan, M. Douglas ...................... 37(1 ),2 Lewis, Randy S............ 38(2),136;40(1),66 Li, Grace X.M.......................... 38(3),196 Lin, Jung-Chou .......................... 38(1),38 Linder, Cedric .......................... 39(4),288 Lipscomb, G. Glenn....... 36(2),82;37(1),46 Liu, X ue ..................................... 38(1),14 Lobban, Lance L ...................... 38(3),162 Lombardo, Stephen J. ............... 38(2),150 Long, Christopher E................... 40(1),24 Loney, Norman W .................... 37(2),126 Lou, Helen H...............................39(1),48 Luks, Kraemer D........................ 36(1),76 Luyben, William L..... 38(2),142;39(3),202 M Maase, Eric L ........................... 40(4),283 Macedo, Eugenia A.................... 38(1),26 Machniewski, Piotr M.............. 38(3),190 Madiera, Luis M............. 38(2),154;(3),228 Madihally, Sundararajan............ 38(2),136; .................................... 40(1),66;(4),283 Magalhaes, Fernao D... 38(3),228;40(1),46 Malone, Mike........................... 38(4),308 Marchal-Heussler, Laurent.......... 39(4),264 Mardones, Olga Mora.............. 38(4),302 Mar Olaya, Maria del............... 36(2),156 Marten, Mark ............................. 37(2),82 Martinez-Urreaga, Joaqufn ........... 37(1),14 Marwaha, Anirudha.................. 40(3),215 Mason, Sarah L ........................ 39(4),328 May, Nicole.............................. 40(4),259 Mazyck, David......................... 39(4),296 Mazzotti, Marco....................... 40(3),175 McCarthy, Joseph J .................. 38(4),292 McCullough Roy L .................. 36(3),226 McDonald, Christopher I ........... 39(3),238 McNeil, Melanie A..... 38(3),212;39(2),134 McNeill, Vivian Faye............... 39(3),232 Mendes, Ad6lio M.................... 38(3),228 Mendes, Joaquim G. ................... 40(1),46 Miaoliang, Zhu......................... 36(2),102 Michaud, Dennis J. ................... 36(3),226 Midoux, Noel........................... 39(4),264 M ira, Jose................................... 37(1),14 Misovich, Michael J................. 36(4),284 Missen, Ronald W.......... 37(3),222;(4),254 .................. .......................... 3 8 (3 ),2 16 Mitchell, Brian S...................... 39(2),160 Moghe, Prabhas V. ................... 40(4),251 Mohan, Marguerite A............... 40(4),259 Monroe, Charles......................... 39(1),42 Moor, S. Scott .......................... 36(1),54; ................................... 37(1),38; (3),202 Moreira, Antonio........................ 37(2),82 Morrison, Faith ......................... 39(2)110 Mosbach, Sebastian.................. 39(3),244 Moshfeghian, Aliakbar............... 40(1),66 Mosto, Patricia......................... 38(2),108 Moura, Maria Jose ................... 40(3),195 Muske, Kenneth R .... .37(4),306;40(3),225 N Naraghi, Mohammad H ........... 39(3),216 Newman, John............................ 39(1),42 Newell, Heidi L............ 36(3),212;38(1),68 .................... .......... .................. (4 ),3 16 Newell, James A............ 36(2),108;(3),212; ....................38(1),68;(4),316;39(3),228 Newman, Austin....................... 37(2),156 Niehues, Patricia K. .................. 39(3),194 Ng, Ka M ................................. 36(3),222 Nguyen, Anh V......................... 38(3),190 Nollert, Matthias U...... 36(1),56;40(4),323 o O'Connor, Kim ........................ 39(2),124 O'Donnell, Brendan R ............... 36(2),94 Fall 2006 Oerther, Daniel B ..................... 36(4),258 Oh, Dong Hee (Lindsey)............. 39(4),316 Olivera-Fuentes, Claudio G ....... 39(4),250 O'Rear, Edgar A....................... 38(3),162 Ortiz. Elizabeth Parra............... 38(4),302 Ostafin, Agnes E....................... 37(3),180 P Palanki, Srinivas ...................... 40(3),239 Panjapornpon, Chanin................ 40(1),40 Papadopoulos, Kyriakos .. 36(2),88;(4),316 Park, YoonKook......................... 36(1),68 Parker, Robert S......... 38(4),292;40(3),181 Parulekar, Satish J........ 38(4),262;40(1),14 Patel, Dhermesh V.................... 37(2),108 Paulaitis, Michael E ................. 36(2),166 Payne, Gregory ......................... 37(2),82 Pedrosa, Cristiana ..................... 40(1),46 Peeples, Tonya L. ..................... 37(3),174 Pena, J.A .................................. 36(3),206 Peretti, Steven W. .................... 39(3),194 Perkins, Douglas M.................. 39(2),104 Peukert, Wolfgang.................... 36(4),272 Pierson, Hazel M...................... 39(2),156 Piluso, Christina......................... 39(1),48 Pinheiro, Maria Nazare Coelho... 40(3),195 Pinho, Simao P. ......................... 38(1),26 Pitt, Martin J ..................... 37(2),108,154 Plouffe, P.B. ............................... 37(3),162 Prabhakar, Rajeev ...................... 37(1),60 Price, Douglas M. ..................... 39(2),156 R Rao, Govind............................... 37(2),82 Rasteiro, Maria G...................... 39(2)116 Rech, Sabine ........... 38(3),212;39(2),134 Reijenga, Jetse C. .................... 37(2),114 Reilly, Peter J ....................... 36(3),178 Rhodes, Martin......................... 36(4),288 Rice, Robert ............................ 37(2),100 Rice, Richard W. ..................... 39(3),238 Rivera, Daniel E........................ 39(4)302 Rives, Christopher.................... 36(3),242 Roberts, Susan.......................... 39(3),222 Robinson, Janet E..................... 37(2),154 Robinson, Ken K...................... 36(3),216 Rochefort, Skip ....................... 37(3),188 Rockstraw, David A. .................. 39(1),68 Rodrigues, Alfrio .... ............ 38(2),154 Rogers, Bridget R....... ......... 37(1),24 Roizard, Christine .................... 39(4),264 Rojas, Orlando ........................ 39(2),146 Rollins Sr., Derrick K.............. 40(4),291 Ross, Julia M................. 37(2),82;(3),184 Roth, Charles M....................... 40(4),251 Ruiz, Joaquin.............................. 39(1),22 Rusli, Effendi..... 38(3)174 Russell, John J. 37(3),208 Russum, James P. .................... 36(2),134 s Saddawi, Salma.......................... 36(1),34 Saliklis, Edmond P. ................... 37(1),38 Salman, Agba D. ....................... 37(2),108 Sandall, Orville C....................... 37(1),74 Santoro, Marina....................... 40(3),175 Saraiva, Pedro M...................... 39(2)116 Sauer, Sharon G. ....................... 38(3),222 Savage, Phillip E. ....................... 37(2),94 Savelski, Mariano J.......36(2),108;(3),192; ....37(1),68;38(3),182;39(1)30;39(2),94 Sayari, Abdelhamid.................... 38(1),34 Scarbrough, Will J.................... 40(4),291 Schmedlen, Rachael................. 39(4),272 Schmid, Hans-Joachim ............ 36(4),272 Schmidt, Hartley T. .................. 37(3),180 Schmidtke, David W. ............... 40(4),323 Schmitz, Roger A............. 36(1),34;(4),296 Schowalter, W.R....................... 37(4),242 Schreiber, Loren B ................... 38(4),286 Schulp, John R. ........................ 40(2),132 Schultz, Jerome........................ 40(2),126 Scuderi, Phillip......................... 39(4),280 Selmer, Anders......................... 39(3),232 Sen, Siddhartha........................ 39(3),232 Shacham, Mordechai................ 37(2),148 Shaefer, Stacey......................... 39(3),216 Shaeiwitz, Joseph A. .................. 40(2),88 Shallcross, David C.... 37(4),268;40(4),275 Shambaugh, Robert L ............... 38(3)162 Shaner, Cyndie ......................... 37(3),188 Shanley, Ed S. ........................... 38(3),188 Sheardown, Heather................... 36(1),60 Shonnard, David R................... 37(4),262 Shulman, Stacey................... 37(3),162 Sides, Paul J. ............................. 36(3),232 Siepe, Hendry........................... 37(2),114 Sikavitsas, Vassilios I. .............. 40(4),323 Silverstein, David L. ................ 37(3),214 Simmons, Christy M. ................. 36(1),68 Simon, Laurent......................... 37(2),126 Sin, Aaron ................................ 36(4),278 Slater, C. Stewart .......... 36(2),138;37(1),8; ............................ 37(1),52,68;38(1),48 Sloan, Dendy........................... 38(3),203 Smart, Jimmy L.......... 37(2),142;38(3),204 Smith, William R. .......... 37(3),222;(4),254 Soroush, Masoud........................ 40(1),40 Sotudeh-Gharebaagh, Rahmat .... 36(2),100 Sousa, Jos6 M........................... 38(3),228 Spencer, Jordan L.... ............ 40(3),159 Srinivasagupta, Deepak.............. 36(1),20 Stoynova, Ludmila................... 39(2),134 Streicher, Samantha ................. 39(4),288 Subramanian, Venkat R............ 40(4),307 Sureshkumar, G.K.......36(4),292;38(2),116 Svrcek, William.......................... 40(1),54 T Tanguy, Philippe A..................... 37(4),296 T llez, C .................................... 36(3),206 Telotte, John C. ......................... 40(3),239 Thomas, Mathew...................... 40(3),215 Thomson, William J. .............. 39(4),280 Ting, Dale............................... 36(4),304 Tomas, Christopher.................. 36(3),216 Tummala, Seshu....................... 36(3),216 Turton, Richard.......................... 40(2),88 II Uygun, Korkut ........................... 39(1),48 Y van der Lee, James..................... 40(1),54 Vahdat, N ader.............................. 40(3),211 Van Wie, Bernie ....................... 39(4),280 Varma, Arvind .......................... 37(4),284 Visco Jr., Donald P..... 36(2),134;39(4),258 w Wagner, Wolfgang.................... 39(3),244 Walsh, Frank .............................. 39(1),14 Wang, Chi-Hwa........................ 37(2),114 Wankat, Phillip.....37(4),310;38(1),2;40(3); ............. .... .............. ........ 40 (3),165 ; Weiss, Alvin H .......................... 36(1),74 Weiss, Brian............................. 40(3),203 West, Kate............................... 39(4),288 Wheeler, Dean R. .................... 39(2),138 Wheelock, Thomas D............. 36(3),178 White, Shannon H. ................... 39(3),194 Whitmire, David ...................... 38(2),122 W iest, J.M ................................... 38(1),8 Wilcox, Jennifer....................... 40(4),268 Wilkens, Bob........................... 39(2),164 Willey, Ronald............ 38(3),188;39(3),183 Winter, H. Henning.................. 36(3),188 Wood, Philip E.......................... 36(1),60 Woods, Donald R. .......... 36(1),60;40(2) Worden, R. Mark...................... 38(4),250 Wright, Pamela ....................... 38(1),14 Y Yabo, Dong ............................. 36(2),102 Ying, Chao-Ming ....................... 36(1),20 Young, Brent .............................. 40(1),54 Young, Ralph ............................. 40(1),32 z Zhang, Tengyan........................ 40(2),132 Zheng, Haishan ........................ 38(4),282 Zydney, Andrew L. ..................... 37(1),33 Zygourakis, Kyriacos................. 38(2),88 Chemical Engineering Education CEE's Annual Fall Graduate School Information Section Published in February, May, August, and November of each year for the past 40 years, Chemical Engineering Education (CEE) is the premier archival journal for chemical engineering educators. 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Riverside: University of .......................................... 352 California, Santa Barbara; University of .................................. 353 California Institute of Technology................... ...................... 354 Carnegie-Mellon University......................... ...................... 355 Case Western Reserve University............................................. 356 City College of New York........................... ....................... 357 Cleveland State University.......................... ....................... 438 Colorado School of M ines............................ ...................... 358 Colorado State University ............................ ...................... 359 Columbia University ............. .......................................... 432 Cornell University ............. ............................................. 360 Dartmouth College ................... ............................................ 361 Delaware, University of ............................... ...................... 362 Denmark, Technical University of ........................ ................. 363 Drexel University ............. ............................................. 364 Florida, University of ........................................ ...................... 365 Florida Institute of Technology ..................... ...................... 366 Georgia Institute of Technology ..................... ........................ 367 Houston, University of ................................. ...................... 368 Illinois, Chicago; University of ................................................. 369 Illinois. Urbana-Champaign, University of.............................. 370 Illinois Institute of Technology................................................. 371 Iowa, University of........................................................... 372 Iowa State University ....... ........................ ........................ 373 Kansas, University of ................... ......................................... 374 Kansas State University................................ ....................... 375 Kentucky, University of...................................... ................... 376 Lamar University............ ............................................. 433 Laval University ............... .............................................. 377 Lehigh University................... .............................................. 378 Louisiana State University .......................... ...................... 379 M aine, University of.............. .......................................... 380 M anhattan College.............................................. ................... 381 Maryland, Baltimore County; University of ............................. 382 Massachusetts, Amherst: University of .................................... 383 Massachusetts, Lowell; University of ....................................... 438 M assachusetts Institute of Technology..................................... 384 McGill University............ ............................................. 385 McMaster University............................... ........................ 386 M ichigan, University of..................................... ...................... 387 M innesota, University of ............................. ....................... 388 M issouri, Columbia; University of........................................... 389 M issouri, Rolla: U university of...................... ........................ 390 M onash University ............. .............................................. 433 Montana, University of................................ ....................... 434 New M exico, University of ......................... ....................... 391 New Mexico State University ...................... ...................... 392 North Carolina State University.................... .......................393 North Dakota, University of ......................... .......................434 Northeastern University.......................................................... 394 Northwestern University ............................. ....................... 395 Notre Dame, University of ......................... ........................ 396 Ohio State University ...................................................... 397 O klahom a, U university of .......................................................... 398 Oklahom a State U university .......................... ....................... 399 Pennsylvania State University.................... ........................ 400 Polytechnic U university ...................................... .................... 40 1 Princeton University................... .......................................... 402 Purdue U niversity................... ............................................. 403 Rensselaer Polytechnic Institute............................................ 404 Rice U niversity................... ................................................ 405 R ochester, U university of ........................................................... 406 Rose-Hulman Institute of Technology...................................... 435 Row an U university ................... .............................................. 407 Ryerson University .................................... ....................... 435 Singapore. National University of..........................................408 Singapore-MIT Alliance Graduate Fellowship .........................409 South Carolina. University of........................ ...................... 410 South Florida. University of......................... ...................... 436 Southern California, University of ........................................... 411 State University of New York....................... ...................... 412 Stevens Institute .................. ........................... 413 Tennessee, University of ........................................................414 Tennessee Technological University .........................................415 Texas at Austin. University of ..................... ........................ 416 Texas A&M University ............................... 417 Texas A&M Kingsville....................................... ...................... 436 Texas Tech University ........................................................418 Toledo, U university of.................................. ........................ 419 Tufts U niversity................... .............................................. 420 Tulane University ............. ............................................. 421 Tulsa, U university of................... ............................................ 422 Vanderbilt University................................... ...................... 423 Villanova U niversity....................... ........................................... 437 Virginia, University of........................... .... ....................... 424 V irginia Tech ................... .................................................. 425 W ashington, University of .......................... ........................ 426 W ashington State University ....................... ........................ 427 Washington University ...................................... .......................428 Waterloo, University of ......................................................... 437 West Virginia University .............................. .......................429 Wisconsin, University of........................................................ 430 Wyoming, University of ............................. .........................438 Yale University ........... ............................................... 431 Chemical Engineering Education Full Text xml version 1.0 encoding UTF-8 REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd INGEST IEID E534FYI6A_HWSKKV INGEST_TIME 2011-07-12T00:08:01Z PACKAGE AA00000383_00168 AGREEMENT_INFO ACCOUNT UF PROJECT UFDC FILES PAGE 1 s:: -~ !;:I \,) l:l.() s ... 'll 'll s:: ... ... .Q 'll ... \,) 0 s:: !;:I \,) i:: t 'll E 'll -si: 'll s:: s::" .. .;: "' ... .... ;:.. ... !;:I Cl -~ E 'll i:: -=: 'll I,,) 'll "c, s:: ... j .... !;:I "' -~ E s:: 'll !;:I -=: -~ I,,) ... 'll E -si: chemical engineering education VOLUME40 NUMBER4 FALL2006 GRADUATE EDUCATION ISSUE Fea tu r i ng articles on graduate c ourse s Teaching Entering Grad u ate Students the Role of Journal Articles in Research (p. 246) Hill Biomass as a Sustainable Energy Source: an Illustration of ChE Thermody n amic Concepts (p. 259) Mohan Ma y, Assaf-Anid Castaldi Multidisciplinary Graduate Curriculum on Integrative Biointerfacial Engineering (p 251) Moghe Roth Incorporating Com pu tational Chemistry into the ChE Curriculum (p. 268) Wilcox 5 Yearlndex 2002-2006 Page 328 .. and articles Qjgeneral interest. Random Thoughts: What s in a Name? (p 281) . . ...... .. ........ .. .. .... ... Fe l der Biomolecular Modeling in a Process Dynamics and Control Course (p 297) ... .. .. ............ ... Gray Research Proposal in Biochem. and Biolog Engineering (p 323) ..... Harrison, Nollert, Schmidtke Sikavitsas Using Visualization and Computation in t h e Analysis of Separation Processes (p. 313) ... .... Joo Choudhary An International Comparison of Final-Year Design Project Curricula (p 275) . .. ... Kentish, Shallcross Biomedica l and Biochemical Engineeri n g for K-12 students (p 283) .................... Madihally Maase Pressure For Fun : IncreasingStudents'Excitement and Interest in Mechanical Parts (p 291) ... Scarbrough, Case Computer-Facilitated Mat h ematical Methods in ChE Similarity Solution (p. 307) .... .. ........ Subraman i an PAGE 3 EDITORIAL AND BUSINESS ADDRESS: Ch e mi c al Engi11 e erin g E ducation Department of Chemical E ngineering University of Florida Gaine s ville FL 3 2611 PHO N E and F A X: 3 52 -39 2 -0 8 61 email: cee@c h e. 11jl .e du EDITOR Tim And e r s on ASSOCIATE EDITOR Phillip C. Wankat MANAGING EDITOR Lynn Heasle y PROBLEM EDITOR James 0. Wilkes U. Mic hi gan LEARNING IN INDUSTRY EDITOR William J. Koros G eo r gia I nsti t ute of Techno l ogy EDITORIAL ASSISTANT N i c h o l as R os ini a PUBLICATIONS BOARD CHAIRMA E D e nd y S loa11 J r. Colorado School of Min es VICE CHAIRMAN John P. O Conn e ll Univers i ty of Virginia MEMBERS Kristi An s eth U n ive r sity of Colorado Pablo Debe11edetti P rinceton U n iversit y Diann e Dorland R owan University Thoma s F Edgar U n ivers i ty of T exas at Aust i n Richard M. Feld e r North Carolina State University Bruc e A. Finla ys on University of Washington H Scott Fogler U n ive r sity of M ic h igan Carol K. Hall North Caroli n a Stat e University William J Koro s Georgia I nstitute of T ec hnolog y St e v e L e Bla11c U n iversity of To l edo Ro11ald W. Rousseau Georgia I ns tit u t e of Techno l ogy Sta11l ey /. Sandler University of Delawar e C St e wart Slater R owan University Donald R Woods McMaste r Un i versity S umm e r 2006 Chemical Engineering Education Volume 40 Number 4 Fall 2006 GRADUATE EDUC A TIO N 246 T eac hin g E n tering Grad u ate Stude n ts t he R o l e of Jou rn a l A r t i c l es in R esearch Pr iscilla J. H i ll 251 Multidi sc i p lin a r y G ra du a t e C urri cu lum o n Int egra ti ve Bi o int e r fac i a l E n gi n ee rin g P rab h as V. Moghe and Char l es M. R oth 259 B io m ass as a Sus t a in a bl e E n ergy So u rce: a n Illu s t rat i o n of C h E Th ermodynamic Co n cepts Ma r gue ri te A. Mo h an N i co l e May, Nada M. Assaf A11id, Marco J Casraldi 268 In co rp ora t i n g Com pu ta ti o n a l C h emis tr y int o th e C h E C urri c ulu m J ennifer Wi l cox CLASSROOM 291 Pr ess ur e Fo r F un : A Co ur se M o dul e fo r In creas in g C h E St ud e nt s'Exc it e m e nt a nd Int e r es t in Mec h a ni ca l P ar t s Wi ll J. Scarbrough, J ennifer M. Case 323 Th e R esearc h Proposa l i n B ioc h emical a n d B i o l og i ca l E n g in eeri n g Courses R oger G. H arrison, Matth i as U. Nollert, Da v id W Schmid t ke Vass i/i os I Sikavirsas RA N DOM THO U GHTS 281 Wh a t 's i n a Name? R ichard M. F e lder OUTREACH 283 Bi omed i ca l and Bi oc h em i ca l E n g in eer in g fo r K-1 2 st u de nt s Sunda r arajan V. Madihall y, Eri c L. Maas e CURRICUL U M 275 A n Int e rn a ti o n a l Com p ariso n of Fi n al -Y ear D es i g n Pro j ec t C urri c ul a Sa n dra K entish, D avid C. S h a ll cross 297 Bi o m o l ec ul ar M o d e lin g in a P rocess D y n a mi cs a nd Co nt ro l Co ur se J effrey J Gray 313 Usi n g V i s u a li za ti o n a nd Comp ut a ti o n in th e A n a l ys i s of S e p ara ti o n Pro cesses Y o n g Lak J oo, D evas hi s h C h oud h a r y CLASS AND HOME PROBLEMS 307 Comp ut er-Facil i tated Ma th ema ti ca l Me th ods i n C h E: S i m il ar it y So luti o n Venkar R Subramanian 327 Teaching Tip 328 5Year Index: 2002-2006 C H EM I CA L ENG I NEE RI NG EDUCAT IO N ( I SSN 0009-2479 ) is p u b li s h ed q u arte rl y by th e C h e m ica l E 11 g i11 ee ri11 g D iv i sio 11 ,A m e r ica11 Society/o r ,r gi 11 ee r fog Educatio11,a11d i s edite d at t h e U 11 ive r si 1 y of F l o r ida. Co r res p o 11 de 11 ce r eg ardi11 g e d i t o ri a l m atte r ci r culatio n and c h a n ges of ad dr ess s h o uld be se 11 I to CE C h e mi ca l 11 gi 11 eeri 11 g D e p art m e nt U n ive r si t y of F l o ri da Ga in esvi ll e, FL 326 116005. Copy ri g h t 2005 by th e C h e mi ca l 11 gi 11 eer i11 g Di v i sio n A m e ri c an Socie t y for 11 gi 11 ee riu g E du c a tio n Th e sta t e m e nt s a ,i d opi n io n s expresse d ; ,, th is pe r iod i ca l are th ose of th e w rit e r s a nd 11 o t 11 eces;1 aril y t h ose of th e C h D i visio 11 ,ASEE, w h ic h body assu m es 110 r es p o n s i b il ity fo r t h e m Def ee l hie copies re pla ce d if n o tifi e d w ithin 1 20 days of pub l ica ti o 11 Wri t efo r i 11 fo rm atio n 0 11 subscriptio n cos t s a 11 dfo r back copy cos t s a n d ava il ab ilit y. P OSTMASTE R : Send ad dr ess c h a n ges to C h e mi ca l 11 gi 11 ee r i 11 g Educatio n C h e m ica l E 11 gi 11 ee ri11 g De p art m e n t., U 11i vers i ly o f Fl o rid a Ga in esv ill e, FL 3261 160 0 5. P e r iodic al s Pos t age P aid a t Gai n esv ill e, Flo ri da a n d addil i o 11 al p os t offices (US P S 1 0 1 90 0 ). 245 PAGE 4 ( Graduate Education ) Teaching Entering Graduate Students THE ROLE OF JOURNAL ARTICLES IN RESEARCH PRISCILLA J. HILL Mississippi State University Mississippi State, MS 39762 S tudents entering graduate school have a variety of backgrounds. While some have actively participated in research as an undergraduate, many have no research experience at all. A lth ough they may have read assigned technical articles, few are in the habit of searching journal articles for information or reading articles critically. These sk ill s, however are essential to being s uccessful as a gradu ate student. Lilja r 1 1 states that good researchers must perform literature searc hes to determine what is already known and to avoid repeating existing work. Included in thi s approach is the need to develop skills to critically evaluate research articles Lilja further states that these are s kills that must be taught. Alt h ough technical articles have long been used in graduate courses to convey technical information they aren't always used to develop critica l-thinkin g and technical-writing ski ll s. To develop critical-thinking skills, severa l educators have required students to summarize the main points of journal ar ticle s, and critically evaluate the research. 1 1 41 Others have required undergraduate st ud ents to list the sections of a journal article to develop technical writing skills_r si A similar view is taken at Michigan Technological Uni versity, where chemical engineering graduate students are required to take a course entitled, "Theory and Methods of Research. "[ 6 1 The purpose of this course is to provide formal training in skills that students need to be successful in grad u a te school. This includes a wide range of subjects from how to present professionally to guidelines on research notebooks. One major goal of the course is to improve paper writing, taught through lectures on the subject and writing assign ments. These lectures discuss the purpose of journal articles, types of journal articles, and the journal submission process. Later in the semester, students are required to review a journal article of their choice and present their critique. One chemica l engineering textbook on reaction engineering includes journal article critiques" 171 as exercises at the end of selected chapters. These exercises use chapter concepts to test claims made in selected papers. Each exercise presents the point being questioned and gives hints on h ow to test the claim. The goal of these exercises is to teach students how to critically eva luat e what they read. Priscilla J Hill is currently an assistant professor at Mississippi State Univer sity. H er research interests include solids processing, crystallization, and particle technology She received her B S and M S degrees from Clemson University and her Ph.D degree from the University of Massachusetts at Amherst. She has taught design and thermodynamics courses at the undergraduate level and a graduate course on thermodynamics Copy ri gh t ChE Di vis i on of ASEE 2006 246 Chem i c a/ Engin ee ring Education PAGE 5 C At the U niv ersity of Michigan student s in the graduate chemical reaction engineering course are required to ana l yze a nd cr itiqu e a related journal article. 181 Thi s co n s i sts of a de tailed analysis in which students are encouraged to critically eva luate the assumptions methods and conclusions in the a rticle. They are asked to determine if there is another ex planation for the paper s r es ult s The stude nt s are also give n eva luation g uid eli ne s u sed by reviewers of AJChE Journal and Transactions of the In stitution o f Chemi c al En g ine e rs At the University of Massachusetts in Amherst, st ud ents in a graduate-level The Graduate Education ) articles and be prepared to discuss each paper. An in-class discu ss ion session of approximately 15 minutes is set aside for each paper. The in s tructor moderates the discussion a nd asks que s tion s to encourage cla s s participation. This participa tion includes a discussion of the paper' s technical points and other issues s u ch as the type of paper. The class discussion meth od i s c ho sen because it e ncoura ges active participation and research has shown that teaching is more effective when active l earning is involved. 1 1 0 11 1 Thi s approach wa s implemented in a graduate-level thermodynamics co ur se at Mississippi State University. The grad u ate c hemical engineering kinetics class 191 were required to present or discuss as s igned technical articles in class On the day of presentation a st ud e nt was se lected at random to s umm arize the key point s of the paper, w hil e the other stude nt s joined the discussion. At the beginning of the seme s ter s tudents were given guidelines a s to what ques tions th ey s hould ask about each article they read. class discussion method is chosen thermodynamics class was chosen because it is o n e of the core co ur ses entering stude nt s take during the first semes ter. During the fa ll semes t ers of 2003 and 2004, there were 10 a nd 12 students, respectively. Generally, graduate classes are sma ll enoug h to a ll ow a ll student s to participate in the discus s ion. because it encourages active participation and research has shown that teaching Although all papers assigned relate to ther modynamics, they are a l so c ho se n to provide students w ith a samp l e of various types of papers and journals. For exam ple the pap ers assigned for the fa ll 2004 semester are given in References 12 21 They ranged from tra ditional papers on fundamental concepts to paper s on recent developments While m ost The goa l is to teach e nt er in g graduate st udent s the role of journal articles in research. This includes teaching students to search journal artic l es when looking for information to cr iti cally eva lu ate journal articles to summarize the key is more effective when active learning is involved. 10 111 points of an article, and to evaluate the app licabilit y of the research These methods are implemented by classroom discussion of technical art icl es. INSTRUCTIONAL OBJECTIVES The objective of journal-related instruction is to better prepare students for research. Meeting thi s objective con s ists of two parts: I ) Giving studenrs a b e tt e r und e rstandin g o f th e r o l e o f te c hni c al article s in r esea r c h 2) Intr oducing students ro th e pap e r submission and r e v i ew pro ce ss Although students will l earn this information during their research projects, it is often helpful for students to hear this in formation from two different s ources. In addition it begins the transition from an und ergraduate student to a researcher of the papers were published within the l ast five year s, one 1 13 1 wa s published in 1914 and another 1181 in 1958 Since most e nterin g grad uat e st ud e nt s are unsur e what to lo ok for whe n reading a paper they are instructed to add r ess the following items. 0 Fundam e ntal i s su e a ddr esse d : What c on ce rn s ar e th e auth o r s addr ess in g ? What p ro bl e m is b e in g so l ve d ? 0 Moti v ati o n p e r s p ec ti ve: Wh y ar e th e author s wr itin g thi s pap e r ? H ow do e s this pap e r fit into oth e r work in th e area ? Is th e r e a n ee d f o r this r e search ? I s th e r e s e arch no ve l ? 0 Main id e as: What ar e th e k ey points ? What ar e the a s sumptions m e thods used limitations and app li c ti o n s? F o r ex ampl e, i s th e wo rk limit e d to a ce rtain pr ess ur e ran ge o r a ce rtain cl a ss of c omp o und s? 0 R e lati o n to co ur se : H ow d oes thi s pap e r fit int o th e IMPLEMENTATION co ur se? T h roughout the semes t er, IO papers are distributed to the c la ss for re a din g At the beginning of the se m es t e r the class is told that they are expected to read th e ass i g ned t ech ni ca l Fa/12006 The discussion is co nduct ed in a manner to elicit volunteer re spo n ses. Since part of the grade depends on di scuss ion a record is kept of parti cipatio n Th e discussion is lar ge l y g uid ed 24 7 PAGE 6 ( Graduate Education ) TABLE 1 Importance of Reading Technical Articles Question I 2 1. What sources do you u se books mainly for technical information? o nl y books 2. What so ur ces do yo u books mainly u se for gjfilD_t technical only books information ? 3. Rank the imp orta nc e of not s li g htl y readin g technical artic le s necesuseful for conducting research. sary by the questions given above The purpose of the assignment is to give students practice reading technical articles, particularly to aid students in developing the ability to understand the main points in technical articles outside their research area. CL ASS DISCUSSIONS At the beginning of the semester, the instructor explains that gra duate students should become more familiar with journal articles. Students usually agree that their undergraduate work relied heavily on textbooks and handbooks and rarely in volved searching journal articles for information The purpose of the explanation is to help students understand the reason for reading assignment s To aid students in understanding the role of technical papers, many concepts can be discu sse d in addition to the items given in the student guidelines. Topics discussed in class include the following 248 0 It is emphasi ze d that the purpos e of journal articles is to disseminate r esearc h r esu lt s in a timely manner, t o bring attention to r esearc h need s, or to enco urage research in certa in a reas. Th e paper on app l y in g thermodynamics to biotechnology 1171 is used to demon strate the last two items. 0 Dis cussion of j ourna l types includes journals w ritt en for various audiences. Class exam pl es includ e scien tific p er iodi ca ls such as Scientific American 1161 for th e scientific la yman, Chemical Engineering Progress for the practicing c h emica l e n gi neer, and o th er journals, e.g Chemical Engineering Science ,' 12 15 211 Indu s trial and Engineering Chemistry ,' 181 and Industri a l a nd Engineering Chemistry Research 1201 for researchers. Oth e r examples include disciplinary journals suc h as Chemical Engineering Sciencefl 2 15 21 1 and Pure and Applied Chemistry 1171 for c hemical eng in eers a nd c h e mist s, r espective l y. Further examp l es such as Fluid Phase Equilibria ,' 14 191 demonstrate journals that are highly speciali ze d. 3 4 5 Initial Final Survey Survey book s mainly articles 2 92 3.20 and articles only art icl es book s mainly articles 3.83 4.3 and articles o nl y articles u se ful ve r y crucial 4 75 4.8 useful 0 Th e stude nts are told that r ese ar c h articles can b e ca tegori ze d as theoretical co mputational, exper im e tal, o r as a comb inat ion of these types. On e paper i s included to show how exper im enta l papers may present new techniques or devi ces-'2 11 Discussion also mentions othe r ty p es of articles, such as published pl e n ary l ec tur es and review a rticl es. Also discussed is ho w a rticl es are categorized b y l ength as l ette r s o r full research articl es 0 Class r oom discussion on article structu r e emphasizes th e purpose of each section in th e paper, showing how sections of a paper vary depending on article type. 0 The students are told that a lth o u gh acceptance crite ria varies among journals th ey s h a r e many common criteria, including determining whet h er a paper is ap pr op riat e for the j ou rn al, presents new mat erial, and i s well-written Each publication h as its own specific submission guidelines. 0 Th e mechanics of journal s ubmission a r e also dis cussed, and students are enco ura ged t o c h eck the submission and a cce ptan ce dates on published articles. ASSESSMENT AND DISCUSSION The first time this teaching method was implemented, no formal assessment was used In 2004, an anonymous assess ment was performed by using brief surveys on the fir s t day of class and at the end of the semester. The purpose of the first s urvey was to determine the s tudents knowledge entering the class, while the second s urv ey determined how much the students learned from class di sc u ssio n s. The final s urvey had additional questions to determine the students' perception of what they had learned through the discu ss ions. The initial s urvey at the beginning of the semester followed the suggestions of Angelo and Cross r 22 i for a background knowledge probe and a misconception / preconception check on the purpo se of technical articles and procedure for pub lic a tion. Some of the s urvey que s tion s were drawn from Chemical Engine er in g Education PAGE 7 C Graduate Education ) TABLE 2 Students' Perception of the Technical Reading Assignments ( Rat e d from I-strongl y disagree to 5-strongly agree) State ment Average Rating I. During this course my a bility to read t ec hnical article s impro ve d 4.22 2. I have a better under s tandin g of th e role of technical a rticles in research. 3.89 3 As a result of the dis c u ss ion s I hav e a better under s tanding of the type s of journal s and articles. 4 11 4 I have a better under standing of the a cceptance criteria a nd procedure for getti n g a journal article 3 67 published. 5. I would recommend that the profe sso r repeat the t echnical article reading as s ignments and discussion s 4.39 the n ext time the course i s taught. misconceptions expressed the first time this approach was taught in 2003 This survey provided a baseline comparison with the second survey. As shown in Table I, the first set of question s addressed the importance of reading technical articles. The s tudents were instructed to answer the question s using a rating of one to five, as defined in the table. The initial and final survey columns are the average ratings for each question. A comparison of the final survey results with the initial s urvey result s s hows more students became convinced technical articles are the main so urce for current information. Since students were a lr eady aware that reading technical articles is important this question showed little change Other question s asked required s hort answers The purpose of using a short-answer format was to avoid leading students to any particular response. The following five question s were asked in this format. I 2. 3. Fa/l 2006 Why do graduate stud e nt s and faculty r ea d technical fl.(1J2ll1. Th e respons es t o thi s qu es tion were mostl y th e same on initial and final s ur veys. The respons e to get c urrent informati o n" c am e from at least half th e class This is probabl y be ca us e most studen t s al r e ady reali ze d that articl es ar e a good source of cur r ent information. One c hang e b e rw ee n surveys was that on th e initial survey 42 % of studen t s responded "to find out what has b ee n don e" o r avoid repeating wo rk while on th e final su r vey 70 % of the students gave these r esponses. Why are technical articles publish e d ? Most students r e sponded either to di sse minat e r ese ar c h results o r to dis sem inat e r esearch results qui c kly ." The main difference berween th e t wo surveys was in th e second response; th e number of students citing this reason in c r eased from 25 % t o 40 %. Why is a literature re v i ew included in an article ? Most stude nts -more than 50 % alr e ad y r e ali ze d that the lit erature review is used to provid e background. In th e initial survey, 33 % of th e students stated that th e purpos e of th e r eview was to g iv e c r e dit to previou s 4. 5. resear c hers but thi s r e sponse dropped to 10 % in the final survey. What are the crite ria for geuing a technical article accepted? The r es pons e of "t h e work being novel or creative in c reas e d from 1 7 to 50 per ce nt during th e semeste r. Also, while one-thi rd of the students re sponded don't know on the initial survey, on l y one studen t r esponded don't know on the final survey. Ho w long does it take for a i ournal article to b e reviewed ? The initial survey showed that 42 % of th e st ud ents w r ote don t know for thi s question, but none of the studen t s used thi s r es ponse on the final s ur vey In genera l on the initial survey most students thought reviews would be r eceived in less than 6 months wh il e th e times b ec ame sl i ghtly long e r on second surve y Student perception of the technical article reading assign ment was assessed in the final survey u s ing the questions s hown in Table 2. For the se question s, the s tudents were asked how much they agreed w ith the s tatements by rating their agreement on a scale from I (s trongly disagree) to 5 (strongly agree) In general, students thought the technical reading assignments and class discus s ions helped their understand ing of how to read technical articles and get a journal article published Furthermore mo st of the students recommended thi s exercise be repeated in future classes. DISCUSSION AND CONCLUSIONS Class discu ss ion of journal articles required little additional time to implement. Facu lt y member s commonly use technical papers to provide more information on technical concepts. Although discussing the role of technical papers in research required some time, it provided graduate students with a bet ter understanding of why they should read recent lit erature. Having reading assignments and class discussion s account for 10 percent of the course grade motivated the students to read the assignments. In addition class participation seemed to encourage the students to be prepared. 249 PAGE 8 ( Graduate Education The survey assessment was supplemented by faculty obser vation during class discussion. It was clear from the students' comments and questions that they had read the papers and were able to comprehend the main points They even com mented on some differences in the types of articles. Some of the concepts, however, were new to them. For example, many of the students had not s ubmitted a paper to a journal at thi s time so they were not aware of the review and publi cation timeline. Most students also didn't know that papers frequently list the date the manuscript was received and the date it was accepted. The response from the students was that they liked reading the papers and discussing them in class Many of the students regularly contributed to the discussions Since this assessment has only been performed once with a class of 12 students, it h as not been well tested Future work will include repeating this technjque and its assessment. A CKNOWLEDGMENTS Parts of thjs paper were originally published in the 2005 ASEE Southeastern Section Conference Proceedings. REFERENCES I Lilja D.J ., Suggestions for Teaching the Engineering Re searc h Pro cess," ASE Annual Conferen ce Pro cee dings, Session 0575 ( 1997) 2 Gleichsner, J .A. Using Journal Articles to Int egrate Critical Thinking with Comp ut er and Writing Skills ," NACTA J. 38(3) 12 (1994) 3. Gleichsner, J.A. "Us in g Journal Articles to Int egra t e Critical Thinking w ith Computer a nd Writing Skills, NACTA J., 38 (4) 34 ( 1994 ) 4. Ludlow D K. Using Critical Evaluation a nd Peer-Review Writin g Assignments in a Chemical Process Safety Co ur se," 2001 ASE Annual Co nf e ren ce Pro cee dings, Session 32 1 3 (2001) 5. Tilstra, L. "Usi n g Journal Articles to Teach Writing Skills for Laborn250 ) tory Rep orts in General Chemi s try ," J Ch e m. Educ. 78 762 (200 I ) 6. Holi es, J H ., Theory a nd Methods of Research (o r, How to Be a Gradu ate Student) ," 2005 ASE Annual Conf e r e n ce Proceedings (2005) 7. Fogler H .S., Eleme111s of Chemi ca l R eaction Engineering 4th Ed., Prentice Hall PTR Englewood C liff s, NJ (2006) 8. Fogler H .S., Elements of Chemical R e a c tion Engineering !st Ed., Prentice Hall PTR, Englewood Cliffs, NJ (1986) 9. Westmoreland P.R. personal communica tion (2003) I 0. Felder R M. and R Brent FAQs ," Chem. Eng. Ed ., 33 32 ( I 999) 11 Wankat P.C., Th e Effe c tiv e, Effi c i e nt Prof esso r: Teaching, Scholarsh ip, and Ser v i ce, Allyn and Bacon Boston (2002) 12. Jaksland C.A., R. Gani and K Lien, Separation Pro cess Design and Synthesis Based on Thermodynamic Insights ," Chem. Eng. S c i., 50 511 ( 1995 ) 13. Bridgm an P.W. A Complete Co llection of Thermodynamic Formu las ," Ph ys. R ev 3 ,2 73 (I 914) 14. Raabe G. and J. Kohler "P h ase Equilibria in the System Nitrogen Ethane a nd Their Prediction Using C ubi c Equations of State with Different Types of Mixing Rul es," Fluid Phase qui/., 222-223, 3-9 (2004) 15. Aslam N. and A.K. Sunol Reliable Computation of Binary Homo geneous Azeotropes of Multicomponent Mixtures a t Hi gher Pressures Through Equations of State ," Chem. Eng. Sci., 59 599 (200 4 ) 16. Barker, J.A. a nd D. H e nd erson, The Fluid Phases of Maner, Sci. Am ., 245 1 30 ( 1981 ) 1 7. Prau s nit z, J .M., Molecular Thermodynamics for Some Applications in Biot ec hnolo gy," Pure Appl. Chem 75 859 (20 0 3) 18 Curl R.F. Jr. and K.S. Pitzer, Volumetric and Thermodynamic Proper tie s of Fluids-Enthalpy Free Energy and Entropy ," lnd. Eng. Chem., 50 265 ( 1958) 19. Gmehling J. "Po tential of Thermodynamic Tools (G roup Contribu tion Methods, Factual Data Banks) for the Development of Chemical Processe s," Fluid Phas e qui/. 210 I 6 I (2003) 20. Givand J., B.-K. Chang A.S. Tej a, and R W. Rou sseau Distribution of I somorph ic Amino Acids Between a Crystal Ph ase and a n Aqueou s Solution ," Ind. Eng. Chem. R es., 41 1873 ( 2002 ) 2 1 Loffelmann, M. and A. Mersmann "How to Measure Supersaturation, Chem. Eng. Sci., 57 430 I (2002) 22. Angelo, T.A., and K.P. Cross, C la ssroom Assessment Techniques: A Hand book for College Teachers 2nd Ed. Jossey-Bass San Francisco ( 1993) 0 Chemical Engineering Education PAGE 9 ( Graduate Education ) MULTIDISCIPLINARY GRADUATE CURRICULUM ON INTEGRATIVE BIOINTERFACIAL ENGINEERING PRABHAS V. MoGHE AND CHARLES M. RoTH Rut ge rs University Pis catawa y, NJ 08854 B iointerface s arise at contacts between biologically de rived sys tem slivin g a nd n o nliving-and sy ntheti c systems typically comprised of sy nthetically de s igned material s. Many new technologie s in cell-based diagno s tic s and therapies tissue engineering, biomolecular therapie s, and biosensors are critically dependent on advances in bio interactive surfaces. I 1. I 2 22 1 Rapid advances have taken place in identifying new biological molecule s a nd in the initial de s ign of diverse materials capable of biomirnicry and scale-specific bio-recognition. 1 4 2I Consequently, the field of biomaterial s is poised for a major impact on our soc iety. In contrast to the traditional development of the materials and biology fields, which largely occurred independently, the next generation of bio-inspired and bio-interactive materials will be systemati cally developed through the integration of these discipline s, with strong link s to traditional molecular / cellular biology structural biochemistry and nano / microsystems material s sc iences and engineering .l2 1u 7 i To realize these opportunities, a structured framework i s needed for cooperative graduate learning and research scholarship that cuts across engineer ing physical and life sciences while focusing on mainstream biointerfacial problems and opportunities. Based on the edu cational core of a new National Science Foundation-supported !GERT initiative at Rutgers we propo se a new Integrativ e Fa/12006 Prabhas V Moghe received his B S and Ph.D degrees in chemical engineering from the Univer sity of Bombay and University of Minnesota respectively. He is currently an associate professor in the Departments of Chemical and Biochemical Engineering and Biomedical Engineering at Rutgers Uni versity. Dr Moghe directs the NSF-funded /GERT training program on biointerface s ( ) His research is focused on cell-interactive biomaterials and bioactive nanosystems with applications to vascular and skin therapies and tissue engineering Charles M. Roth received his B S and Ph.D degrees in chemical engineering from the University of Pennsylvania and University of Delaware respectively. He is currently an associate professor in the Department s of Chemical and B iochemical Eng ineering and Biomed ical Eng ineering at Rutg ers. Dr Roth is one of the leading core faculty for the Rutger s /GERT on biointerfaces. Hi s research is focused on molecular syste m s bioengineering with major emphasis on nucleic acids technologies and applications to liver therapies and cancer. Copyrigh t ChE Divi s i on of ASE E 20 0 6 25 1 PAGE 10 ( Graduate Education Biointerfacial Engineering (IBE) curricu lum that involves a three-pronged focus on molecular/cellular engineering; micro/nano sca le biomaterials; and tools to quantitatively probe biointerface s (see Figure 1 ). While such a curr i c ulum ca n be best rooted within a bioengineering core (designated bio-x-engineering) the integrative curriculum is designed to effectively resonate among a diverse range of nonengineers. In the following sec tion we review the core curriculum and the best instructional practices of the IBE curriculum. TECHNOLOGICAL CONTEXT FOR CURRICULUM: RESEARCH PROGRAMS ON BIOINTERFACES The curriculum on biointerfaces can be designed to ar ticulate with the specific areas of research expertise of each graduate institution The research thrusts are an important prerequisite, as they provide the technological context and research infrastructure for the courses Three major thru s ts were identified at Rutger s: (1) living cell biointerfaces i. e ., engineered ce llul ar/intracellular sys tems that elucidate/affect Systems/DMce Level Integration of biointerfaces Qj -.; u t/'l 0 C ,a z Biosystems Bioengineering ) biointerfacial phenomena; (2) biologically interactive na noscale and microscale interfaces ; and (3) systems or devices built from designed biointerface s. Thrust l involves studies at the interfaces that occur be tween living cells and biomaterial s, between living cells and supported biomolecules (ligands), and intracellular in terfaces between cytoskeletal proteins and signaling targets within living cells. Such interfaces are fundamental to any cell-based diagno s tic, therapeutic or model systems used to st ud y stem-cell development pathology, and bio-inspired devices. The interpretation and modeling of cell ular dynamics o n more comp l ex ligand substrates is also an area that often falls outside the expertise of cell biologists but is central to the integrated curriculum proposed here. A recent report in the Annals of Biom edica l Engineering describes a curriculum concentrating on cellular engineeringl 2 01 that embraces many of these principle s. Thrust 2 involves investigation of inorganic and polymeric substrates from micron-sized cell interfaces to nano-sized peptide/protein interfaces Such interfaces are widely emerg ing in biophotonics bioMEMs single-cell s tudies and therapeutic Engtneered cellular /intracellular systems that elucidate I effect biointerfacial phenomena '1:1 ,a C U 0 t/'l >, 0 Qj ti t0 :E 12:1 Characterization approaches to tissue regeneration and drug delivery. For exam ple interfaces created by micropatterning proteins on sy nthetic polymeric s ubstrates can be fabricated us ing microlithographic or microcontact print ing technologie s, then analyzed using micro scopic, spectroscopic, and cell ul ar approaches The capabilities of mi crofa bricati on-the physicochemical characterization-and biological s tudies fall outside the expertise of any single di sc ipline and, therefore consti tute a major area in the integrated training ap proach we envision Biojunctional Micro,ca/eandNanoscale ~ ---Interfaces Figure 1. A triad of graduate courses has been designed to capture the synthetic and analytical approaches related to biointerfacial problems involving living engineered ce lls on: substrates; microand nanos ca le biofunctional materials ; and bio sys t e ms and processes for ce ll signaling biosensing, and actuation. The schematic backdrop illu s trates the lands cape of the curric ulum in terms of (a) the biointerfacial co nflu e nce of cells, biomolecules, and mat eria ls ; and (b) int e disciplinary research thrusts denoted as IRT's Emerging opportunities allow e n gineers and life scientists to address biointerfacial problems at the nanothrough microscales. Thrust 3 involves studies of systems or processes involving 252 Chemical Engineering Educatio n PAGE 11 ( biomaterial s ub s trate s designed to elicit sys t e matic re s pon ses fro m li ving ce ll s or biomolecular moietie s (e g., oligonucle ot ide s, peptides / proteins) ca ll ed bio-respon s ive interface s; s ub strates designed t o detect and se nse biomolecules and cells called biosensor s; and substrates engineered to be phy s iolo g ic three-dimen s ional ,c' 91 and / or actuated through the media tion of biologic mechanism s or motor s. Such int erfaces are fundamental to the d eve l op m ent of therapeutic implantable biomaterials impl a nt ab l e bio se nsor s, a nd biomicro-electro mechanical sys tems ( BioMEMS ). COURSE LEVEL AND PREREQUISITES Th e biointerfacial eng in eeri n g curr i cu lum is aimed at seco nd -year or higher gra duate students in chemical and biomolecular engineering, biomedical engineering allied en gineering disciplines (mechanical and materials engineering), a nd ph ys i ca l a nd li fe sciences. At Rutgers, nearly 60 graduate s tudent s (50 % chemica l a nd bio-engineers; 10 % mechani cal and materials engineers; 25 % molecular bioscienti s t s; Graduate Education ) further to the courseload beyond the expected graduate e l ec tives for a Ph.D. degree. For example, the Rutgers C h emical a n d Biochemical Engineering grad u ate program requires 15 elective credits ( be yo nd 15 core credits) for which a n y or all of the three integrative courses ( IC ) described below may be u sed Further, engineering graduate programs t h at have rece ntl y in s tituted a life sc ience co ur se requireme nt ca n eas ily adopt a n y IC co ur ses. Simi l ar l y, biomedical e n gi ne er in g graduate programs, s u c h as those at Rut gers, require three bioengineering electives (9 credits), which can be readi l y met through the IC courses CURRICULUM COMPOSITION The proposed curriculum involve s a triad of co ur ses, denoted as ICl IC2 and IC3 (see Table 1) We utilize an integrative philo so phy to develop curric ul ar theme s For example, we designed courses that integrate biointerfaces across the ra n ge of orga ni zat i on of biological components of the interface s (e g., ge ne s, protein s, cells: see IC I) or s i ze TABLE 1 and 10 % physical scien tists) participated in the se co ur ses in academic year 20 05-6 B eca u se st ud e nt s e nt er th e curricu lum from diverse backgrounds, pre requisite s are expressed topically rather than by s p ecific course numb ers, and cons ult ation with co ur se in st ructors and / or IGERT administration i s encouraged. Prerequisite s include und ergrad uat e li fe sc ienc es co ur ses (ge n era l biology ce ll biology/bio chemistry / molecular biol ogy) as well as structured under grad u ate co ur ses in the ph ysica l a nd quanti tative sciences, s u c h as physical c h emistry and advanced calcu lu s. Th e c urriculum builds l a t er a ll y on grad u ate core e gi ne ering courses such as transport phenomena an alytical method s in chemi ca l and bioengineering a nd th er m ody n amics a nd kinetics. The c urriculum does n ot typically add a n y Co urse Syllabus for Integrative Biointerfaces Curriculum Course and underlyin g Sy ll abi of course module s inte gra tive philosophy ICl: Molecular and Modul e 1: Genes-sequence and function technologies and dataCe llular Bioengine e rbases; gene expression profiling ; ge netic e n g ineerin g ing ( int egrated across Modul e 2: Proteins-structure and function; molecular recog ni scales of b i o -organization ; protein adsorption; nanopatterning of protei n s; proteomic tion ) te c hn o l ogies Modul e 3: Biochemical Networks-gene expression data mining; metabolic flux analysis ; s ignal transduction and gene network modeling Module 4: Cells-growt h a nd differe nti ation; ce ll-m a terial responses; expression-phenotype relationship s; act u a t ed ce ll respon ses; stem cells IC2 : Microscale and Module 1: Microlithography a nd microfabrication anoscale BiointerModul e 2: Nanoscale proce ss ing a nd fabrication faces (i nt egrated across Modul e 3: Soft tissue-nanostructures microstruct ur es, macrosca l es) structures Module 4: Hard tissue-n a n ostr ucture s, micro s tru c tur es, and functional components Module 5: Nanostructures and microstructures of biosensor s, bioseparations, implantable devices bioMEMs IC3: Biointerfacial Module]: Chemical surface characterization; electron s p ec tr osCharacterization copy (i nt egrated across Module 2: Phy sica l s urfa ce c har ac terization-topography surface biointerfacial phases: energetics microscopy s pectroscopies (s ur face Raman ; s in gle chemical physical, molecule ; FflR) ; nanoparticle sizi n g a nd morphology biological) Module 3: Biological Surface Characterization-protei n s at in terfaces a nd protein arrays; ce ll dynamics at interfaces (ad h esio n ; migration ; endocytosis; growt h / differentiation) ; biofunctionalized s ub strates; gene mi cro-arrays Module 4: Integrative design, applications and case Fa/12006 253 PAGE 12 ( Graduate Education scales (e.g., nano-rnicro-macroscales : see IC2) or the two phases that constitute a typical biointerface (e.g., the gene element, plus the silico nw afer, that form a class of gene-chips: see IC3). In the future, other integrative philosophies can be envisioned as well (e g integration across time scales for dynamic interfaces). INTEGRATIVE TREATMENT OF THE CURRICULUM A variety of fundamental tools and phenomena are in troduced in each of the three courses within the context of significant technological problems. In order to provide a cohesive framework in the overall curricu lum many key problems are dissected within all three courses. Naturally each course treats the problem differently as illustrated in Table 2. For example, the problem of tissue-specific target ing of drug nanoparticles is discussed in ICl at the level of receptor-ligand binding, and in the theory and analysis of binding affinity; IC2 treats the nanofabrication of particles and biofunctionalization; while IC3 treats the experimental tools for nanoparticle characterization. These too l s include the u se of dynamic laser scattering and zeta potential measurements to characterize nanoparticle c h arge and sizing, and quartz-crystal microbalance and surface plasmon resonance techniques to eva luate ligand-receptor affinity. Other cross-cutting topic s are summarized in Table 2. ) BEST PRACTICES In developing the new curriculum, an overarching goa l ha s been integration of the graduate students' research and learning experiences, i.e., to help usher the frontier s of bio interfacial science and engineering into the classroom. The instructor s have identified severa l instructional approaches that have proven to be particularly effective in merging active learning with emerging scien tific advances a nd technolo g i ca l applications. These approaches include the se lected inclusion of faculty experts as guest l ecturers, extensive incorporation of readings from current research literature and demon s tra tions of techniques and in s trumentation at laboratories around campus. Additionally mid-course corrections in response to s tudent feedback have occurred. Use of the Current Biointerfacial Research Literature For all three courses, each major topic was contextua l ized through extensive u se of recent, leading publications in th e field The manuscripts were assigned prior to respective lec ture s, and s ignificant portions of class were allotted to critical review and discussion In IC3, following each lecture s tudents were assigned homework based on the key publication The homework involved writing a s hort essay highlightin g key principle s, insights obtained, and shortcomings of biointer facial characterization techniques treated in each reading. TABLE2 Breakdown of Topics Treated Across the Triad of Integrative Courses C RO SS CUTTING PROBLEMS SPECIFIC TOPICS AND REFERENCES !Cl IC 2 IC3 Hi g h -Co ntent Living Cell Assays Signal tran sduc tion ; ce ll Ce ll microreactors 1 32 1 Ce ll ad h es i o n a nd motility cyc le and pro li feration ; c hara cterizat i o n 14 1 0 '" 45 471 differentiation; metabolic engi neerin g 1 6 30 4 01 DNA and Protein Microarrays Applications of microarPhotolithography ; Chemica l physical and rays; interpretation of s urface attachment and functional characterizadata 13. 231 functionalization l""I tion 136.481 Di scovery and Applications of Novel Protein molecular recogMicro / n a nosca l e orSingle molecule and Biological Transformations nition and function 151 gan i c substrates 1 8 31 1 FRET imaging 1 2 us 1 function 1 1 Targeted Biofunctionalized a nd Drug Ligand-receptor bindin g Fabrication of Si z e; c harge; biofuncCarriers a nd intracellular traffickmicroa nd nano s cale tional characterization ; in gl 291 inorganic and organic fluore sce nce s pectro ss ub s trates 17 4 17 221 copy l 33. "I R ege n era ti ve Biomaterials Scaffolds Protein adsorption and Fabrication of nanoMolecular modeling; biocompatability l 4 6 i and microporous scafco nformation ; topography fold s and fiber s l 16 24 1 and microstructure character i za tion 1 27 41 431 Mu l ticellular Tissue Assembly Cell-cell and ce ll m a trix Cell-ma tri x assemb l y Ce llul ar phenotypi c a nd a nd Engineering comm uni cat ion 19 26 39 1 and patternin g l 1 31 s i gna lin g within ti ss ue assemb li es 1 1 91 254 Chemi c al Engin ee ring Edu c ation PAGE 13 C Retrospectively, students have reported this exercise was critica l to und ersta ndin g the key elements of eac h technique within an application area As described below student feed back to the u se of scientific literature has been consistently enthusiastic. Tracking Student Learning and Integrative Outcomes Careful attention has been given to choosing student as sessment vehicles that both support the research-centric a nd int egrat i ve goa l s of the new curriculum and address the divergence in student backgrounds and preparation (i.e., the enro llm e nt across e n gineering, physical sciences and life sciences graduate programs) All three courses used a three fold combination of short (homework ) assignments mid-term and/or final exams, and clas s projects-thereby providing students with different ways to demonstrate mastery of the material. Class projects in particular have proven to be a va luabl e mechanism fo r promoting integration of classroom l earning and student research and promoting cross -di sciplin ary interactions. In all three courses students were assigned one or more integrative project reports to prepare over the course of the semester. Students presented their findings orally to the entire class and also submitted their slides and / or a paper to the instructor. Students were challenged to select topics that related to their own thesis research, and to consult the co ur se instructors s hould they need help in doing so Several strategies were adopted to encourage cross-disciplinary dialog and l earning during the course projects. For example, the IC I course projects allowed pairs of students to work on such reports with the teams composed of students from different graduate disciplines. In IC2 Rutgers graduate students from remote fields were asked to review and comment on student projects. The instructor for IC3 encouraged each student to select another student from an orthogonal field to be a con s ult a nt on his or her project. Student Early Assessment and Curriculum Refinement Given the diverse backgrounds of s tudents a first-day sur vey administered by the instructors has proven invaluable in assessing the knowledge base of each student population, and appropriate l y customizing the focus of the modules within eac h course For instance, in IC 1 which has now been offered twice, the student body was further along in research and more fami li ar with tissue engineering and other bioengineering top ics. The second year's class was on average, still formulating research projects a nd had a preponderance of students wit h bioinformatics backgrounds Mid-course surveys also proved helpful in refining the course delivery. For example, students Fa/12006 Graduate Education ) asked for additional background information, s u c h as further definitions of specific terms and references to fo undational papers. These modifications were r eadi l y implemented as postings on the course Web sites Curriculum Assessment Given the interdisciplinary nature and lack of precedent for such a curriculum, continuing assessment is n ecessary to as sure that it meets its goals and the needs of constituents. The ultimate goal of the curriculum is to provide st ud ents with knowledge that will increase the quality and productivity of their r esearch. While the c urr ent curriculum form ha s b ee n at Rutgers since 2003, a more compre hen sive quantitative assessment of this outcome wi ll have to wait for curr icul ar knowledge to be translated to research output. Comments on course assessments suggest that students feel more knowl edgeable and empowered in the areas of this interdisciplinary curriculum. The curriculum serves as an effective platform for eva lu ating the success of students from diverse backgrounds. To gather additiona l data on possible differences in stude nt per formance, based on disciplinary background a nd / or IGERT participation, all students in IC3 were asked t o evaluate each other s oral course project presentations using a structured questionnaire designed by the instructor. Evaluation criteria included not only presentation quality (clarity, organization etc ) but also the appropriateness of the characterization methods chosen and the degree to w hi ch the chosen re search problem was significan tl y biointerfacial. As rated by their peers IGERT Fellows and non-IGERT students fared comparably, on average indicating that the student l earni n g outcomes were not systematically biased by their training program affiliation Likewise, engineers biologists, and chemists all fared similarly, with some st ud e nt s from eac h discipline giving stronger presentations than ot h ers from the same discipline An excellent source of data abo ut student feedback on courses is the "Student Instructional Ratings Survey" (S IRS ) program that is administered by the Rutgers Center for Ad vancement of Teaching. All courses at Rutgers are eva lu ated using a standard I 0-question survey with a oneto five-point rating scale. The survey is reproduced, along with actua l rat ings for the first offering of the three IC courses, as Tab l e 3 (next page). Additionally, three ope nended questions were posed to acquire qualitative feedback (not shown for brev ity ) To put the curriculum feedback in context, we calc ul ated an average bio-x-eng response by using the SIRS data for "mean of responses from all courses this level" from the biomedical eng in eering and chemica l and biochemical engi neering graduate programs at Rut gers for the two academ i c semesters the IC courses were offered. 255 PAGE 14 ( Graduate Education Generalizable Positive Comments St ud ents co mplimented the teaching quality of all thr ee courses, which is consis t e nt with the high numerical scores for each of the three lead instructor s in Questions 1 -5. Students noted the care given to the choice of topics (both breadth and relevance) and to the organization and delivery of the course material. Many comments addressed the ways in which all three courses incorporated current research literature into the course curriculum. Students appreciated the time devoted to di sc us s ion of the papers, and how these discussions together with written assignments, helped students develop "alternative way(s) to look at data and critically review papers. Finally, s tudent s appreciated the attempts to tie course content and assignments to the biointerfacial aspects of their graduate di sse rtation research. The project s/ pre se ntations assigned in a ll three courses were useful in term s of "cover ing topics of interest instead of recycling research or s pending too much time out of research ." As expressed by another student, in structor and peer feedback from classroom presentations of final projects "w ill be important in directing and focusing the research in a biointerfacial twist. Student Constructive Criticisms Students in ICl, which did not use guest lecturers, expressed interest in having a few guest lecturers Conversely, students in IC2 and IC3 felt that courses might be improved by fewer g uest lecturers and / or better quality control. In IC2 students TABLE3 ) were primarily concerned that they some times could not deduce the relevance of a certain lecture i.e., its relationship to the overall curriculum. Other constructive criticism and suggestions of the s tudent s focused on not decrea s ing-and perhap s increasingthe frequency of short assignments and other ongoing student assessments In IC2 there was concern about the difficulty of knowing what to study and having too much weight attributed to a final exam. In ICl th e re was input that optional s hort exercises calculations, and readings could be provided to address respective gaps in st udent s' background s. Finally so me students suggested the creation of a textbook for IC3, and a more modular organization of topics as in IC L. CURRICULUM EVOLUTION AND INSTITUTIONALIZATION The Rutger s curriculum on biointerfacial engineering was first structured around the core gradua te training pathway of the I GERT program ( ). We expect the curriculum to evolve in re s pon se to the emerging areas of biomaterials and biointerfaces. The dynamic participation of a large number of research-active institutional faculty with access to state-of-the-art re searc h infrastructure and tool s will be integral to ensuring the timely evolution of the cur riculum The biointerfacial engineering area also resonates particularly well with the field of biomaterials science and Rutgers Student Instructional Rating Survey (SIRS) engineering. Given the close ties of our I GERT to the New Jersey Center for Biomateri als ( ) we expect to offer the IC courses along with core biomaterials-related courses as part of a comprehensive cer tificate program a t Rut gers on biointerfaces and biomaterials. The certificate program, to be established fall 2006, indicates success ful institutionalization of the curriculum and will help s ustain an identity for the curriculum. N=l5 Questions IC! 1 The in s tructor was prepared for class and 4 .7 5 presented the material in an organized manner 2. The instructor responded effectively to 4.63 st ud en t comments and questions 3. The in st ructor generated int erest in th e 4 44 course material 4 The instructor had a po s itive attitude to ward 4.63 ass i sting a ll students in under s tandin g co ur se m a teri a l 5. The instructor assigned grades fairly 4.38 6. The in s tructional method s encouraged 4.31 s tudent le a rning 7. I l ear n ed a grea t deal in thi s course 4.50 8. I had a s trong prior inter est in th e s ubject 4.56 matter an d wanted to take thi s co ur se 9 I rate the teaching effectiveness of th e 4 44 instructor as 10. I rate the overa ll quality of th e course as 4 25 256 N=l3 N=l6 1C2 IC3 4.67 4.75 4.60 4 67 4 .73 4.67 4 53 4.58 4 .20 4.38 4.00 4 50 4.27 4.58 4.53 4.42 4 .33 4.77 4.13 4.77 bio-xeng 4 .32 4 .30 4.09 4.40 4.22 3.98 3.97 3 73 4 .10 4.08 CONCLUSIONS A new graduate curriculum on integrative biointerfacial engineering was developed This curriculum treat s the Chemical Engineering Education PAGE 15 C sy nthe sis, a n a l ys i s, and de sign of biological interfaces in t erms of th e constituent components ( bi o l og i cs, materials sys t e m s), a nd with a n eye to e mer g in g t ec hn o l og ical a pplication s s uch as ti ss ue engineering, biotechnol ogy, n a n o biomaterial s, and biomedi c ine Each course within th e c urri c ulum i s d es i g n ed ba se d on a fundam e nt a l int egra tin g philosophy The n o d e for th e c urri c ulum lie s within bio-x-engineering, whi l e the breadth of th e c urri c ulum enables li fe scient i sts, physical sc i e nti sts, a nd ot h er bio-engineer s t o participate fully wit hin th e c urri c ulum Various in s tru ctio n a l s trategies we r e adop t e d to mor e fully inte gra te the multiple disciplines represented in the field. B ase d on student p erce pti o n during ear l y s tudent assessment, the curriculum i s eq uival e ntl y a m e n a bl e to s tu dents from a wide range of disciplines, effec ti ve l y s tru c tur e d a nd rigorou s, dynamic in embodying s t a t e-of -th e -art re searc h a dvan ces, a nd fills a major vo id in the grad u a t e ed uc a ti o n of e n g in ee r s a nd sc ienti s t s. G radua t e cu 1Ti c ulum o n int egra tiv e bio sc i e n ces a nd bio e ngin eer in g would resonate we ll in other American a nd int e rn a tion a l uni ve r s iti es, particularly those with s i g nific a nt research stre n gt h s in molecular biosciences a d va nc e d m a t eria l s and engineering sc i e n ces. ACKNOWLEDGMENTS Th e a uthor s gra tefull y ack n ow l edge s upp ort from th e National Science Foundation Int egrat i ve Graduate Educa tion a nd R esea r ch Traineeship ( IG E R T) OGE 0333196 ( Pl : P Moghe) a nd from Rut gers Univers it y. The authors are ind e bt e d t o Professor Kathr y n U hri ch for her active participa tion a nd s i g nifi ca nt contribution t o c urri c ulum development. Dr. Linda J. Anthony pro vi d ed exce ll e n ce assis t a n ce with the m a n age m e nt of the educational program. P Moghe exp r esses grat itud e for the contributions of many fac ult y co ll eag u es at Rut ge r s a nd UMDNJ includin g Yves C h a b a l D av id Sh r e ib er, Theodore M a d ey, Gary Brewer William Welsh Jack Ri cci, A dri a n Mann Rich ard Rim a n Sobi n Kim a nd Edward Castner, a m ong severa l o th ers, whose instruct i o n al h e lp has st r e n g th e n e d th e quality of the c urri culum. REFERENCES I Anderson, D .G. S. Levenber g, a nd R. Langer, "Na noliter-Sc a le Syn the s i s of Arrayed Biomaterial s and Application to Hum a n Embryonic S t em Ce ll s, Nat. Bi otech., 22 863 (2004) 2. A nd e r so n D.G., D. Putnam E.B. L av ik T.A. 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H o ll is t er, S.J Porous Scaffo ld Design for Tissue Engineering ," Nat Mare,:, 4 5 1 8 (2005) 25. K a nnan, B K Casteli n o FF. C h e n a nd A. Majumdar Lith og r ap hi c T ec hnique s and Surface C h em i s tri es for th e Fabrication of P eg-Pas s i vated Protein Microarray s," Bi ose ns. Bio elec rron ., 21 1 960 (2006) 26 Khetani, S.R., G. Szu l gi t J.A. Del Ri o, C. Barlow, a nd S.N. Bhatia ; ,E xp l or in g Int erac tion s B etween R at Hepatocytes a n d Nonpare n chy mal Cells Using Gene Expression Profiling, H epatology, 40 545 (2 004) 27. K o hn J ., New Approaches to Bi omateria l s Design ," Nat Mar e r ., 3 745 (2004) 28 La n ger K. S. Balthasar, V. Vogel N. Dinauer, H von Br iesen a n d D. Schubert, Optimization of th e Preparation Proces s for Hum a n Serum Albumin ( h sa) Nanoparticles, /111. J. Phann ., 257 1 69 (20 0 3) 257 PAGE 16 ( Graduate Education 29. L a uff en bur ger D .A., E.M. Fallon a nd J .M. H a u g h "Scra t c hin g the (ce ll ) Surface: Cytokine Engineering for Improv ed Li ga nd / R ece ptor Trafficking Dynamic ," Chem. Bi o 5 R 257 (I 998) 30. L ee, K D ., T.K .C. Kuo, J Wh a n gP e n g, Y.-F. C hun g, C.T. Lin S .H Chou, J -R Chen, Y.-P. Chen, and O.K.-S. Le e, In Vitro H e patic Dif ferentiation of Human Mesench y mal Stem Ce ll s," H epato l ogy, 40 1 275 (2004) 3 1. Lin D.C. B Yurk e and N.A L a n gra n a M ec h an i ca l Properties of a R eve r s ibl e, DNA-Cro ss linked Polyacr y l am id e Hydro ge l J. Bi omech. Eng 126 104 (2 004 ) 32. M a h a rbi z M.M. W.J. Holt z R.T H owe a nd J.D K eas lin g, Mi cro bior eac tor Arrays with Param e tri c Co ntrol for Hi gh -Throu g hput Experimentation ," Bi otec hn o / Bioeng. 86 485 (2004) 33. Maheshwari G., G Brown D. A. L a uff e nbur ge r A. Wells and L.G Griffith "Ce ll Adhesion and Motility D e p e nd on Na n osca l e r gd Clus t e rin g ," J Ce ll Sci. 113 16 77 (2000) 34. Mo o r crof t M.J ., W.R. 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Y a na g id a, Single-Molecule Im ag in g of Eg fr Signalling o n th e Surfac e of Living Ce ll s, Nat Cell Bi o l ., 2 258 ) 1 68 (2000) 39. Semler E .J A. Dasgupta, P. Lan c in and P.V. Moghe, "E n g in ee rin g H epatoce llul ar Morphogenesis a nd Function Via Ligand-Presenting H ydroge l s w ith Graded Mechanical Compliance Biot ec hnol Bioeng. 89 297 (2005) 40. Sem l er E .J a n d P.V. Moghe, Engineering H epa t ocyte F un c ti o n a l Fate Through Growth Fac t or D y nami cs : The R o l e of Ce ll Morphologic Primin g, Biote ch n ol Bio e n g. 75 510 (200 1 ) 4 1. Smith, J R ., V. Kholodovych D. Kni g ht J. Kohn a nd W.J. Wel s h Predicting Fibrinogen Adsorption to Pol y m eric Surfaces in Silico: A Co mbin ed Method Approac h ," Pol y mer, 46 4296 (2005) 42. Stevens M M. and J H George Exploring a nd Engineering th e Ce ll Surface Int erface ," Science, 310 11 35 (2005) 43. Sun Y. W.J. Wel s h and R.A. Latour Prediction of the Orientations of Adsorbed Protein Using a n Empir i cal Ene r gy Funct i on wit h lmpli ct So l va t io n ," Langmuir 21 56 1 6 (2005) 44 Tan J .L., J. Tien D.M. Pirone D .S. Gray K. Bhadrira ju a nd C.S. C h e n Ce ll s Lying on a Bed of Microneedles: A n Ap pro ac h to I so lat e M ec h a ni ca l Force ," Proc. Nari. Acad. Sc i. 100 14 84 (2003) 45 Tjia, J S ., a nd P.V. Moghe Ce ll Mi gra ti o n on Ce ll-lnt e rn a li za bl e Li g and Microdepot s : A Phenomenologica l Model ," An n a l s of Biomed Eng., 30 85 I (2002) 46. Yoon J.J ., Y.S Nam J H Kim, a nd T.G. Par k, Surface Imm ob ili zat i o n of Galacto se on t o Aliphatic Biodegradab l e P o l yme r s for H e p a t ocyte C ultu re ," Biote ch nol. Bioen g., 78 (1 ) 1-10 (2002) 47. Zama n M.H. R.D Kamm P. Matsudaira an d D.A. Lauffenburger Comp u tatio n a l Model for Cell Migration in Three-Dimensional Matrice s," Bioph ys. J. 89, 1389 (20 05 ) 48 Zhu H ., M. Bilgin R. Bangham D Hall A. Casamayor, P. Bertone N Lan R Jan se n S Bidlingmaier T. H o ufe k, T. Mitchell P. Miller R.A. Dean, M. Gerstein a nd M Synder, Global Analysis of Protein Activ iti es Us in g Proteome C hip s, Science, 293 2 101 (2 001) 0 Chemical Engine e rin g Education PAGE 17 C Graduate Education ) BIOMASS AS A SUSTAINABLE ENERGY SOURCE: an Illustration of ChE Thermodynamic Concepts MARGUERITE A. MoHAN, NICOLE MAY, NADA M. AssAF-ANID, AND MARco J. CASTALDI Manhattan College Riverdale NY A s discussed in an earlier paper 111 the overall objective of the thermodynamics course sequence at Manhat tan College is to allow students to become confident about their understanding of theoretical material and familiar enough with mathematical manipulations to properly and ac curately set up solutions to problems involving thermodynam ics Toward the end of the semester, students have a chance to explore and propose feasible solutions for what-if scenarios to contemporary problems such as Methyl Tert-Butyl Ether (MTBE) contamination of groundwater 111 biofuels, 121 and thermodynamics of power plants 131 The desired outcome is to develop the students' engineering judgment and capabilities along with their mathematical skills in solving complicated equations with many inputs. This major assignment intr oduces the students to a practical and current problem they can tackle somewhat intuitively, rather than by a direct application of formulas as presented by Cengel. 141 The only requirement for a solution is the use of computer programming, possibly a spreadsheet, and the thermodynamic principles taught in class (e.g. phase equilibria solubility, fugacity). Such an open-ended approach is common in engineering education and C o lumbia U ni ve r s i ty Earth and En viro nm e ntal En g in ee rin g D e partm e nt Fall 2006 Nada M. Assaf-Anid is an associate professor and chairperson of the Chemical Engineering Department at Manhattan College. She earned her 8 S and M S in chemical engineering from the Royal Institute of Technology in Stockholm Sweden and her Ph.D in environmental engi neering from the University of Michigan in Ann Arbor Her research and teaching interests are in separations biochemical engineering hazardous chemicals remediation thermodynamics, and water purification. She is director of the ASEE Chemical Engineering Division and director of the Environmental Division of AIChE. Marguerite A. Mohan is currently working towards her M. S. in chemical engineering at Manhattan College where she previously obtained a 8. S in chemical engineering. After completing her graduate degree she will be employed full time by Merck & Co ., Inc as a staff chemical engineer Marguerite s research interests include chemical thermodynamics and nanoscale science Nicole May is currently pursuing her M.S in chemical engineering at Manhattan College She also holds a 8 S in chemical engineering from Manhattan College Her interests include engineering education, bioreac tion engineering, and environmental conservation. Marco J. Castaldi is an assistant professor in the Earth and En vironmental Engineering Department at Columbia University He received his 8. S. ChE from Manhattan College and M.S and Ph.D ChE from the University of California Los Angeles Prior to joining Columbia University he worked in industry for seven years researching and developing novel catalytic reactors. His teaching interests lie in thermodynamics combustion phe nomena and reaction engineering His research is focused on beneficial uses of CO in catalytic and combustion environments waste-to-energy processes and novel extraction techniques for methane hydrates. Copyrigh t C hE D i v i sion of ASEE 20 0 6 259 PAGE 18 ( Graduate Education has b ee n used in thermodynamics courses 151 because it resembles problem-solving situations en countered in industry .l 6 l The objectives of this paper are to present an open-ended prob lem given as a final project to a graduate process thermodynamics class, describe how one student tackled it, and demonstrate how it was a useful addition to the therLiquid modynamics concepts taught in Draw ott the class Portions of the problem may be suitable in an undergraduate thermodynamics, modeling 1 Bioreactor u 0 >u (I] (I] Q) c'3 a::: Air ) Power Plant or design class,17 1 if presented in a less open-ended manner or as a continuing problem integrated in Figure 1. Schematic of system components a series of courses using the approach of Shaeiwitz. 1 8 1 The problem given to students, with three references on anaerobic digestion ,1 9 II I is shown below. Students were instructed on literature research methods using online libraries and Internet sites, s u ch as About.com, 1121 to assist them in finding back ground inform a tion. Topics a nd information searched ranged from gasification of biomass for distributed energy production systems, to physical property data needed to perform calcula tions to ideas for possible so luti ons. TABLE 1 Overview of Course Syllabus (T he chapters refer to the class textbook 1I 3 1 ) Week Subject I R ev iew of classical thermodynamics 2 Revi ew of classical thermod y n am ic s (co nt 'd) 3 Ch. 2 prepare for exam #1 4 Ch. 3, exa m #1 (classical thermo and Ch. 2) 5 Ch. 4 ( part s) 6 Ch. 5 (parts) review exam # l 7 Ch 6 (pa rt s); computer ass ignment discussed 8 Ch 7 (parts) 9 Ch 7 (par ts) exa m #2 (C h 3 4, 5 6) IO Ch. 8, Ch. 9 (pa rt s) II R ev iew exam #2, Ch 9 ( part s) 12 Ch. IO ( part s), Ch 11 (pa rt s), Ch 12 (pa rt s) 13 Statistical th e rmodynamics computer assignment due review 14 Final exam 260 PROBLEM STATEMENT As shown in Table 1 the students had about s ix weeks to comp le te the project and were expected to work indepen dently By the time the computer assignment was issued the students were exposed to solution equilibrium theory, which begins with Chapter 6. Th e demand for power, especially e l ect ri c ity has driven many engineers to propose possible ways to generate power. Of course that power generation must be compatib le with environmental regulations and must be fueled by available resources. One novel power-generation system uses a bioreac tor to decompose various types of biomass anaerobically. The off-gas from that process will generate methane (CH 4 ), which can be used as ju.el. However, carbon dioxide (CO 2 ) is also generated In this gas mixture of CH 4 and CO 2 the latter is cons id e red a diluent and effectively low ers the energy content of the gas stream. One cou ld separate out the CO 2 from the stream, but the energy requirements are prohibitivel y high. The total power that can b e obtained from the system is governed by volumetric flow rate and energy content. It has b ee n proposed to accelerate the decomposition of the biomass to generate more CH 4 or at least a higher flow rat e of the CH / CO 2 mixture. One way to do this is to "feed" the bacteria that is decomposing the biomass a warm stream of CO 2 and hydrog en ( H / In addition, this CO 2 can s e rve as a car bon source for the bacteria This allows the bacteria population to increase and the decomposition of the biomass to occur faster. The supply of CO 2 and H 2 is secured b y another reactor placed upstream to convert some of the bioreactor product stream (CH 4 and CO 2 ) to H 2 carbon monoxide (CO), and CO r This second rea cto r is a catalytic r efo rming rea ct ion that uses a Chemical E n g in ee rin g Education PAGE 19 C small amount of air. Lastly it is known that the bacteria will have some waste byproducts as a result of their digesti v e process. Some of those b y produ c ts could harm the bacteria if the y a cc umulate to dangerous levels. As an engineer on this job you need to provide a full understanding of the bio reactor. That is what types of b y products will be formed by the bacteria and how will those byproducts distribute them selves between liquid and gas phases. In addition, you also need to determine the preferred concentrations of c arbon in the bioreactor f e ed stream as a fun c tion of residence time in the bioreactor, to ensur e that adequat e carbon is dissolved in the liquid phase for the bacteria to access. In addition to the statement a concep tual schematic (Figure I) was provided to show the overall system. Finally a survey was distributed to students assessing how this type of a project impacts their understanding of the subject and overall learning experience BACKGROUND AND THEORY Anaerobic digestion, or methane fermentation is the process by which microorganisms convert biomass to methane in the absence of oxygen. Of ten a water layer serves as a b l anket to exclude oxygen and promote growth of the appropriate anaerobes. 1 1 41 With higher (gross) heating values ranging from 15.7 to 29.5 MJ / m 3 (n), the gas produced by the anaerobic digestion of biomass, called biogas, is a medium-energy fuel that may be used for heating and power. 1 14 1 Methane fermentation i s a three-step process that utilizes three main categories of bacteria: fermentative, acetogenic and methanogenic. 1 1 4 1 5 1 In the first step the fermentative bacteria convert complex polysaccharides, proteins, and lipids present in biomass to lower molecular weight fragments such as carbon dioxide and hydrogen 1141 according to the main reactions shown. 1 1 41 Fal/ 2006 Reactions Graduate Education ) 11G 0 (kJ) C 6 Hl 2 O 6 + 6H 2 O 6CO 2 + l 2H 2 -26 (Rxn 1) C 6 H 12 O 6 2CH 3 Coco ; + 2H + + 2H 2 -112 (Rxn 2) C 6 H 12 O 6 + 2H 2 O CH 3 CH 2 co ; + H + + 3co 2 + 5H 2 -192 (Rxn 3) C 6 H 12 O 6 CH 3 CH 2 CH 2 co ; + H + + 2co 2 + 2H 2 -264 (Rxn 4) In the s econd step hydrogen-producing acetogenic bacteria catabolize the longer chain organic compounds formed in the first step to yield acetate, carbon dioxide and hydrogen. Also, some carbon dioxide and hydrogen are converted to acetate by the acetogens according to the main acetogenic reactions considered below 1 1 41 : Reactions 11G 0 (kJ) CH 3 Coco ; + H 2 O CH 3 co ; + CO 2 + H 2 -52 (Rxn 5) 2CO 2 + 4H 2 CH 3 co ; + H + + 2H 2 O -95 (Rxn 6) 2Hco ; + 4H 2 + w CH 3 co ; + 4H 2 O -105 (Rxn 7) C 6 H 1 2 O 6 + 4H 2 O 2cH 3 co ; + 2Hco ; + 4W + 4H 2 -206 (Rxn 8) C 6 H l2 O 6 + 2H 2 O 2CH 3 co ; + 2H + + 2CO 2 + 4H 2 -216 (Rxn 9) C 6 H l2 O 6 3CH 3 co ; + 3W -311 (Rxn 10) In the third and final s tage of the fermentation process methanogenic bacteria convert acetate to methane and carbon dioxide by decarboxylation, and the latter to additional methane upon reaction with hydrogen according to Reference 14: Reactions 11G 0 (kJ) CH 3 co ; + H + CH 4 + CO 2 -36 (Rxn 11) CO 2 + 4H 2 CH 4 + 2H 2 O -131 (Rxn 12) HCO ; + W + 4H 2 CH 4 + 3H 2 O -136 (Rxn 13) In the three stages described above CH 4 H 2 and CO 2 are in the gaseous state. In addition the standard physiological conditions are atmospheric pressure, unit activity and a temperature of 25 C at a pH of 7 .0. 114 1 As evidenced by the reactions there are a number of intermediate acids gen erated. Since all reactions do not go to completion a certain amount of these compounds builds up within the bioreactor changing the solution pH, poisoning the bacteria or inhibiting the digestion rate s. Since the bioreactor usually takes days to dige s t the initial charge of biomas s an equilibrium is established between the vapor and liquid phase s in which the compounds partition. The information presented thus far on biochemical reactions taking place in the bioreactor can now be applied to solve the problem at hand. One unique feature of this type of problem is the dynamic nature of the system That is, starting the s ystem with an initial charge results in changing stream composition while steady state is achieved. This requires students to develop a solution that is iterative in nature and exposes them to realistic processes in industry, where thought must be given to system s tartup and shutdown as well as adjustments that must be made on the way to a targeted operational condition As was previously discussed, the 261 PAGE 20 ( Graduate Education problem statement is open-ended; therefore, there are several possible approaches and solutions. ONE STUDENT S SOLUTION A computer solution was created in Mathematica to perform the calculations described in the Background and Theory section, and can be obtained, in Mathematica format, upon request. Tr aditional Bioreactor The objective of this project was to determine if it is possible to increase the total power that may be harnessed from a traditional bioreactor system. Therefore, the logical starting point is to calculate the amount of power actually generated from a traditional system, which consists solely of a batch bioreactor set to operate in the mesophilic 30 C 38 C temperature range, at a pH within the range 6.67.4 to maintain the proper alkalinity. Furthermore, a high-rate digestion is assumed, and an appropriate residence time of 10 days is s pecified. The volume of the reactor is estimated using values from the literature ,1 1 1 and it is assumed that ap proximately two-thirds of the total volume is charged with an initial amount of municipal solid waste (MSW). The MSW is simplified to a 50 % (by weight) glucose suspension in water, and its volume, along with the density of the waste (a weighted density of water and glucose), allows the calculation of the total amount of MSW in the reactor or the total amount of glucose initially charged (S 0 ). Once the initial amount of glucose is calculated, three sets of reactions (Rxn 1 -13) are assumed to occur, and the resulting biogas (vapor product stream) may be evaluated. Its composition (which is directly proportional to the power generated) is noted This will serve as the control to which all subsequent biogas compositions will be compared. C atalytic Reforming Reacto r The next aspect of the solution is the introduction of addi tional equipment (the catalytic reforming reactor and the shift reactor) that along with the bioreactor constitute a modified system that may be used to meet the objective of increasing the total power harnessed as specified in the problem state ment. The product stream from the bioreactor is split: 90 % i s sent to a power generation plant, and the remaining 10 % is routed to a catalytic reforming reactor which is brought online to generate hydrogen that will be fed continuously to the bioreactor. Hydrogen is used by the bacteria in the bioreactor as an electron donor for methanogenesis In most cases, the hydrogen is the limiting reactant. Therefore feeding hydrogen to the bioreactor may help to accelerate the decomposition of the biomass and generate a higher flow rate of methane and carbon dioxide. This was one of the major outcomes of the investigation That is, once the student developed the 262 ) computer routine that accurately predicted the performance of the system it w as discovered that under several sce nario s the hydrogen fed back to the bioreactor was completely consumed long before the other s ub s trates. This result bring s into question the entire concept of feeding a warm stream of hydrogen to accelerate the digestion process. In addition to the 10 % split, an air s tream is fed to the catalytic reforming reactor The air s tream provides the oxygen nece ssary for a partial oxidation reaction which will produce (among other things) the desired hydrogen. In order to maximize the concentration of hydrogen in the catalytic reforming reactor 's product stream, the equivalence ratio ( cp) of the system is varied, a nd the effect on product composition observed. The equivalence ratio is defined as: <1J = (F / A) ac tu a l { F / A) s toichiometric (1) where F I A= the fuel (CH 4 ) to air (0 2 ) ratio After te s ting various eq uivalence ratios, an cp = 3.0 i s cho se n and a partial oxidation reaction follows: 4CH 4 (g) + 2.670z(g) + 10 0N 2 (g) 0.449CO 2 (g) + 3.55CO(g) + 0 901H 2 O(g) + 7 21H 2 (g) + l0.0N 2 (g) (Rxnl4) The stoichiometry of the above partial oxidation reaction was obtained through the u se of the thermodynamic equilib rium software, GasEQ. 117 1 At the adiabatic flame temperature (1020 K), Rxn (14) ha s an equilibrium co nversion X of e q 0 9969. Shift Reacto r The effluent of the catalytic reforming reactor contains a significant amount of CO, which is toxic to the bacteria within the bioreactor In order to avoid feeding this CO to the bioreactor a s hift reactor is added to the process after the catalytic reactor, and before the bioreactor to convert, or shift, the CO to CO 2 according to: CO(g ) + H 2 O {::}CO 2 + H 2 (g) ( Rxn 15) The benefit s of s hifting the CO to CO 2 are two-fold. First it removes the entire amount of poisonous CO from the bioreactor feed s tream Second it provides the bacteria with the other spec ies necessary for methane production carbon dioxide (the first spec ie s being hydrogen) Modif i ed Bi o r e actor The next step in the so lution involves returning to the bioreactor (w hich will now be referred to as the modified bioreactor). Thi s bioreactor operates as a semi-batch reactor since the waste that is decomposed by the bacteria is charged Chemical Engineering Education PAGE 21 ( in as necessary (this is dictated by the residence time) while the stream of hydrogen and carbon dioxide produced from the other reactors (ca talytic reforming and shift) is fed continuously. The same assumptions as in the traditional sys tem regard ing the MSW are made, and once the total amount of glucose initially charged is calculated, it is further assumed that at the end of the charge life all of the glucose will have decom posed, reaching a final concentration of S l = 0. Assuming a residence time of 10 day s, which is typical for high-rate anaerobic digestion and assuming that glucose decomposes at a constant rate throughout the 10-day period, the rate of glucose decomposition may be calculated and compared to the continuous flow ofH 2 and CO 2 that is fed to the bioreactor since both will be on a time ba s is. The initial charge of MSW is allowed to start decompos ing before the external H 2 and CO 2 stream is fed into the bioreactor, and for a duration that is sufficient to allow all of the fermentative and mo s t of the acetogenic reactions to occur As this decomposition approaches the end of the ace togenic stage and the beginning of the methanogenic stage, the continuous feed ofH 2 and CO 2 is introduced. The benefits of introducing this external feed stream into the bioreactor are three-fold : first the H 2 and CO 2 provide an immediate electron and carbon source for the bacteria ; second, the gas stream increases the contact area between the bacteria and the available food sources; and third, since the external feed stream is at an e l evated temperature, it enhances the digestion rate within the bioreactor. As this stream feeds into the bioreactor the so lubilities of it s components in water must be considered. Mo s t of those (N H 2 and the acid vapors) are gaseous and insoluble in wate~ The solubility of CO is of particular intere s t, however as it is dictated by the carbonate system. When CO 2 enters an aqueous solution, the following dissolution and dissociation occur: K H K m K a CO 2 (g)c;,CO 2 (aq) c;, H 2 CO 3 (aq) c;, HCO ~ (aq) (Rxn 16) The initial concentration of the CO entering the bioreactor is used along with Henry 's constant, Kw to find the concentra tion of CO 2 (aq). The l atter i s then used in combination with K '" to find the concentration of carbonic acid H 2 CO 3 The concentration of H 2 CO 3 along with K a and the pH of the system, are used to find the concentration of the bicarbonate ion HCO 3 Once the concentrations of CO /a q) H 2 CO 3 and HCO 3 have been calculated, the remaining concentration of the CO /g) is tabulated. Acid Phase Distribution As the remaining acetogenic and methanogenic reactions take place CH 4 and CO 2 are continually produced, whi l e Fall 2006 Graduate Education ) most of the other components are consumed. The exceptions to thi s are the acid byproducts-acetic butyric, and propionic acids-produced in the fermentation and acetogenic reactions and if their levels in the liquid continue to increase, the alkalin ity of the bioreactor will change. As a re s ult the pH may drop outside of the allowable range for methane fermentation. In order to find the distribution of acids between the l iquid and vapor phases chemical thermodynamic concepts are applied using the assumptions s ummarized in Table 2 (next page) The first concept used is the equilibrium criterion : fML =f MV .I .I (2) The fugacity of component i in a liquid solution is related to the mole fraction x;, according to the following equation f ~_; = X ; Y ; (T,P,x;)( 0 (T,P) where Y ; = the activity coefficient (3) ( 0 = the fugacity at so me arbitrary condition known as the standard s tate In this so lution, the standard state is assumed to be that of the pure substance and the fugacity of the standard state is defined as: I I I 1 VdP R T f o ( T P) = p_ sa1 ( T) ,a, _e u I I lpl (4) The Poynti!];g pres s ure correction factor and the fugacity coefficient, 'P, are ass umed to be negligible (i.e., they equal unity ). Another term in the s tandard state fugacity is the vapor pressure for the pure liquid P s at (T), which can be calculated using the Antoine Equation 1 The final term needed for the liquid phase fugacity i s the liquid mole fraction In this system, the only nongaseou s components formed from the bioreactor reactions are water and organic acids, which are assumed to be produced as byproducts in a supernatant layer that is separate from the sludge. Thus, the original liquid mole frac tion i s known and the liquid phase fugacity for each compo nent may be calculated Once the standard state fugacity is known, the next step in obtaining the liquid phase fugacity is to calculate the activity coefficient, Y ,, which is a funct i on of composition, tempera ture and pressure as seen in Eq. (3) Unless the pressure is very high, however, its effect on the activity coefficient may be neglected as i s done in this solution and the van Laar equation used to calculate the activity coefficients. The fugacity of component i in a gas mixture may be related to the fugacity of pure gaseous i at the same temperature and pressure by the following relationship, 263 PAGE 22 ( Graduate Education ) 26 4 TABLE2 Summary of Thermodynamic Model Ass umption s Liquid Phase Assumptions Justification I) The Standard State is that of the Pure Substance ... 2) Poynting Pressure Correct i on Acco unt s for s ituations where the actua l sys tem Pct P "' Since it is an exponential funct i on p of P it is small at l ow P s. The bioreactor i s operated at l ow Ps, therefore the Poyntin g I 1 correction factor i s assumed to be a ne g li g ible term which was confirmed by preliminary Y dP RT calculations. Factor= 1 e r ta t is negligible 3) The saturation fugac it y coefficient cp ;"' = 1 Corrects for devi at ion s of the saturated vapor from idea l gas behavior 'P ;"' differs considerably from I as T n ""' is approached. Since the T of the system i s n ot near any of the components critical Ts, it is assumed that this term equa l s unity 4) The activity coefficient, Y;, is n ot a function of P The activity coefficie nt becomes a function of Pat very high pressures. Since the system P i s l ow, this term i s primarily a function ofT and composition. 5) The activity coefficient is calcu l ated from the The van Laar equat i on i s typically used for binary sys tem s. When it i s em ploy ed however van Laar Equation the co n centra ti ons of all other components are so s mall that a binary sys t e m ca n be assumed. Vapor Phase Assumptions Justification 1 ) Lewi s Fugacity Rule app li es (f; = Y ; fP""') The LFR assumes that at a fixed T and P the fugacity coeffic i ent of species i i s independent of the composi ti on of the mixture and is independent of the natur e of other com pon ents in the mixture. The LFR relie s o n the assumption that Amagat s rule is valid over th e e ntir e range of pressures from O system P. The LFR is a go od approximation at s uffi c iently l ow Ps where the gas phase is ide a l as is the case in this system. 2) The pure fug ac ity coefficient 'Pp, re.; and mole For a pure ide a l gas the fugacity i s equal to the pressure (i.e the fu gaci ty coefficient and fraction y P "_; = 1 mole fraction are both 1 ). It i s assumed th at the sys t em follows idealgas behavior because it is at low pre ss ur e, th erefo re the coefficient is se t to unity The mole fraction i s unit y because the spec ie s i s pure F Ai, =1.94 Bioreactor (.) ... :;::; 0 >(.) n, n, 6305 m 3 T = 86 F P = 14.7 psia Liquid Draw Off F Acids = 1 13 F wate, =0 722 F co 2 =1 943 ....................... FH 2 = 0 905 F CH4 = 0.00253 F co = 0 Q) 8 et:: Power Plant Air F[=] lbmol/min Figure 2. Flow rates (in lbmollmin) of major components usin g modified system. Chemical Engineering Education PAGE 23 C Graduate Education ) TABLE3 Mathematica Model: Traditional vs. Modified Bioreactor Traditional BR CH Produced lbmo l/m in 7.65 CH 4 Sacrifi ced lbmo l/ min -CH Sent to Power Plant 7 65 lbmo l/m in Biogas CH / CO 0. 89 / 1 f MV ( T p y ) f p RTln '' = (v -v)dP Y/ purc( T P ) 0 (5) To more easily so lve for the va por phase fugacity e ither an equation of state or the principle of correspo ndin g states with a simplifying assumption s uch as the L ew i s Fugacity Rule may be used According to thi s rule the fugacity coef ficient of i i s independent of the composi tion of the mixture and of the nature of the other components of the mixture at constant temperature and pre ss ure. As a re s ult the fugacity of component i in a vapor mixture is expressed as : f ~_i( T P,y ;) = y i -f purei ( T P ) = y i l.j) ) (6) where l.fJ = the vapor phase fugacity coefficie nt of component i in the gaseous mixture The pure pha se fugacity is determined using an equation of state s uch as the van der Waal s equation. Although the van der Waals equation, s hown below is the si mple st non trivial equation of s tate it pro v ide s a r easo n ab le estimation of volumetric behavior of th e vapor phase: ( ln [ [ -v, l l-a' +[ ~1 ]1n [~ ] R T n = e v,b, R-T v, RT R T where v = __ + b .,.,, I p I RT (7) In this solution l.fJ was calculated and was clo se to unity Once all of the terms in both the liquid and vapor pha se fugacities have been tabulated the criterion for equilibrium may be written as: Eq. (8) i s used to solve for the composition of the vapor phase and allows the calculation of the composition of the liquid phase in equilibrium with this va por. RESULTS While not all s tudent s followed the above dev e lopm e nt the results obtained from the students were ge nerally sa tisfactory, Fa/l 2006 Modified BR Sing le Pa ss 8. 16 0 7 65 7.40 0.72 / 1 in that most of th e m analyzed the entire system Figure 2 de pict s th e flow rates (i n lbmol / min ) of the mo s t important com ponent s as they move throu g h the modified sys tem in a single pass a nd Tabl e 3 illustrates how the external feed s tream of H 2 and CO 2 ( i .e th e modified sys tem ) affects the power ge nerated and s ummarize s the comparison of the traditional a nd modified systems The result s s hown in Table 3 indicate that the c urrent modifi ed sys tem does meet the objective of accelerating the decompo s ition of the biomass by producing more m e thane: 8.16 lbmol/min vs. 7.65 lbmol/min produced from the modified biorea c tor and the traditional bioreactor respectively Although th e quantity of the methane produced increase s in the modified sys t e m the qualit y of the bioga s ( defined as CH 4 to CO 2 ratio) decreases from 0.89 / 1 to 0.72/1 in th e traditional an d modified sys tem respectively COURSE ASSESSMENT Once the projects were s ubmitted the s tudents were asked to asses s the overall success of the ass ignment. The student a n swers to qu es tions 2 a nd 3 indicate that they overwhelm in g ly found the project to have enhanced their understanding of thermodynamic s ( n = 8). In Table 4 ( next page ), a score of 5 indicates ag r eeme nt wi th th e s tatement and 1 indicate s disagre e ment. In addition to th e four questions li s ted in Table 4 s tudents were asked for their comments on two other topics When a nswering the question, "What sources (e.g., World Wide Web online libraries handbook s publications) were useful in obtaining thermodyn a mic data bioreactor information, etc .?," s tudent s li s ted a variety of so urces including the Web ( mor e spec ificall y and Web sites linked to c hemic a l engineering departments at large universities, e.g., Texa s A&M) Students a l so indicated the u se of the Manhattan College and Columbia University online libraries Vapor / Liq uid Equilibrium Data handbooks the research article s handed out with the assignment and microbiology and bioreaction e ngin eeri ng textbooks. In their answer to the que s tion, Did you pro gra m the s olution yourself or use a computer program in your so lution ? If computer pro gra m was used which one a nd w h y?," s tudents reported u s in g a variety of program min g t oo l s includin g Mathemati ca (es pecially for it s useful indexin g feature and for repetitive and iterative calculations) 265 PAGE 24 ( Graduate Education ) TABLE4 Course Assessment Question 5 1. Overall do you fee l that the cla ss l ectures 12.5 % a nd homework provided yo u with the nece s sary background for deve l oping a so luti on to the co mputer proje c t ? 2. Did the comp ut er project g ive yo u a b e tt er 1 2.5 % under s tanding of thermodynamic princip l es s uch as fugacity so lu bi lit y, and multi-pha se eq uilibrium and how they are u sed in practica l s ituation s? 3 Was th e computer p ro j ec t a relevant 75% practical a nd open-ended app li cat i on of the principle s taught in the class ? 4 Did th e computer project en h ance your 1 2.5 % re sea rch s kills ? Excel (fo r both programmin g a nd grap hin g), and the Pro/II Simulation Pack age. CONCLUSIONS Thi s p a per pr ese nted the results of one s tudent 's work for a c l assr e quired computer proj ect. Model results va lid tionu si n g Pro/II and an ex p er iment a l anaerobic bioreactor i s the s ubject of another s tudy in preparation. The require ment g iven to the s tudent s was to only use th e thermodynami c co ncept s l earne d during th e semes t er to a nal yze a nd propo se a feasible so lution to a current e nvironment a l or indu s trially s i g nificant problem The outcome of s uch an exercise allows s tudent s to apply so metim es-a b s tra c t thermodynamic con ce pt s to an important problem while training them to focus on the bi g picture : how to find a so lution to the problem. An a dditional ben e fit is that s tudent s obtain an appreciation for what co mmercially available th e rmodynamic packa ges involve, as well as their capabilities, s ince s tudents find th e need to o btain property information not found in literatur e. Also, th e exe rci se g ives st udent s a se n se of acco mplishment in that they applied the principle s of thermodynamics to analyze a nd propo se feasible, reali s tic so lution s to problems they ma y e ncounter during their careers. Lastly, as the need for renewabl e e nergy s ource s grows, research a nd development will require a workforce that i s well educated and trained to develop the technologie s nece s sary for a s u s tainable futur e. The example pre se nted in thi s paper demon s trate s that s uch trainin g i s po ss ible through an in-depth approach to a soc ietal problem. It also se t s the s tage for furth er development of the chemical engineering curricu lum at Manhattan College to includ e g rounding in alternative 266 4 3 2 I 75 % 12.5 % 75 % 12.5 % 25 % 1 2 5 % 50.0 % 12 .5 % 12 .5 % energy so urce s and s u s t a inability following the call of J.W. Sutherl a nd e t al.,f' 9 of Michigan Technological University for the need for "g lob a ll y aware s tudent s." NOMENCLATURE f~ .i f~ i Fugacity of co mp o n e nt i in th e liquid mixture Fugacity of component, i in the va por mixture. Liquid phase mole fraction of species, i. Act i vity coeffic i ent of species i ,as a function of temperature pres s ur e a nd liquid ph ase mo l e fraction f; 0 ( T P ) Pure co mpon e nt fugacity of i in the liquid phase. V Vapor pressure of spec i es, i as a function of temp erat ur e. Fugacity coeffic i en t of th e sa turated vapor of spec i es, i. Molar vo lum e of the liquid (co nd e nsed ) phase Gas phase mole fract i on of spec i es, i. Tot a l pressure of the syste m Fugacity coefficient of s peci es, i. Equivalence ratio. REFERENCES I. Casta ldi M. L. D oraz io and N. Assaf-An i d, R elating Abstract Concepts of Chemical Engineering Thermod y namic s to Current, Real World Probl e m s, Chem. Eng. Ed., 38 (4) 268 (20 04 ) 2 Kau se r J K Holla r F. Lau E Co n s tan s P Von Lockette a nd L. H ead Gettin g Student s t o Think Abou t A lt ernate Ener gy Sources, ASE Annual Conference and Exposi ti on: Vive L ing e ni e ur, 4593-4600 (2 002 ) C h e mi ca l Engineering Education PAGE 25 C 3 Farley E.T., and D.L. Erne s t Applicati o n o f Power Generation Mod e lin g and Simulati o n to Enhance Student Intere s t in Thermod y n a ics ," Mod e lin g and Simulmi o n Pr ocee din gs of th e Annual Pitt s bur g h Conf e r e n ce 21 ( 3 ) 1275 (1990 ) 4. Cengel, Y.A. Intuitive and Unified Approa c h to Teaching Thermod y namics, Pro ce edin g s of th e ASME Advan ce d En e r g y S y stems Di v ision 36, 25 1 ( 1 996 ) 5 Lombardo S. Open-Ended Estimation Desi g n Project for Thermo dynamic s Student s," Chem. En g Ed 34 ( 2 ) 154 ( 2000 ) 6. Tsatsaronis G. M. Moran and A Bejan Education in Thermo dynamics and Energ y Systems Am e ri c an S oc i ety of M ec hani c a l Engineers Advan ce d En e r gy S y st e m s Di v i s i o n ( Publication ) AES, 20 644 (1990 ) 7. Reistad, G.M. R.A. Gaggioli A. Bejan and G. Ts a t s aronis Ther modynamic s and Energy Systems Fundamentals Education and Compu t er-Aided An a ly s is ," American S o ciet y of Mechanical Engi neers, Advanced Energy Sy s tem s Divi s ion ( Publication ) AES 24, I 03 (199 I ) 8 Shaeiwitz J.A. Teaching Desi g n b y Inte g ration Throu g hout the Curric ulum and A ss essing the Curricu l um U s ing Design Projects ," Int ernational J o urnal o f En g Ed. 17 4 7 9 ( 200 I ) 9. Garcia-Ochoa F., VE. Santos L. Nava l E. Guardiola, and B Lopez Kinetic Model for Anaerob i c Dige s tion of Live s tock Manure En z y m e and Mi c robial T ec hnolo gy, 25 55 ( 1 999 ) Fall 2006 Graduate Education ) 10. Jagadish K.S ., H N. Ch a nak ya P Rajabapaiah, and V. Anand Plug Fl o w Dige s ter s for Bia g a s Generation from Leaf Bioma s s Bioma ss and Bi oe n e r gy 14 ( 5 1 6 ) 415 ( 1998 ) 11. Ca s telblanque J. a nd F. Salimbeni Application of Membrane Sy s tem s for COD Removal and Reu s e of Waste Water from Anaerob i c Dige s ter s," D es alination 126 ,293 (1999) 1 2. Chem i cal Engineering" section About com < http : // www.abou t. com> 13. Prausnitz,J ., R N. Lichtenthaler, and E. Gome s de Azevedo Mole c ular Th e rm o d y nami cs o f Fluid-Phas e Equilibria Prentice Hall International Serie s Upp e r S a ddle River NJ ( 1999 ) 14. Kla ss D.L ., Bi o mas s f o r R e ne w abl e En e r gy Fuels and Chem i c al Academic Pr ess New York 452 ( 1 998 ) 1 5. Madigan M.T J. Martinko and J. Parker, Bro c k Biolog y of Mi c roor ganism s, Prentice Hall Upper Saddle River, NJ (2000) 16. Muller E A. Thermodynamic s Problem with Two Co nfli cting Solu tions, Ch e m. En g Ed. 34 ( 4 ) ( 2000 ) 17. Morley C. 18. Sutherland J W., V. Kumar J.C. Crittenden M.H. Durfe e, J.K. Gersh enson H. Gorman, D R. Hokanson N.J Hutzler D.J. Michalek, J R. Mihelcic D.R. Shonnard B.D. Solomon a nd S. Sorby, An Educa tion Program in Support of a Sustainable Future ," Ameri c an So c iety of M ec hani c al En g in ee rs, Manufa c turing Engineering Division 14 611 ( 200 3) 0 267 PAGE 26 ( Graduate Education ) Incorporating COMPUTATIONAL CHEMISTRY i nto the ChE Curriculum JENNIFER WILCOX Worcester Polytechnic Institute Worcester, MA 01609 I n many engineering curricula it is difficult to cover the fundamental concepts that are required to provide all students with an optimum base for the solution develop ment of new problems and applications. Although this ta sk is daunting replacing the learning and understanding of fundamental concepts with starting parameters and a list of equations to use as tools is not a so l ution Such an approach subsequently limits the capabilities and potential accomplish ments of the students. This trap is easy to fall into however si nce it is nearly im possible to cover all of the fundamentals in addition to the ap plications Yet a failure to emphasize these basics could mean putting emerging chemical engineers at a disadvantage against chemists or physicists who may be able to develop new ideas more readily because their training through education has taught them to derive the equations they are using. Engineers are typically admired for their ingenuity and creativity but with a curriculum that does not obligate them to derive and to consistently ask "why" and "from where," engineers will soon lose the merits for which they are so well known Within a graduate-level chemical engineering course, fun damental chemical principles combined with computational chemistry software were used as a tool to bridge the gap that often exists between chemistry and applications within the Copyrig ht ChE Divi s i o n of ASEE 2006 268 field of chemical engineering In the case of reactor design problems in which rate expressions mu s t be known activa tion energies and rate constants are typically provided as input parameters for a particular design equation. Since more sophisticated methods for approximating rate constants are not taught in traditional chemical engineering courses, the development of a rate expression was chosen as one of the main objectives of this computational chemistry course The theoretical calculation of a rate expression involves many tasks including the development of a quantum mechanical based potential energy surface ( PES) and the understanding of reaction kinetic tools such as transition state theory. Similar methodologies have emerged recently in the literature for as similation into graduate chemistry coursework. ri 2 1 The current methodology, however is different from its typical inclusion Jennife r Wilco x is an assistant pro fessor in the Chemical Engineering Department at Worcester Polytechnic Institute She received her B.S. de gree from Wellesley College in math ematics and her M.A. and Ph D from the University of Arizona in chemical engineering. Ch e mi c al En gi n ee rin g Edu c ation PAGE 27 C within a ch e mi s tr y c our se s in ce it h as b ee n in co rp o rat e d int o a chemi ca l e n g in e erin g c urriculum w h e r e it se r ves t o co upl e fundam e nt a l ch e mic a l prin c ipl es t o a p p li ca ti o n s in c h e mi ca l e n g in ee rin g throu g h a co mbin a ti o n of a b initi o th eo r y a nd r ea ction kin e ti cs. Durin g th e fa ll 2 0 05 se m ester thi s co ur se wa s off e r e d for th e fi r s t tim e in th e C h e m ica l E n gi n ee rin g Departm e nt a t W o r ces t e r P o l y t ec hni c In s titut e A s i x-week ass i g nm e nt t e rm e d Le a min g th ro u g h a R eac ti o n E xa mpl e ," s er v ed as th e m a in dri v in g fo r ce th ro u g h o ut th e co ur se a nd was r e fl ec t e d b o th in l ec tur e m a t e ri a l a nd st ud e nt exe r c i ses The cour se m e th o d o lo gy c arri ed o ut t o acco mpli s h th e goa l of brid g in g the ga p b e tw ee n fund a m e nt a l p r in c ipl es in chemi s try t o a ppli ca tion s in c h e mi ca l e n g in ee rin g i s se l f co nt a in e d in th a t it ca n b e a d o pt e d b y any i n s tru c t o r w i s hin g to a chi eve thi s goa l th ro u g h offe r i n g a s i m il ar c l ass wit hi n hi s / h e r d e p a rtm e nt. COURSE OVERVIEW Th e co ur se s p a nn e d 1 4 weeks a nd was h e ld for 1. 5 h o ur s t w i ce a wee k ; h o m ewo r k was ass i g n ed o n a wee kl y b as i s. The c our se was di v ided int o th e fo ll ow in g sec ti o n s w ith l ess than ha l f t a kin g pla ce out s id e th e co mput e r l a b : Pri n ci pl es by which ab initio based method s a nd basis sets a r e compr i sed. B ackgro un d of k ey fea tur es a nd co n ce p ts of qu a ntum m ec h a n ics ( QM ) w e r e t a u g ht. H o m e w o rk ass i g nm e nt s in clud e d th e fo ll o win g: m e th o d s u se d in so l v in g a p rox im a ti o n s t o th e S WE, e.g., varia ti o n a l m e th o d s a nd p e rturb a ti o n t h eo r y; class i ca l p ro bl e m s fro m QM e g p ar ticl e in a 1-D b ox; h ar m o ni c osc ill a t o r ; a nd th e h y d roge n a t o m H o m ewo r k ass i g nm e nt s throu g h o ut thi s aspec t of t h e co ur se r e qu ire d a b ac k gro un d in calc u l u s a n d differe n t i a l e qu a ti o n s A bri ef r ev i ew of co mpl ex nu m b ers a n d di ffe r e nti a le qu a ti o n so luti o n t y p es was g i ve n Th ese t o pi cs co mpri se d fo ur wee k s of th e co ur se, c u l min a tin g with a cl ose d-b oo k in -class exa m "Lea rnin g T hrou g h a R eact i on Exam pl e Thi s ass i g nm e nt includ e d fi ve wee kl y p ro j ec t s a nd a t a k e -h o m e exa m th a t req uir ed s tud e n t s t o comp il e th e indi v idu a l co mp o n e nt s int o th e fo rm of scie tifi c p a p e r s (s o th a t s tud e nt s c ould ga in fa mili a rit y with writin g in a sc i e ntific mann e r ) A n a ddition a l manu sc ript i s b e in g s ubmitted fo r pub l i ca tion th a t d esc rib es furth e r d e t a il s a nd r es ult s of thi s ass i g m e nt pur e l y t h rou g h th e s tud e nt s' p e r s p ec ti ve .13 1 In a dditi o n s tud e nt s r e fl ec t o n eac h of th ese Fa /1 2006 fo ur sec ti o n s of t h e co u rse in d etai l d eter minin g w hi c h exe r c i ses we r e mo r e b e n eficia l t h a n o th ers Graduate Education ) a nd w h y Throu g h o ut th e L ea rnin g Thr o u g h a R eac ti o n Exa mpl e" topi c a co mbin a ti o n of l ec tur e a nd int erac t ive l ear nin g th ro u g h co mput t i o n a l in-cl ass l a b exe r c i ses was u se d i. e., u s in g t h e Ga u ss i a n 98 sof t ware p ackage for e l ec t ro ni c e n ergy p re d ic ti o n s. Ex t rac ti o n of th ese e n e r g i es co mbin e d w ith r eac ti o n kin e ti c t oo l s s u c h as p o t e n t i a l e n ergy s u rface d eve l o pm e nt a nd tr a n s i t ion s t a t e th eory (TS T ) l e d t o t h e d eve l o pm e n t of ra t e express i o n s. T o e n s ur e m as t ery of th e so ft ware, a n i n-cl ass, co mput er -b ase d exa m was g i ve n seve n wee k s int o th e co ur se, i.e. thr ee wee k s a ft e r th e sof t wa r e was int ro du ce d Fina l p r oject. Durin g t h e l ast fo ur wee k s of th e co ur se s tu den t s were asked t o c h oose a t o pi c for a fi n a l p ro j ect. It was r e qui re d th a t th e fi n a l p ro j ec t r e l a t e t o a s tud e nt s r es ear c h proj ec t i.e., within t h e i r se ni or th es i s M.S th es i s o r Ph.D. di sse rt t i o n Th e goa l of thi s fi n a l p ro j ect was t o a ppl y th e co mput a ti o n a l a n d ki n e ti c t oo l s l ear n e d th ro u g o ut th e c ou rse t o a n as p ec t w ithin th e ir c h e mi ca l e n g in ee rin g r esea r c h. In so m e cases, th e r esea r c h area of focus r eq u ire d a n a d va n ce d b ac k gro und in mo l ec ul ar modeling th at t h e co u rse was n ot a bl e t o prov id e in j u st 14 weeks, a n d in th ese cases th e s tud e nt s ga in e d m as t e r y of th e lit era tur e ava il a bl e o n th e c omput a ti o n a l c h e mi ca l as p ec t o f th e i r researc h. A d di ti o n a ll y, th e s tud e nt s u se d w h a t was l ea rn e d from t h e co ur se t o p rov id e in s i g ht int o th e c h e mi ca l m ec h a ni s m s th at m ay pl ay a ro l e in th e exp l a n a ti o n of ex p e rim e nt a ll y o b se r ve d ph e n o e n a Th e goa l of t hi s fi n a l exe r c i se was t o p rov id e a way t o eval u a t e s tud e nt s un de r s t a n d in g of th e ma t e ri a l w ith a meas ur e of th e co ur se s u ccess de p e ndent up o n w h e th er a s tud e nt was a b l e t o ef fec ti ve l y a ppl y k n ow l e d ge ga in ed fro m th e co ur se t o th e ir r esea r c h in a n ove l way. So m e exa mpl es of t hi s a ppli ca ti o n includ e: E l ec tr oc h em i ca l wa t er gas s hi ft r eac ti o n s o n pl a ti n u m a n d rutheni u m ca t a l ysts A pplication : fu e l ce ll c h e mistr y A d so rp t i o n m ec h a ni s m s of MTB E, c hl o ro fo rm a nd 1 4 -diox a n e w ith ca ti o n s App li ca t ion sepa r a ti o n of con t amina nt s from g rou n dwa t e r using z eo li te s M ec h a ni sm deve l o pm e nt of s ulfur s ro l e in p o i so i ng p a ll ad iu m App li cation h y d r o g en s e paration us i ng pa ll adium m e mbran es 269 PAGE 28 ( Graduate Education With regard to several of the student projects-such as the one involving the application of ab initio theory for modeling complicated catalytic processes s uch as those involved in fuel cell researchthe student completed the final project with an understanding of the computational literature in this field and a visua l interpretation of the mechanjsms involved within the comp l exities of the process which will likely benefit hjm by providing focused direction when deciding which experiments to carry out in the lab. This theoretical understanding became the goal oftrns student's project since heterogeneous modeling was o ut side the scope of the course. With respect to the sec ond project listed above, the student used ab initio energetic predictions along with electrostatic potential and molecular orbital maps to und erstand the reactivity between groundwater contaminants and zeolite exchange ions. This student has since had a paper accepted a nd has presented her research at the International Conference in Engineering Education in Puerto Rico in July 2006. 14 1 Therefore the measure of success spans a wide range, whether it is based on the direct inclusion of ab initio-based calculations in a student's work or based on an appreciation and understanding of the ab initio language to a level that allows for material retention from a peer-reviewed art icl e within the student s specific research area If one wished to integrate molecular modeling and compu tation a l chemistry technjques into a graduate curricu lum to supp lem ent the chemical engineering background tradition alJy acquired, carrying out this reaction assignment would ens ur e student ma s tery of the computational tools necessary for incorporating a molecular per s pective into their graduate research. Therefore, it is this aspect of the course that wilJ be described in detail within this article. COURSE SPECIFICS In the Learning Through a Reaction Example assign ment e l eme nt ary gas-phase reactions were considered for a complete thermodynamic and kinetic analysis The goal was to produce a high-level potential energy surface based upon ab initio energetics, and to derive accurate rate expressions for the reaction using transition state theory Computational-based ab initio techniques were emp lo yed to solve approximations to the Schrodinger wave equation (SWE), whjch describes the loc ation and energetics associated with the electrons in a given system. The level of theory chosen to investigate the species within a given reaction requires two components, i.e a mathematical method to solve the approximation to the SWE and a wave function (spatial description of the electrons in space) This computational chemistry course was highly techn logically based with approximately two-thirds of the classes 270 ) involving active learning through the use of computers Stu dent s used the sof tware package Gaussian98 151 to calculate the electroruc ener g ie s from approximations to the SWE. To visualize vibrational frequencies, chemical bonding electron density maps and molecular orbital maps, gOpenMol soft ware was emp lo yed. In a traditional course in introductory chemistry these topic s are covered in detail but oftentimes teaching s tudents about them is difficult due to the underlying abstract quantum chemis try involved. Using the visualiza tion software the s tudents were responsible for developing electron density and molecular orbital maps to gai n under standing into th e c hemical reactivity of various species Straightforward molecules such as water and methane were introduced and in additional assignments students explored molecules of increa s ing interatomic bonding complexity such as cyclohexane and 1,4-dioxane. For the development of the quantum mechanical-based potential energy surfaces, MATLAB software was used A Sun Microsystems Sun Fire V20z se rver with a du a l AMD Opteron 64 bit processor and 4 gigabytes of memor y with a 73 gigabyte hard disk was devoted s pecific a lJy for the course. The software program Web MO 4 1 was us ed as an interface to s ubmit jobs to Gaus s ian98 through the Sun server. Students were able to submit their calculations to the server s uch that the local desktop computers could remain active throughout each class period; this also provided s tudents with the flexibility to work on homework assignments and s ubmit jobs from any computer with Internet capabilities. DESCRIPTION OF REACTION ASSIGNMENT One of the folJowing elementary gas pha se reactions was assigned to each pair of students in the class. H 2 + Cl -> HCl + H D 2 + Cl -> DCl + D H 2 + F ----> HF + H D 2 + F ----> DF + D F 2 + H ----> HF + F ( 1) (2) (3) (4) (5) Two students inve s tigating the same reaction were doing so for validation of the molecular results generated with each investigation being performed at a unique level of theory, i. e., method and basi s se t combination. Stea One: Student s were asked to retrieve experimentally based chemical propertie s of the s pecies within their assigned reaction in addition to experimental thermochemical and kinetic data for the total reaction The chemical properties included equilibrium bond distance s, vibrational frequencies Ch e mi c al En g in ee rin g Edu c ation PAGE 29 C dipole moment s, and rotational constants. Seeking the se experimental data required s tudents to gain familiarity with standard references s uch as JANAF' 61 tables, the Handb ook of Chemistr y and Ph ys ics, 171 a nd H erzbe r g spectrosco p y texts. 181 The ex periment a l thermochemical data includ ed reaction enthalpies, entropies, Gibb s free e nergie s, and equilibrium constants u s ing the NIST Chemistry Web Book. 191 To locate experimental kinetic data for the reaction students were encouraged to perform lit erat ure sea rche s in addition to accessing th e data ava ilable in the NIST kinetic databa se. 1 9 1 Step Two: Within this step of the assignment s tudent s per formed geometry optimization and s pectro sco pic calculations on their assigned reaction spec ie s. They were required to perform the calculations at varying le ve l s of theory, includ ing the den s ity functional method i .e., Becke-3-parameter Yee-Lang-Parr (B3LYP), as well as Hartree-Fock and the second order perturbation method-Moller-Plesset (M P2 ) Additionally, higher electron-correlated methods s uch as quadratic configuration interaction ( QCI ) a nd coupled cluster Graduate Education ) (CC) techniques were also explored. Both Pople a nd Dunning basis se t s were considered with each of these calculational method s. The complexity of the basi s sets assigned ranged from minimal-such as the double-zeta Pople ba s is set, 6-31 G-to more extensive including both diffu se a nd po larization functions-such as the triple-zeta Pople basis set, 6-311 ++G **. Students were assigned nine levels of theory for the energetic and spectroscopic predictions, and asked to consider three additional others. Step Three: Within thi s s tep students compared their theoreti cal predictions to the experimental data that was compiled in step one of the assignment. It is this aspect of the assignment that allows the students to be in control of their learning; they are able to see how well a chosen level of theory agrees to experiment. There i s flexibility as well s ince the students are asked to choose three levels of theory to consider in addition to those assigned. An examp l e of equilibrium geometry and spectroscopic predictions for Reaction (2) is shown in Table 1 Thermochemical predictions including reaction enthalpies, entropies, and Gibb s free energies, at varying levels of theory TABLE 1 Compariso n of Chemical Properties of Species from D 2 + CI DCI + D Bond Vibrational Dipole Rotational Theory Length Frequency Moment Constant (Al (cm') ( Debye) (cm ') DC! D DC! D DCI DCI D 83LYP / LANL 2DZ 1.3 1 49 0.7435 1943 3153 1.80 5.11 30.28 HF / 6-31G 1.2953 0.7297 2097 3289 1.87 5.27 31.44 HF / STO-6G 1.3112 0.7105 2097 3886 1.77 5.14 33. 16 MP2 / 6-31G 1.3174 0.7376 1970 3206 1. 88 5.10 30.77 MP2 / 6-3ll+G 1.3269 0.7376 1 943 3 1 49 1.89 5 02 30.77 MP2 / 6-3 I I +G(d p ) 1 .273 1 0.7383 22 14 3206 1.44 5.46 30.7 1 MP2 / 6-3 I +G 1.2810 0.7375 2177 3206 1.53 5.39 30.77 MP2 / 6-3 l I (3df 3pd) 1 .272 0.7367 2 1 90 3 1 95 1.17 5.47 30.84 QCISD / 6-31G 1.3262 0.7462 1901 3089 1.8 8 5 03 30.06 QCISD / 6-3 I I +G 1 .3262 0.7465 1875 30 1 8 1.71 5.03 30.04 QCISD / 6-3 I I +G ** 1 2758 0 7435 2183 3 1 26 1.33 5.43 30 .28 QCISD / 6-311 ++G ** 1 .2762 0.7435 2 1 81 3126 1.32 5.43 30 29 CCSD / 6-31G 1.3261 0.7462 1 90 1 3089 1.88 5.03 30 06 CCSD / 6-31 I +G 1 .336 5 0.7465 1 876 3018 1.89 4.95 30.0 4 CCSD / cc-pVDZ 1 2905 0 7609 2144 3100 1.16 5.31 28.91 CCSD(T) / 6-31 IG ** 1 .2772 0.7435 2174 3127 1.46 5.42 30.28 CCD / a u g-cc-pVDZ 1.2897 0 .76 10 2151 3084 1.16 5.32 28.90 CC D / cc-pVTZ 1.2 7 48 0.7421 2172 3 1 27 1.18 5.44 30.39 Experimental 1.2746 0.7420 2145 3116 5.44 30 44 t R ef 17 8 1 Fall 2006 271 PAGE 30 ( Graduate Education are presented for Reaction (5) in Table 2 In mo s t cases, the st udent s wou ld choose more than three additional l evels of theory for investigation in an effort to obtain a theoretical prediction with minimal deviation from experiment. Within thjs step of the assignment students learned how the add iti on of polarization and diffuse functions to a basis set ca n influ ence the theoretical predictions Of course l ecture material incl uded a discussion of the details of methods and basis sets ; however, the interactive experience of testing, checking, and 1 8 1 6 fi.F 1.4 1.2 0 7 0 75 0 8 0 85 0 9 0 95 1 H-H 1 05 1 1 1 15 1 2 Figure 1. PES for the reaction H 2 + F--t HF+ H g enerated at the QCISD / 6-311 G( 3 df 3pd) level of theory TABLE2 ) comparing to experiment was far more valuable allowing these concepts to sink in to a deeper level of understanding from the student perspective. Class at thjs time included dis cussions concerning the difference in accuracy of the various levels of theory and the reasons associated with why some levels work better than others. Additionally discussions also included why at times some levels of theory work but not necessarily for the right reasons, i e. cancellations in error could provide a reasonable heat of reaction prediction in one case but may deviate from experiment in terms of the predicted equilibrium geometry The goal of matching the ex perimental data provided a motivation for the students to push forward through obstacles that are typical of a traditional lec ture-formatted curriculum For example, traditional teaching methods such as Microsoft Office PowerPoint presentations or conventional rote lectures tend to neglect participation of the students con s equently allowing their minds to wander losing the ability to grasp the material at hand. Providing a motivated student with an objective and the responsibility for his or her own learrung through a series of interactive exercises ensures active participation which undoubtedly enhances the likelihood of material retention. Sten Four: This step involves the development of a high level potential energy surface (PES) For a student to proceed with this step two criteria must be met i.e., students must first choose a level of theory that accurate l y predicts the heat of reaction and equilibrium constant. Once a student obtains a level of theory which predicts a heat of reaction to within 2 kcal/mo) to experiment and an equilibrium constant to Thermochemistry Comparison for F 2 + ff --. HF+ F within an order of magnjtude of experiment, he or she can proceed to develop a PES at this chosen level of theory. A PES genera ted from the class for Reaction (3) at the QCISD/6-311G(3df,3pd) level of theory is presented in Figure 1 The software program MATLAB was employed for the PES plots. Most of the surfaces generated in the class consisted of approxi mately 200 single-point energies Since the reactions assigned were all elementary gas-phase reactions involving at most three atoms the large s t transition structures were three-atom complexes. It was assumed that each ac ti vated complex was linear so that two degrees of freedom could be con sidered along two dimensions of the Theory H "" (kcal/mol) B3LYP/LANL2DZ -91.61 HF/6-3IG 121.20 MP2 / 6-31G -82 76 MP2 / 6 3ll+G -91.99 MP2 / 63 1 I +G ( d p ) -103 .8 QCISD / 6 31G -84 5 2 QCISD / 6-3ll+G -94 24 CCSD / 63 I G -84 65 CCSD / 6-3 11 +G 94.44 CCSD / au gcc-pVDZ -I 04.4 CCSD ( T )/ 63 1 IG ** -98 96 QCISD ( T )/ 6-311 G ** -98 92 Experimenta tl -98 2 7 tN umb e r s in pa r e nth es i s de n o t e powe r s of J O. :f: R ef {6 9 1 5 ] 272 s G rxn nm ( cal/mol K) (kcal/mol) 1. 8 41 92 16 1. 9 04 1 2 1.7 1. 6 77 -8 3.2 6 1.586 92.46 1.7 8 7 -104 3 1 578 -84.99 1.510 -94 69 1.577 -85.1 2 1.51 3 -94. 8 9 1.79 8 -104 9 1.607 99.44 1.61 2 -99.40 3. 596 -9 9 3 4 K t "' 3 87( +67 ) 2 01 ( +89 ) 1.16 ( +61) 6 4 8 (+67) 3.44 ( + 76 ) 2 .14 ( +62 ) 2.82 ( +69 ) 2. 68 ( +6 2) 3.9 1 ( +69 ) 9 08 ( + 76 ) 8 .56 ( + 72 ) 7.9 2( + 72 ) 7.2 0 ( + 72 ) three-dimensional PES plot with C h e mi c al En g in e erin g Edu c ati o n PAGE 31 C the third dimension serving as the potential energ y. From the PES plots students extracted the relative ge ometr y of the reaction s activated complex. A s a further check that this activa ted complex corresponded to a true transition s tructure a frequency calcu l ation was performed to ensure the existence of one negative frequency alon g th e reaction coordin a te Oftentimes thi s additional calculation would pro v id e more accurate coordinate s of the tran s ition st ructure ensuring ac curacy in the barrier-height calculation. Ste.JJ Five: The la st step of the a ss ignment involved the cal culation of rate expression parameter s, i e the rate con s tant using the hard-sphere collision model ( HSCM ) for an upper bound and tran s ition s tate theor y ( TST ) for a more accurate rate prediction In determinin g the rate constant for each reaction the value predicted by tran s ition s tate theor y ,1 10 1 Eq. (6), was modified with the tunneling correction of Wi g n erl 11 i given by Eq (7), so that the final rate constant value was given by Eq (8) k m= k b T Q T s e (R ~ ] h Q l Q 2 k = l + J_ [ hcv l2 T 2 4 k b T 3 k k TST _k T mol s (6) (7) (8) where v repre se nt s the single negative frequency value of the transition structure and the partition function Q T oial = Q ,ran s Q ro Q v i b Q e l ec Two lectures and one homework assignment were dedicated to providing th e st ud e nt s with an introdu c tor y background in s tati s tical mech a nic s so that they could under s tand the assumptions that are m a de in Gau ss ian to obtain th e partition function data. Three to four lectures were dedic a ted to reaction kinetics in which the HSCM and TST were tau g ht. Graduate Education ) p erfo rmed u s in g Eq. (9), (9) where the barrier hei g ht E i s the sa me as for ~ s T 1 2 is the reduc e d m ass a nd 0 12 i s the collision diamet e r. Since E i s already known, and 12 ca n b e d e termined with a s imple cal culation, the only difficult y was in determining the collision diameter. Here the lack of experimental data required the use of estimation technique s to find an approximate value of o The primary technique utilized was a traditional approach ba se d o n th e critical prop e rtie s of the species in the reaction as s ho w n in Eq. ( 10 ) in which V e a nd Z c are the critical volume a nd c riti ca l compressibility parameter s, re s pectivel y. 1 6 cr = 0.1866V } Z ~ 5 A (10) An exa mple of the pr e dicted reverse rate expre ss ions for R eac tion ( 1 ) calculated at the CCSD / 6-311G(3df 3pd) level of theory compared to lit era tur e prediction s and experiment i s pr ese nted in Table 3. Fi g ure 2 ( next page ) i s a graphical repre se ntation of the rate prediction for the forward direction of Reaction (1), s howin g th a t thi s high level of theory with a mod es t kinetic tool s uch as TST provided a fairly accurate kinetic prediction. CONCLUSIONS A gra duate-level chemical engineering course in com putational chemistry was developed that served to provide chemical e n g ineerin g s tudent s with an introduction to a mol ec ul ar a pproach in und e r s tanding chemical re ac tivity Oft e n there exis t s a disconnect between the topic s in an ap plied e n g in eer in g di sc iplin e a nd the fundamental chemical and ph ysica l principle s on which applications are based. Thi s cour se se rv e d as a mean s to provide students with additional TABLE3 Students were required to work through two TST problems in a homework assignment before applying the knowledge to their reac tion example. Further details of TST can be found in standard kinetic texts which se rved as references for the co urse. 112 1 3 1 In addition, the barrier heights required for Eq. (6) were extracted from the previously developed high-level PES. The barrier height was calcu lated by takin g the energy difference between the thermal-corrected (i ncludin g zero-point energies) transition s tructure and the s um of the thermal-corrected reactant species Comparison of Arrhenius Parameters for the Reaction, HCI + H _, Cl + H 2 Temp Range A Ea Reference ( K ) ( cm 3 / mol *s ec ) ( kcal / mol ) 29 1 11 92 2.999(13 ) 5. 1 0 Adu se i and Fontijn l 1 1000 1 500 3 .11 4 ( 1 3) 4.84 Allison, e t al. 1171 600 1000 2.3 I 8(1 3) 4.25 Allison e t a/. 1171 200 1000 7.94(12 ) 4 39 Lend vay e t a / _11 8 1 298. 15 -2500 5.015 ( 1 3 ) 4 39 Pr ese nt wor k ( TST ) CCSD / 6-3 11 G(3df, 3 pd ) 298. 1 5 2500 6 .1 34 ( 1 4 ) 4 67 Pr ese nt wo rk ( HSCM ) The calculation of the rate constant ba se d t N um bers i 11 parent h esis de n ote powers of J O. upon the hards phere collision model was Fall 2006 273 PAGE 32 ( Graduate Education 34 32 ?" 30 0 E 28 .. ~26 .,. .!: 24 22 20 0 0.001 TST {CCSD / 6-311G(3df 3pd)} ---HSCM {CCSD / 6 311G(3df,3pd)} Al li son et al. [ 17] + Kumaran et al. [ 19) Miller and Gordon [21) :i: Westenberg and de Hass [22) :.. 0 002 1/T{K 1 ) 0 003 0 004 Figure 2. Rate-constant comparison for the rea c tion Cl + H 2 -+ HCJ + H. tools to supplement their graduate research projects This connection was established through the development of a reaction a s signment which led students through a s erie s of steps ranging from an introduction to quantum mechanic s to the development of a potential energy surface, from which barrier heights were extracted for predicted rate expression calculation s Thi s series of steps ensured students compre hension of the concepts covered which was evident based upon final projects that required the s tudents to implement these tools of computational chemistry into their individual research projects. ACKNOWLEDGMENTS The author acknowledges graduate students Erdem Sasmaz Bihter Padak and Saurabh Vilekar and undergraduate student Nicole Labbe for use of their reaction results in this work. In addition, the s uggestions and careful reading of this manu script by Caitlin A Ca ll aghan are appreciated. Finally WPI s Unix administrator, Mark Taylor is recognized for assisting in the administration of the course-designated server. REFERENCES I. Leach A G ., and E Go ld s tein En e r g y C ontour Plot s: S li ces through th e Pot e nti a l Ener g y Surfa ce Th a t Simplify Quantum Me c hanical Studie s of R ea ctin g Sy s t e m s," J. C h e m Edu c., 83 451 ( 2006 ) 2 Galano A. J.R Alvare z -ldaboy a nd A Vivier-Bun ge, Comp ut ational Quantum Chemistr y : A Reliabl e T o o l in the Under s tandin g of Gas Ph as e R eac ti o n s," J Ch e m Edu c., 83 481 ( 2006 ) 3 L a bb e, N S Vilekar E Sa s ma z, B P a dak N P o m e rant z, J.-R 27 4 P asc ault P V a lli e re s, G Within g t o n C. Call ag h a n and J. Wilc o x The Connecti o n Betwe e n Comput a tion a l Chemi s try and Ch e mical ) En g in ee rin g: A S tud e nt s P e r s p ec ti ve," in p rogress 4. L a bb e, N., J. Wil cox, a nd R W. Th o mp so n An a b initi o In ves ti ga ti o n of Cyc l o he xa n e a nd Zeo lit e Int e ra c ti o n s," Pro cee din gs of th e 2 00 6 Int e rn a ti o nal C o nf e r e n ce in E n g in ee rin g E du c ati o n (2 00 6) 5 Fri sc h M.J G W. Tru c k s, H B. S c hlegel G .E. S c u se ri a, M A R o bb J.R C h e e s eman VG Zakr ze w s ki J.A. M o nt g om e r y Jr ., R.E. Strat m a nn J C. Bur a nt S D a ppri c h J M Mill a m A. O D a ni e l s, K.N Kudin M C. Strain b Fark as, J Tom as i V. B aro n e, M. C oss i R C a mmi B Mennu cc i C. P o m e lli C. Ad a m o, S C liff o rd J. O c ht e s ki G.A Peter sso n P.Y. A ya la Q. Cui K. M o rokuma P. Salvador J.J. D a nnenber g, D K. Mali c k A.O. Rabu c k K. Ra g hav ac hari J B. For es man J. Ci os l o w s ki J V. O r ti z, A G B a b o ul B B St e fanov G. Liu A Li as henk o, P Pi s k o r z, I K o m a romi R G o mpert s, R L. M a rtin D.J Fox, T. K e ith M. A Al L a h a m C .Y. P e n g, A. N a n ayakk ar a, M Chall aco mb e P.M.W. Gill B. John s on W. C h e n M W W o n g, J L. Andr es, C. Gonzal ez, M H ea d G o rd o n E S R e pl og l e a nd J A. Pop l e, Gau ss i a n 98, G a u ss i a n In c. Pitt s bur g h ( 1 998) 6 C ha se, M W. Jr ., N I S T JA NA F Th e m oc h e mi ca / T a bl es, 4th E d ., J. Ph ys C h e m R ef Data Monograph 9, 1 1951 (19 98) 7. C R C Handboo k o f C h e mistr y and Ph ys i cs, 58th Ed C RC Pr ess, Cl e v e l a nd Ohi o ( 1 978) 8. Hub e r K P ., a nd G. H erz b e r g, M o l ec ular S p ec tr a and M o l ec ul a r Stru tur e. IV Co nstant s of Diat o mi c M o l ec ul es, V a n No s tr a nd R e inhold Co. ( I 979) 9. NIST Co mputati o n a l C h e mi stry Co mpari so n a nd B e n c hm ark D a t a b ase NIST St a ndard R efere n ce D a t abase Num be r I O I R e l ease 1 2 A u g 2005 Editor : Ru sse ll D John so n ill < http ://s rd a t a. ni s t. gov/ cccbdb > I 0 Eyrin g, H. The A c ti va t e d Compl ex in Ch e mi ca l R e a c ti o n s," J. Ch e m Ph ys. 3 I 0 7 ( 1 93 5 ) 11 Wi g n e r E ., Cro ss in g o f P o t e nti a l Thre s hold s in Ch e mi ca l R eac ti o n s Z. Ph ys. C h e m 8 ., 19 20 3 ( 1 932) 12. Simon s J An Intr o du c ti o n t o Th e or e ti c al C h e mi s tr y, C ambrid ge U ni ve r s it y Pr ess (2003) 1 3. St e inf e ld J I., a nd J .S F ran c i sco, C h e mi c a l Kin e ti cs a nd D y nami cs, Pr e nti ce H a ll ( 1 999) 14. Shim a nouchi, T. T ab l es of M o l ec ular Vibrati o n a l Fr e qu e n c i es, Co n so lidat ed V o lum e I 39 ( 1 972) 15 C ox, J D ., D D W ag m a n. a nd V A. Med ve d ev, C OD ATA K ey Va lu es fo r Th e rm o d y n a m i cs, H e mi s ph ere, Ne w Y o rk ( 1 989) 16. Adu se i G.Y and A. Fo ntijn A High-Temp e ratur e Ph o t o chemi s tr y Stud y o f the H + H C I +-+ H + C I Reacti o n fr o m 29 8 t o I 192 K ," J Ph ys. C h e m. 97 1 4 0 9 ( 19 93) 1 7. Alli so n T.C. G. C. L y n c h D G Truhlar and M S. G o rd o n An Im proved Potential En e r g y Sur face fo r th e H 2 C l Sys t e m a nd It s Use for Calcul a tion s of R a t e Coe ffici e nt s a nd Kin e ti c I so t o pe Eff ec t s," J. Ph ys. C h e m ., 100 1 3575 (1996) 1 8. Lend vay, G. B Lasz l o a nd T. B erces, Th eo r et i cal s tud y of X + H, -+ XH + H a nd Re ve r se R eac ti o n s (X = F C l Br I ) u s in g a n ew e mpiri ca l pot e nti a l ener gy s ur face," C h e m Ph ys. L e n ., 137 I 75 ( 1 987) 19 Kum a ran S S. K.P Lim a nd J V. Micha e l Th e rm a l Rat e C on s t a nt s for th e Cl+H, and C I+D 2 Re ac ti o n s B e t wee n 296 a nd 3 000 K ," J Ch e m Ph ys., 101 94 87 ( 1 99 4 ) 20. We s t e nber g, A A ., a nd N. de Haas Atom M o l e cule Kin e ti c s u s in g ESR D e t e ction IV. R es ult s fo r C I+ H 2 +-+ H C I +Hin B o th Dir e ction s," J. C h e m Ph ys., 48 4 4 0 5 ( 1 968) 2 1 MilJ e r J .C. and R.J G o rd o n Kin e ti cs of th e C I H sys t e m I. D e tail e d balan ce in the C I+H 2 r eac ti o n J C h e m Ph y s. 75 5 3 0 5 ( 19 8 1 ) 0 C h e mi c al E n g in ee rin g E du c ati o n PAGE 33 (.9 ... fi 11111 ._c u r_r_i_c_u_l_u m ___ ____ ) An International Comparison of FINAL-YEAR DESIGN PROJECT CURRICULA SANDRA E. KENTISH AND DAVID C. SHALL CROSS University of Melbourne Victoria Australia 3010 T he final-year design project has been an essential part of the chemical engineering under gra du a te curriculum for many decade s Some would argue that the structure of this s ubject h as changed little .r 11 As will be s hown in this paper however there is considerable evidence of a substantial shift in the teaching of the de s ign project to better reflect the demands of bot h a changing di sc ipline and the wider ex pe c ta tions of futur e employers This paper review s design project teaching at 15 chemical engineering departments across Australia, Singapore and th e United Kingdom. Information on Australian courses was obtained during a design project workshop organized by the Australian-based Education Subject Group of the In s titution of Chem i cal Engineer s, and sponsored by Aker K vaemer Aus tralia. The workshop was he l d Feb 14-15 2005 Information regarding the courses in Singapor e a nd th e UK was obtained during a study tour by one of the authors in July 2005. Historically the capstone design project was developed to draw together the design technique s deve l oped during David Shallcross is an associate professor in the Department of Chemical and Biomo lecular E ngineering at the University of Mel bourne He is founding chair of the Institution of Chemical Engineer s' Education Subject Group and is editor of the in t ernational jour nal Education for Chemical E ngineers He is the author of three books and is active in promoting the profession within the seco nd ary-school community. Sandra Ken tis h ( Ph.D .) is a senior lecturer within the Department of Chemical and Bio molecular Engineering at the University of Melbourne and the coordinator of their capstone Design Project s ubject. She joined the department in 2000 after working within the chemical indu s try for n i ne years. Her research interests are focused in two areas : membrane se paration s and sonoprocess ing (the use of ultrasound i n the chemical industry ). Copyright ChE Division of ASEE 2006 Fall 2006 275 PAGE 34 the chemical engineering course into a single, integrated project. Reference to the instructions for the 1974 Institu tion of Chemical Engineers design projectl 2 1 indicates that the requirements were for process selection and descrip tion material and energy balances process and mechanical design, and costing There was a requirement to complete a Hazard and Operability st udy but generally the emphasis on health safety, and the environment was minimal. The learn ing outcomes were clearly intellectual ability and practical design skills. Transferable skills such as teamwork, oral com munication, and open-ended problem-solving ability were not considered relevant. By 1991 ,1 3 1 the scope of the project brief had broadened with inclusion of topics such as market assessment, energy efficiency, and environmental impact. At this stage, however there was still no evidence of generic skill development. More recently, emphasis within chemical engineering edu cation has shifted to focus on learnjng outcomes beyond only a technical nature. Transferable skills that will assist graduates in a range of employment roles are gaining importance_f 47 J Evidence from the institutions considered here shows that the final-year design project is evolving as a crucial mechanism for developing these skills because of its position at the trul end of the course and the minimal demands for technical knowledge transfer. Indeed the design project acts as the "ex it transition s ubject at most institutions bridging the gap from university study to a real-world position of a trend in thls direction with many institutions running product design project s in separate subjects, as well as design exercises in the earlier years of study. Thls paper however focuses in particular on the final project at the M Eng. level, which is the fourth year of continuous study at almost all in stitutions (the fifth year at Scotti s h universities). The IChemE accreditation guide [7 l indicates that at this M Eng. level: ... the course shall include a major design exerc ise demon strating that issues of comp l exity have been appropriately addressed. The major project is normally und e rtak en in the final year and is normally weighted at 20 c redit points minimum (This equa t es to 16.6 % of the final-year credit). The major project at M.Eng. l evel can be up to 50 % of the final-year credit Table 1 shows that among the departments co n sidered, the design project had a credit range between 12 5 and 40 % of the final year. In most cases, the project ran across either a single semester or the full year. Some English institutions, however undertook the design project in the penultimate year of an M.Eng. course to accommodate B.Eng. students into a common program. It should be noted that within the UK system, a degree of uniformity between departments is provided by the use of external examiners. All design project briefs, assessments, and samples of final project submissions are reviewed by a senior academic from another institution. Within Australia, a TABLE 1 The greater computing and word processing power available to today 's students and the ready access to electronic literature resources ha s enabled the design project scope to expand. Larger and/or more diverse project s are being undertaken focusing on broader learning outcomes such as sustainability, process safety, and the use of design standards and regulations. Pro cess simulation can be practiced and practical computing skills developed. Chemical Engineering Departments Considered in this Study A common feature of c h emical engineering courses considered here is that they are accredited by the UK-based professional body, Institution of Chemical Engineers (IChemE).f7l The IChemE promotes the concept of a design portfolio, in which a number of design exercises are completed over the curriculum. There was certainly evidence 276 and the Format of Their Capstone Design Projects Country Percent Timing of No. of Written of FinalProj ec t Submissions Year Credit Curtin University Australia 25 0 Final Semester 12 James Cook University Austral i a 25 0 Full Final Year 5 Monash University Australia 25 0 Final Semester 1 RMIT University Australia 25.0 Final Semester 4 University of Adelaide Australia 25.0 Final Semester 1 University of Melbourne Australia 1 8 .75 Final Semester 2 University of New South Australia 18.75 Penultimat e 7 Wales Semester University of Newcastle Australia 25.0 Full Final Year 3 University of Queensland Australia 25.0 Final Semester 5 University of Sydney Australia 33.3 Full Final Year 5 National University of Singapore 12 5 Final Semester 3 Singapore University College London UK 37.5 Full Third Year 8 University of Birmingham UK 40 0 Full Third Year 8 University of Nottingham UK 42.0 Full Year I Unjversity of Edinburgh UK 33.0 Full Year 1 Chemica l Engineering Education PAGE 35 ----------~ __ ,. ____ ___________ ___ similar de gree of uniformit y is engendered b y the availability of an Australia-wide design project s tudent prize ( the Aker K vaemer award) and several regional prize s. For example the Aker Kvaerner Prize guidelines currently restrict assessment components for safety and environmental considerations to between 10 and 20 % of the final grade a nd proce ss economics to five to 10 % of the total grade. PROJECT STRUCTURE Five of the 15 institutions offered only a single project topic per year, arguing this reduced staff workload. Others offered a range of project topic s. In the "varia tion s on a theme ap proach a single proc ess was considered but var iation s in things such a s raw material purity or plant location were used to differentiate team project s. Thi s approach was u se d by three institution s in order to reduce the opportunity for collu sio n between classmates, while also limitin g staff workload. Only at the University of Melbourne was plagi aris m sof t ware implemented as a tool for monitorin g both collusion and plagiarism from the Internet. When introduced in 2004 thi s proved very effective Substantial plagiari s m was detected in one student's work, and appropriate action was taken At virtually all institution s, the s tudent s were initially pre sented with a de s ign brief of between one and three pa ges outlining the de s ign problem This brief often contained ba s ic TABLE2 Basis for Team Assignments in the t ec hni cal and / or costing data. In most cases the students were first ex pect e d to use thi s information to complete a feasibility s tudy ; that i s, to assess alternate proces s routes and develop a proce ss flowshe e t to determine market demand and optimum plant capacity, and to identify potential environmental and safe t y i ss ue s. Thi s was fo llowed b y more det a iled equipment design work th e d eve lopment of process control s trategie s, and a proce ss and instrumentation dia gra m At the feasibility s tudy s ta ge or at the co nclusion of more detailed work, an assessment of the process economics was required. In most cases, st udents were ex pected to argue a busines s case to management as to whether the facility s hould proceed In a ll cases, project work was s upported by a lecture pro gram that provided in s truction in de s ign methodology Thi s lecture pro gram was often s tructur e d to cover subject material mi sse d in other areas Thu s, for example, it was recognized that th e design of proce ss utilitie s s uch as s team and cooling water sys tem s needed to be covered within thi s program The number of assessable written reports required from each st udent or team varied s ignificantly (see Table 1) from a si n g l e s ubmi ss ion at the end of a yearlong project to weekly s ubmi ssio n s for a 12 -week program TEAMWORK AND PEER ASSESSMENT The design project was conducted as a team exercise at a ll institutions. Generally broader Capstone Design Project at the Institutions Studied process i ss ue s s uch as economics, environmental impact and health and safety were assessed a s team based ta s k s, with proces s design remaining an individual activity. It was common for the individual b ase d tasks to equate to s lightl y more than 50 % of the total grade C la ss Group Size Size 12-25 5-6 25-35 4-5 25 -40 2-3 a nd then 10-12 40 s 45 s so 6 58 5-6 60 4 70 3-4 60-70 4-5 70-80 4 80100 s 100 610 80-120 4 200-300 7 Fall 2006 Team Allocation random by proje c t pr efe rence random mix of abi liti es / ge nd er by severa l fac t ors random academic merit s tudent s ca n exclude others by aca demic merit and project preference random self-se l ection random mix of abi liti es / et hni city/back gro und se lfse l ect ion se l f-selection Team Leaders ro t a t ed e l ec t ed by team rotated weekly no yes no no no --rotated week:l y rotated n o no e l ec t ed b y team Peer Assessment no no n o no yes n o yes no yes n o n o no yes yes no As s hown in Table 2, the s ize of the team s varied, with typically four or five st udents on a team. In institutions with larger cla ss sizes, s tudent s were allowed to select their own team members This was ge nerally because of the logistic s involved in a central teamse lection process when the number of stu dents is large A sig nificant propor tion of de s ign project coordinators with s maller class sizes, however spent considerable effort to develop team membership Interestingly there was a range of ways to do this. Some se l ec ted s tudent s of common academic ability to be in the same team while others deliberately placed s tudent s of varying academic 277 7 _J PAGE 36 ability within one team The University of Queensland is considering the use of specific assessment of team skills from previous years as a basis for team membership in the final-year project. Many instit u tions provided explicit works h ops or training sessions to develop teamwork skills. For examp l e, the Uni versi t y of Sydney had fortnig h tly sessions on team bui l ding with group leaders Un i versity College London (UCL) had a two-day workshop o n effective teamwork a year before the capstone design project, and followed up with a one-day refresher course at t h e project's start. Similar l y, many i nstitu tions defined a forma l ro l e for team leaders. Rotating t h e posi tion of team l eader a ll owed l eaders h ip skills to be deve l oped amo n g t h e majority of students Some campuses had interdisciplinary teams, which is more representative of the two cases where the design task was specified by such design engineers, the hazard analysis was considered at an earlier stage as a more integral part of the de sig n proces s than in other cases. Many other institutions relied on corpora te eng in eers to assist with setting a valid technical scenario, and in many cases personnel from these companies provided a consu l tant ro l e. In most cases, the academic in charge of the project also h ad extensive indu s trial expertise PROCESS SIMULATION AND COMPUTING TECHNOLOGY A ll institutions incorporated the use of simulation package s such as HYSYS a nd ASPEN PLUS to assist in design In most cases, their use was actively encouraged. In so me cases, the design project brief was even manipulated to ensure that simulation actual industrial environments. For ex amp l e, both the University of Queens l and and t h e Nationa l U n iversity of Singapore incl u ded an environmenta l engineering student in each team w h ile the Uni versity of New South Wales included industrial chemists. The University of Birmingham had an optional project that integrated civi l engineers, while Sydney had a multidisciplinary project for h i ghly academic st u dents only that integrated civi l and mechanical engineer ing students. While teamwork was clearly well established as part of was pos si ble Other s, however felt that the use of simulation packages could detract from the design exercise because proper implementation required sig nificant time input. They also argued that there was a tendency for st udents to accept si mulation output without question and the educa tiona l va l ue was therefore limited. An em p h asis on proper justification of s imulation output was essential, and was usually the basis for assess ment. Justification by both shortcut hand calculations and reference to literature data was encouraged. The use of dynamic simulation for process control and hazard assessment by RMIT University was noteworthy the Design Project it was somewhat disappointing Whi l e teamwork was c l early well established as part of t h e design project it was somewhat disappointing to the authors that only a third of the institu tions used this opportunity to introduce to the authors that only a third of the institutions used this opportunity to introduce peer assessment. peer assessment. Between t h e institutions that did a considerab l e range of methods was used to man age the process. In some cases, peer assessment marks were determined collaborative l y by all team members in an open forum. In others, s u bmission of peer assessment rat i ngs was anonymous, so that students could not discover how their team members rated them. T h e University of New Sout h Wales presented a relatively sophisticated peer assessment method des i gned to improve t h e consistency of assessors.[ 81 While this method would provide high accuracy and a l ack of bias it co ul d be time consuming in large classes. INDUSTRIAL INVOLVEMENT A ll institutions active l y involved engineers with a desig n or proce ss ing background in the design project curriculum Some institutions notably Me l bo u rne and Birmingham mai n tained part-time adj u nct professor-type positions for engineers with engineering design experience, typ i cally one day a week. In 278 Also of note was the extensive u se of Web-based learning. A significant pro portion maintained s ubject Web pages as a major mec h anism for relaying information to s tudent s. These subject sites also often u se d online discus s ion forums as a mean s of bringing common que st ions into the open and creat in g inter-student debate. E l ectronic l i brary resources such as Proquest, SciFinder Scholar and Knovel were also ut il ized A range of smaller, discrete computer programs was also used to support student learning, such as Microsoft Visio for engineering drawings. ORAL PRESENTATION Now cons i dered an important transferable skill oral pre sentation served as an assessment component in nine of the 15 curricula. In so me cases, t h ese pre se ntations were made direct l y to engineers and management of the company whose operations had formed the basis of the design task. Presen tations cou l d be individualor team-based and so metimes invo l ved the use of posters to s u pport oral commentary. Chemical Engineering Edu ca tion PAGE 37 TABLE3 Bio-Based Design Project Topics Use d at the Institutions Studied Enzymatic production of glucose and galactose from c heese whey waste Lactic ac id production Plasmid DNA based AIDS vaccine Bio-ethanol from waste paper Production of ti ss ue plasminogen activator Penicillin production SU STAI NABI LITY The IChemE now prescribe s that graduates must be aware of the priorities and role of s ustai_nable development. There was little evidence, however that sustainability was being oiven a focus in the capstone de s ign project. RMIT University :as the only institution formally requiring a s ustainabilit y report as part of the project relyi_ng on the IChemE Su sta in ability Metrics [ 9 1 as a template for students. No more than five other institutions discussed s ustainability during the course This is clearly an area that could be improved and many PAGE 38 ACKNOWLEDGMENTS A Case Study Approach, 2 nd Ed. Overseas Publishers Associa ti on, Amsterdam ( I 998) Information was provided by staff at Curtin, James Cook Monash, and RMIT Universities, the Universities of Ad e l aide, New South Wales, Newcastle, Queensland, Sydney, Birmingham, Nottingham, and Edinburgh University Col lege London, and the National University of Singapore. This input is gratefu ll y acknowledged. Financial support for travel to Singapore and the United Kingdom was provided by the University of Melbourne through a Universitas 21 Fellowship, and this support is also appreciated. 4. C han gi n g the Cult ur e: E11gineering Education int o the Future: The Institution of Engineers, Australia ( 1996 ) 5 Criteria for Accrediting Engineering Pro gra m s ABET Engineering Accreditation Commission, Accessed from (2004) 6 Ho w D oes Chemical Engineering Education Meet th e R equ ir eme nts of Employment ?, World Chemical Engineering Council, Dechem a Frankfurt (2004) Accessed from 7 Accreditation Guide: U11dergraduate Study, 2nd Ed In sti tution of Chemical Engineers (2005) 8. Bushell G. "Modera tion of Peer Assess m en t in Group Project s," Ass. and Eva/. in Hi gher Ed. (2005) 9. The Sustainability Metrics: Sustainable D eve l opme/1/ Pr ogress Metrics R ecomme11dedfor Use i11 th e Pr ocess Indu st ri es, Institution of Chemical Engineers, REFERENCES I Murray K.R., T. Pekdemir, and R. Dei g hton A New Approach to the Final-Year Design Projects," Pro ceed in gs of the 7th World Congress of Chemical Engineering Glasgow ( July 2005) 10. We l bourn J. "Goo d Manufacturing Practice in Pharmaceutical Pro duction, An Engineering Guide," [ChemE Rugby, UK, Bennett B ., G Cole (Eds) (2003) 11 Ha za rd Analysis and Critical Contro l P o int U S. Food and Drug Administration, Center for Food Safety and Applied Nutrition 2. Austin, D G. and G. Jeffreys, "T he Manufacture Of Methyl Ethyl Keton e From 2-Butano l : A Worked Solution to a Problem In Chemical Engineering Design ," Institution of Chemical Engineers in association with G. Godwin Ltd. Rugby UK ( 1979 ) 3. Ray M .S., and M Snee s by Chemical E11gineering D es i gn Proj ect: 12 Shanklin, T. K. Roper P. Yegneswaran, and M. Marten, Selection of Bioproce ss Simulation Software for Industrial Applications Bi o t ec h nology and Bi oengineering, 72 (4) 483 (2001) 0 280 r POSITIONS AVAILABLE Use CEE's reasonable rates to advertise. Minimum rate 1 / 8 pa ge,$ 100; Each additional column inch or portion thereof $40. Johns Hopkins University The Department of Chemical and Biomolecular Engineering at Johns Hopkin s University invites app li ca tion s for a full-time l ec turer. This i s a career-oriented, r e n ewa bl e appointment. Re spo n s i bilities include: Teach 3 courses each semester (c urrently with lab s). Manage c urriculum issues including degree requir eme nt updates and course development. Coord in ate advising for undergraduate Chemical and Biomolecular Engineering major s. Organize prospective freshmen activ iti es, including open houses and welcome letter s, and serve as liaison to th e Admissions office. Oversee and train graduate TA s a nd graders. Maintain retention and growth statistics. Applicants mu s t have a Ph D. in Chemical Engineering or a c lo se ly related field and demonstrated excellence in teaching. Applications must include a letter of app li cation, c urri c ulum vitae, and a stateme nt of teaching philo so phy Applicants s hould arrange for three reference letter s to be sent directly to the a ddr ess below. All material s hould arrive by Nov. 30 2006. Lecturer Search Comm itt ee C h emica l and Biomolecular Engineering Department Johns Hopkin s University 3400 N Charles St 22 1 MD HALL Baltimor e, MD 2 1 2 1 8 410-516-7170 tpaulhal @ jhu.edu Johns Hopkin s University is an EEO / AA employer. Wom e n a nd minoritie s are s trongly encouraged to app l y Chem i cal Engineering Education PAGE 39 Random Thoughts ... WHAT'S IN A NAME? RICHARD M. F ELDER North Carolina State University Raleigh NC 27695 T he monthl y Chemical En g in ee rin g D e partment faculty meeting is in full swing. They spent the usual half hour discussing the latest ca tastrophi c budget shortfall and the urgent n ee d to bring in mor e g rants and more graduate students with NSF fellowships and th en they moved on to the upcoming ABET visit. A prolong ed argument brok e out about whether teaching students the Gibbs-Duhem equation cou nts as preparing them to be ethical and professionally respon sib l e lif elong l earners who und e rstand co nt e mporar y issues and can work in multidisciplinar y t eams to solve global and soc ietal problems. The argument ended unresolved. Chu ck, th e department c hair, rela ye d a message from the department administrative assistant that unl ess th e professors started cleaning up their messes in th e faculty lounge the y could sta rt making their own coffee. Onc e the e n su in g pani c subsided, th e meeting turned to New Busin ess, and th e c riti ca l is sue on everyone s mind was brought up first. Chuck: "OK, folks, let 's take up Diane 's proposition to change our n a me to th e Department of Chemical and Biomolecular Engineering. Diane wa nt to say somet hin g about it?" Diane: Sure. Everyone know s that biotech is the future and the ones who know it best are the stu d ents ... the freshmen are go in g more and more for departments that do biology a nd grad uat e s tud ents a ll want to work for fac ult y doing bio research. Mo s t Chem. E. departm e nt s ha ve a lr eady put bio so mething in their name s and i f we don't we're gonna lo se out." Ch: Make s se n se to me OK if no one e l se ha s anyt hin g to say, l et's vote o n it. All in favor of our b eco min g the Departm ent of Chemica l and Bi omo l ecular Engineering, say Carl: Hold on Chuck. If yo u ju st say biomolecular engineering, people will think we re on l y a bout Fa!l 2006 DNA and all that s tuff which i s yes terday 's new s Sam and I do a lot of bioc a taly s i s and biosepara tions which are much sex i er than all that gene stuff, but the s tud e nt s won t know we do tho se things here unle ss we mak e it explicit." C h: You mean ... Sam: Yeah, l et 's b e the Department of C h emical, Biocata l ytic and Bio se paration s Engineering." D: Wait just a minute, buster -ge n es are a whole lot sex ier than enzymes and c hrom atogra phy and we 'v e got twice the gra nt s upport you guys do! S: "O h yeah-well who's got mor e CAREE R awards, and w h at's more ... C h: All right, a ll right-calm down Tell you what-we ll just make the t e nt bigger and call it the Department of Chemical Biomolecular Bio ca talytic a nd Bio se par a tion s Eng in eering. How' s that ?" C: Make it Biocat a l y ti c, Biomolecular Biosepara tions, a nd Chemica l -a lph abetical order." D: "T h at's the dumbest s ug ges tion I ever. .. C h: "O K all in favor say .. Richard M. Felder is Hoech st Celanese Profe ssor Emeritus of Chemical Engineering at North Carolina State University. H e is co author of Elementary Principle s of Chemical Pr ocesses ( Wiley 2005) and numerou s articles on chemical process engineering and engi neering and scie nce education, and regularly presents workshops on ef fective college teaching at campuses and conferences around the world Many of his publications can be seen at . Copyrigh t ChE Divisi o n of ASEE 2006 28 1 PAGE 40 2 8 2 Morrie: "Hey what am I chopped liver? I don't like to brag but have you forgotten that I'm heading a$3 million artificial organ program with five graduate students .. S: Can you believe the guy who deals in artificial organs just asked if he s chopped liver?" M: [Glares at Sam] ... five graduate students and two postdocs, and what about our cooperative agreement with St. Swithen s Hospital? Biomedi cal engineering is every bit a s important as those other bios around here besides, we heal people and save lives-let s see somebody here top that for sexy ." Ch: "OK OK .I guess we can t include three of our four bio areas and leave out the fourth .. so all in favor of renaming ourselves the Department of Biocatalytic, Biomolecular, Bioseparations, Chemical, and Biomedical Engineering say ... M: Ahem .. Ch: "Right right-the Department of Biocatalytic Biomedical Biomolecular Bioseparations, and Chemical Engineering ... Ned: Look, you want to talk about sexy areas, you can t dream of leaving out nanotechnology-it's the hottest field in science ... you just put nano in your proposal title and you can start looking for your check by return mail -we II pull the students in here like a vacuum cleaner ." Ch: I see your pointI gues s if we don t have nanotechnology in our name Berkeley grads won t look twice at us. OK, so all for the Depart ment of Biocatalytic, Biomedical, Biomolecular, Bioseparations, Chemical, and Nanotechnological Engineering say ... N: My mother always s aid to let the smallest one go first and you don't get much smaller than 10 9 meters so it should be the Department of Nano technological. Ch: Enough already-don t push your luck! Now all in favor of .. Ernie: "Whoa Chuck-have you forgotten Mother Earth?" Ch: "Say what?" E: "Saving lives may be important but nothing is more important than s aving the planet, and the environmental engineering program in this depart ment is second to none in its dedication to ... Ch: Yeah yeah ... and what could be sexier than sav ing Mother Earth? E: Just what I wa s going to s ay. Ch: OK but thi s is it gang. My final offer to you is the Department of Biocatalytic Biomedical Biomolecular, Bioseparations, Chemical, Environ mental, and N a notechnological Engineering-take it or leave it. All in favor say ... D: You know that s kind of an awkward name ." Ch: Oh really-I hadn t noticed. So are you offer ing to drop Biomolecular to help us solve this problem? D: "Of course not-you can t begin to count the graduate s tudent s you d lo s e by dropping Bio molecular I wa s thinkin g, thou g h-nobody here really doe s anything you could call chemical engineering do they ?" E: Hey she s right. .. and we got rid of the last of our unit operation s equipment in the undergraduate lab to make room for Ned 's scanning electron mi croscopy experiment and Morrie s heart catheter ization demo. M: Besides .. s tudents don t seem to have much u s e for chemical engineering anymore. S: "That s for s ure-the late s t Roper poll had chemi cal engineering and pig-lagoon maintenance tied for 247th place in job desirability rankings. Ch: "Well, I guess that settles it. All in favor of be coming the Department of Biocatalytic, Biomedi cal Biomolecular, Bioseparations Environmental and Nanotechnological Engineering say aye. All: Aye!" Ch: Done! I'll have Patsy order our new letterhead stationery immediately ." C: "Hey Chuck dropping chemical won t cause a problem with ABET will it ?" Ch: "Nah. A s long a s we can find someplace to slip in the Gibb s -Duhem equation, we re cool." 0 All of the Random Thoughts columns are now available on the World Wide Web at http: // www.ncsu edu / effective_teachin g and at http :// che.ufl.edu / ~cee / C h e mi ca l En g in e erin g Edu c a1io11

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t.a ... 5 ... ._o_u_t_r_e_a_c_h _________ ) BIOMEDICAL AND BIOCHEMICAL ENGINEERING FOR K-12 STUDENTS SUNDARARAJAN V. MADIHALLY AND ERI C L. MAASE Oklahoma State University Stillwater, OK 74078 0 ne problem facing the United States is a declining number of s tudents interested in an engineering major. 1 11 Between 1992 and 2002 the percentage of high sc hool students expressing an intere s t in engineering de creased sig nificantly .12 1 In addition, U.S. st udent s demon strate a lack of preparedness in math and science 131 To address these issues a number of programs have been initiated throughout the country in which high schoo l teachers are retrained or students are exposed to science and engineering through summer outreach programs .H 7 1 The College of Engineering Architecture, and Technology (CEAT) at Oklahoma State University (OSU) has developed a multidisciplinary week.long re s ident s ummer academy for high school students called REACH (Reaching Engineer ing and Architectural Career Height s). The primary goal of REACH is to provide factual experiential information to all participants increasing their knowledge in the various fields of engineering, architecture, and technology. Another goal involves increasing the number of students from underrep resented groups studying these disciplines. The academy is designed to help students make individual career decisions, with the intention of attracting them to engineering careers. Participants are primarily junior or se nior high school stu dent s. In the 2005 program nearly 70 % of the 30 students (18 Copyrig ht ChE Division of ASEE 2006 Fall 2006 female an d 12 male ) were from groups under-repre se nted in engineering, architecture, and technology (such as fema l es, Hi s panic s, and Native Americans) Each academy begin s with a recreational activity such as rock climbing or camping so that participants get to know each other. Afterwards, participants get exposure to engineering Eric L. Maase is an adjunct lecturer of chemical engineering at Oklahoma State University. He received his B S in chemi cal engineering from the University of Maryland his M S in chemical and petro leum engineering from Colorado School of Mines and his Ph.D from Oklahoma State University in 2004. His research interests are teaching methods computer model ing, thermodynamics and bio-related engineering Sundararajan V. Madihal/y is an assis tant professor of chemical engineering at Oklahoma State University He received his B.E. from Bangalore University, and his Ph.D from Wayne State University both in chemical engineering. He held a research fellow position at Massachusetts General Hospital / Harvard Medical School / Shriners Hospital for Children. His research interests include stem-cell-based tissue engineer ing and the development of therapies for traumatic conditions 2 83

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disciplines including civi l a nd e nvironm e ntal; architectural, electrical, and computer ; technology; biosystems and agricultural; mechanical and aerospace; indu s trial; and chemical and biomedical / biochemical. These di sc iplines are taught using a modular approach by instructors from each specialty. Hands-on projects are tailored to high school students. During the week participant s are a l so exposed to the engineering industry through a plant tour. At the conclusion of the week, s tudents give a presentation describing their experience at the academy in front of their peer s, parents and teachers. TABLE 1 Bioengineering Module Schedule Initial Survey 9:00 I 0 : 00 Overview a nd Intr od u c ti o n I 0:00 I 1:40 Experimentation I 0 : 20 I 0:50 Lab Tour I 10 :50 -11 :20 Lab Tour II ( 15 st udent s) 11 : 45 I: 15 Lunch br eak I :30 I :45 Wrap up th e expe rim e nt I :45 2 : 00 Prepare for th e presentation Thi s paper focuses on u se of a new module at the 2005 academy, in which s tudent s were introduced to biomedical and biochemical engineering. Thi s was the la st modul e in the se rie s. The prim a ry goal was to expose students to various activities in bioengineer ing Additional goals included teaching s tudents good re sea rch methodology and presentation s kill s. The activities for the day and scheduled events for the module (Table 1 ) included an introductory presentation, a laboratory tour and experimental work. In these ac tivities both deductive and inductive learning s tyle s were used i 8 1 3 1 to maximize teaching effectiveness and s uccessful completion of the module goals. STUDENT PRE-ASSESSMENT 2:00 2:45 Presentations (5 min eac h g roup) 2:45 3 : 15 Summarize / question s Final Surv ey After being informed about the sc heduled events for the module 2005 BioModule REACH Pre-Surve y Na me: _____________ What is your long term care er goal ? P1"ase provide appropriate replies to each of the following questiom 1. Have you thought of goi n g to medi c al s c hool ? YES or NO 2. Have you thought of becoming m, e n gineer withfocu.s on biotechonology ? YES or NO 3. What is th e co nfid e n ce in saying you know Basic Biology and l\llo/ecular Biology ? 0 10% 0 30% 0 50 % 0 60% 0 70% 0 90% 0 100% 0 Don t know Courses taken : 4 What is the c onfidence in sayi n g you know Bi,ochemist r y a,1d BiotecJmology ? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don't know Courses taken : 5. What is the co nfid e n ce in saying you know Humm, Physiology Immwzology Genetics ? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don t know Courses taken 6 What is the co nfi de n ce in saying you know Fluid Mec hmzi c s Stati cs, and Ele c tri c al Ci r cuits? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don't know Courses taken 7 How much do you know abo,t the c orn syrup added u, the nzm iy ofthejui ces you drink ? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don't know 8. How much do you know abotl e n zymes a nd degradation ? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don't know 9 Do you know any prosthetic devi ces that one if your friends or relativ es use ? Lisi. JO Do you know anew field ca/ledTissw, Engi.neering ? YES or NO Figure 1. Pre-assessment survey form 284 and their activities for the day s tudent s were asked to complete a one-page s ur vey ( Figure 1 ). Of 10 que s tions on the s urvey two were about intere st in a bio e n g ineerin g career or attending medical sc hool. The eight remaining questions required s tudent s to self-assess their confidence level s of knowledge in vari ous topic s : biological ( basic biology and molecular biology) ; medical (biochem istry a nd biotechnology human phy s iology, immunolo gy, and genetics); and engineering ( fluid mechanic s, sta tic s, and electrical circuits). Results of the first two questions s howed th at 19 of the s tudent s expressed interest in medical sc hool a nd 10 in a bio-ba se d engineer ing In the self-assessed confidence level in biolo g i ca l medical and engineering topics (Fig ure 2), average values varied from 36 % ( % ) to 56 % ( %) The only s ignific a nt difference in confidence l eve l s b etween male and female students was in th e e n gi neering sc ience s. In the more s pecific bio-related engineering question s on the uses of corn syrup and enzyme-dependent degradation of biopolymer s, the average confidence level was 33%. In que st ion s on the aware ne ss of prosthetic devices and tissue engineering, 12 s tudents could name vari o u s prosthetic devices and nine had some knowledge of tissue engineering. Chemi c al Engin ee rin g Edu c ation

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PRESENTING AN OVERVIEW AND INTRODUCTION TO BIOENGINEERING After completion of th e s ur vey, the n ext event initi a ll y ap pear e d as an introdu ctory presentation. But its intent instead was as a tool t o initiate co n versa ti o n with th e s tud e nt s. 1 1 -11 Th e pre se nt a tion b ega n w ith a discussion of five m ajo r top ic s in bioen g in eeri n g, i. e., physiologic sys t ems modeling pro s thetic devi ces, ti ss u e e n gi n eer in g, drug d e li ve r y a nd biotechnolo gy. Using a n interactive presentation approach, in s tructor s drew a ttenti o n t o practical app li cat i o n s studen t s co uld ha ve observed in soc iet y and asked st ud e nt s to pro v ide t h eir knowl e d ge and aware n ess of th e topics. Further, s tud e nt s were e n co urag ed to ask questions. Thi s approac h was ben e ficial in that in s tru c tor s were a bl e t o m ake s tud e nt s comfortable while providin g n ew in fo rmation o n biomaterials a nd bioengin eer in g. The di sc u ss i o n o n modeling phy s iological factors includ ed two examples The first in vo l ved measuring lun g vo lum es a nd modelin g thoracic forces. The exa mpl e was Lance Armstrong's s uc cess in Tour de Fra n ce com p e tition s, th ereby connecting s tud e nt s with a r ea l-li fe eve nt. Th e other exa mpl e involved mod e lin g th e di a l ys i s process a nd s tudents were informed th ey wou ld see an entire dialysis unit during the l a b ora t ory tour. In di sc u ss in g prosthetic d ev ic es, the n eed fo r artificial orga n s was introduced b y a c h art describing the deficit of available donor s To encourage parti c ip a ti o n st ud e nt s were asked abo ut their knowled ge of individu a l s w ith artificial limb s, h ea rin g a id s, p ace m akers, a nd co nt act l enses (t he most likel y device w ith which a n a udi e nc e member would have direct experi e n ce). Furth er, they were asked How do they work?," and What i s th e n eed?" Thi s was done to overco m e possible student reluc tanc e to parti c ipatin g in th e di sc ussion Th e final portion on pro s th e tic d v i ces dealt with ar tifi c i a l heart valves, covering th e pro g r ess ion of research and u se from m ec h a nic a l valves to biopro s thetic va l ves, a nd th e difference with tis s u e e n gi n ee r e d valves. Th e basic concepts in ti ss u e e n g in eer in g were th e n introdu ced u s in g exa mple s of c urr e ntl y ava il a ble ar tificial s kin product s and th e ir manu facturers. Aft e r ex posin g Cl) VI C 0 a. VI Cl) C) ctl ... C Cl) c., ... Cl) e:. Cl) C) ctl ... Cl) > 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Biol ogy and Mole cu lar Biolog y s tud e nt s to o th er id e ntifi a bl e products the qu es ti o n po se d was: How do we e n g in ee r s uch products? In order to show the e n gi n eer in g principles co ntroll ed drug d e liv e r y devices were co n s id ered. Questions suc h as: Wh at happ e n s when a person takes Tylenol ?," a nd Why does that person n ee d to take pills r epea t e dl y?," serve d as a basis for pondering better drug-delivery methods Further fig ure s of nicotin e patches initi a t e d a di sc u ss i on o n th e importance of biolo g ic a l factors ( h a lf-li fe, a b so rption a nd met a boli s m ) vs physioch e mical factors (dose so lubilit y / reactivity / pH, s tabilit y) in drug de li very. In addition, c h arac t er i stics of traditional oral do s in g (cycl i c conce ntration s) a nd m ore desirable co n s t a nt (co ntinu o u s) dru g delivery co n ce pt s a ll owe d a s hort di sc u ss ion of c h e mi ca l diffusion Drug delivery se r ve d as a link to discussino di oes tiv e b b physiology a nd e n zymes. T o int ro duc e this topic randomly se l ected st ud ents were asked to read th e con tent li s t o n severa l emp t y soft drink co nt a in ers. The most common ingredient, hi g h-fru c to se co m sy rup was id e ntified on all containers. Stu dents were asked a bout the ne ed for com sy rup creating some discussion on th e swee tn ess, so lubility, a nd production cost of the sy rup This l e d t o discussion on re ac tor de s i o n and the b c h emica l process for ob t a inin g co rn sy rup. A co mpr e h e n s iv e engineering proces s diagram for comp l ete corn wet millin g was presented 1151 emp h as i zi n g the importance of acid hydro l ys i s o r e n zy m a ti c degradation. Th e discussion co ncluded by introdu c in g a spec i fic ex p erime nt s tud e nt s would co ndu c t exa minin g e n zy m e (a nd ac id ) degradation of s t a rch HANDS-ON EXPERIMENT For a hands-on experime nt stude nt s were asked to s tud y enzyme-mediate d o r acid hydrolysis of pot a t o starc h Students Biochemistry and Bi o t e ch no l ogy Human Physi ology Immunology, Ge neti cs Male F ema l e Flui d Mechanics, S tati CS and Ele ctrical Ci r cui t s Figure 2. Student pre-assessment: sc i ence and eng in eering knowledge by ge nd er. Fa/12006 285

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Figure 3. Different groups pulverizing potatoes. were split into groups of five Each group was pre-selected to be from differing high schools, and balanced by gender with three females and two males The low-budget experiment is straightforward, as students either mash cooked potatoes or cut raw potatoes to place in a water bath. Enzyme (a-Amy lase) or acid is added, and the solution is mixed, maintaining a constant temperature. In presence of the enzyme or acid starch hydrolyzes to smaller sugars. The presence and amount of starch in a sample can be measured using the iodine-clock reaction-in which the abundant presence of starch is indi cated by the fast appearance of blue color ; reduced presence delays the appearance of blue color; and complete degradation of starch into glucose is indicated by the loss of blue color. Digestion and saliva reactions having already been discussed in the overview the background consisted of a short (one slide) presentation on the importance of carbohydrates (e.g., immediate source of energy for the body), and various sources of carbohydrates including rice com, wheat, and potatoes. Other information included types of sugars (granulated sugar maple sugar, honey, and molasses), and more specifically, simple sugars (fructose and fruit sugar) and double sugars (sugar cane, sugar beet, maltose or malt sugar, and lactose or milk sugar). The experiment was conducted so that students had to take an active role in developing and clarifying experimental pro cedures. [ 1 6 1 A brief experimental protocol, with instructions regarding volumes of water directions to use the enzyme or acid, and the solution temperature was provided to students. 286 The detailed protocols with complete instructions were deliberately not given while critical direc tions were provided. Furthermore, although each team had the same experimental task, each group was given a unique experimental condition, so that the influence of temperature, mixing, and substrate-size on reaction rate could be discussed. Variables included the amount of potato used, whether it was baked or unbaked, mashed or cut, the temperature (30 C 50 C or 70 C), and either enzyme or hydrochloric acid. Potatoes were purchased from a local supermarket while a-Amylase (e nzyme ) was purchased from Sigma Aldrich Co. An iodide-clock reaction kit was from Universe of Science, Inc Experiments were conducted in 500 mL or 1000 mL conical flasks and each group was equipped with a hotplate / magnetic s tirrer, thermometer and pH strips. Each group was told to record initial potato weight and solution pH, and to take samples at regular inter vals to measure starch content. Baked potatoes needed to be mashed and unbaked potatoes cut into s mall piece s using a kitchen knife. Students enjoyed this part of the work as an easy means of team participation (Figure 3). Each group had 20 minutes to get experiments under way before laboratory tours began LABORATOR Y T OUR Each experimental group was split, with half of the class (15 students) accompanying an instructor on a laboratory tour while the other half stayed to continue experimentation. After the first tour, the students exchanged places. Each laboratory tour was scheduled for 30 minutes. In the laboratory tour students were taken to an undergradu ate in s tructional laboratory containing various unit operations While emphasis was given to a packed bed reactor containing a resin enzyme, other equipment included a heat exchanger skid, bioreactor assembly, dialysis, absorption column, and a two-phase flow pipe assembly. A demonstration running a two-phase flow of water and air was conducted, including discussion of computer interface s and control valves Students liked the demonstrations, and asked a number of questions regarding the computer interface ORAL PRESENTATION S After a lunch break during which experiments continued the students returned to conclude their experiments. Each group was asked to present the experimental observations / outcomes as a team. They were given 10 minutes preparation time. During this recess they were told the presentation should be a group effort, all member s should be respectful to other Chemical En g in ee rin g Educatian

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group members and the audience should ask questions. Each group was allowed five minute s to pre se nt it s report, including question-and-answer sessions. In the first group, the two male members monopolized the presentation with the three female m e mber s only par ticipating during the question-and-an swe r portion. The initial group also provided no introductions of gro up members or motivation(s) for experimental work. Prior to the beginning of second presentation, instructors gave immediate feedback on presentation strategy and reminded the st udents about the required equal participation from all gro up members Thi s method of immediate feedback to influence presentation be havior was followed for all pre se ntation s. Further instructor s so licited additiona l critiques from the audience so the entire c l ass cou l d become a so u rce of feedback on presentation s ty l e and effectivenes s. The instructor s ensured their remarks were neither admonishing nor overly negati ve Subsequent gro up pre se ntations continued to improve. The second group correctly followed initial in s truction s by introd u cing all team member s, a nd allowing th e m to actively participate Pr ese ntations from each group improved overall, but st u dents had difficulty adequately reporting experimental resu l ts. Furthermore none of the te ams mentioned conclu sions and recommendation s for future in ves ti ga tions. Inter estingly, one group that performed the ex p e riment s imilar to another group reported that s i gnifica ntl y more starc h remained in their solution but failed to make any compar i so n with the other team. Neither group initiated a n y di s cussion or ques tions of the results Instructor s had to ask s tudents for po ss ib l e explanations of the difference s between eac h outcome. EFFECTIVE PRESENTATIONS EXPERIMENTAL PRACTICE AND PROCEDURE AND CRITICAL THINKING After the pre se ntation s, an overview of what needed to be included in the pr ese nt a tion was discussed. Some of the point s a ddressed included : 0 Wh y did yo u do thi s ex p e rim e nt ? 0 What was yo ur e xp e rim e ntal se t-up ? 0 What we r e yo ur r es ult s? 0 What co nclusions c an b e dra w n ? 0 What future plans wo uld yo u su gges t ? The students were commended for excellent performance in explaining their se tup s so the discu ss ion would be viewed po s itively rather than as criticism. Using the completed experiments as a guide and while their ow n presentation s were still fresh, a discus s ion on the attributes of an effective presentation was initiated Using question s s tated above the instructors introduced a general presentation format includin g introduction methodology re s ult s, conclu s ion s, and recom Fall 2006 mendation sec tion s. Although this pre se ntation out l ine is not robust it doe s incorporate many features of an effective presentation. 1 1 71 Th e s tudent s s eemed to e njoy participating in a discussion of effec tive presentation s from the unique per spect iv e of de v il' s advocate, with a recent presentation from which to consider s pecific need s, individual shortcom ing s, a nd de s irable impro ve ment s The in s tructor s also opened a general di sc ussion on ap propriate experimental practices and procedures. Specific que s tion s included were: 0 Wh y did th e p H drop in th e ex p e rim e nt s w h e r e ac id was used ? 0 What happ e n e d t o th e pH of the solution ? 0 What happ ened to th e temperatur e? 0 Did it tak e a l o n g tim e at the e nd of th e ex periment ? 0 Did yo u k ee p tra c k of tim e it ha s b ee n s ittin g in th e co ntain e r ? 0 Did th e v i scosity of th e slurr y c r e at e mixing probl e ms ? 0 What happ e n e d w h e n yo u add e d p o t a t oes to a pr e -mea s ur e d vo lum e of w at e r ? 0 What probl e m s arose ? The se que s tion s allowed discussion of the criteria neces sary for good experimental procedure s, the problems that may occur in experimental setups a nd necessary data to pro vide adeq uate a nd s ufficient information for experimental analysis. In addition th e re was an opportunity to emphasize the ethical aspect of reporting. One of the teams had forgot ten to include a ma g neti c s tirring rod, and thus their so lution was not well mixed r es ulting in le ss d egra dation of s tarch than ex pe cted. The y were hone s t about it and the other team s thought th a t was a humorous mistake. T h is allowed a discus s ion of how no experiment i s really a fai l ure every experiment provide s information and in this specific case, mixing matters a great deal. Other as pect s of th e ex periment encouraged critical think in g. Some s tudent s s pilled excess water from their beakers becau se they did not account for additional vo l ume when adding potatoe s In other experiments uniform heat distri bution was a n i ss u e. These complications were built i nto experimental protoco l s and the students needed to ide n tify overcome, and otherwise consider these is s ues to accompli s h their experimental work Together with the hands-on experiment, students were s hown a 5 liter bioreactor with a jacketed heater and control lable agitator durin g th e l a boratory tour. Explanations were given about how bior eac tor s work. Reexamining these factors after their experiments emphasized the differences and simi laritie s between the two se tups and the need for engineering design of equipment. 287

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2 8 8 9 8 ., 7 .... al 6 ..,,, .E 5 ,;,:, ..... 0 al 4 .=, 3 s = z 2 0 Medical School Bioengineering H ad Not Considered/ Encouraged to Pursue Considered and More Encouraged Figure 4. Modu l e effect on students perceptions of available career options 2005BioModule REACH Outcome-Smyey Name: ___________ What is your long term career goal? Please provide appropriate rep lie s to each of the following questions PROBLEMS AND RECOMMENDATIONS At the end of the module, a general discussion was initiated asking students to comment on their experiences during the module Principal comments included : a ) Confusi o n from swit c hin g of operators takin g care of e xp e riments b) N ee d for pr o p e r e quipm e nt to mash potato e s or c ut th e m into small pi e c e s c ) D e sir e to hav e an experiment wher e th e produ c t is a take-hom e s ubstance ( not som e f o rm of potato e s that are discard e d) cl) Better e xp e rimental information and more specifi c experim e ntal protocols e) A pri ze for th e b e st p e rforman ce t o moti v at e their work With each suggestion the instructors provided immediate feedback and an explanation of the current module structure in order to elicit further group discussion For example, team splitting can cause confusion due to lack of commun i cation, but may not necessarily be a problem It is very common in industrial practice to have three continuous shifts, and personnel must effec tively communicate between shifts. One way to promote communication may be to include 1. Did the module e11t:011rage y o,1 to comider at.te11di11g medical school ? YES or NO a IO-minute break between the tours with specific instructions given to update group members regarding exper im ental status. 2 Are you more i11Jere.rled in becomiJ,gm, engineer focusing on biole c ho11D/ogy ? YES or NO 3 Wlw is your ca,lfident:e level iJisayiJ,g you ,oulerstmui the importmice of com syn,p ? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don t know 4 Wlw is yo1u level of wulerstmuii1,g of the concepts belwui ca,itrol/ed dn1gdeli:v ery .IJl!lems? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100 % 0 Don t know 5 Wlw is yo1u ca,lfide1ice level iJ1sayiJ,g yo11 ,oulerstmui 1111! tlJ!edfor prarthelic devices? 0 10% 0 30% 0 50% 0 60% 0 70% 0 90% 0 100% 0 Don't know 6 Wlw is yollT co,ifide 1ice level in sayi,,g you ,ouierstmui lv w to properly prese11L experimeiitaJ dat.a? 0 10% 0 30% 0 50% 0 60"/a O 70% 0 90% 0 100% 0 Don't know 7 How mu c h didym uke the iJ1Lrod11clory lecture ? 0 10% 0 30"/a O 50% 0 60"/a O 70% 0 90% 0 100% 0 Don t know 8 How much didym eiyoy the laboralory tmu md did yo,, learn anyllwzg ? 0 O"/o O 20"/a O 40% 0 60"/o O 70% 0 80% 0 90"/o O 100% 9. Howmucl1didyo,1uketl,e experimeilt ? YES or NO 0 CJD/a O 20"/a O 40% 0 60"/a O 70% 0 80% 0 90"/a O 100% 10. Please name the topic yo,1 most enjoyed in thi.r module Figure 5. Post-assessment survey form. In order to save time one could use a household food processor to mash or chop the potatoes. The incomplete nature of the experimental protocols has already been mentioned and the students were provided some reasoning for the lack of information. Their reactions were noted on this approach in future classes The suggestion of a prize for the best group was interesting as the students had been conditioned over the previous week by many of the REACH faculty to expect such forms of praise While considering the suggestion the current module seems best served by not including prizes as a form of reward Overall the students enjoyed the desired give-and take interaction enco u raged by the instruc tors, and were open in their suggestions for improvements. OUTCOME ASSESSMENT To understand the effectiveness of the mod ule on student learning an outcome assess ment was provided (Figure 5), similar to the C h e mi c al En g in ee rin g Edu c ati o n

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pre-a ssess ment survey. To mea s ure the main objectives of the modu l e, i .e., the influence on st udent s per s pectives of careers in bioengineering and medical engineering / sc ience the first two questions in the pre-as sess ment were repeated. Out of 30 students, a large number (~2 / 3) had already expressed interest in attending medical school (pre-assessment data ). Therefore no s pecific conclusions could be drawn r egard ing an increase in the student desire awareness of medical sc hool, or career options (F igure 4). By comparison, an increa se in st udent awareness of bioengineering as a career was observed, as four students indicated a new interest in th e bioengineering field. Thi s suggested that the module was s ucce ss ful in introducing bioengineering. Students were also asked to rank their confidence in the importance of corn syrup, for which the overall confide n ce doubled (F igure 6) with a lar ge gro up of s tudent s indicating more than a 70 % confidence level. When asked about their confidence in drug delivery and prosthetic devices, the aver age was 63 % 13 % ) and 76 % ( 20 % ) re s pecconclusions regarding differences between male and female re s pon ses i s indeterminate given the small samp l e popu l ation, the overall nature of s tudent s' responses indicated both s ignifi cant interest and engagement with instructors and presented material s. Further, a larger number of female students t h an male s tudents indicated the experimenta l portio n was the most enjoyable topic. The trend was opposite the previous response to the s pecific question in which male s tudents ranked their enjoyment of the experiment at 54 % compared to female s tudent s at an average of 47 % SUMMARY The module introduced K-12 s tudents to the field throug h interactive presentation s, discu ss ions experimental proce dure ( hands on work), and a tour of working engineering laboratorie s The pre se ntation was designed to encourage s tudent s' questions while presenting five major aspects of the bioengineering field. Within each primary topic were TA B LE2 tively for each category. Further, st udent s indicated a 74 % 22 % ) confidence lev e l in experimental data presentation. Without a pre-a ssessme nt que st ion re garding their abilities in data presentation, however the effectiveness of this aspect of the module could not be assessed, a l though one s tudent did mention that this portion of the modul e was hi s / her favorite experience. "W h at was t h e to p ic yo u most enjoye d ? by category and ge n de r The final assessment question s ga uged overall interest in the introductory presentation materi a ls laboratory tour and hand son experiment, for which re sponses were ~50 % ( 28 % ). A follow-up, open-ended que tion asked for s tudents favorite experience d u ring the day with re s pon ses grouped into six gen eral categories ( Table 2). Sur pri s ingly nearly 53 % indicated the lecture materials as their favorite events (o ne s tudent noted that the afternoon lectur e on effective presentations was the mo s t intere s ting and said it included information th at he / she had never been shown or heard previously) ti) ..... C: Q) "C ::::, ..... (J) ..... 0 ... Q) ..c E ::::, z 12 10 8 6 4 2 0 C) Category General Lectur e Pro s thetic Device s Artific i a l Organ s Experim e nt Lab Tour o Re s pon s e >7 C) C) C) N M M 2 2 4 2 I I C) C) L[') (D Student Response F Total % I 3 10 4 6 20 3 7 23 6 8 27 I 2 7 3 4 13 Pre Q#l Post Q#3 I C) C) co C) The introductory material s are likely the most intere s ting s imply due to the interactive nature of the presentation s in relation to identifiable product s and aspects of importance in st udents live s. While drawing Fig u re 6. Student responses to Importan ce of Corn Syrup. Fa/12006 289

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sec ondary investigations that delved into both scientific and engineering aspects. All topic s incorporated de s ign aspect s to draw on per so nal experiences with bio e ngineering product s, processes and re se arch Student s enjoyed the presentation s tyle and topics and were a ble to connect much of the mate rial to their own experiences and knowledge Based on the immediate responses the overall module was successful in influencin g their intere s t in bio-b ase d e n g ineering. To better under s tand the effectiveness of the module however long term follow-up s tudie s are needed examining the students' ca reer choices. The assessments also need to be redesigned to more effectively mea s ure modul e fea ture s a nd goals. ACKNOWLEDGMENTS We would like to thank Oklahoma St a te Regents for Higher Education Conoco-Phillips, NASA and OSU CEAT for financial s upport and Eileen Nel so n for h e lp with the s ur vey a naly s i s and manuscript preparation REFERENCES I Th e Scie n ce and Engin ee ring W o r kfo r ce: R ea li z ing Americas P otenr i a/ National Scie n ce Board A u g u s t (20 03 ) 2 Lea rnin g for th e Futur e: Changi n g th e Culture of Math and Sci e n ce Educat i o n to Ensure a Compe titi ve Workfor ce, Committee for Eco nomic D eve l o pm e nt M ay (2003) 3 Bayer Fac t s of Science Education IX : A m e ri ca n s' Vi ews o n the R o l e of Scie n ce a nd Technology in U.S. Na ti ona l Defen se" (2003) 4. Old s, S.A. D .E. Kant er, A. Knud so n a nd S.B. Mehta D es i g nin g a n O utr eac h P rojec t th at Tra in s Both F utur e Faculty a nd Future E n gineers," Pr ocee din gs of th e American Society for Engineering Edu ca ti o n, Nas h v ille (2003) 290 5 Knight M .. and C. Cunning h a m Draw an E n gi n eer Test ( DAET ): Development of a Tool to In ves ti ga te S tud e nt s Id eas abo ut E n g in eers a nd E n gineering," Pr oceedings of the American Society for Engi n eer in g Education, Sa lt Lake City (2004) 6. Cha n d l er J.R ., and A. Dean-Font e n ot, TIU Co ll ege of E n g in eer in g Pr e-Co ll ege En g in ee rin g Academy Teacher Trainin g Pro gra m Pr oceedi n gs of th e American Society fo r Eng i neer in g Education, Salt Lake Ci t y (2004) 7. D o u g l as, J ., E. I ve r se n a n d C. Kalyandurg "E n gi ne eri n g in the K-1 2 C l assroom: An Ana l ysis of C uIT ent Practice s & Guidelines for th e F utu re ASE Eng in ee rin g Kl 2 Ce 111 e r Nove mb e r (20 04 ) 8. K o lb D. A Experiential L ea rnin g: Experience as th e Source of Learn in g and D evelopme111 Prenti ceH a ll E n g lewood Cliffs NJ ( 1984 ) 9. H o n ey, P ., a n d A. M umf ord, "T h e Manual of Learning Style s Maid e nh ead H o m ey ( 19 86) 1 0. Bran sfo rd J. A. Brown, a n d R Cooking, H ow P eop l e L ea rn : Brain Mind Experience a nd School Nat i ona l Academy P ress, Wa s h ingto n D.C. ( 1 999) 11. Donovan, M .S. J .D Bran sfo r d, a nd J W. P e ll eg rin o H ow P eo pl e L ea rn: Brid g in g R esearc h a nd Practice Na ti o nal R esearc h Co un c il ( I 999) 1 2. Fe ld er R ., a nd L. S il verman Le a rnin g a n d Teaching Styles In E n g n eer in g Education ," Eng. Ed., 78 (7), 674 ( 1 988) 1 3. Fe ld e r R. and R Brent "U nd ers tandin g Student Difference s J Engr. Ed 94 ( I ) 57 (2005) 14. Baker A., P Jen sen a nd D. K o l b, Conversationa l L eami n g: An Expe rie n tial Approach 10 Knowledg e C r eation, Quorum B ooks, Westport, CT (2002) 1 5. C h ap t e r 9, Intr oduction to AP 42 Vo lum e I Stationary Point a n d Area So ur ces," US EPA, 5t h Ed. ( 1 995) < http : // www.epa gov / ttn / chief / ef p ac / ind ex. html > I 6. Watai L. A. Brodersen a nd S. Brophy, D es i g nin g Effective E n g i n ee rin g Laboratorie s: Application of C h a ll e n ge -Ba se d Instruction Asy n c hron o u s Learning Method s a nd Comp ut er -Su pported In stru mentation American Society for Engi n ee ring Edu c ation Ann u al Conference & Exposition Salt Lake City (2004) 1 7. H e n dricks, W Secrets of P ower Preselllations, Career Pre ss, Frank lin Lake s, NJ ( 1996) 0 C h e mi ca l Engineering Educat i on

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lej5::j classroom ) ... _._....__ -------PRESSURE FOR FUN: A Course Module for Increasing ChE Students Excitement and Interest in Mechanical Parts WILL J. S CARBROUGH AND JENNIFER M. CA SE Univ e rsity of Cape Town Rond ebosc h South Africa 7701 C hemical engineeri n g as a pro fess ion g r ew in th e late 19th century out of co ll a bo ra ti o n between chemists a nd mechanical engineers worki n g to d eve lop large sca l e indu s trial processe s To thi s d ay chemica l enginee r s workin g in the pro cess indu s tri es are clo se l y involved not o nly with particular chemical proc esses-a nd unit operations s u c h as reactor s a nd se pa rators that ca n accomp li sh these proces sesbut a l so w ith mech a ni cal d ev ic es s u c h as pump s a nd va l ves that e n able the tran s port of m a teri a l s. We h ave found, how ever, that skill or even familiar it y with mechani ca l components is often unde ve lop e d in first-year chemical e n g ineerin g s tudents even thou g h th ey a r e often the be s t and bri g hte s t sc i e n ce a nd mathematic s s tudent s a t the high sc hool l evel. The firsta nd second-year c urriculum i s often theory intensive a nd the practical exposure that doe s take place i s more in the t radit ional scie n ce s ubj ects, comp l eme nt ed by some experime ntal work u sing ba s i c pilotsca l e un it opera tion s. By the time they reach th e ir se nior year, we find man y s tudent s, although academically re l atively s ucce ss ful still s truggle to co nne ct reality to theory. In a ddition a large seg ment of the cla ss i s relativel y intimid a ted by the prospect of worki n g in a plant environment. In the Department of Chemic a l Engineering at the Univer s ity of Cape Town (UCT) we have be e n consideri n g for some time how best to modify our curriculum to afford fir s t-year s tudent s better expos ur e to m ec h a ni ca l aspects of c h emica l engi n eeri n g. It was fortuitous that the oppo rtunit y arose to design -s pecifically for chemical e n gi n eeri n g s tudent s-a five-week module that would form part of th e mandatory fir s t-year mechanical dra wi n g course Pr evio u s l y this part of the co ur se dealt w ith the int erpretation of chemica l e n gineer in g flow diagrams but recently it was decided to move thi s Copyrigh t Ch Division of ASEE 2 00 6 Fa/12006 material t o the seco nd year to int egra t e it more clo se l y with co r e c h e mic a l e ngin eer in g co ur ses. In di sc u ss ion a mon g a gro up of academic s taff we de cid e d that our objec ti ves for thi s modul e wo uld not be primarily foc u se d o n detailed co nt ent knowledge but rather on c h a n g in g s tudent s' att itud es toward thi s aspect of c h emica l engi n eer in g. The se were th e objectives for th e new module : G e t s tud e nts exci ted abou t mechanical thin gs. D eve l op s tud en t s' ab ili ty a nd co nfid e n ce t o ex plai n h ow things work (a nd the d es ire t o l ea rn more). Will J Scarbr oug h is currently a postgradu ate in the Engineer i ng Education Re searc h Group within the D epartment of Chemical Engineering at the University of Cape Town. H e was appointed as lecturer / course orga nizer for the duration of this module Pre vio us experie n ce includes work i n i n s piration and excitement through the robotics program s of F. I.R. S T. a nonprofit ba se d in the United States. H e received hi s A.B. i n engineering sciences with a minor in ed ucation from Dartm out h College i n 1998 His research interests include scie nce and technology education, inspiration, and classroom knowledge network s. Jenn if e r M Ca s e is a senior lecturer i n the Department of Chemical Engineer ing at the University of Cape Town with a res e arch focu s on educational development H er early career experie nce was in teaching high school mathematics and science and s he subseq u ently co mpleted an M.Ed in science education at the Univer s ity of Leed s and a Ph D at Monash University. Her research interests are in st udent learning with a focus on improving the s ucce ss of students from nontraditional backgrounds She lectures in the junior undergraduate program. 29 1

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H elp students start building a sense of "mechanical intuition." Provide familiarity with equi pm ent diagrams and hard ware. D eve lop students' ability to link the "real world" and theor y This is a rather different set of objectives compared to what chemical engineering lecturers usually design courses around. How do you explicitly design a course module for excitement? This paper describes how we went about meeting this cur riculum development challenge. The new course module ran for the first time in 2004, and is now an established feature of the first-year B.Sc (chemical engineering) program at UCT. In this paper we focus on the process of setting up and eva l uating the course during its first year. APPROACH TO COURSE DESIGN We found a useful rationa l e for running this type of course in the classic work by Woolnough 111 regarding practical work in school science. He argued against the widely held belief that practical work should be done for the sake of theory, and that conceptual understanding will be an automatic outcome of successful practical work. Instead he suggested that practi cal work is better understood as having its own end, either to develop skills, to develop the abi l ity to conduct investigations or to simply get a feel for important physical phenomena. The modu l e we developed fits clearly in the latter category, with the chief aim being to allow students physical interaction with the mechanical aspects of chemical engineering. In recent times a number of innovative courses have been reported on that offer such hands-on experiences to first-year chemical engineering students. For example, Barritt, et al. 1 2 1 describes a highly successful multidisciplinary project that invo l ved small groups of students in the design man u facture, and operation of a pilot-scale water treatment plant. Moor, et al., 1 3 1 also ran a multidisciplinary project for first-year engi neering students, this time involving the de s ign of a reverse osmos i s system, with the co ll ection and interpretation of experimental data from an existing rig Willey, et a[.,1 4 1 de signed a first-year project that involves experimentation with a sequential batch-processing system. Most of the courses reported in past literature such as tho se described here, incorporate relatively sophisticated design projects that run over a long duration. Our aims were more limited as we had a large class and a short period of time. We therefore decided to focus on our primary objectives, which were centered on changing students' attitudes toward working with mechani ca l artifacts. To meet these objectives we adopted a particular teaching approach that included small class size, group work, and excellently trained facilitation Additiona l ly the activ i ties were planned to give students a sense of accomplishment and 292 encourage experiential learning and un so licited experimen tation In traditional term s, this resulted in a combination of practice and some tutorial in one class period without the use of a lecture period Assessment was based on a combination of individual a n d group assignments, and contributed 10 % toward the final mark for the mechanica l engineering course in which this module was located. By concentrating on the primary objectives of the course, content topics that s uited these objectives could be chosen and a rapid movement between topics undertaken if necessary. We chose to use valves, pumps, pressure, and flow regimes in our activities. The intended objectives, however remained focused on excitement and learning how to explain, rather than on content. Class and Group Size The class of nearly 100 students was split into five groups of approximately 20 students, and each group was allocated a weekly 85-minute session over the duration of the five week course module. Each session was attended by two or three tutors and the course organizer Each class made use of s tudent teams ranging in size from two to four members. In most cases students continued with the same team for two s uccessive classes. An introductory chemical engineering course running concurrently had given the students s ufficient group-work practice so this aspect posed no difficulty by the time they began this module in the seco nd semester of their first year. Facilitation by T utors One vital component of the course was facilitation by tutor s. Students were asked to operate unlike they had in any previous school or university situation Such unfamiliar expectations occasionally caused students to balk at requests. Additionally, with little experience in a potentially intimidating si tuation s tudents often had no idea where to begin or how to proceed after achieving a portion of the activity. Our solution was to handpick tutors and train them in facilitation (a lso known as coaching). The primary role of the tutors was to closely observe student teams and offer guidance when necessary. The tutors were mainly graduate students who were selected based on previous experience with tutoring and an observed ability to patiently facilitate the group proce ss. Tutors were given a s hort manual on facilitation and practiced a short role play illustrating typical situations. Detailed tutor notes were provided for each class including a time schedule, jobs for specific tutors likely problems student teams would encoun ter, and topic-specific reference material for tutors to use as prompts while facilitating. One example is the specific list of difficulties when taking apart and re-assembling a hand pump Before each week s class, the tutors met to go over the activity, practice it themselve s, and discu ss the reference materials for the topic and facilitation tactic s for the activity. The environment within the classroom was also an impor Chemica l Engineering Education

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tant consideration From the initial de s cription of the module to the manner of facilitation s tudent s were told they had freedom to experiment try things out or fiddle ." The class organizer and tutors m a de a c areful effort throughout the mod ul e to create an environment saf e" for experimentation, in particular for the s tudent s mo s t n e rvou s about ph ys ical parts and equipment. THE ACTIVITIES Each week students were pre s ented with a different activity with the final challenge taking place over two week s. The assessment wa s integrated throughout the module Industry Parts The introductory cla ss con s isted s imply of pairs of students taking apart larges cale components from industry and attempting to intuitively figure out the item s main purpo s e and interpret the mechanical design. Student s were allowed the time to construct their o wn id e a s An important elem e nt wa s g iving e a ch s tudent pra c tical experienc e with phy s ic a l part s Mo s t of the paits were nothing more complicated than v alve s, yet th e novelty of valve s weighing 20 kg w as clearly demon s trated with an in i tial com ment Thi s i s a pump right? After the activity a handout with information on each type of valve wa s given During cla s s we tr i ed not to criticize or correct s tudent s' ideas but instead encourage each pair to comp l ete Diogr9!:!Ll = Imp o rtant Feol\.Jres Di ogr om c. Pump C '::l c\ e S t ep 1 the line of thinking them selve s. For a s sessment purpo s es each s tudent was required to submit rough notes and a written explanation of how the mechanica l part worked. Ba n s QCti '::"3 a s VO l \.lcS 11-+ +-f,.j r V erirs t:: + --P iston Spr i ng I'-..... t----1-\-c ~\in de r Ai r 1----l:!= = :::J-"2 ~r aw Flui d ~ram 3 : Purnp C~ cl e Step 2 t Force r .err,ovecl t Sp ir,q cka:impres.ses =u ,i ,l"\q p \ stcirl +o mo ve ~tds A S UCl
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Key cl'.J I Figure 2. The Challenge ri g s etup. 16mm ID clear tubing ---10mm ID clear reinforced tubing 5mm black irrigation tubing a task to a reasonable degree of satisfaction. Only in written feedback afterward were stu dent misconceptions noted. .. C> [DJ) adaptor from 5mm tube to large tube Ball, gate or globe valve T connector for 16mm tubing T connector for 10mm tubing Mechanical Drawings adaptor 16mm tubing to 1 / 2" thread In a rever s e from previous exercises the next class began with sets of mechanical draw ings for six types of pumps. Each group of three or four students had a limited amount adaptor 1 0mm tubing to 1 / 2" thread clamp for tubing hose clamp I syringe of time to work backwards from the drawings for two types of pumps to discover how the pumps operate. The previous hands-on experience with a reciprocating pi s ton pump (the hand pump) provid ed a base for interpretation of the pump drawings. Partway through the class students were rearranged into new groups such that no one in the new group had encountered the s ame pumps Then in a very restricted time each s tudent wa s required to explain the pumps they knew to others. THE CHALLENGE The final project was a bit of a competition and a fun way to complete the experience. We named it The Challenge. For both the fourth and final classes, a custom-designed but inexpensive rig was provided for each team of three to four students. A diagram of the rig is s hown in Figure 2 For the first day students were required to complete a preparation worksheet and then experiment with the rig to demonstrate concepts relating to pres s ure head, laminar and turbulent flow and Reynold s number. Figure 3. Students participating in The Challenge. Within this class and the whole module, students were faced with the need to come up with their own answers. When students asked questions about the pump, tutors-rather than provide the answer immediately encouraged students to "try it and see what happens ." Similar to other activities in this module, free experimentation was required to discover the workings of the mechanism For The Challenge, students worked to control the motion of a bead in a system of pipes using pressure changes (Figure 3). Students had to experiment with the equipment to learn the effect of closing and opening particular valves. The activitie s were carefully designed to be initially difficult, but easily ac complished through effort teamwork, and practice Many unplanned learning points arose as a result of the phy s ical activities For example, a s dye flowed through the system of pipes with water and dye flowing from the lower left to the upper left of a D s hape a trickle of dye left the Creating a detailed exp l anation of a relatively simple pump allowed students to build confidence by being able to complete 2 94 C h e mi c al En g in ee rin g Edu c ati o n

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main flow to s l owly swirl in the loop on the right of the D ." A student remarked that they h a d no idea any water would leave the main flow. The final competition was run as a s porting event with team name s, an elimination tree s tructure s topwatche s to record time s, and a prize for the winning t ea m. A video ca era captured the event and projected it onto the big sc reen behind the two compet in g team s The other s tudents cheered as their classmates competed (s hown in Figure 4 ) For as sessme nt purposes each team was required to submit a brief report on "T h e Challenge ," and thi s counted as 30% of the module grade. EVALUATION OF THE MODULE From simp l e observat i on of students during the module, it appeared that they had gained both confidence and interest in finding o ut how mechanical thing s work. In particular we noticed stude nt s' enth u siasm with the activities and high level s of verbal interaction within s tudent team s as they sought to exp lain what they had deduced. We needed however to find a way to more systemat i ca ll y gauge the s u ccess of the activ it y in meeting it s objectives, and therefore administered a s hort Likert-type survey to all s tudent s before and af ter the module. Five s tat ements were provided and students were asked to in dicate th eir response on a sca l e of ( 5) strongly agree, (4) agree, (3) uncertain (2) disagree or ( 1 ) s trongly di sag ree Ninety-two comp let ed question" intuition ," began with the greatest di sag ree" of all questions at 15 % After the module this was reduced to 3 % a lth ough this qu es tion retained the largest number of uncertain re sponses, with 27 % indicating students who did not have the confidence to claim mechanical intuition in the other ques tions. The combined respon ses "ag ree and "strongly agree" to intuition moved from 42 % to 73 % Student interest in how things work, Question 3, started high and had nowhere to go; thi s group of stude nt s began and remained a curious Figure 4. The w inning group ce lebrate s. naires were returned Table 1 (next page ) s h ows the change in the mode (most frequently reported response ) for each statement. A more comp lete indication of the range of re sponses is given in Figure 5 Box & Whisker Plot: Response The large s t change observed was ques tion 1, "exp l ain"; most students (51 % ) began not knowing if they could explain how a mechanical object works to some one else or not. The responses "ag ree and "s tron gly agree" moved from 3 8 % before the module to 97 % after the module Question 2, Fal/ 2006 strongly~ ree ~ree uncertan dsagree strorg ly dsag ree strongly~ ree ~ree uncertan dsagree strorg ly dsag ree -= I __ Before Aller Quasllon: 1 'El)(l)l ain' Before After auasuon: 4 'emild' Before Alter OUlstion : 2 'lntutlon' Before Alter OLestion : 5 'lheaY Before After OuesUon : 3 'find out' Figure 5. Box and Whisker plot of survey responses N = 92. Median D 2s%-7s% I Min-Max 295

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TABLE 1 Modal Responses by Students, Before and After Module, N=92 # Question I I can explain how a mechanical object works to someo ne e l se 2 I h ave an intuition that allows me to under s tand mechanical thin gs. 3 I am interested in finding out how things work. 4 I am exci ted t o do a practi ca l or job that involv es mechanical thin gs 5 I ca n connect chemical engine eri n g theory to an ima ge in my mind of what actually happen s. bunch Question 4 "excited," saw only a small decrease (3%) in those "uncertain" about working with mechanical things Nevertheless, the combined responses "agree" and "s trongly agree" moved from 67% to 78%. For the final ques tion theory, the combined responses "ag ree and "s trongly agree" moved from 64% to 86%. CONCLUSION In this paper we have reported on the development and evaluation of a new module in our chemical engineering undergraduate program, which has the primary objective of getting students excited and confident about working with mechanical artifacts. It has been shown that the module successfully increased students' confidence and perceptions in their ability to work with and explain mechanical things It was also great fun for the students, tutors, and the course organizer. The module is now fully established in the program, and makes an imp011ant contribution to the development of degree outcomes It was a fairly radical move to design a course module around attitudinal objectives (exci tem ent, etc.) rather than 296 Refer e nc e Mode Mode I'!. in te x t Before After "exp lain uncertain ag ree t "i ntuition uncertain ag r ee t find out" stro n g l y strongly agree agree "excite d agree stro n g l y t agree theory" agree agree the more conventional content-based de s ign Even with the current focus on outcomes -b ased design, this is still often a neglected aspect of curriculum development in chemica l engineering We hope that the descriptions of the activities given in this article will encourage others to try them out with their first-year students. ACKNOWLEDGMENTS The tutor Ryan A. Stevenson was invaluable for his help in brainstorming creative ideas for this module. The support and encouragement of other colleagues in the Department of Chemical Engineering at UCT is also acknowledged. REFERENCES I. Woolnough B.E. Exercises, Investi ga tion s and Experiences, Phy. Ed. 18 60-63 ( 1 983) 2 Barritt, A., J Drwiega, R Caite r D Ma zyck and A. Chauhan A F r es hman D esig n Experience: Multidisciplinary D es i gn of a Potabl e Water Treatment Pl a nt, Chem Eng. Ed., 39 (4) 296 (2005) 3. Moor S S., E.P. Saliklis, S.R Hummel and Y.C. Yu A Pr ess RO Sys tem: An Int e rdi sc iplinary Project for First-Year Engineering Students C h e m Eng. Ed 37(1 ), 38 (2003) 4. Will ey R.J J .A Wilson, W.E Jones, and J H Hill s "Se quential Batch Processing Experiment for First-Year Chemical Engineering Student s," C h e m. Eng. Ed., 33(3 ) 216 ( 1999) 0 Chemical Engineering Education

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.ta.5.._c_u_r_r_i_c_u_l_u_m __________ ) BIOMOLECULAR MODELING in a Process Dynamics and Control Course JEFFREY J. GRAY Johns Hopkins University Baltim ore, MD 21218 T he field of chemical engineering ha s always been dynamic and evo l ving, from the field of applied in dustrial chemistry at the beginnin g of the last century, through the revolutionary reformul a tion of unit operations and engineering sc ience in the 1960 s to the extensive u se of computing and the incorporation of biology over the la s t two decades. l lJ This latter change i s now maturing. Chemical engineering departments around the world are changing their names and refocusing their mi ss ion s to include the fundamen tal sc ience of biology. BRINGING IN BIOLOGY There are significant reasons biology i s needed in engineer ing curr i cu l a. Most prominently the human genome was declared finished (at lea s t within a reasonable tolerance) in 2001, 12 3 1 and thus the full part s li s t of thi s organism and many others is now available. High-throughput and systems biology tools are extending thi s "parts li s t to provide com plex views of biological systems at the molecular and cellular level. 1 4 51 Concurrently the pharmaceutic a l industry is creating new drugs and products using new biotechnology ( cell culture, protein engineering, genetics). The se advances rely on tools from the fields of microand nanotechnology, and allow us to measure and affect processes on the biological-length scales (Angstroms to microns) Biological sys tem s are complex, rob u st, specific, and tightly regulated. Many engineers are interested in mimicking these qualitie s in designed materials, processe s devices and systems. In addition we are poised to discover new insights into biology by bringing chemica l engineering perspectives to the field. Changes at JHU At Johns Hopkins University (JHU), the Department of Chemical Engineering ha s lon g had a significant focus on biologically relevant problems, du e in p ar t to the proximity and diffusion of idea s from our prominent medical school and biomedical engineering department. Of our 12 full-tim e faculty, s ix have research pro gra m s primarily focused on biolo gica l problems (prote in engineering, cell engineer in g, drug delivery etc ) and mo s t of the remaining six have projects with biologica l implication s or applications (nanofl uidic s and n a node vices, se lf-a sse mbly ). Therefore as discussions within the chemical engineering community be ga n to s uggest that renaming departments could be useful to the field, we immediatel y implemented such a change at Hopkin s. Our department officially became the Department of Chemical and Biomolecular Engineering (ChemBE) in fall 2002 We also recognized that to be a department including biomolecular engineering it i s nece ssary to train students both undergraduate and gra du ate in this field. In practice many Hopkins students were already receiving such training Jeffrey Gray is an assistant professor of chemical and biomolecular engineering at the John s Hopkins University He has won a Beckman Young Investigator award and the 2006 Johns Hopkins Alumni Association E xcelle nce in Teaching Award. H is research interests are in protein docking therapeutic antibodies protein-surface interactions, and allostery Co p yr i g ht C h E Div i sion of ASEE 2006 Fa/12006 297

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as research ideas naturally diffuse into traditional courses and new electives. We r es olved to criti cally examine our undergraduate curriculum and revise course requirement s and topic s within all core courses to realign the undergraduate cur ricul um with our new mis s ion The co ntext and purpose for these new courses can best be summed up by the new JHU ChemBE mi ss ion s tat e ment: Our mis s ion is to define and educate a n ew archetype of inno va ti ve and fundamentally grounded engineer at the undergraduate and gra duat e l eve ls throu g h the fusion of fundamental c hemical e ngin ee ring prin ci pl es and eme rgin g di sc iplin es. We wi ll nurture a passion for technological innova l. 2. 3 4. 5. 6. 7. 8. 9. 10 tion scientific dis covery, and l eaders hip in existing and newly create d fields that cuts across traditional boundaries. W e will b e known for d eve loping l ea de r s in our in creasing l y technological soc i ety w ho are un afra id to ex plor e un c hart e d e n g in ee rin g, scientific, and m ed ical frontiers that wi ll benefit humani ty. Th e D e partm e nt of Chemical and Bi o mol ec ular Engineering o ff ers courses and training toward a B.S degree in c h emica l and biomol ec ular engi neering. Thi s discipline is dedicated to solving probl ems and generating va luabl e products from c h e mi ca l and bio lo g i ca l transformations at the mol ecu lar scale The und e r gradua t e program e mphasi zes the mol ecu lar science aspects of biol ogy an d c hemistr y along with engineering conce pt s essentia l to developing com mercial products and processes. B y se l ect in g an ap propri ate conce ntration or by free e l ec ti ves, students can pr epare for a professional career path or for further stu d y in c hemi ca l, biomolecular, o r a related engi n eering field as we ll as medical, la w or business school In the tradition of ]HU many und e r g raduat es are also involved in r esea r c hwo rking closely with fa cu l ty and graduate st ud ents in research grou p s. Changes in the Needs of a Dynamics and Control Course With the departmental deci s ion to change the undergradu ate curriculum, I contemplated que s tions about the proce ss co ntrol course. What s kills and abilities of dynamic s and control" are also applicable to biomolecular and nano sca le sys tems ? What new sk ills and a bilities mu s t be taught ? How are biolo g ical dynamical systems si mil a r to and different from traditional chemical proce ss sys tems ? How will our new graduates differ from their predece sso r s? Similar qu est ion s were discu sse d a t a recent series of national workshops. 1 61 A s additional background has been added to the curriculum, so me hav e even s ugge s ted that dynamic s and control be 298 BOXl Specific Course Objectives C r eate dynamk model s for c hemical a n d biol og ical proce sses including s ingle-variable and multivariable linear a nd n o nlin ea r sys t ems. Int eg rate dynamic models t o dete rmjn e sys tem behavior over tim e u si n g Laplace m ethods, s t a t e s pace method s or numerical method s. D es i g n co ntrol sc h e m es to con t ro l system beh avio r An a l yze dynamics a nd co nt ro l wi th frequency a pproa c h es. Analy z e n o nlin ea r dynamic s w ith phase portraits a nd num erica l method s. Meet e nvi ro nm e nt a l and safety objective s through proces s co nt ro l. Use com put a tion a l t oo l s for sys t em a n a l ys i s. Op era te a n indu str i a l co ntr o l syste m o n a l a b-scale process. Collaborate in s mall working team s on research ana l ys i s and de s ign Pr ese nt wo rk ora ll y a nd in w ritten r eports BOX2 Topics Covered I. Motivation for modeling a nd co ntrol 2. Modelin g and sys t em r ep r ese nt atio n s 3. State space model s and lineari za ti on 4. Int roduction to MATLAB 5. Ph a rm acoki n et i c modeling biomolecular modeling, and the Ce nt ral Dogma 6. Laplace tran sfo rms 7. Transfer functions 8. First seco n d and higher-order systems 9. Poles and zeros, tim e delay 1 0. Empirica l model form ul a ti on 11. Control of ge ne exp r essio n l ac operon 1 2. Feedback co ntr o l 1 3. PIO controllers 14. C l osedlo op tra n sfer fun c ti o n a nd s t a bilit y 1 5. Largesca l e biosimulation (g u es t l ect ur e) 1 6. Con t ro ll er tuning in indust r y (g ue s t l ec tur e) 1 7. Frequ e nc y re s pons e 1 8. Bode and Nyq ui st ap p roac h es, ro bu s tness 1 9. Intro duc ti on to n on lin ear dynamics 20. Lotka-Volterra model limit cycles, chaos 2 1. C urrent topics in th e lit erat ur e eliminated. 17 1 Th e s pecialty however is important in biology because biological proc esses are dynamic nonequilibrium and tightl y integrated a nd regulated as a sys tem 171 Ther e are severa l m ai n ways in which biolo g ical systems differ from traditional c hemi ca l process sys t e m s First, chemi cal pro cess syste m s a re human-cr ea ted with known p a rt s and components. Biological systems evolve without human design and they involve m a ny part s and co mponent s th a t we are still discovering Inde ed, the fact th a t we are rapidly disChemical Enginee ri ng Education

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In traditional process dynamics and control courses, students learn about sensors, transducers, and actuators. In the new ChemBE curriculum, students must also examine the structures of biomolecular control components. coveri n g these parts and their function s now (via the genome project and various microand nanoscale analyses) is one of the main reasons this topic is important today. In the study of dynamics of biological systems, the task is often to rever se engineer the workings of the sys tem whereas in a chemical process the task is to build a model from the components and parts of a known process 181 Secondly biological systems are almost always nonlinear Enzymatic reactions and active transport channels follow Michaelis-Menten kinetics allosteric protein s have multistate behavior and intracellular and tissue tran s port can be superor sub -diffu sive due to the structured environment. Biological sys tem s are often comp l ex, involving multiple length sca les from the atomic and molecular throu g h the tissue organ ism, and even ecosystem le ve l. The range of time scales i s equa ll y broad from the fluctuation s of protein molecules over nanoseconds to ecologica l changes over decade s. Biologi ca l systems incorporate multiple regulatory loop s including feed back feedforward, and more complex control sc heme s. These issue s are not limited to biological systems : real chemical processes also exhibit the challenges of interplay between multiple length and time scales nonlinear underly ing equations, and multiple interacting control loops Newer textbooks treat these subjects judiciou s l y in l a ter chapters 1 9 111 The utility of these topic s to both biological and chemjcal process systems provides additional motivation to include these ideas in a new dynamic s and control class. Recent chemical engineering textbook s have begun to include biological problem s and examp l es. For example Bequette's text includes module s on a biochemical reactor and pharmacokinetic models for diabetic patient s 19 l Ogunnaik e and Ra y a l so include problems from ph a rmacokinetic s, bio technology tissue engineering, and physiology (see problem s in chapter 6 on dynamics of higher-order sys tems ). LJOJ Seborg Edgar, and Mellichamp now include a sec tion on fed-batch bioreactors. 1111 In thi s article I detail the ways in which I have modified the traditional process dynamic s and control course to create a new course Modeling Dynamics and Control of Chemi cal and Biological Processe s." The course i s semester long (13 weeks) with two 1.5-hour lectures and one hour-long discussion per week. It is typically taken during the senior year. It is required for ChemBE major s, and typically 25 % of the students are nonmajor s or part-time students from local industry Below I discuss the changing nature of students Fall 2006 observed in the new chemical and biomolecular engineering program, and detail the revisions in the syllabus, the new module s in the course, and the modifications of traditional module s. Student learning in the course i s assessed through homework exams and a s hort pre se ntation. The usefulness of course changes is assessed through a survey of alumni. I conclude with my opinions on the material that remains omit ted and prospects for the future of this course in the chemical engineering curriculum. STUDENTS The chemical and biomolecular engineering students at JHU reflect the changing intere s ts of the new generation entering the field, perhaps to an extreme given Hopkins reputation in life scie nces. The se interests are reflected in previous courses taken by the st udents. Figure 1 ( next page) shows the perc e ntage of s tud e nts enrolled in the dynamics class who had taken biology s ubjects. ChemBE majors are list ed separately ( nonmajor s include biomedical engineering stu dent s who have taken an e ngineering Molecules and Cells course). Biochemistr y became a mandatory course for the graduating class of 2007, but the classes before that showed intere s t in the subject and in 2005 77 % of the students had taken biochemistry. This background allows me to move more quickly through the Central Dogma of Biology and assume some knowledge from the students about the role of DNA RNA a nd proteins in the cell. Hopkins students are highly involved in research. In fall 2005, 65 % of students participated in research at some time during their tenure at Hopkins and of those, 55 % were involved in biologically related research. This background elevated the level of di sc u ss ion on current engineering topics as well as on the basic elements of biological systems, and what those components do. In applying these course modifications at other sc hools it ma y be neces sary to take into account the background of the s tud e nt s. SYLLABUS AND OBJECTIVES Boxe s 1 and 2 show the course objectives and the li st of topic s covered in the course from the syllabus. In a broad sense, the course is structured similarly to a traditional process control course: the first third of the course covers dynamics and the second third feedback control. Both of these parts are infused with biological examples and systems, includ ing a couple of special lectures. The last third of the course include s a new section on nonlinear dynamics, and a week 299

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to review current mode l ing and control literature. Students are graded on the traditiona l tests and homework, and in ad dition they perform an experimental lab exercise and present a literature article to the class. Box 3 shows the bio l ogica ll y related l earning objectives and those from the novel nonlinear dynamics segment. T raditional components Many portions of a traditional chemical process control course have been retained In particular, the philosophies of model building Laplace approaches, transfer functions block diagrams, feedback control, and frequency response methods are essential. Many traditional concepts can be reinforced through biologica l examples from recent literature, e g., Mark Marten s lab has recently characterized experimental fre quency responses of fungal cell cultures.1 1 2 1 Some of the more advanced and specialized treatments for process ana l ysis, however, have been trimmed to make additional time for new concepts. Topics now minimized include in-depth treatments of model identification, discrete control, control methodologies such as ratio control and cascade control, and, regretfully, modem control approaches such as model-based controllers. MAJOR REVISIONS The major subject material addit i ons to the course are as fo ll ows. Central Dogma The Central Dogma of Biology concerns the flow of infor mation in a cell. Deoxyribonucleic acid (DNA) is transcribed by the polymerase into ribonucleic acid (RNA), and RNA is translated by the ribosome into protein. Proteins perform functions within the cell. Therefore control in a cell can be exerted at any of these l evels-interfering with transcription translation or the protein function directly. These systems can be modeled as a set of c h emical reactions in a cascade for ex ample, r tra n s l a 1i o /t) = k tra n s l a 1i o nc po l y m e r as c (t-8)Cm RN /t8 ) expresses the rate of translation of mRNA into protein, given the concentra tion of the polymerase and the mRNA transcript, and assuming a transcription time delay of 8. These concepts are access i b l e to students with training in kinetics and reactor des i gn. Pharmacokinetic and Pharmacodynamic Approaches Organism models have been built using so-called phar macokinetic approaches. In this approach, each tissue in the body (e g., brain, liver, muscle) is modeled as a one-, two-, or three-compartment chamber. The compartments are assumed to be either diffusion-limited or reaction-limited, and are modeled accordingly as an ideal system. The bloodstream is mode l ed as a single (or double) well-mixed compartment that connects the other organs together. The set of compartments can be distilled into a system of coupled ordinary differential equations. These models are most often used to characterize the movement of a drug or specific set of molecules around the body. 1 13 1 41 3 00 Populat i on Balances Molecular cellular and ecological systems can be con sidered by writing population balances, or balances on the number of cells, molecules or organisms in the system: dN/dt = bN-dN+f, where N is the number of units in the system, b and d are birth and death rates, and r represents additional fluxes in or out of the system These types of models can describe the number of molecules inside a cellular organ elle, the number of cells in a culture or tissue, or the number of organisms in an ecosystem, for example Such equations are intuitive for a chemical engineering student with training in mass and energy balances, and they q u ickly allow the student to work problems with these applications. An example study in literature is the measurement of leukocyte birth and death rates using tracing with the BrdU label. 1 1 5 1 Control of Gene Express i on One of the most fundamental ways in whjch a cell exhjbits control is by changing which genes are expressed thus what proteins exist to carry out function 1 1 61 Gene expression is controlled by transcription factors-proteins that bind to the DNA and either recruit the po l ymerase or prevent the poly merase from initiating a transcript. The transcription factors themselves are often switches activated by the presence of a small molecule or a covalent modification. For example, the bacterial l ac operon system regulates cell metabolism to use either glucose or lacto s e as a carbon source 1 1 6 1 When lactose is present allolacto s e (a lactose derivative) binds the lac re pressor, which can then dissociate from the DNA allowing transcr i ption of the genes encoding the proteins necessary for metabolizing lactose. In the presence of the more efficient glucose feed however additional proteins are regulated via the level of cyclic AMP to ensure metabolic energy is not wasted producing lactose-metabolizing machinery. Keasling s group has constructed a straightforward dynamic model of the system, 1 1 7 1 and t h eir article makes an excellent demonstration of a nonlinear multivariable system that can be simulated using concepts, skills, and tools that students learn in the first third of a dynamics and control course. Furthermore, this segment allows me to introduce a descrip tion of the biomolecules involved in the process. In traditional process dynamics and control courses students learn about sensors, transd u cers, and actuators. In the new ChemBE cur riculum, students must also examine the structures of biomo lecular control components. PowerPoint slides available from publisher W.H. Freeman 1 1 8 1 (Chapter 31) show the structures of molecules involved in control loops in both prokaryotic and eukaryotic cells from the small molecule effectors, to allosteric proteins and transcription factors, to the ribosome, polymerase, and hi stones. With this biomolecular background students were challenged in a homework assignment to imag ine other nanoscopic implementations of a control scheme. In addition they could predict the effect of perturbations to the existing biological s y s tem (see Box 4 page 304). Ch e mi c al En g in ee rin g Edu c ati o n

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Large-Scale Biosimulation The s cope a nd impa ct of bi os imulati o n i s dem o n stra t ed b y exami nin g recent s imulation s b y a biot ec hn o l ogy s tartup co pany that h as publi s hed detail s o n it s m o d e l s Entelo s ( D a ly Ci t y, CA ) e mpl oys chemical e n g ineer s a l ong wit h biolo g i s t s, biochemi s t s, and comp ut e r s cienti s t s t o c re a te r ea li s ti c di seas e model s. We re v i ew the id ea of takin g a model to th e extre m e u s ing a case st ud y of E nt e l os arthrit i s m o d e l th a t s imul a t es a rheumatoid joint. The m o d e l ha s hundr eds of s tate variab le s a nd ca ptur es ce ll population dyn a mic s, bi oc h emica l m ed iator production ce ll co nt act of sy novi a l fibrob l asts m acro ph ages T-ce ll s, and c hondrocyte s. Ultimately th e model pr edic t s car til age degradation 1191 With thi s e xa mple be co m e more imp ortant in indu s tri a l proce ss contro l and are m o r e e mpha s i ze d in recent textbook treatments Whil e Lapl ace a ppro ac h es crea t e e l egant ana l yt i c trea tm e nt s, tool s s u c h as MATLAB a nd Mathematica make it easy to r e pre se nt vec t o r s a nd cre at e s t a tes p ace repre se ntation s. In p ar ticular B e qu e tt e s r ece nt textbook l 9 1 in co rp ora t es th e state s pa ce v i ewpo int from th e beginning introdu c in g e i ge n va lue/ei ge vecto r tr ea tm e nt s imm e diat e ly a nd l a ter d eve lopin g Laplac e treatments. With co mput atio n a l tool s it i s a stra i g htforw ar d ge n era li za ti o n to include multipl e va ri a bl es for input s a nd outputs in a dynamic mod e l. The se a ppro ac he s c ulmin ate in a unit o n n o nlinear d y nami cs at th e end of the se m es t e r. we ca n di sc u ss i ss ue s of numeri ca l accuracy experi m ental va lid ation, a nd un cer taint y. 100% Additional Dynamical Analysis Topics 90% 80% 70% 60% 50% 40% 30% 20% 10% Biochemistry (409) Severa] fundamental s kill s und e rlie bi o lo g ca l d y nami cs problem s a nd need ex tra e mpha s i s in our course. Fortunately, so me of these sa me co n cepts, s u ch as s t ate-s p ace repr ese nt a tion multi variab l e sys t e m s, a nd treatm e nt of co upl ed n o nlin ear evo luti on equation s, ha ve Biochemistry (maj ors ) Cell Biology (409) Ill Cell Biology (majors) Fig ur e 1: Biologyco urse ba c kground of s tud e nt s in th e dynami cs and co ntrol class (C h emBE 409) and for ChemBE majors o nl y. Th e numb er of st ud e nt s s urv eye d in th e co urs e each year was 21 29, and 3 1 in Fall 2003 2004, and 2005 respective l y. Th e numb e r of ChemBE graduates was 12, 15, 14 20, and 15 for the classes of 2002 2006. Students were not surveyed about th eir academic background in Spring 2002 2003, and data for majors are from student tra n scripts 0% Sp02 Sp03 BOX3 Nontraditiona l Learning Objective s Ba s i c s of Modeling: I D e ri ve population model eq uation s for ce ll s mo l ec ul es or organisms. 2. D escribe the approach of p h an n acokine ti c m odeling 3 Deriv e dynam i c e quation s for compartment-based m ode l s of li v in g orga ni s m s Biomolecular Co ntrol Sys tem s : F03 4. D esc rib e th e l ac o p ero n as a m ode l b i omo l ec ul a r co nt ro l sys tem u s in g s t a nd a rd bi oc h e mi ca l term s properly (o perator, induc er, r epresso r promoter ge n e co n s tituti ve, induced ). 5 I dentify s t a nd ard contro l feat ur es in biomo l ec ul ar co nt rol systems F04 6. De sc ribe po s t -trans l ationa l co ntrol s tr a tegie s a n d eukaryotic s trat eg ie s such as chroma tin packin g. 7. De scri b e the Central Dogm a of Biolo gy and identi fy s t eps w h e r e contro l can be ac hi eved 8. Im agine new complex contro l arrangements u s in g biom o lecul ar compo nent s. 9. Create co mple x dy n amic model s for biomo l ec ul ar sys t ems. Introduction to No nlin ear D y namic s: 10. Ana l y ti ca ll y so l ve for a trajectory given initial conditions and a lin ear syste m 11 Sketch a pha se p o rtrait for a line a r sys t em or for so me n o nlin ear sys t ems. I 2. Id entify a ttra c t ors, r epe llor s, center s, and sadd l es fro m th e eige n va lu es of a sys tem n ear a fixed point. 1 3. I dentify o r defin e limit cycles a nd describe qualitative feat ur es of c h ao ti c t rajectories 1 4. Int egrate a nonlin ea r sys t em u s in g a num e ri ca l t oo l. F05 Fall 2006 30 1

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302 Sample Homework and Exam Problems in Biomolecular Modeling and Control Population balances and compartment models BOX4 Develop a ve,y simp l e dynamic mod e l for an E. c oli cell consuming a met a bolite Ultimately we would lik e to know the in s tantaneou s rate of hydroly s i s of th e metabolite in response to dynamic c han ges in the m e tabolite concentration outside of the cell. Th e hydroly sis occurs via an enzyme that i s it se lf regulated (through molecular mechani s m s in th e cell) by the external metabolite concentration. ( receptor d etects M 0 and signals production of E) (passive diffilsion of met a bolite ) M o M, M~P Assume the concentration of the metabolit e outside of the ce ll M 0 can be manipul ated dynamically. The met a bolite diffu ses passive ly into the ce ll. In s ide the cell an enzyme hydrol yzes the metabolite (co ncentration M ) into a product. The enzyme (co n ce ntration E) is expressed in response to the presence of the m eta bolite: a receptor on the outside of the ce ll detects the externa l co n ce ntration of metabolite and signals this information to the transcription and tran s lation machinery; for s implicit y ignore those intermedi ate s tep s and assume that the rate of enzyme production in the cell i s in s tantaneously proportional t o the co n ce ntration of the met abo lit e ou t side th e cell. The e nzyme cannot diffu se through the ce ll membrane and it de grades n a turall y with a rate of r d = k d E The met a bolite kME h y droly s i s obeys Michaeli s-Me nt e n kinetics r = --K111 + M a. Identify the s tate variable(s). input and output variable(s) and parameter(s). b Derive model differential equations to describ e this sys tem Define a n y physical parameters yo u n ee d as nec essa ry. c. Put your model in d ev iation var iable form a nd linearize if necessary. You mi g ht want t o replace co mbination s of co n s t a nt s with new parameters (a ~ etc.) to make your math e matic s convenient particularly as yo u proceed to (d). d. Find a tran sfe r function from th e input to output variable(s) Pharmacokinetics a. Sketch a proce ss flow diagram for a pharmacokineti c mod e l th a t includ es a one-compartment pancreas and a two-compart ment brain, connected by the bloodstream. b. Formulate model equations for the concentrations of a mo l ecule in the brain Assume the flux between the two compartments i s membrane-limited a nd pa ss i ve, i.e. n = -h(C 1 -C 11 / R ). Also, ass ume th e molecule i s degraded in the inn er compartment with fir s t-order rate constant k d c Identify input and output variables and par a m eters for the most ge n era l mod el. I s yo ur sys tem und er-, over, o r exact l y determined ? Control of gene expression (a dapted from Ber g 11 6 l) A common ge netic m a nipul at ion employed by cell biolo gis t s i s to delete a particular gene. What would be the effect of deleting th e following ge ne s in the la c repressor sys tem ? a lacY b l acZ C. Nonlinear dynamics (adapted from Beltramil 2 0 3 1 l) Consider thi s coupled sys tem of OD Es: lacl X 1 = 9X 1 (1~I ) 2X 1 X 2 X 2 = 6x 2 ( 1 ;; )X 1 X 2 This model captures the dynami cs of two competing population s of bacteria The two state variables represent the population densi ties of each s peci es, the terms in parenthe ses cap the growt h due to limitation s in the environment, a nd th e x 1 x 2 terms represent the negative effects of competition between th e species. a. Show that the point [ 5 2 ]Tis a fixed point. b Linearize the system around [ 5 2 F a nd find th e eigenvalues and e i ge n vecto r s I s this point stab l e or un s tabl e ? I s the lo ca l behavior oscillatory? c. Sketch the pha se portrait for this system, includin g the four fixed point s nullclin es and representative traj ector ie s Note that s ince the variab l es represent population densities, va lu es le ss than zero are not meaningful and can be omitted from the dia gra m. d. Briefly interpret the physical meanin g of the phase portrait. Ch e mi c al Engineerin g Edu c ation

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BOXS Se l ected L it erat u re Articles, Incl u d i ng Bio l ogica l Dy n amics, Suitab l e for Review in an Un d ergrad u ate Course a chaotic dynamical sys tem might be controlled Literature Review R ob u s t co nt rol o f initiation of prok a r yo tic c h ro m osome replication : esse nti a l co n s id erat i ons for a minimal ce ll S.T. Brownin g M. Caste ll a no s, a nd M L. Shuler Bi o t ec h Bi oe n g ., 88( 5 ), 575 (2 004 ) Student und e rstanding of modeling dyn a mics a nd control concepts in the application to biological systems can be immedi ate l y assessed by an oral literature review. In sma ll groups of two to three people s tudent s review a current paper in scientific literature on the subject of mod eling dynamic s and control of a chemi cal or biologica l process. The goals are: (1) to apply knowledge of modeling and Co nt a inin g pandemic influen za a t th e so ur ce ," l.M L o n g ini Jr ., et al. S c i e n ce, 309, I 083 (2 005 ) A computat i ona l s tud y of feedback effec t s o n sig n a l d y n a mic s in a mit oge n -ac ti va ted prot e in kina se ( MAPK ) pathw ay model, A .R. Asthagiri and D .A. L a uffenbur ger, Bi otec/1110/. Pr ag., 1 7 227, (2 001 ) A mathematical model of caspase function in apoptosi s." M Fu sse n egge r, J.E. B a il ey a nd J Varn e r Nat. Bi o t ec hn o l. 1 8, 768 ( 2000 ) R o bu s t p e rfect adap t a ti on in bact e rial chemota x i s through integral feedback co ntrol ," T.M. Yi Y. Huan g, M I. Simon a nd J Do y l e, Pr oc Nat. Acad. Sci. 97(9 ) 4649 (20 00 ) Nonlinear Dynamics Since biological systems are often hi g hly nonlinear and can exhibit multiple steady-state and non-ste a dy-state be havior, I have incorporated a unit on nonlinear d y namic s. We begin with a set of nonlin ear, multi variable dynamic equa tions such as .x. 1 = x 2 ; .x. 2 = -x 2 s in x 1 which represents large motion s of a forced pendulum. Approaches to the se prob l ems are covered in Beltrami 's s hort treati se 1201 and in a later chapter in Coughanowr's text. 12 1 1 W e di sc u ss the idea of multiple s teady states and how a complete analysis mu s t capture a sys tem 's behavior throughout the phase space. We then discu ss fixed points (steady sta te s), eigenvalues ( pole s), and eigenvectors relating them to concepts introduced in the Laplace framework. We proceed to ske t c hing phase portrait s of a ttractor s repellors sadd le s, a nd ce nter s. Finally we dis cuss me a n s of constructing a complete nonlinear pha se portrait u s ing nullcline s and linear analysi s of a ll fixed points Y 01 The Lotka-Volterra problem ,'2 21 which i s u s ually associated with predator-prey ecological phenomena but was in fact, first derived to analyze chemical kinetics provides an excellent and tractable in-class problem for s tudent s to work in small groups Discussion leads naturally to concepts of robustness ( or the lack thereof in the Lotk aVolterra s ystem) and the idea of a limit cycle. In discus si ng limit cycles we review oscil lating chemical sys tems s uch as th e B e lou sov -Zhabotin s k y reaction, 123 241 for which chemical kinetic models h ave been constructed .l2 51 Finally in a homework assignment students integrate the Lorenz equations to plot trajectorie s for a strange a ttractor based on the Raylei g h in s tability of a liquid heated from below _l2 61 In the final cla ss discu ss ion we contrast this sys tem 's dynamics with that of le ss strange attractors, and we identify the defining characteristics of chaos (i .e. sensitivity to initial conditions, trajectory returning infinitely often albeit erratically to the neighborhood of each point on the attrac tor, fractal micro s tructure and noi sy pow er s pectra ). With a background in d y namic s developed throu g hout the semes ter s tudents have an appreciation for the oddities of a chaotic sys tem and a strange attractor and are able to speculate how Fa/12006 control to current applications, particu l arly in biomolec ul ar and cellular applications for which the course ha s relative l y few homework problem s during the se mester ; (2) to gain experience extracting relevant information from primary literature ; (3) to synthesize the topics cove red during the se me s ter ; and ( 4) to practice oral presentation ski ll s. Talk s pre se nt the basic concepts of the article particularly th e modeling and control aspects. Stu dents n eed to rephrase the work into s tandard control term s (co ntrol objective, input s, outputs, state variables feedback feedforward s tability robustness, etc.). Short presentations a nd written summaries include ba s ic background of the apClass discussion however often clarified points and helped students recognize the motivations and strategies emplo y ed b y each paper s authors. plication, so me details on the model or controller formulation, a nd s ome of the results. The ambitious groups replicate some of the work a simplified model or a s imple extension using MATLAB. I provide the s tudent s a li st of articles in literature (see Box 5), but s tudent s are allowed to chose articles that interest them, and occasionally they contribute something from a lab where they work Overall, s tudents demonstrate ease in ex plaining the biological context of the problems and the dynamic behavior or control systems s tudied. Occasion a lly s tudents needed help identifying proper state variab l es a nd sys tem inputs and outputs and some complex mode l s in the lit era ture were challenging for undergraduates to fully a ppreci ate Cla ss discu ss ion however often clarified point s a nd helped students recognize the motivations and strategies employed by each paper 's authors. Students complete peer assess ments of the members of their team, 1271 and I eva l uate 303

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their talks, focusing on how well students learn the concepts of dynamics and control (see Box 6). G uest L ec t ure s To further broaden the perspectives heard in-class, I typi cally include two guest lectures per semester. One is given by Red Bradley and Lochlann Kehoe of GSE Systems, a local control systems company. These engineers give an industrial perspective on the challenges and complexities of modeling and controlling real chemical process systems. The second guest lecture is given by someone involved in biological modeling and differs each year. Two recent speakers were Prof. Kenneth Kauffman of the University of California at Davis who discussed optimal control in cellular systems, I 28 1 and Dr. Saroja Ramanujan of Entelos, Inc. who discussed large-scale biosimulation of arthritis. 1 1 91 Guest lectures include a question-and-answer period and student comprehension of the main topics is evaluated through short-answer, closed book exam questions. A SSESSMENT Students complete a mid-semester survey and an end-of semester course evaluation, both of which include questions about the usefulness of the biological content in the course. Opinions are mixed, as some students enjoy the new perspec tives while others are clearly uncomfortable with the biologi cal topics ( data not shown). Resistance has decreased in recent years, probably due to a combination of changed expectations and improved teaching of the material due to past feedback. To assess the long-term effectiveness of the class, alumni from the first three offerings of the course were surveyed online Respondents included students from the graduating classes of 2003 through 2005 currently in industry, graduate school in ChE or ChemBE, graduate school in other fields, or professional school. The survey and responses are shown in Box 7. Overwhelmingly the alumni felt that the addition of biological material helped make the course more practical, and prepared them for their future careers. They also felt that the course did not suffer from lack of traditional content; this view was shared by an alum working in the process control industry and another in a graduate process control research group. Anecdotally one alumnus reported that he had vigor ously opposed the integration of biology into the curriculum in his end-of-semester course evaluation and senior exit interview, but that he had experienced a complete change of heart and now is thankful for his biologically related training Another alumnus, now a graduate student in biological and environmental engineering, noted that the study of the lac operon was specifically useful to converse with biologists and understand gene regulation. Interestingly, 62 % reported that knowledge of biology is essential to their current positions, and only one respondent reported that biology is not at all needed in his or her current position. OUTSTANDIN G T OPIC S Much of dynamic biological phenomena requires math ematical treatments that are significantly different from traditional, lumped-parameter, continuous, or deterministic treatments In particular many molecular systems are known to be stochastic and require treatments such as Fokker-Planck and Langevin equations.l2 9I Recently, one institution has developed a Web module to teach stochas tic modeling using batch reactor models and oscillating reactions. 130I I have so far been unable to introduce this material but perhaps as students enter with more biology background the time devoted to introducing biological concepts can be redirected toward these novel treatments. One possibility to free up additional time might be teach ing dynamics entirely in state-space form and removing BOX6 304 Literature Review Evaluation of Team Oral Presentations Assessment Questions (50 % ) Have the students demonstrated under s tandin g of the major concepts of modeling dynamics and co ntrol ( modelin g, solution of dynamic equations nonlinearitie s, control feedback s tability robustness validation phase behavior etc as appropriate for the article)? ( I 0 %) Have the students demon s trated an understanding of computational tools ? (20%) Have the s tudent s demonstrated excellent communication s kills? (10%) Have the students demonstrated an ability to work to ge th e r in team s? (10 %) Are the s tudent s aware of co ntemporary i ss ue s, the impa c t of the work, and any profes s i o nal or e thical re s pon s ibilitie s? Components Technical Content (6 5 %) : Introduction (15 % ): Problem and goals explained clearly to a udience Model de scr iption ( 15 % ): Origin of mod e l explained and s ignificant assumptions det a iled model exp lained clearly to audience Re s ults (15 % ): Mo s t s i g nific a nt results s hared clearly result s teach something to the audience, control sc hemes are u sef ul Other Design Criteria / Broader Impact s (5 % ): Safety environmental, economic, biological criteria; relate work to current knowledge in field Reasonable re s pon ses to que s tion s (I 5 %) Presentation (35 %, roughly 5 points each): Overall flow and pace organized pre se ntation clear and interesting s lides time limit met rea so nable e nergy l eve l patti c ipation by all group members, creativity, clear one-page s ummary s h eet Chemical Engin ee rin g Education

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Laplace treatment s, but thi s could prov e challenging with the absence of appropriate textbooks. CONCLUSIONS This paper surveys a radical re v ision of a chemical engineer ing process control course to include new material appropriate for chemical and biomolecular engineers. The revi se d c ur riculum ha s excited st udent s and provided stro n g preparation for graduate school profes s ional school, or industry. I hope this description of our remolded dynamic s and control clas s will be u se ful inspiring and perhaps help others to determine the next step in the chemical engineering curricular evolution Brown has remarked that the transformation of a curriculum can take a decade_ 11. 6 1 Th e s hift in the chemical engineering curriculum h as just begun and we will see more changes in the next few years ACKNOWLEDGMENTS The teaching assistants for this course over the last several years Tom Mansell Aroop Sircar Jullian Jones and Robert Plemon s, added their perspective on biomolecular engineering to help formulate problems and topic s. I also thank former d e partment chair Michael Betenbaugh for encouraging me to ex periment with the content of this course. Kenneth Kauffman generously provided insightful comments on the manuscript and guidance on course assessment. BOX7 Assessment Results From Alumni Survey Sixteen alumni responded (o ut of 55) Respondent s came from the classes of 2003 (5), 2004 (7) and 2005 (3) Rate your agreement with the following s tate ments. I. I am comfo 11 ab l e w ith m y proce ss dynam ic s, mod e lin g and contro l background from the Chemica l & Bi omolecular Engineering D e part m e nl a t JHU 2. l feel this course has prepared me for the chal lenges I have encountered with modelin g, dynam ics and control after leaving JHU 3. 1 feel thi s co ur se s honchanged m e by o mittin g key concept s from c la ss i ca l d y nami cs an d co ntrol. 4. The integration of biology helped to make the co n cepts of the course more practical. 5. The int egratio n of biolog y h e lp ed t o m ake the co n ce pt s of the course more intuitive 6. The integration of biology helped prepare me for my career or education after m y B S. in ChemBE. 7. I have developed an appreciation for the cha ll enges of analyzing comp l ex dy n amic s a nd regulation in biological and chemica l s ystems 8. I feel I lack a sufficient foundation from JHU in dynamic s, modeling, and control to be successful at the types of tasks required of me in my current position. Largest re s pon ses indicated in bold. NIA 0 % (0) 6% (I) 19 %( 3) 6 % (I} 6 % ( 1 ) 6%(1) 6 % (1 ) 6 % (l) !-strongly di sag re e 0 % (0) 0 % (0) 19 % (3) 0 % (0) 0 % (0) 6 % {I) 0 % ( 0 ) 25 % (4) 2-dis agree 6 % ( I ) 6 % {I) 44 % (7) 6 % {I ) 1 2 % (2) 0 % (0) 6 % {I ) 38% (6) 3-neutral 4-agree 1 2 % (2) 50 % (8) 19 % (3) 38% (6) 6 %( 1 ) 12 % (2) 12 % (2) 31% (5) 1 2 % (2) 44 % ( 7 ) 1 2% (2) 31 % (5) 0 % (0 ) 62 % (10 ) 6 % {I) 19 % (3) 5-strongly agree 3 1 % (5) 3 1 % (5) 0 % (0) 44% (7) 25 % (4) 44% (7) 25 % ( 4) 6 % (I) Response Average 4.06 4.00 2. 1 5 4.20 3.87 4.13 4.13 2.40 8 7 6 5 4 3 2 1 0 12 T"""------------------,1 Industry Fall 2006 Graduate school in ChE or CherrBE What is your current posit i on? Graduate school in other field Professional school (medical, business, law etc) Other 10 8 6 4 2 How important is biology in your current position? Not at all Peripherally Routine relevant Essential 305

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Additional course material can be accessed at . REFERENCES I. Kim I. A Rich and Diver se History ," Chem. Eng. Prag. 98 2S-9S (2002) 2 Lander E.S L.M. Linton B. Birr e n C. Nusbaum, M C. Zody and J. Baldwin et al. Initial Sequencing a nd Analysis of the Human Genom e ," Nature, 409 ,860 (2 001 ) 3 Venter, J.C. M.D. Adams E W. Myer s, P.W. Li R.J Mural, and G.G Sutton e t al., The Sequence of the Human Genome S c ien ce, 291, 1 304 (200 1 ) 4. Henry C.M. Sy s tems Biolog y Chem. and Eng. News 81 45 (2 003) 5. Kitano H. Systems Biology : A Brief Overview ," Science, 295, 1662 (2002) 6 Brown R.A., Frontiers in Chem i ca l Engineering Education (Web site), < http ://mjt.edu/c hecurricu lum > (2002-2006) 7 Edgar, T.F. "C hECurriculum of the Future: Re-Evaluating the Process Control Course Chem. Eng. Ed. 37 in si de cover (2 003) 8 Csete, M.E and J.C. Doyle Rever se Engineering of Biological Complexity," Science 295 1 664 (2 002) 9 Bequette W.B. Pr ocess Control: M o d e lin g, D es i g n and Simulation Prentice Hall PTR Upper Saddle Riv er NJ ( 2003 ) 10. O g unnaike B.A. and W.H Ray Pr ocess D y nami cs, Mod e lin g, and Co ntr o l, Oxford U niversity Pre ss New Y or k ( I 994) 11. S e bor g, D.E. T.F. Edgar and D.A Mellichamp, Pr ocess D yna mi cs and Control, 2nd Ed Wiley (2 004 ) 12 Bhargava S ., K.S. Wenger, K. Rane V Rising, and M R. Marten "E ffect of Cycle Time on Fungal Morphology Broth Rheology, a nd Recombinant Enzyme Productivity durin g Pulsed Addition of Limjting Carbon Source ," Biote c h. Bio e n g., 89 524 (2005) 13. Gerlow sk i L.E., a nd R.K. Jain, Phy s iol og ically Ba se d Pharmacokinetic Modelin g: Principles and Applications," J Pharm Sci, 72, I l03 (I 983) 14 Salt z man W M Dru g D e li very: Engineering Prin ciples for Dru g Th e rap y Oxford University Pr ess, New York (200 I ) 15. M o hri H. S. Bonhoeffer, S. Monard, A.S. Per e l so n and D D Ho Rapid Turnover ofT Lymphocyte s in SIV-infected Rhesus Macaqu es," Science, 279 1223 ( I 998) 16 Berg J M., J.L. Tymoczko, and L. Stry e r Bi oc h e mistr y 5th Ed. W.H. 306 Freeman New York (2002) 17 Won g P ., S. Gl a dne y, a nd J.D K eas lin g, Mathematical Model of th e lac operon: Indu cer Exclusion Catabo lit e Repre ss ion, and Di a u x ic Growth on Gluco se and La c to se," Bi o t ec hn o l Pr ag 13 1 32 ( 1997 ) 18. C larke N .D ., J.M Ber g J.L. Tymoczko and L. Stryer W eb Conte/I/ t o Accompany Bi oche mistr y 5th Ed. ( W e b s ite ), < http: // bc s.w hfreem a n co m / biochem5> (2002) 19 Rullmann J A. C. H Stru e mp er N.A. D e franoux S. Ramanujan C.M.L. Meeuwi sse, and A. V. Elsas, S ys t e ms Biolo gy for B a ttlin g Rh e umatoid Arthritis: Application of the Entelos PhysioLab Platform ," I EE Pro cee din gs-Sys t e m s Bi o lo gy, 152 ,256 (2 005) 20. Beltrami E.J. Math e mati c s for D y nami c Mod e lin g 2nd Ed., A ca demic Pre ss, Bo s ton ( 199 8) 21. Coughanowr, D.R. Pr ocess Systems Analysis and Control 2nd Ed. McGraw Hill Bo s ton ( 1991 ) 22. Kreb s, C.J., E cology 5th Ed., Pe arso n Bo s ton (2 002 ) 23. Belou sov B.P. "T he O sc illatin g Rea c ti o n and it s Mechani s m ," Khimi ya i Zhizn, 7 65 ( 1 982) 24 Za ikin A N. and A.M. Zhabotinsky, "Co ncentration Wave Propagation in Tw oDimen s ional Liquid-Ph ase S e lf-O sc illating Sy s t e m ," Nature, 225, 535 (1970) 25. Fie l d R.J. and R M. Noye s, O sc illations in Chemica l Sy s tems IV. Limit Cycle Behavior in a Mod e l of a Real Chemical Re ac tion, J. Chem. Ph ys., 60 1 877 ( 19 73) 26. Loren z E.N., D e termini s tic Nonperiodic Flow, J Atmos Sci., 20 1 3 0 (I 963) 27. K a ufm a n D.B. R.M Felder, a nd H. Fuller, Accounting for Indi vidual Effort in Cooperative Learning T ea m s J of Eng. Ed., 89 1 33 (20 00 ) 28. Kauffman K.J. E.M Prid ge n, F.J. Doyle III P.S Dhurj a ti a nd A.S Robin so n Decreased Prot e in Expression and Intermittent Recoverie s in BiPLevels Result from Cellular Stre ss Durin g Heterolo go u s Prot e in Express i on in Saccharomyces Cerevisiae Bi o t ech. Pr ag., 18 942 (2002) 29 R ao, C.V.. D M Wolf a nd A.P. Arkin Control, Exploitation, a nd T o lerance of Intra ce llul ar Noise ," Na tur e, 231 (7), 420 (2002) 30 Kraft M ., S. Mo s ba c h and W. W a n ge r Teaching Stoch as ti c Model in g t o Chemical Engineers Us in g a W eb Module," Chem. Eng. Ed. 39 (2005) 3 1. Beltrami E.J. Mathematical Models for Society and Bi o l ogy, Academic Pre ss San Die go (2002) 0 Chemical Engineering Education

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ta 5 3 class and h ome problems ) r \.. The object of this column i s to enhance our readers' collections of interesting and nov e l prob lems in chemical engineering. Problem s of the type that ca n be used to motivate the student by presenting a particular principle in clas s, or in a new light or that can be assigned as a novel home problem, are reque s ted as well as tho se that are more traditional in n a ture and that elucidate dif ficult concepts. Manuscripts s hould not exceed 14 double-spaced page s and s hould be accompanied by the originals of any figures or photo gra phs. Plea se submit them to Profe sso r James 0 Wilkes (e -mail: wilkes@umich.edu), Chemjcal Engineering Department University of Michigan, Ann Arbor, MI 48109-2136. Computer-Facilitated Mathematical Methods in ChE SIMILARITY SOLUTION VENKAT R. SUBRAMANIAN Tennessee Te ch nolo gical University Cookeville, TN 38505 H igh-performance computers coupled with hi g hl y ef ficient numeric a l sc heme s a nd u ser-fr iendl y software package s hav e helped in s tru cto r s t eac h num er i ca l solutions and analysis of various nonlinear models more efficiently in th e clas sroo m One of the main objectives of a model is to provide in s ight about a sys tem of intere st. Ana lytical solutions provide very goo d phy s ical in s ight as they are explicit in the system parameter s. Havin g t a ught app li ed math to both se nior und ergra du ate and first-year grad uat e students for five years, thi s author feels th a t s tudent s do not appreciate the value of analytical so lution s because ( I ) they wrongly believe numerical method s are b est u sed to so lve comp l ex prob l ems with high-speed computers, and (2) they are not comfortable or confident doing the complicated integrals rigorou s algebra, and tran sfo rmation s invol ve d in obtaining ana l ytical solutions Such so lution s, however can be gained using various computer techniques. For example, computer algebra systems such as Maple l 1 J Mathematica, l 21 MATLAB 131 and REDUCE ,l4 1 can b e u sed to perform the tedious algebra manipulation s, complicated integral s, va ri ab l e transformations and differenti a tion s e tc ., invol ve d in app l ying mathematical method s Th e goa l of thi s paper is t o s how how Maple ca n be used to fac ilit ate si mil ari t y tran sfor mation t ec hnique s for so lv in g chemical engineering problems. The utilit y of Map l e in performin g the m a th so lvin g the equations, and p l otting the results w ill be d e monstrat ed. For an understandin g of the physics in the probl e m s so lv ed, reader s are advised to refer to th e cited referenc es. For the sake of re a der s not familiar with Maple a bri ef introdu ct ion a bout Mapl e i s g iven F all 2006 V e nk a t Sub r aman i a n is an assistant professor in the Department of Chemical Engin eering at Tenn essee Technological University H e received a B .S degree in chemical and electrochemical engineering from Central Electrochemical Re sea rch In sti tut e in India and his Ph.D in chemical engineering from the University of South Carolina H is research interests include modeling control and sim ulation of electro chemical sys tem s including batteries fuel cells hybrids, and multiscale simulation. He is the principal investigator of the Modeling Analysis and P rocess-Control Lab oratory for Electrochemical Systems (MA PLE lab ). Copyright Ch E D ivision of ASEE 2006 307

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M AP LE Maple 111 i s a computer-algebra system capable of perform ing symbolic calc ul atio n s. Although Maple can be used for performing number cru n ch i ng or n u merical calculations j u st like FORTRAN, the main advantage of Maple is its symbolic capability and user-friendly graphical interface. In a Maple program, commands are entered after a">". Maple prints the results if a";" is used at the end of the s tatement. This helps in fixing mistakes in the program after a particular step, as the results are s hown after every step or command. For brevity in this paper most of the Maple commands are ended with a colon (:). In general, while Maple is very useful in doing transformations, the user might have to manipulate resulting expressions from a Maple command to obtain the equation in the s implest or desired form. Often, these manipulations can be done in Maple itself by "see ing the resulting expres s ions. Hence first-time user s should use a ";" instead of a :" at the end of each statement to view the results after each command/statement. Many of the mistakes made by students are identified and rectified easily if they rep l ace":" with";" in all of the s tatements. Maple can be used to perform all steps from setting up an equation to analyzing the final plots on the same sheet. All the mathematical steps and manipulations involved can be performed in the same program or file For clarity between the Maple commands and output, all the text describing the proce ss or Maple commands is given within brackets, [ ]" SIMILARITY TRANSFORMATION FOR PARTIAL DIFFERENTIAL EQUATIONS Similarity transformation is a powerful technique for treating partial differential equations arising from heat mass momentum transfer, or other phenomena, because it reduces the order of the governing differential equation (from partial to ordinary). Depending on the governing equation, boundary conditions, domain, and complexity, the similarity transformation technique might yield a closed-form solu tion, a series solution, or a numerical solution. One of the major difficulties students encounter is that they find it very difficult to convert the governing equation from the original independent variables to a similarity variable. The following examples illustrate the use of computers and software in teaching / obtaining similarity solutions for various chemi cal engineering problems. Example 1 Diffusion/Heat Transfer in Semi infinite Domains Consider the transient heat-conduction problem in a s l ab .'' 2 The governing equation and initial/boundary conditions are expressed in Eq. (1). 308 & u & 2 u -=a:& t &x 2 u(x 0) = 0 (1) u(0 t) = 1 and u( oo, t) = 0 where u is the temperature xis the distance from the s urface of the slab, tis the time and a is the thermal diffusivity Eq (I) is solved b_y usi ng the ~ansformation Tl = x / ( 2 M ) The origi nal partial differential equat10n is converted to an ordinary differential equation in the similarity variable, 11 The bound ary conditions for U (u in the similarity variable), are: U(0) = 1 U(oo) = 0 (2) The steps involved in the similarity transformation method are illustrated below: Typically Map l e program s are started with a restart com mand to clear all the variables. Next, the "w ith (s tudent) package is called to facilitate variable transformations : >resta rt : w i th (student): >e q : = d i ff(u(x, t), t)-a l p h a d iff( u (x, t),x$2 ); eq := (!t u(x t))-a:( :: 2 u(x t)) [First, u(x,t) is transformed to U(1'](x,t)). Then, the governing equation is converted to the similarity variable:] >e q 1 : =ehangevar(u(x, t)=U(eta(x, t)),eq):eq2 :=expand (s i m p l ify(su bs(eta(x, t)=x/2/(al pha t)"( 1 /2),eq 1 ))) : eq2 : =expan d (eq2 t) : eq2 : =s u bs (x=eta 2 (alpha t)"( 1 / 2), eq2 ): eq 2 : =co n v ert(e q 2 d if f): [The final form of the governing equation is:] >eq2 : =expan d (-2 eq2) ; eq2:=(~U(TJ))TJ + __!_( d 2 U ( TJ ) ) d'fl 2 d'fl [The given boundary conditions are used to solve the govern ing equation : ] >be 1 :=U(O)= 1 ; bcl: =U(0) =1 >be 2 := U ( i n fi nit y)=O; bc2: =U( oo ) = 0 >U : =rh s(d s o lv e ({ eq 2, be 1 be2 }, U(eta))): > U : =con v er t ( U ,erfe); U: = erfc (1']) >u :=s u bs(eta=x/2/(al pha t)"( 1 /2), U); u := erfc( 2 ~J [The solution is plotted in Figure 1 which shows how the temperature u, penetrates to progres s ively greater distances as the time, t, increases:] > p l o t3d(sub s (alpha=0.001 ,u),x= l .. 0,t=S00 .. 0,axes=b o xed, l abel s=[x, t u ],orientation=[-60,60]) ; Ch e mi c al Engineer in g Edu c ation PAGE 67 u 50D 211 I Figure 1. Dimensionless t e mp e ratur e distribution in a semi-infinite domain. Example 2 Plane Flow Past a Flat PlateBlasius Equation The velocity distribution in the boundary layer of a plane l aminar flow past a flat plate is given by Eq. (3): o u +o v=O o x oy o u o u o 2 u u+ v=8x oy 8y2 u ( 0,y )= l ( 3 ) u ( x,0 ) = 0 and u ( x, oo) = l v ( x 0 ) = 0 For this problem first the velocities, u and v, s hould be converted to stream function s defined b y u = o 'lj; I o y a nd v = -o 'lj; I ox. The stream function by default sa ti sfies the continuity equation (E q. 1 ). The second equation yields the governing equation for the stream function 1jl Next the s tream function is expressed as 'lj; = f(TJ ), where 'Tl= y / i s th e similarity variable. Th e boundary condition s for u and v yie ld the boundary conditions for 1jl, and finally for f(11). Once the function f(11) is obtained (numerically), both stream functions and velocity ex pr ess ion s can be ex pr esse d in term s off and 11 The s tep s involv e d in thi s example are more tediou s compared to the previou s example. All the comp li cated s tep s involved can be facilitated u s ing Maple : >res tart :with (student) : with (p I ots): Warning, the name changecoords has been redefined [The governi n g eq uation i s entered:] >eq :=u(x y) d iff(u(x ,y),x)+v(x ,y) d iff(u(x, y), y)d iff(u(x, y), y$ 2) ; Fa/l 2006 [Next Stream function s ( u = o 'lj; I oy and v = -o'lj; I O X ) are introduced] >var s : ={u(x,y)=diff(psi(x,y),y),v(x,y)= d iff(psi(x,y),x)} : eq : =subs(vars,eq); e q : = r~ 'lj;( x,y )) (~ 't);( x ,y)) oy oxoy -[ :x 't);( x,y )) (:; 2 't);( x y ) )-(:: 3 't);( x,y ) ) [Next the transformation 'lj; = f ( TJ ), where 'Tl= y / i s u se d to obtain the equation for f : ] >eq : =changevar(psi(x y)=x "( 1 /2) f(eta(x y)),eq) : eq 1 : =(s imp I ify(s u bs(eta(x, y)=y /x"( 1 /2), eq))) : eq 1 :=s ubs (y=eta x"(l / 2),eq 1 ):eq 1 : =si mplify(eql x):eq2:= convert(-eql ,diff); eq2 := f ( TJ ) f ( TJ)+ 3 f ( TJ ) l (d 2 ) (d 3 ) 2 d TJdTJ [Next, the ve l ocity variables, u and v ( i e., derivatives of the s tream function ), are expressed in terms off a nd th e s imilarit y va riable 11 :) >v(eta) : =diff(psi(x y ),x) : v ( eta) : =ch an gevar( psi (x, y)=x "( 1 / 2 ) f (eta(x, y)), v( eta)) : v(eta) : =expand (subs (eta(x ,y)=y/x"(l / 2) v(eta))):v(eta) : = subs(y=eta x"(l / 2), v( eta)) : v( eta): =facto r(v( eta)) ; v ( 'Tl ) : = _I_ f ( TJ ) D ( f) ( TJ ) TJ 2 >u(eta) : =diff(psi(x,y),y) u(eta) : =changevar(ps i(x, y)=x A( 1 /2) f(et a(x, y)), u ( eta )) : u(eta) : =expand (subs (eta(x, y)= y /x"( l / 2),u(eta))): u(eta) : =subs(y=eta x (l / 2),u(eta)) ; [D(f)(11) in Maple repre se nt s the derivative off with re s pect to 11 Next the boundary con dition s are ex pre sse d in term s off : ] >bcl : =subs(eta=O,v(eta))=O ; 1 f ( 0 ) bcl: = = 0 2 vx >bcl : = bcl 2 x A( l / 2); bcl := f ( 0 ) = 0 >b c2 : =subs(eta=O, u(eta))=O ; bc 2 : = D ( f )( o ) = o > bc3 : =su bs(eta=infinity u(eta))= 1 ; bc3 : = D ( f )(oo) = 1 [The len gt h of the domain is taken to be five (to replace infinit y) Thi s number is found by trial and error Increas3 09

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ing the length beyond five does not change the results ] > bc3 := subs(infinity=S, bc3) ; bc3 := D(f)(5) = 1 [For this problem, analytical so luti ons are not possible (al tho u gh approximate so luti ons are possible) For this examp l e, numerical so lution for the Blasius equatio n is obtained as:] > sol :=dsolve({eq2 ,be 1 bc2 bc3},f(eta),type=numeric) ; so l := proc (x_ bvp ) ... end proc [The so luti o n is plotted in Figure 2 which shows how the function, f ( related to the stream function) varies wit h the simi larit y variab l e, 'Y] from zero to five] > odeplot ( sol, [ eta f(eta)] ,0 5 th ickness=3 ,axes=boxed); [Next ve lo city profiles are obtained : ] > u (eta) : =convert( u (eta), d iff) ; v( eta): =co nve rt(v( eta) ,d iff) ; u(ri) : = ~f(ri ) d'fl l f(ri ) -(dd f ( ri ) Jri v ( ri ) := -Tl 2 [Figure 3 shows how the x component of velocity increases from zero at the wall, and levels off at its main s tr eam value for l arger val u es ofl] from zero to five] > odeplot (s ol, [ eta u(eta)] 0 5, th ickness=3 ,axes=boxed labels=[eta ,u]); [Since v is a function of x, v x 1 1 2 is plotted Figure 4 shows the y component of velocity (multip li ed by x 1 1 2 ) in creases from zero at the wall, and l evels off at its main stream va lu e for larger va lu es of 1l from zero to five] > odeplot ( sol,[eta,v ( eta ) x"( l / 2)] ,0 .. 5 ,th ickness=3 a x es=boxed, lab els=[eta,"v x"(l /2)"]); [The solutio n at 1'] = 0 is o bt ained as:] > sol(O) ; d d 2 'fl = O ., f ( 'fl )= O., ~ f ( 'fl )= 0 ., 2 f ( 'fl )= 0.336152378983949952 d'fl d'fl ela Figure 2. Function fas a function of the simi l arity variab l e 11 3 10 [Stress is related to the Reynolds number (re) and the velocity gradie nt at y = O:] > 5 : =re d iff(u(x, y ), y); S : = re( : y u ( x y )J [The ve l ocity gradient in terms of the stream function is : ] >s u bs(u(x, y)=d iff(ps i(x, y), y),S ) ; re( :; 2 ( x y ) J [The second derivative of the stream function (d) is expressed in terms off and 'Y]:] > d : =d iff(ps i (x, y ), y$2): d: =ch an gevar ( ps i (x, y)=x"( 1 / 2) f(eta(x, y)), d ) : d : =expand(su bs(eta (x, y)=y /x"( l /2), d )): d:=subs(y=eta x"(l / 2),d ) : d : =convert(d,diff); d 2 d2 f(ri ) d := >5:=re d : [The second derivative of f i s found from the numerical so luti on:] > eqd3 : =sol(0)[4 ] ; eqd3 := d 2 2 f ( ri ) = 0.336152378983949952 dri [Hence, the stress -R eyno ld s number relationship becomes:] > 5:=subs(diff(f ( eta ),$ ( eta,2))=rhs(eqd3),5) ; S = 0.336152378983949952 re Example 3 Graetz Problem in Rectangular Coordinates Co n sider the Graetz problem in rectangular coordinates (to s implif y the mathematical complexity involved with cylindri ca l geometry) .14 1 The governing equat i on and initial/boundary conditions are: ( l x 2)& u = & 2 u & z & x 2 u ( x O ) = 1 ( & u u 0 z ) = 0 and ( 1 z ) = 0 &x (4) For this problem a s imilarity transformation cannot be used to red u ce the partial differential equation to one ordinary dif ferentia l equation ( boundary value problem in 11 ) To obtain so lution s very close to z = 0 E9(4) is converted to the new coordinate s defined by Tl = x / and z = z (note s ome textbooks use z = z 1 as the second coordinate but for simp li ity it is left as z in this paper ) In the new coordinates 1l and z u is obtained using a perturbation technique by expressing C h e mi c al En g in ee rin g Edu c ation

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u ela Figure 3. The xc omp o n e nt v e lo c it y a s a fun c tion of th e s imilarit y v ariabl e, 110 6 n'( 1 12) 0.4 2 3 4 Figure 4. Th ey co mp o n e nt ve lo c it y as a fun c tion of th e s imilarit y v ariabl e TJ. k u as u = L Z k f; ( 11 ) The boundary co nditi o n s for f ( in the sim ilarit y ; v ir i ab l e 11 ) are: f 0 ( 0 ) = l ; f k ( 0 )= l k = 1 2 3 f 0 (00)= 0;f k(oo) =0,k = l,2,3... ( 5 ) Th e s tep s inv o lv ed in th e s imil ar it y t ra n sformat i o n m e th o d are performed in Maple. > restart : with(student): >eq : =( 1 -xA2) d iff(u (x z) z )diff ( u (x z ), x $2 ); e q := ( 1 x 2 ) [:z u ( x,z ) ) ( : : 2 u ( x z ) ) [First, th e governi n g equation is conve rt e d to s imil ar it y var iable s ( 11 a nd z ) :] >eql :=changevar(u(x,z)=U(eta(x,z),z),eq) : eq 2 : =expand ( s imp I ify(s u bs(eta (x, z ) =x / 2 /( z )"( 1 / 2),eql))):eq2:=expand(eq2 z ): eq2 : =subs (x= e ta 2 ( z) ( 1 / 2), e q 2 ) : e q 2 : =convert ( e q 2 di ff): eq2 : =expand(-4 eq2) ; F a /12006 [For illu s tration onl y term s up to z 2 are co n s id ered i n th e perturbation s er i es : ] > N :=2 ; vars : ={U(eta,z)=sum(zAk f[k](eta ), k=O .. N)} ; N : = 2 vars := {U (17, z ) = f 0 ( 11 )+ zf 1 ( TJ )+ z 2 f 2 ( 11 ) } [T h e governi n g equation s for th e dependent va ri a bl es are obtained a s :] >eq3 : =e x pand(subs ( vars,eq2 )) : for i from O to 2 do Eq [iJ : =coeff(eq 3 z ,i) ; od ; Eq 0 2 a[ ,: fo ( a )] + [ ,: 2 ro ( ) l Eq1 ~ 2" [ ,: Ii ( ) ]-4 Ii ( a )s" 3 [ ,: fo ( a ) H ,: 2 f1 ( a) j Eq2 : = 2 11(_i_ f 2 ( 11 ) )8f2 ( 11)8 11 3 (_i_ f 1 ( 11 )) d 17 d17 + J 6"211 (a)+ [ ,:2 f2 ( ) l [The fir s t three terms ar e obtained by so l vi n g these differential eq u at i on s wit h the g i ve n boundary co nditi o n s ( not e that th e boundary condit i on at x = I is so l ved approx imat e l y as U = 0 at 11 = oo :] > sol [OJ : =dsolve({Eq [OJ f[O](O )= O f[O)(infin ity)= 1 }) ; assign ( sol[OJ ) : s o l 0 : = f / r1) = erf( T] ) >sol[l J : =dsolve({Eq[l )}) ; s ol ~ [f ( ") ( 1 + 2 a' ) C2 [The con s tants have to be zero t o sa ti sfy th e b o undar y co ndi tions : ] >assign(sol[l )):_Cl :=0 : C2 : =0 : f[l ](eta) := eval(f[l ](eta)) ; ( ._ 1 (317 41'] 3 ) e (-,i') f l 17 ) ,.J; 3 'IT [Similarl y, f 2 is obtained : ] 3 11 PAGE 70 >sol [2] : =d solve(Eq [2]): ass ig n(sol [2]):_C3 :=0 :_C4 :=0 : f[2 ](eta): =eval (f[2] (eta)); 1 (-285T) 570T) 3 -38 4T) 5 -160'fl 7 )e ( 11 ') f 2 ('Tl):= 180 [Once the functions (the f's) are obtained the Sherwood number can be obtained:l 4 l] >u :=su bs(vars, U(eta,z)): u : =su bs(eta=x/2/sq rt(z), u); [ 3x x 3 ) [-fz] ( X ) 1 -Uz-~ e u .-erf + 2'-JZ 3 ',/Ti 2 [ 285x 285x 3 12x 5 5x 7 ) [-fz] 1 z 4z ( 3 1 2 ) z ( s 1 2 ) 4z ( 1 1 2 ) e +-------------------180 [The dimensionless temperature distribution is plotted in Figure 5 which shows that temperature increases from the center of the slab to the surface value along the x-coordinate The increase in temperature is more rapid at the entrance and temperature increases are more gradual for higher values of z from Oto 0 05 the distance along the flow ] >plot3d(u ,x= 1 .. 0,z=0.05 .. 0,axes=boxed,labels=[x,z, "u"], orientatio n=[l 20,60]); SUMMARY This paper illustrates that mathematical methods for nontrivial problems in chemical engineering can be taught efficiently in a class using computers and user-friendly s oftware. The similarity solution approach is a very powerful tech nique for obtaining closed-form solutions for problems in ,..,.._::::,, 0 8 6 0 4 0 2 0 X heat m ass, momentum tran sfe r and other disciplines in chemical engineering. A traditional approach to teaching this technique would involve complicated variable transformations and integrals done by hand. In this paper, it was shown how an analytical technique could be facilitated using computers and s oftware. While Maple ha s been used in this paper Math ematica, MATLAB REDUCE or other symbolic software packages can be used to obtain similar results. In addition to teaching numerical simulation, computers and software pack ages can be used to teach traditional mathem a tical methods for a wide variety of problem s. Mathematical methods such as separation of variables, Laplace transform perturbation, conformal mapping Green 's function, analytical method of lines, and series solutions for nonlinear problems (multiple steady states) can be facilitated using Maple. Reader s can contact the author for further detail s or copies of related Maple programs. Some of the se methods are illustrated in a book to be published in the future. l 9 1 REFERENCES I < http : // www m a plesoft.com> 2. < http : // www wo lfram. com> 3. < http : // www m a thwork s.c om> 4 < http : // www reduce-algebra.com> 5. Carslaw H .S. a nd J. C. Jaeger Conductio n of H e ar i n S o lids Oxford University Pr ess London ( 1 973) 6. Crank J Math em ari cs of Diffu s ion Oxford University Press New York (1975) 7 Slattery J ., Advanced Tran sporr Ph e n o m e na Cambridge U ni ve r s it y Pre ss, New York (1999) 8. Vill e d se n J. a nd M.L. Michel se n Solution of D if.ferenrial Equarion M o del s by P o l y n o mial Approximarion Pr e ntice-Hall E n g l ewood C liff s N J ( 19 78) 9. White R. E., a nd Y.R. Subramanian Comp utari onal Merhod s in C h e mical En g ine e rin g w irh Mapl e Applicarion s, Springer-Verlag ( t o b e s ubmitt ed in 2006). 0 0 01 0 02 83 O CM O 0 05 z Figure 5. Dimensionl ess temperature distribution in rectangular coordinates, governed by th e Graetz equation. 3 12 Che 1ni cal Eng in eeri n g Edu car i o n PAGE 71 5$1 curriculum ) ---1111111-11111-.-------USING VISUALIZATION AND COMPUTATION in the Analysis of Separation Processes YONG LAK J 00 AND DEVASHISH CHOUDHARY Cornell University Ithaca NY 14853 M ATLAB l 1 l is best de s cribed a s ea s y-to-use math ematical software that allow s powerful graphical pre s entation and numerical analy s is At Cornell University MATLAB has been u s ed inten s ively as a teaching aid in undergraduate cour s e s For example e very engineering freshman i s required to tak e a c omputer pro g ramming cour s e (COMSl00 ) that include s ba s ic programming concept s and problem analysis using MATLAB. Student s in chemical engi neering take an engineering distribution cour s e on computer s and programming (ENGRD2 l l ), which deal s extensively with MS Excel and MATLAB. They also develop user-friendly computer programs using MATLAB to s olve homework in many chemical engineering core course s, including heat and mass transfer. This early integration of MATLAB provides an excellent background for u s e in the second semester of the junior year, allowing these s tud e nts to be comfortable with MATLAB in the separation s cour s e In addition MATLAB can be a very u s eful teaching aid in a separations course a s it s powerful graphical presentation and numerical analysis tool s can be utilized both in an interactive step-by step graphical display of conventional method s and also in s olving systems of equations for complex s eparation proce ss e s. The abilit y to integrate powerful computer s oftware into the course re s t s on the availability of appropriate computing equipment. Our department 's undergraduate computin g laboratory i s an excellent facility for such activities and i s equipped with 4 2 Windows-based PCs with a site license for MATLAB. THE COURSE Although typical chemical engineering curricula recognize the importance of recent trends in emerging technologies, it is always a challenge to convey them without sacrificing F a /12006 fundamentals .l 2 1 ChemE332 at Cornell is a three-credit course for chemical engineering juniors covering separation methods The emphasis of the course had formerly been placed on traditional equilibrium-based methods that involve using manual graphical techniques including McCabe-Thiele Ponchon-Savarit and Hunter-Nash .13 71 A s computers became readily available, however the graphical approache s were supplemented with assignments to write Fortran code and / or use s preadsheets for distillation columns 1 8 1 11 Modern tools Yon g Lak Joo has been an assistant pro fe ss or of chemical and biomolecular engi neering at Cornell Univer s ity since 2001 He received his B S in chemical engineering from Seoul National University in Korea and his M.S and Ph.D in chemical engineer i ng from Stanford University His research i nterests are i n the area of non-Newtonian fluid mechanics and advanced materials processing with particular emphasis on molecular modeling and complex flow s imulation of polymeric liquids. Devashish Chou d hary was born in New Delhi India He majored in chemical engineering at the Indian Institute of Tech nology Bombay In 2004 he received hi s Ph D from the School of Chemical and B i omolecular Engineer i ng at Cornell Un iv ers i ty During his Ph D ., he worked on order-property relationships in semi conducting materials Currently he works at Intel Corp. Cop y ri g ht ChE D i v i s i on of ASEE 2006 3 1 3

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suc h as the easy-to-use mathematical software MATLAB 1 1 1 and Mathematica 11 21 can be u sed to write simple codes that allow undergraduate s to calculate and display accurate graphi ca l so luti ons interactively and thus make l earning graphical met hod s more enjoyab l e and effective We introduced in class visualization of conventional graphical methods u si ng a simp l e MATLAB code The interactive n at u re of MATLAB a llowed what if' analyses r 1 1. 1 3 1 in which the effect of cha n g in g parameter values s uch as relative volatility, reflux ratio feed condition, and stage efficie n cy are graphically di s played By s pending le ss time on the details of solving problems graphi ca lly or by trial and error we can spend more time discussing the conceptual and quantitative descriptions of proces ses, recent trends and de s ign aspects. With condensed l ectures on equilibrium-based proce sses, ChemE332 in s pring 2001 was recon st ructed to reinforce rate-based proce sses such as membrane and sorption separations. Furthermore, emerging proce sses in bio se parations s uch as electrophoresis and i s u es in choosing a nd designing separation proces ses, were integrated in the course without sacrificing conven ti onal se paration s. More than half of the total le c tures in ChemE332 are currently spent on rate-based method s, bioseparations, and the de sign of separatio n processes. 3 14 Obtain e quilibrium data ,------------Thermodynamic Input _______________ : Cons t ant relative vo l a tility / Raoult's law / Act ual : data L--------------------------------------------------St e p I : Display y vs x di agra m (eq curve) ,---------~ Desi g n Input ~---------, : Reflu x ratio & fe e d co nditi on : ; or i a.--; Reflux ratio & b o ilup ratio : or [ Boilup ratio & feed condition ___ ___ St e p 2: Display operatin g lines a nd feed lin e St e p 3 : Determine theoretical equilibrium stages, N 1 H orizonta l lin e to equi librium c urv e Vertical drop to operating line ____ ________ J D esign Input 1------------, : ____ Murphr ee vapor effic ien cy Em v ___ [ St e p 4: Di s play new s teppin g based o n Em v D etermine actual stages N a and overall ef ficiency E 0 Figure 1. Flowchart of Example 1: McCabe-Thiele method for binary di s tillation Despite th e advantage of helping students visualize the se paration graphical methods no longer represent the mod ern practice of chemical engineering _l7l Modern practice for de s igning and simulating separations involve s commercial process s imul a tor s s uch as AspenPlus ChemCad H ysys, a nd Pro s im 1 14 1 To be prepared for commercial pra c tic e, s tu dent s need experience s imul ati ng and designing se paration proces ses using th ese method s Unfortunately, s tud e nt s often treat the se commercial s imulator s as bla ck box es, an d tend to believe the res ult s they obtain without further checking Y 141 Th e exact m e thods u se d in the se simulators involv e solving sys tem s of nonlinear equations a nd large matrice s. Altho u gh there is a limit for complicated sys tem s, these exact method s are now tractable due to u se r -fr iendly routines and sof tw are for numeric a l analy s i s. To avoi d the pot e ntial creation of yet anot h er black bo x" u s ing MATLAB st udent s can b e asked to imp l ement specific parts of the code such as a therm ody namic model matrix so lvin g, and time integration scheme. In this paper we demonstrate that u s ing easy-to-deve l op m a thematical solutions for visualization and numer i cal comp ut ation can make conventional gra phical approaches more enjoyable and effec tiv e, providing s tudent s better un der s tandin g of more complex prob l ems Visualization a nd interactive display of graphical methods in di s tillation solution pro cedures for comp lex processes suc h as mul ticomponent di s tillation and thermal sw in g adsorption can promote understanding of how these se paration proce sses work. Although we pre se nt the exa mples in distillation and adsorption, this approach can a l so be extended to many other se paration proce sses s uch as absorption s trippin g, and extraction W e present four examples u se d in the se paration s course. In the first two exa mpl es, the step-by-s tep int erac tive display of co nv e ntion a l graphica l methods for binary distillation were facilitated b y MATL A B while sys tem s of nonlin ear equations were rigorous l y solved usin g MATLAB in the l as t two example s on multicomponent distillation and adsorption Example 1 Visualization of McCabeThiele Method and Stage Efficiency in Binary Distillation We u se d MATLAB to v i s ualize the McC a be-Thiel e graphical equilibrium-stage method and estimation of stage efficiency in a distillation proce ss for a binary mix ture of A and B. A s describ e d in Table 1 the code consists of (i) constructing and displaying th e equilibrium curve, ( ii) drawing operating line s and feed line, (iii) disp l aying the equi lib rium stages and (iv) illu stra tin g stage and over all efficiency. We u se the comm and s plot a nd "mov i e in MATLAB 1 11 to visualize a nd animate the di agra ms (see Table 1 ) The code was u sed for interactive di sp lay of the method in lectur es and homework assignment s C h e mi cal Engineering Education

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Interactive Display in Lectu r es Before the McCabe-Thiele gra phical method was dem onstrated by step-by-s tep display a lecture was given on the concept and a handout on the detailed description of the options and functions of th e MATLAB code for the method was distributed. In-class visualization of the graphical method and stage efficiency consists of four ste p s, and the overall flowchart of the examp l e is illu s trated in Figure 1. Step 1. We show how the equilibrium curves can be co n structed. Three ways of determining the equilibrium re lationship between liquid and vapor phases are implemented in the code : using (i) a constant volatility for mixtures with a similar heat of vaporization, (ii) a simple thermodynamic model such as Raoult's law 141 in which the Antoine equation is used to provide the vapor pressure information and (iii) actual data. For the Antoine equation the function fzero in MATLAB l 1 1 is used to find a temperature at which the sum of partial pressures of two components equals the total pres sure (i.e., P t + P ,;" = P ,o1,, ) for a liquid composition x A and x 8 (see Table l ). Step 4. The actual stages, based on the Murphree vapor efficiency, E MV' for each stage, are displayed on top of theoreti cal s tages to demonstrate the effect of stage efficiency on the actua l number of stages. In the current example, we note that a single Murphree vapor efficiency, EM V' is used throughout the entire distillation co lumn for simplicity and symmetry in the feed s tage The overall efficiency E 0 is then determined by the ratio of the number of the theoretical equilibrium stages to that of the actual stages i .e., E 0 = N / N Some snapshots of the McCabe-Thiele method and s tage efficiency for distillation of acetone and toluene that are displayed in class are shown in Figure 2 (page 318) Homework Assignments Step 2 We show how to draw operating lin es. Once any two of three parameters (e .g., the reflux ratio R ; boil up ratio, V 8 ; and feed condition, q) are s pecified the operating lines and the feed line are uniquely determined. We After the graphical method by MATLAB code was in troduced a couple of problem s associated with using and modifying the MATLAB code were given as homework. For example, students were asked to determine various feed condi tions such as subcooled, partially vaporized, and superheated using the thermodynamic properties of benzene and toluene and then determine the number of equilibrium stages and boilup ratio at a given feed composition and reflux ratio (see Table 2 page 3 I 8). The effect of feed conditions on column performance is demonstrated by entering different q values also explain the relation between the s lope of the q-line and the state of the feed (subcooled, saturated liquid partially vaporized, saturated vapor, and superheated). Step 3. We demonstrate how to determine theoretical stages. Once the equilibrium curve, operati n g lin es, and feed line are drawn the equilibrium composi tion at each s tage i s deter mined by the McCabe-Thiele method Starting from the distillate x 0 (or bottom s product x 8 ), drawing a horizontal line from (x 0 x 0 ) on the y = x line to the equilibrium curve, followed by dropping a vertical line to the operating line is repeated until x reaches x 8 When actual data is used for the equilibrium curve the MATLAB interpolation function called interp I is u se d to find the intersection point s along the equi1 ibrium curve (see Table 1) 1 1 1 The transfer in the operating line from the rectifying section to stripping section is typically made when the liquid composition, x, passes the intersection of the two operating lines and feed line The interactive nature of MATLAB allows what if' analyses 1 9 111 in which parameter values such as relative volatility, reflux ratio, and feed con dition may be changed, and their effects on the disti ll ation column are graphically displayed during the presentation. Fall 2006 TA BL E 1 Portion of a MATLAB Code for Example 1 w hile x >= x_B % l oop for stepp in g ynew = y if iflag==O xnew = ynew / (a-y new *( a-1 )); % usin g co n s t a nt a lpha for eq. relation elseif iflag== 1 % u sing Antoine Eq ( 2 ) for eq. relation t=f zero('a nt o in e2' tmid optimse t (' disp ', iter ),y n ew a 1 b l c l a2, b2 c2 Ptotal) ; xnew=y n ew Ptotal / pvapor (a l bl.cl t ); e lse xnew=interp 1 (y data xdata ynew) ; end % usin g ac tu a l data for eq relation plot([x xnew] [y ynew],'r' ,' LineWidth ', 2 ) % a. Draw a horizontal line to the eq. curve hold on Frames(: i ) = ge tfr ame ; pau s e i=i+l ; x = ,rnew if x >= x_c o/o ifx >= z y=Lov e rV D *x +x D / ( R+ 1 ) else y =Lov erV B x-x B /V B e nd % using th e op lin e for rectifying sec tion % u sing th e op. lin e for s trippin g sec ti on plot([xnew,x] [ynew,y] ,' r ,' Line Width 2) % b. Draw a vertical line to the op. line hold on Frame s( : i )=getframe; pause if x> =x B nstage=n s t age + 1 else nstage=n s t age + x/ x_B end e nd % calculating # of s ta ges % c. Repeat a and b until x reaches x_B 3 /5

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a in the MATLAB code and displaying the stage-stepping inter0 9 actively. In the second problem students were asked to modify 0.8 and extend the MATLAB code 0.7 0 7 / to determine the actual number , 0 6 ~/ of stages based on the stage ef ficiency. This was demonstrated >-0 5 , and displayed in the lecture but 0 4 this time the students were asked , 0 3 to reconstruct w h at they had , see n in class and use it to solve a homework problem. About 0 1 0 1 85% of the st ud ents were able 0 0.1 0 2 0 3 0.4 0.5 0 6 0 7 0 8 0.9 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 to modify the code correctly to C @) determine the act ual number of stages. 0.9 0 9 ,--' :: : / ,' 0.8 0 8 / , 0 7 0 7 Figure 2. Snapshots of graphi, 0.6 0 6 cal output in Example 1 : Mc>-0 5 >-0 5 Cabe-Thiele method for binary distillation of acetone and tolu0 4 0 4 ene: a) equilibrium curve from Raoult's law; b) operating lines 0.3 0 3 and feed line for zA = 0.5, x 0 = 0 2 0 2 0 .95, x 8 = 0 05, q = 0.5, R = 2; c) 0.1 0 1 theoretical equilibrium stages; and d) actual stages (shown in 0 1 0 0 0 1 0 2 0 3 0.4 0 5 0. 6 0 .7 dashed line) with Em v = 0.7 for 0. 2 0 3 0.4 0 5 0 6 0 7 0 8 0 9 0. 8 0.9 th e e ntire distillation column. TABLE2 An Example of MATLAB Homework Problem To Link the Effect of Feed Conditions to the Number of Theoretical Stages and Boil up Ratio 4 A mixture of 50 mo! % ben ze ne and toluene is to be se parated by distillation at atmospheric pressur e into product s of 95 % purity using a reflux ratio L/O=3.0 in the rectifying section. The feed has a boilin g point of 92 C and a dew point of 98 Cat a pressure of I a tm. Determine the q value if ( i) the feed i s vapor a t 150 C; (ii) the feed i s liquid and a t 20 C; (i ii) if the feed i s a mixture of two-third s vapor a nd one-third liquid. Component ~H" P (ca l / g mol ) C,(cal/g mol C) Liquid Vapor Benzene 7 360 33 23 Toluene 7,960 40 33 Assume a relative volatility of2 5 and use a s imple MATLAB code (fee d.m) that is available a t the ChernE 332 Web page to determine the number of theoretical stages and the boilup ratio in the str ipping sect ion for thr ee different feed conditions. Submit the printouts (gra phs). Each grap h s hould have your name and the outp ut (n umb er of s tages and boil up ratio) printed on the upper left corner. To do thi s the MATLAB code has th e following gtext command that writes the specified string at a location c li cked with the mouse in the graphics window: gtext( {'number of stages: num2str(nstage)}) gtex t ( { boilup ratio: ,' num2str ( V B)} ) gtext({'run by ,' your_name}) First the co de asks you your name a nd input conditions including the q va lu e. After runnin g the code go to the gra ph and click a location ( total three times) to print out the number of stages boil up ratio and your name on the g raph. 316 Chem i ca l Engineering Education

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Example 2 Visualization of Enthalpy Method in Binary Distillation[ 6 l The McCabe-Thiele method uses an e nergy balance only at the feed tray whereas the Ponchon-Savarit graph ical method u ses a rigorou s energy balance throughout the distillation co lumn 14 61 A lth oug h the Ponchon-Savarit method for distillation ha s l argely been s uppl eme nt ed b y rigorous computer-aided method s, the concept of u s in g a diagram for the separating agent (heat in di s tillation ) and difference point s is very important and u sefu l in un derstanding simi l ar grap hi ca l approaches in ot h er separa tion proce sses, s uch as the Malone y -S chubert gra phic a l method 141 in extractio n that u ses the analogous Janecke diagram for the separa tin g agent ( the so l vent). We u sed recitation sessions as well as l ectures to in troduce a nd demonstrate the Ponchon-Savarit graphical method. A handout on the method usin g the MATLAB code was distributed fir s t, and the graphical method was demonstrated u s ing s tep-b y-step di s pl ay. The visualiza tion of the Ponchon-Savarit method consists of determin ing difference point s a nd di s playing ray s a nd equilibr ium I Obtain equilibrium and entha lp y data 1 ... I I --------1 Thermodynamic Input 1-----, : Actua l e quilibrium & e nthalp y data : ,i, I ---_I I Step 1: Displa y y vs. x and entha lp y I 1------------, ;-----------1 Design [nput Reflux ratio & feed condition Di s tillate bottoms composi tion s w ----------I Step 2: Determine and display differ e nce and feed points I I On entha lp y diagram I Displa y rays th a t pass difference point and liquid (va por ) composition Display eq uilibrium tie line to determine th e corresponding vapor (liquid) co mp os ition. v I Step 3 : Det erm ine the number of equilibrium stages I Figure 3. Flowchart of Example 2: Pon c hon-Savarit method for binary distillation tie line s on th e entha lp y diagram. /a--------------------------------------, The flowchart of the P onchon-Sa varit method for binary di s tillation i s s hown in Figure 3. We again used the co mm a nd s plot" and mov ie in MATLAB to visualize and grap hic a ll y display the diagram s, 1 1 1 a nd some snapshots of the method for distillation of aceto n e and water mixtures are shown in F i gure 4, rig ht as well as in Figure 5 (next page). The operating line s obta in ed und er th e assumption of consta nt molal overflow are s hown by the dashed lin es in the y vs. x diagram for comparison in the figure The st ud e nt s were asked to run the same co d e as the l ect ur e to so l ve similar homework probl ems by varying de s ign inputs s u c h as feed conditions. In the future, we will ask s tud e nt s to modify the MATLAB code for the Pon c hon-S avari t method for Figure 4. Graphical output for Example 2: a) e nthalp y-composi tion dia gram from ent halp y data; and b) difference points (open c ircles) and feed line for z A = 0 .5, X 0 = 0 90 X 8 = 0.0216 q = 0.5 and R = 0.288. The y-x compos tion diagram is a l so s h own at t h e Fa/12006 b 5000 10000 5000 5000 Ponchon-Savarit Method 0 1 0 2 0 3 0.4 0 5 0 6 0 7 0 8 0 9 0 1 0 2 0 3 Compositio n ll or y P onction-S ava rit Method 0.4 0 5 0 6 Composition, >c or y 0 7 0 8 0 9 0 9 0 8 0 4 0 3 0 2 0 1 0 9 0 8 0 4 0 3 0 2 0 1 / / ,' ,' ,' ,' ,' ,' y vs x d i agram / ,' / y vs x diagram / ,' / / ,' / 0 o"---=o~ 1 ---:0~ 2 ---:o ~. 3---:o ~. 4 --: 0 ':. o --:o"=. s--=o"=. --:occ: 8 --:o:-:c 9----'. 3 1 7

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distillation such that the extraction process can be solved, analyzed, and displayed interactively. Example 3 Direct Solving Exact Methods for Multicomponent Distillation 4 1 Despite it s practical importance, multicomponent distil lation has not been thoroughly discussed in first courses on separation s This is mainly because analysis of multi component separations requires solving material balan ces, enthalpy balances, and equilibrium relations at each stage and solution procedures can be difficult and tedious. H ence, only an approximate method commonly referred to as Fen ske-Underwood-Gilli land (FUG) h as been used to make preliminary designs and optimize simple distillation. 14 1 Al ternatively, commercial simu l ators have been introduced to so l ve multicomponent separations in detail, but students often treat these commercial process a multicomponent distillation of hydrocarbons and compare the results with those obtained from the commercial pro cess simulator AspenPlus (see Table 4 page 322). Again a handou t that describes the method used in the code was distributed and explained in a recitation session before the homework was distributed. As depicted in Figure 7 (page 323) a simple thermodynamic model (Raoult s law in which the Antoine equation has been used to provide the vapor pres sure information) overpredicts the volatility of light non-key (LNK)" component (ethane) and underpredicts that of"heavy non-key (HNK)" components (pentane and hexane) in the multicomponent distillation of hydrocarbons. As a result the compositions of the Light key (LK) component (propane) in the distillate and the heavy key (HK) component (butane) in the bottoms are slightly lower than the values obtained from Aspen simulation with more accurate thermodynamics models such as Soave-Redlich-Kwong equation simulators as black boxes.1 7 1 41 a We u sed MATLAB to so lv e the nonlinear algebraic equations for multicomponent distillation in P onchon-Savarit Me thod y vs x diagram this example. More specifically, user-friendly routines in MAT LAB were used to employ the equation-tearing, bubble-point method in solving the governing equations This numerical method consists of calculating equilibrium compositions and enthalpies, solving the modified material balance equations, and updating solutions using Newton s method (see Table 3). As indicated in the b flowchart of the procedure in Figure 6 (page 322), the system of equations was solved for composi tions at each stage by the matrix solver sparse" in MATLAB_ [IJ The Newton's method was used to update the guess of tearing vari ables, temperature, and vapor rate at each stage. A function "froot.m" was created which solves nonlinear equations using a Newton s method to update the temperature and vapor rate at each stage Once temperature enthalpy and com positions are obtained the heat duties can be determined. 15000 I I 10000 5000 I I I I I I ,, /, ,,,' 1 ':,, /; / I I I I 1 I I I I I I I I I I I I I I I f' I f l / ,' ,' ,/ / l I ___ .L, _______ ;_ ______ L ___ 5 000 Composition x or y Ponchon-Savarit M ethod 20000 ---~--------~ 1 0000 5 000 0 U U U U M U M U Composition x or y 0 9 0 4 0 3 0 .2 0 1 / 0 0 0 1 0 9 0 8 0 .7 0 6 >-0 5 0 4 0 3 0.2 I 0 1 / / 0 0 0 1 / / / ,' 0 2 03 0 4 0 5 0.6 y vs x
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TABLE4 A n Exam pl e of MATLAB Hom ework Problem Paired With a Problem U sing Aspen Plus to So l ve a Multicomponent Distillation of Hydrocarbons. I Multi co mp o n e nt Di s till a ti o n u s in g As p e n Plu s Di s till a ti o n co lumn s p ec ifi ca ti o n s a r e g i ve n as b e l ow: Feed (sa tu ra t ed liquid a t 250 p s i a a n d 2 1 3 F) Co m po n e nt Lbm ol/ h Et h a n e 3.0 P ro p ane 20.0 n But a n e 37 0 n-P e nt a n e 35.0 n-H ex an e 5.0 Co lumn pr ess u re = 25 0 p s i a P a rti a l co nden se r a nd p a rti a l r e b o il e r Di s till a t e ra t e = 23.0 lbm ol/ h R e flu x ra t e = 1 5 0 .0 lbm ol/ h N umb e r o f equilibrium pl a t es (excl u s i ve o f co nd e n se r a nd r e b o il e r ) = 1 5 Feed i s se nt t o mi d dl e s t age Em a il th e fo ll ow in g t o th e T A: I ) a print o ut o f y our As p e n p rocess w ith yo u r N e tID as the co lumn n a m e as we ll as a s tr ea m t ab l e s h ow in g t h e res ult s u s in g th e co ndi t i o n s desc rib e d in th e exe r c i se in cl u d in g s t age te mp era tur es, va p or a n d liqui d flow r a t es a nd reboi l er a n d co n denser d uti es. 2) a gra ph of liqui d co mp osi ti o n of eac h co mp o n e nt vs s t age numb e r 3) a gra ph of va p o r co mpo s iti o n of eac h co mp o n e nt vs s ta ge num be r 2. Multi co m po n e nt Di s till a ti o n u s in g M A TL A B 320 R e p ea t P ro bl e m I u s in g s impl e M A TL A B co d es ( problem 2. m a nd fr oo t.m ) ava il a bl e a t th e Ch e m E 332 W e b s it e Th e code utili zes th e e qu ti o n t ea rin g, bubbl e -p o int m e th o d in so l v in g th e MESH e quati o n s as d esc rib e d in th e h a ndout. Fo r s imp l i c it y, t h e A nt o in e e quati o n i s u se d t o eva lu a t e Kva lu es a nd e nth a lp y o f eac h co mp o nent Th e fil e fr oo t.m i s a f un c ti o n ro utin e w hi c h so l ves n o nlin ea r e qu a ti o n s u s in g a New t o n 's m e th o d See th e h a nd o ut fo r d e t a il s. Wh e n th e co d e i s run yo u a r e aske d t o input th e co nditi o n s d esc rib e d in th e p ro bl e m S ubmit th e fo ll ow in g print o ut s I ) a gra ph of liqui d co mp os iti o n of eac h co mp o n e nt vs. s t age numb er 2) a gra ph of v ap o r co mp os iti o n of eac h co mp o n e n t vs. s t age numb er Co mp are yo ur re s ult s w ith th ose o bt a in ed in P ro bl e m I initi a l guesses for t ea r va ri a bl es T ; a nd II; A nt oi n e e qu a ti o n __ E nth a lp y e qu a ti o n __ ............ D es i g n Inp ut : Reflu x ra ti o & fee d s ta ge : Di s till a t e, b o tt o m s co mp os iti o n s '----------------------------------Ca lcu l at e e nthalp y ( h 1 H ;) a nd v o l atility ( K ; ; ) : S p a r se m a tri x so l ve r ------------------------------' Sol ve tri-dia go nal m a tri x fo r x ; ---; __ New t o n s m et h od ___ C ompute n e w T;, Q ;, V ; a nd L ; ---------------------------, 14---__,; ; __ Co n verging criter i a ____ ---. It era t e until T; i s co n ve r ged TABLES R es pon ses of the S tud ents R es p o n ses t o: H ow v aluab l e wer e th e l ec tur es a n d h o m e w o rk a ss i g nment s ba se d o n MATLAB ?" % r es p o n ses I = t a u g ht m e littl e 2 = t a u g ht m e some 3 = ed u ca t io n a l 4 = ve r y e du ca ti o n a l 5 = ex tr e m e l y e du cat i o n a l 3.0 4 2 16.3 57 7 1 7.8 S o m e co mm e nt s fr o m th e s tud e nt s Th e mi x o f co n ve nti o n a l m e th o d a nd a nimati o n h e lp s u s t o und e r s t a nd th e co n ce pt from th e fr o nt. I lik e h ow mu c h of it i s g raphi c Thi s mak es th e l e arnin g mor e intuiti ve I h a t e gra phi ca l m e th ods b ut u s in g M A TL A B i s okay. "So m e M A TL A B h omewo r k p ro bl e m s we r e t oo easy b eca u se I ju s t pun c h ed in nu m b ers" No more MA TL AB p l ease. Di s pl ay va por a nd liquid co mp os iti o n profile s Figure 6. Flow c hart o f Exampl e 3 : mul t i co mpon e nt di s til lati o n C h e mi ca l E n g in ee rin g Ed u ca ti o n

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and coo lin g cycle in therm a l s wing ad s orption wa s discu s sed in detail. Students were asked to us e the MATLAB code to determine the regeneration characteri s tic s in thermal s wing adsorption at vario u s operating condition s, s uch a s air flow. In the future, the students will be a s ked to extend the code to so l ve simi l ar rate-based s orption processe s s uch a s ion excha n ge and chromatography. PEDAGOGICAL ASPEC T S O F STUDENT ACTIVITIES AND RESPONSES OF STUDENTS The pedagogical aspects of s tudent a ctivitie s have evolved over the years. The incorporation of interactive disp l ay of graphical methods was done in lecture s to effectively dem onstrate the effect of de s ign param e ter s on the distillation a 0 9 0 8 0 7 0 6 >0 5 0.4 0 3 0 2 0 1 b 0 9 0 8 0 7 :,., 0 6 0 ., {J f! LL 0 5 ., 0 ::. &. 0 .4 ., > 0 3 0 2 0 1 0 0 F a /l 20 06 D i stillate 2 Distill ate >( >( 2 Feed Tray ___ /--'---' ~ ;, 4 6 8 1 0 1 2 )( ---4 6 st ag e no F eed Tr ay 10 Stage No 12 14 14 co lumn Then s tudents were asked to run the same code used in l ecture to solve s imil ar problems by varying design input s su c h a s feed conditions We s tarted a s king the s tudents to modify th e MATLAB code s to extend it s capab iliti es a nd analyze the results. A tutorial on how to develop a MAT LAB code was instituted in the recitation se s s i ons to make thi s tran s ition smoother. We conducted a s ur vey on using MATLAB in lectures and homework assignments a s a part of mid-term eva lu ation and resu lt s are summarized in Table 5. The word in g of question s and re s ponses in the table is taken verbatim from the s ur vey. The s urvey a l so provided a space for written comment s As indicated in Table 5 the use of MATLAB w as generall y a ccepted as a u s eful a i d in teaching s eparation s. In the future w e wou ld like to a ll ow the student s to play more act i ve ro l es in so lvin g variou s separation problem s using MATLAB In B ottom particular s tudent s will be a s k e d to modify the MATLAB codes and extend them to work o ut many other separation processes s u c h as absorption, s trip ping and extraction 16 1 6 C2 x C3 + C4 C5 C 6 I I Bo tt om C2 ->
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.tA .. 5 .. ._c_l_a_s_s_r_o o_m __________ ) THE RESEARCH PROPOSAL in Biochemical and Biological Engineering Courses ROGER G HARRISON, MATTHIAS U. NOLLERT, D AVID W SCHMIDTKE, AND VASSILIOS I. SIKAVITSAS University of Oklahoma Norman, OK 73019-1004 T he advancement of the U S. economy i s critically de pendent on new development s in science and engineer ing technology. Undergraduate student s in engineering are typically well trained in solving well-defined problems. They receive very l ittle training past reading a textbook, however, in the creative activities involved in development of new techno l ogy. One way to help students think creatively about develop ing new technology is to incorporate a research proposa l into the coursework. A l though numerous efforts have been made to incorporate more writing into engineering and sci ence course s, 11 41 little has been reported about using research proposals in undergraduate courses. In an undergraduate course for chemistry majors at Brooklyn College entitled "Introduction to Research students were req u ired to select a research project prov i ded by the instructor 1 5 1 Students then wrote a ro u gh draft of t h e proposal. After receiving feedback from the instructor, they wrote a final draft. In a Youngstown State University course entitled Chemistry Research ," stu dents were required to select a research proposal topic write a roug h draft of the proposal and then write a final draft after receiving feedback from the professor 16 l For both proposals the time allotted for writing (five weeks at Brooklyn College and three weeks at Youngstown State) seems too short for undergrad u a t es, given t h e challe n gi n g n ature of writing a researc h proposal. This paper presents o u r experiences incorporating a research proposal in four biochemical or biological engineering courses F a ll 2006 Roge r G Ha rri so n is an a s sociate professor in the School of Chemical Biological and Materials Engineering at the University of Oklahoma His research focuses on the expression and purification of recombinant protein s, and the design of proteins for oncologic and cardiovascu lar applications. He is the lead author with three coauthors of the textbook Bioseparations Science and Engineering (Oxford University Press, 2003). He received his B S in chemical engineering from the University of Oklahoma and his M. S and Ph.D from the University of Wisconsin-Madison After his Ph D he also worked in R&D at Upjohn Company and Phillips Petroleum Company. Matth i as U Nollert is an associate professor in the School of Chemical Biological, and Materials Engineering at the University of Oklahoma. His research in the area of biomedical engineering seeks to understand the role of fluid mechanics in modulating the biology of blood cells and the cells of the blood vessel wall He received his B.S. in chemical engineering from the University of Virginia and his Ph.D. from Cornell University He was a postdoctoral fellow at Rice University Dav i d W Schmidtke is an assistant professor in the School of Chemical Biological and Materials Engineering at the University of Oklahoma His research interests are in the areas of biosensors and cell adhesion He received his B S in chemical engineering from the University of Wisconsin-Madison and his M.S and Ph.D. from the University of Texas at Austin He was a postdoctoral fellow at the University of Pennsylvania Vassilios I Sikavitsas is an assistant professor in the School of Chemical Biological and Materials Engineering at the University of Oklahoma His research interests include the use of molecular and cell biology approaches together with engineering principles in developing cellular and tissue engineering strategies for organ regeneration and assessment of human health risk. H e received his B. S. in chemical engineering from Aristotle University of Thessaloniki, Greece, and his M.S. and P h. D from the Sta t e Un ive r sity of N ew Yor k at B uffalo. H e was a postdoctoral fellow at R ice University. Copyrigh t ChE Division of ASEE 2006 323

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for gra du ate s tud e nt s a nd upp er -l eve l und e rgraduate s at the University of Oklahoma ( OU ). Biochemical and biological engineering are broad fields under go ing rapid development and ha ve m a ny opportunities for s tudent s to write re searc h pro p osals on the adva n cement of sc i e n ce a nd engineering We found that th e grea t majorit y of s tudent s could write proposals on biochemic a l and bio e n g ineerin g topic s w ith out m a jor probl e ms. Writin g the propo sa l in s tage s over a t least h a l f the se me s t er-w ith feedback provided by the in s tructor af ter each s t age-was h e lpful to the students. Our findings are s upport ed by our own observation s and an anonymo u s s urvey of the s tudent s. RESEARCH PROPOSAL A research propo sa l was requir e d in each of the fo ll owing co ur ses, with the number of s tudent s indic a t e d in parenth eses: Biochemic a l Engineering (25), Bio se nsor s (9), Cellu l ar As pects in Tissue Regeneration (9), and Ti ss ue Engineering ( 15). Eac h of the se courses i s a n upper-le ve l engineering course for juniors, se nior s, and gra duate s tud e nts. Students devoted at l eas t half the se mester to developing their research propo sa l s in these courses. While the requir e ment to do a research paper did not cause a reduction in course material covere d in l ec ture there was a red u ction in homework requir e d compared to what it wo uld have been h ad a research proposal not been required es pe c ially n ear deadline s for th e re searc h propo sal. The propo sa l s ranged from a se ri es of gra ded writing assign ments (objectives, rough or first draft and final draft in Bio c hemical Engineering a nd in Tissue Engineer in g; objectives a nd final draft in Bio se n so r s), to one writing assignment for the e ntir e proposal (Ce llul ar Aspects in Ti ss ue Regeneration). For one of th e propo sa l s (Ce llul ar Aspects in Ti ss ue Regenera tion ), th e s tudent s were requir ed to give a pr ese ntation a nd feedback from that presentation was incorporated into the fina l written propo sa l. A sa mple outline of requirem e nt s and handed out to s tud e nt s as g uid es. Stud e nts were a llowed to choose a propo sa l topic in which the y h a d an int e re s t ba sed on th e ir ow n r esearc h and / or prior courses in the biolo gica l sc ienc es or bioen g in eeri n g. (Nea rly all of the st ud e nts in the courses were e ith er gra du a t e s tudent s in the a r ea of bio e gi neerin g or were undergraduates w h o were in one of the bio elective patt erns -biot ec hnolo gy or pre-med.) In some cases s tudent s read ahead in th e t ex tbook about topics of interest. Eac h s tudent m e t with the in st ructor to discuss the a ppropriatene ss of hi s or her c ho se n topic It was some time s nece ssa ry for a topic to be modified b ase d on the instructor's experience and knowledge of the topic Stud e nt s we r e given g uidan ce about ho w to searc h th e lit erature. In one co ur se, Bio c hemical Engineering a univer sity librari a n came to class and gave a pr ese ntation on the various resources ava il a bl e for searc hin g literatur e, includin g th e u se of search program s a nd int e rlibrary l oan. OBSERVATIONS AND OUTCOMES Our main observations were the following : 1 Writing a r esea r c h pr o posal was a c halleng e for students in these four courses It was the fi r s t tim e any of them had been r eq uir ed to w rit e a prop osa l, w ith th e exce ption of a few students who had wr itt e n a proposal in one of th e four co urs es in a p ri or semester. For man y of th e m it was th e first time that th ey had been required t o do r ea ding outside of the assigned t ex books. I n addition, we observed that students t e nded to under es timat e th e difficulty of writing a proposal es pecially in com ing up w ith n ew id e as t o research. 2. What separates th i s ass i g nment from a traditional term paper i s that, besides needing t o und e rstand th e lit era tur e, th e s tudent also has to develop his o r h e r new ideas for r esearc h. Challenging students to d eve lop new ideas and to express them in w r iting is what we see as the major reason to use this ass i gnment. TABLE 1 the ge neral gra din g g uideline s for th e research propo sa l in Bioc hemi cal Engi n ee ring are g iven in the Appendix. Summary of an Anonymous Surve y of Students The se l ec tion of the re sea rch topi c and dev e lopment of the objectives and sig nificanc e by eac h s tudent were very i mportant to s uccess ful proposal s Exam ples of statements of objectives a nd sig nificance from our ow n re sea rch were 324 A bout the Re searc h Proposal in Bioen gineeri n g Cou r ses Percent of Respondent s State ment S tr o n gly Agree Di sag r ee Stro n g ly Agree Di sag ree The re sea r c h propo sa l was a good way to l earn 64 29 7 0 abo ut a topic in bioengineering in depth. T h e r esearc h proposal in vo l ved more c r ea tivity 2 1 43 36 0 than any ot h e r assign m e nt I have h ad w hil e at OU. T h e r esearch proposal gave me a better app r ecia 14 5 8 2 1 7 tion abo ut h ow n ew t ec hn o l ogy i s c r ea t ed The re sea r ch proposal was one of the mo s t c h a 21 43 29 7 len g in g ass i g nme)1t S I h ave had a t OU Writin g a researc h proposal in thi s course h e lp ed w ith a n o th er co ur se/co ur ses tak e n af t e r wards 36 64 0 0 a nd / or a re searc h project. Chem i ca l Engineering Education

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REFERENCES I. Plumb C., and C. Scott Outc o m es Assessment of Engineering Writin g a t th e University of Washin g t o n ," J. Eng Ed. 91 ,333 (2 002 ) 2 Boyd G a nd M F. H asse tt Developin g Crit i ca l Writ in g Ski ll s in Engineering a nd Technolo gy Student s," J Eng Ed 89 ,409 ( 2000) 3 Newe ll J .A D .K Lud l ow and P.K Sternb e r g, Development of Ora l a nd Written Comm uni ca ti o n Skill s Across a n Int egra ted Laborator y Sequen ce Chem. Eng. Ed., 31 116 ( 1 99 7) 4. VanOrd e n N., l s Writin g a n Effective W ay t o L ea rn C h emica l Con cepts?" J Chem. Ed ., 67 ,583 ( 1 990) 5. William s E T. and Bramwell F.B. Int rod u ction to R esearch, J. Chem Ed. 66 565 ( 19 89) 6. Schild cro ut, S M ., Learnin g C h em i s tr y R esearch Outside the Labora tor y : Nove l Gr a du ate a nd U nd e r g raduate Co ur ses in R esearc h M e th odo l ogy," J C h e m Edu c ., 79 1 340 (2002) APPENDIX Sample Outline of Requirements for the Research Proposal in Biochemical Engineering Each s tud e nt i s required to write a r esea r c h propo sa l on a topic associated with the production and proce ss ing of bioproduct s. Specific t opics includ e but are not lim ited to fu ndam e nt a l st udies of: Molecular and Cellular Engineering. Thi s expanding area of e n g in eeri n g re se arch encompasses pur e and mixed c ultur e processes, modelin g, optimization and control of ce ll and metabolite production development of new biochemical reac tor s, bi ocata l ys i s, and conversion of synthet i c gas and ot h e r c hemical feedstocks to value-added product s via biologic a l mean s New techniques in the monitorin g a nd contro l of molecular a nd ce llul ar e n g in ee rin g are a l so of int e re s t. Downstream Processing The capability to purify bioprod u cts in a cos teffective mann e r on a commercia l s cale i s an important technical goa l in bioproces s ing of subs t ances of biological origin. New proce sses and a m ajor enhancement of ex i s tin g pro cesses are n eeded to accomplish nece ssary purification. Guidelines 326 1 Obj ec ti ves and s i gnificance: Wr it e one to two pages g i v in g th e objectives of yo ur pr o posal a nd th e ex pe c t e d s i g nifi ca n ce. Inn ova ti ve o r orig i nal aspec t s of th e ob j ec tiv es s hould b e discuss e d. Also on a separa t e page, give th e co mpl e t e cita tion s, in clud in g th e titl es, of fiv e or s ix lit eratu r e r efe r ences t hat relate to your proposal. 2. Ea c h proposal ( initi a l draft and.fina l draft) must includ e: A. Pr o j ec t Summa ry li mit one pa ge 8 Pr o j ec t D esc ripti on limit JO pa ges C. R efere n ces n o pag e limit 3. Th e proj ec t d e scription s hould b e a clear s t atemen t of th e wo rk to b e undertaken and s h ou l d include th e fo ll ow in g: o jectiv es fo r th e period of th e prop ose d wor k and ex p ec t e d s i g nifi ca n ce and r e lati on t o th e pr ese nt state of knowl e dg e in the field Th e s tat e ment should out lin e the gene r al plan of wo rk includin g th e broad d es i g n of a c ti v iti es to b e und e rtaken and an adequate de sc ripti o n of exper im e ntal m e th o d s and procedu r es. T y pi ca l sec ti o n head in gs of th e project description are as fo ll ows: Obj ec ti ves, Significance and I mpact; Ba ckg r ou nd ; General Plan of W o rk; and Experimental M e thod s and Pr oce dur es. 4 Specifications for mar g in s, s pa c in g and fo nt s i ze: 2 5 c m margins on t o p bottom and on eac h s id e; doubl e s pa ce d ; and 12-p o int font s i z e. 5. W eb s it e r eferences s h o uld b e limit ed t o busin ess and gove rnm e nt W eb s it es only. A ll o th e r r efe r e nc e c itati o n s s h o uld b e t o peer-reviewed articles in publish ed journa l s. 6. For th e r ev is e d pr oposa l any c han ges mad e to th e initi a l pr o p osa l should be und er li ned o r hi g hli gh t ed. Grading/Schedule The grade for the research proposal wi ll be b ase d on the fo ll owi n g criteria: J Approach. Are th e co nceptual fram ewo rk desi g n m e th o d s, and ana l yses adequately developed, we ll -integrated, and appropriate t o th e object i ves of the proj ec t ? 2 Inno va tion D oes th e projec t e mpl o y novel co n ce pt s ap pr oac h es, or m e th o d s ? Ar e th e o bj ec tiv es o riginal and in n ova t i ve? D oes th e proj ec t c hall e n ge ex isting paradi g m s or d eve lop n ew m e th o d o l og i es o r t ec hn o l og i es ? 3. U tilit y or relevance of the research. Thi s c rit e ri o n i s us ed t o assess th e l i kelihood th at th e r ese ar c h c an co tribut e to th e ach i eveme nt of a goa l that is ex trin sic o r in add iti on to that of th e r ese ar c h fi e ld itself, and th e r e b y se r ve as th e ba s i s for new or impr oved t ec hn o l ogy o r as s i s t in th e so luti o n of soc i e tal pr o bl e m s. Grade Cred it and Schedul e : Se l ec tion of propo s al topic (d ue after thr ee weeks) 0 % Obj ec tive s a n d significance ( due after s ix week s) 5 % Initial draft ( due af ter 10 weeks) 20% Revi sed draft ( du e af t er 15 week s) 15 % Total for the propo sa l 40 % General Grading Guidelines for the Research Proposal in Biochemical Engineering The o n eto two-pa ge s t a t e ment of objec tive s a nd s i g nifi ca n ce was gra ded ba se d o n th e de gree to w hich th e objectives were s p ecifica ll y s t ated. The stateme nt of s ignificance s hould de sc rib e what i s innovative a bout the propo sa l. The initial and revi se d draft s of the propo sa l were gra ded based on a carefu l reading by the in s tru c tor with com ment s and qu est ion s written where ap propriat e in the margins. Th e que s tion s and / or problems about the propo sa l led to a rating of th e prop osa l into one of thr ee categories: minor moderat e, or m ajor questions / prob l ems. In a dditi o n the objectives a nd signjficance sec tion of th e propo sa l wa s c hecked to see i f any defici e n cies not ed in the ea rli er objective s a nd s ignificance assignment were correcte d Numerical gra d es were ass i g n e d ba se d on the degre e to w hi ch que s tion s and / or problem s were minimal a nd th e objectives a nd s i g nific a n ce were we ll s t a t e d 0 Chem i cal E n g in ee rin g Education

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tab teaching tips ) r This one-page column wi ll present practical teaching tips in sufficient detail that ChE educators can adopt the tip. The focus should be on the teaching method, not content. With no tables or figures the column should be approximately 450 words. If graphics are included, the length needs to be reduced Tips that are too long will be edited to fit on one page. Please submit a Word file to Phil Wankat subject: CEE Teaching Tip. 'MAKE YOUR TEACHING ASSISTANT A CO-INSTRUCTOR BARATH BABURAO, SARAVANAN SwAMINATHAN, AND D ONALD P. Vrsco, JR. Tennessee Technological University Cookeville, TN 38505 M ost engineering graduate students acros s the country are not trained in teaching. When training occurs, one of three models is normally used i 1 1 : 1) Enr o llm e nt informal d eg r ee or ce rtifi c at e e n g in ee rin g edu c ation programs 2) Formali z ed future facult y preparator y pro g rams su c h as th e Pr e paring Furur e Fa c ulty ( PFF ) pr og ram 3) Informal ( shar e a co ur se w ith a g raduar e s rudenr ) o r formal ( wirh c ours e c r e dit ) n aining in p e da g og y The Department of Chemical Engineering at Tennessee Technological University recently adopted a procedure similar to the third type that fully integrates a teaching assis tant (TA) into a senior-level Process Dynamics and Control course. Training occurs throughout the semester and the TA is involved in a meaningful way in all aspects of the course. Implementation was done with two graduate students as co instructors (CI) supervised by a full-time faculty member (FM). In presenting this model below however we use just a single CI for clarity. PROCEDURE The CI was chosen based on interest in an academic career and past experience with the course material. Prior to the beginning of the semester, the FM discussed the Cl's in volvement with the course from developing the syllabus and delivering the material to preparing and grading homework and examinations. The FM also provided reading materials on important pedagogy tentatively planned for the class suc h as active l earning or team-based approaches. A week l y meeting was arranged to discuss all relevant aspects of the course, s uch as feedback on the previous week's class, plans for the upcoming week etc In addition, the FM and the CI met 10 minutes prior to each class in order to briefly review Fa/12006 the day s plan as well as discuss any unforeseen issues that have arisen. During the first few class periods the FM provided a co ur se overview and discussed the role of the CI. The CI was trained to design the teaching methods, hom ework questions, quiz zes, laboratory, examinations, and the evaluation of the final project and presentation The CI was given the freedom to use the previous year s course material or design new mate rial. When the CI taught the class (which happened more than half the time) the FM observed the Cl's performance and vice-versa. RESULTS An individual assessment form for the CI was developed under the supervision of the FM This 18-question form covered six areas: lectures, l abs, organization, student int er action in-class activities and assignments / testing. Overall the students rated the CI as above average. The best area was Student Interaction. Student comments indicated that it was easier to approach a grad u ate student than a facu lt y member. Additio n ally, gradua t e st ud ents are lik e l y to keep similar hours to that of undergraduate students, making them more accessible. Overall the Cl's involvement in every aspect of the co ur se proved to be effective training. The FM often had an advisory role. Based on the feedback, the students generally agreed that the Cl's involvement was a positive experience for all involved REFERENCE I. Wankat P.C. and F.S. Oreov i cz Teaching Prospective Engineer i ng Faculty How To Teach," Intl J. Engr Edu c., 21(5), 925 (2005) 0 Copyright ChE Division of ASEE 2006 32 7

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( __ --=-5--=-Y-=EA:.......::..:R_IN_D_E_X--=--2_0-=--02--:-::-::--2_00_6 __ ) Volumes 36 through 40 (Note: Author In dex begins o n p age 338 ) TITLE INDEX Note: Titl es in itali cs are books reviews A Active Learning and Critical Thinkin g, Using Small Blo c k s of Tim es fo r .......... ....................... ... ... ....... 38 (2), 150 Act ive Learning Th a t Addresses Four Typ es of Student Motiv a tion Survivor Classroom: A M e thod of.. ........ 39 (3),228 Adsorption L abora t o ry Experiment A Fluidized Bed ....... 38(1 ) 14 Agitation and Aeration : an Automated Did act i c Ex pe r im e nt ... .. .. .. ....................................... .. 38 (2), 100 Agitation Experiment with Multipl e Aspects An ............ 40 (3) 15 9 A n a lo g i es: Th ose Littl e Tri cks That H e lp Students t o Understand Ba s i c Concepts in Chemical Engineering 39 ( 4 )302 A pplied Prob a bilit y a nd Stati s ti cs, A n U nd ergrad uat e Course in ...... .................................... .... .......... ....... 36 (2), 170 ASEE Annual Meetin g Pro gra m 2002 ...... ..................... 36 (2), 1 28 ASEE Annual Meetin g P rogram, 2003 .. .................. .. .... 37 (2), 120 Aspec ts of Engineering Practic e Examining Value and B e h av i ors in Organizations ................ ............... .... .. 36 ( 4 ),3 I 6 Aspen Plu s in the C h E Curriculum: Suitable Course Co nt e nt and Teaching M e th odo l ogy ... ... .... .. ... .. ... .. .. .. 39 ( 1 ),68 Assessing the In corporatio n of Green E n g in eer in g int o a De s i g n-Ori e nt e d H ea t Tran sfer Co ur se .. ... .... .. ...... 39 (4),320 Assessing Learning Outcomes, Rubri c D eve lopm e nt and Inter Rat er Reli a bilit y I ss u es in .. .................... .... ... ..... 36 (3),2 1 2 Assessment of a Simple Viscosity Experiment for Hi g h School Science Classes D e mon s t ra ti o n a nd .......... .. 40 (3),2 1 I Assessment of Teaching a nd Learning, Us in g T est R es ult s for .. .... ... ..... . ............ .. ........ .................... 36 (3), 1 88 Assessment of U nd e r gra duate R esearc h Eva lu a tin g Multidisciplinary Team Projects, Rubri c D eve lopm e nt for ............................................... ... ..... ... 38 (1),68 A utom a t ed Di st ill a ti o n Column for th e U nit Operations L a borator y An ............... .. ...... ... ...... ................ .. ... 39 (2), 104 A utomoti ve Applications Design of a F u e l Processor System for Generating H ydroge n for ......................... 40 (3),239 Award Lectures E qu a tion s (of C h a n ge), D o n t Change, The: But the Profession of E n g ine er in g Does ..... .............. 37 (4),242 M e mbran e Science a nd Technology in the 2 1 st Century .... .. ... ... .. ..... ... .... .. .... ........ ...... .. .. .... .. ... .. 38 (2),94 Future Dir ec ti o n s in ChE Education : A New P a th to Glory .... ... ......... .. .... ............. ...... .... .. ... 37 (4),284 Azeotropic System in a Laboratorial Distillation Column, Validating The E quilibrium Stage Model for a n ......... 40 (3) 1 95 .B B a t c h Fermentation Ex p e rim e nt for L-Lysine Produ c tion in th e Senior L a borat o r y, A .... ..... .......... 37 (4),262 ( BLEV E), B o ilin g-L iquid Expanding-Vapor Explosion: 328 An Introdu c tion to Consequence a nd Vulnerability Analysis ................................. ................................... 36 (3),206 Be er, T eac hin g Produ ct D es i g n Through th e In ves ti ga ti o n of Comme r c i a l ... .................. .. ... ... .. ... 36 (2), 10 8 Bin a r y M o le c ular Diffusion Experiments, In expens i ve and Simple ... ...... ... ........... ........... .. .. . .... 36 ( 1 ),68 Bi oc h em i ca l a nd Bi o l ogica l Engineering Co u rses, The R esearc h Propo sa l in ... .. ...... ......................... ... ..... .. 40 ( 4 ),323 Bio c hemi ca l Engineering Taught in the Context of Drug Discovery to Manufacturing ... ............. ............ 39 (3),208 Bi od ie se l Producti o n Us in g Acid-Catalyzed Transesterification of Yellow Grease Pl a nt Design Project: .... .... ......................... ........ ................ 40 (3 ),2 15 Bi o int erfac ial Engineering Multidisciplinary G rad uat e C urri c ulum o n Integrative ....... .... .. ........ .. ............ 40 ( 4) ,2 51 Biological Systems in the Process D y n am i cs a nd Co nt ro l Curriculum Int egra tin g ............. .. . .. .. ...... 40 (3), 1 8 1 Biology a nd C h E at the Lower Levels Int egra tin g ....... .. 38 (2),108 Biomass as a Sustainable E n ergy Source: An Illu stration of ChE Th e rm o d y n am i c Concepts .... .. ....... .. .. ... ..... 40 (4),259 Biomedi ca l and Bi oc h em i cal Engineering for K-1 2 Students ................. ... .. . ..... .. ... ...... ... .. .... .......... 40 (4),283 Biomolecular Modeling in a P rocess Dynamics a nd Control Course .. ... .. .. .. .. .. ......... ...... ................... 40 (4),297 Bioprocess Engineering, A Co u rse In: Engaging the Im ag in a ti o n of Students Using Experie n ces Outside th e Classroom ................................. .... ... ... .. .... . .... 37 (3), 180 Bi oreactor Mass Tra n sfe r a nd Ce ll Growth Kinetics in a .. .. .. .... ....... .. .... .. .... ... .... ... ................... ... .. .... 36 (3),2 1 6 Bl ock -S c h e dul ed C urriculum Pillars of Chemical E n g in eeri n g, A .............. .. .. ...... ......................... .. .. ... 38 (4),292 Brin eW a t er Mixing Tank Ex p erime nt Teaching Semiphysical Modeling to ChE Students Us in g a ...... 39 (4),308 Building Molecular Biology Laboratory Skills in C h E Students ..... ............................ .. .. ... ................. ... 39 (2), 1 34 Buildin g Multivariable Proces s Contro l Intuiti o n Us in g Contro l Stat i o n .... ....... .......... .. ... .... ... ........... 37 (2), 100 .c Carbon Cycle Earth's: C h e mi ca l Engineering Co urs e Material ...... .. . ..... ... .. .... ........ ......................... .... 36 (4),296 Career Factors Influ e ncin g th e Selection of Chemical E n g in eer in g as a .. ........ ....... ...................................... 37 (4),268 Cars Accelerate Learning Fast: High-Performance E n gi n es .. .. ............... .. ..... .. .... .... ................ ... .. ...... 37 (3),208 Catalytic Re ac t or, Expe rim e nt s wi th a F i xed-Bed ............. 36 ( 1),34 Cell Growth Kinetic s in a Bioreactor Mass Transfer a nd .. .. .............. .... .. .. .. .... .. .. .. .... ..................... ... 36 (3),2 1 6 C h e mi ca l Enginee r ing Education

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Ce llular Bi o l ogy into a ChE D eg r ee Pro gra m Incorpo ra tin g Molecular a nd .... .... .. .... .. ... .......... 39 (2), 124 CF D Tool s, Teaching Nonideal R eactors w ith .. .. ....... .. .... 38 (2) 1 54 C hE Principl es, A R esp irati o n Exper im e nt to Int rod u ce. 38 (3) 1 82 C hem-E-Car Competition En g in eer in g A n a l ys i s in th e .... 40 ( 1 ),66 C h e m-E-Car D ow n U nder ............................................ 36 (4),288 Chemical P rod u c t E n g ineerin g, A Graduate-Leve lEq ui va l e nt Curric ulum in .. .. ....................... .. .. .. .... 39 (4),264 C h e mi ca l R eact i on En g in eer in g L a b Experiment An Int egra t ed ... .... .... ... .. ........................................ 38 (3),228 Chemical Th er mod y n a mi c Conc e pt s to Re al-Wor ld Probl e m s, R elat in g Abstra c t ................................... .. 38 (4),268 Chemistry int o the ChE Curriculum In corporat in g Computational .. ..... .. ...... .. ... ............... .. ... .. .. ... . 40 ( 4 ),268 Classroom Demon s tration of Natural Co nv ec tion A Simpl e .......... .. ..... ...... ............. .... ....................... 39 (2), 1 38 Choosing and Evaluating Equation s of State for Therm op h ys i cal Propertie s ... .... .. ..... .. .. ..... .. 37 (3),236 Coffee on D emand: A T wo -H our D es i g n Probl e m .. .. .. .. 36 ( 1 ) 54 Coherence in Technical Writin g Imp roving .. .... .. .. ... .. 38 (2) 11 6 Collaborative L e arning and C y ber-Cooperation in Multidi sc iplin a r y Projects ............... ............... ........ 37 (2), 114 Combining M o d e rn Learning P edagogies in Fluid M ec h a ni cs and H eat Tran sfer .... ........... .. ... .... .... 39 ( 4 ) 280 Combustion Prin c ipl es for En g in ee ring Fre s hm an, The Pot a t o Cannon: D etermination of.. ............... ... 39 (2) 15 6 Commercial Simulator to Te ac h S or ption Separation s, Us in g A .. ... . .. .... ........ .. .. ..... .. .. ... ...... .... ... .. 40 (3), 165 Co mmon Plumbin g a nd Control Errors in Pl a ntwid e Flow Sheet s .. .. .. .. .... .. ..... .... .. .. ... . 39 (3) 202 Comm unit y -B ase d Pre se nt ations in the U nit Op s L a borat o r y . .. .... .... .. .. .. .... .. .. .. .. ... .... . .. . .. 39 (2), 160 Communication Skills in Engineerin g Students A n Innovati ve Method For D eve l op in g .. ... ....... ... .... 38 ( 4 ),3 02 Co mpa c t H ea t Exchangers A Pro ject to D es i g n a nd Build .......... ........ .... .... .. ... .. .. ... .................. 39 ( I ),38 C o mpendium of Open-Ended Membrane Probl e m s in th e Curriculum A .... .. ... .. .. .. . . .... .. ... .. 37 ( I ), 46 Co mpr ess ibl e Flow A n alysis Di sc h arg in g V esse l s .. .. .. .. 38 (3), 190 Co mput a ti o n in th e Analysis of Separation Pro cesses Using Visualization and .. .. . ...... ........................... 40 (4),3 1 3 Computational Fluid D y n a mi cs In corporati n g Nonid ea l R eac tor s in a Junior-Le ve l Cour se .. .. .. ..... .... ... 38 (2) 136 Computer Evaluation of Exchan ge F ac tors in Thermal Radiation ....................... .... ................... 38 ( 2 ) 126 Computer-Facilitated Mathem a ti ca l Method s in C h E Similarity Solution ... .. .................. .. ..... .. .... . 40 (4),307 Co mputer Pro gra mmin g t o T eac h N um erical Method s Incre as in g Time Spent o n Cour se Objectiv es b y Us in g .. . .. . .. .... .. .. .. .. .. ..... .. .... ... .. ... .. . 37 (3),2 1 4 Computer Science or Spreadsheet En g in ee rin g: A n Excel/VBA-Based Pro gra mmin g a nd P rob l emSol v in g Cour se .. ........ ....... ... .... .... ..................... 39 (2), 14 2 Computing Experience Enhancing the U nd ergrad uat e ... 40 (3),23 1 ConcepTests a nd In s tant Feedback in Thermod y n am i cs, Use of .. ... ........ .... .. .. .. .. .. . .. . ..... .. .. .. .. . 38 ( 1 ),64 Conceptual Under s tanding in Ch e mical En g ineering .... .... 36 ( l ),42 Condensation Solvent R ecovery b y: A n Appli ca ti o n of Phas e Equilibrium a nd Sen s iti v it y Ana l ys i s .. .. .... 38 (3),2 1 6 Conduc tin g th e En g in ee r 's Approach t o Probl em Solving Fa/12006 Di s c ussion of the M e th od: .. .... ... .. .... ... .. .......... 38 (3),2 03 Consequen ce a nd Vulnerabi lit y Analysis Boiling-Liquid Expandin g-Va por Explo s i o n ( BLEVE ) ... ... .... .. .. .. 36 (3) 206 Constru c tion a nd V i s u a li zatio n of VLE Envelopes in M a th ca d .... ..... .. ... ... ... . .... ... .... ... .... ..... .. .. ... ....... .. .. 37 ( 1 ),20 Con s ultin g, The Vagaries of. .............. .. ...................... 36 ( l ),74 Control Station Buil d in g Multi va ri a ble Pro cess Control Intuiti o n Usi n g ... .. .. ... .. . . ... .... ......... ............. 37 (2), 10 0 Cooking P o t a t oes: Experimentation and M a th ema ti cal Mod e lin g ............... .... . .. .. ... .. .... ............... .......... 36 ( I ),26 Cooperativ e Work That Get s Sophomores o n Board ..... 39 (2), 12 8 Copper R otat in g-Disc E l ec t rode, R ed u c ti o n of Di sso lv e d Ox yge n a t a ...... .... .... ....... .. ... ................. 39 ( 1 ), 14 Coupled Tran s port and R a t e Proce sses, Teachin g ........... 38 (4),254 Cour se -L eve l Strateg y for Co ntinuou s Improv e m e nt A 39 (3), 1 86 Cour se Proj ect, Partnering With Indu s tr y for a Meanin g ful .............. .. ... .... .. . .. .. .. .. .. .. . ...... 40 ( 1 ),32 Cross-Discip lin ary Proj ec t s in a ChE U nd ergrad u ate Curriculum, De ve l o pm e nt of... ... .. .... .. .. .. .... .. .. .. .. 38 ( 4 ),296 Curricu lum : Su it a bl e Course Content a nd Teaching M e thodology Aspe n Plu s in th e ChE ............ .... .... .... 39 ( 1 ),68 Cyber-Cooperation in Multidi sc iplin ary Proj ects, Collaborative Learnin g a nd ...... .... ... .. ...... ..... ...... .... 37 (2), 114 Class and Home Problem s D A Simpl e Op e n-End ed Vapor Diffu s ion Exper im e nt.. 38 (2), 1 22 An Op e n-Ended Ma ss B a l a nce Problem . . .. ......... 39 ( I ),22 B o ilin g -Liquid Expandin g-Va por Explo s ion ( BLEVE ) A n Introdu cto n to Co n se quen ce a nd Vu ln erab ilit y A n alys i s ............ .. .. .. .... .. .. .. .. ...... 36 (3),2 06 Computer-Faci lit a ted M a thematic a l M e thod s in ChE Simil ar it y Soluti o n . .. .. .. ... .. .... .. ..... .. .... .. 40 (4),309 Cooperative Work That G e t s Sophomore s o n Board .. 39 (2), I 28 D ata An a l ys i s Mad e Ea sy With DataFit ........ .... ....... ... 40(1 ),60 Fuel P rocesso r System for Generating H y dro ge n for Au t o m o ti ve Applications .. .. ................. ......... .. 40 ( 3 ),239 G as P e rm ea ti o n Comput a tion s wit h M a thematica ..... 40 (2), 1 40 Gr ee nin g a D es ign-Ori e nt ed Heat Tran sfe r Co ur se. 39 (3),2 16 In co rp ora tin g Green En g in ee ring into a M a t er i a l a n d E n e r gy B a l a n ce Co ur se .. .... ..... .. ..... .... ......... 38 ( 1 ),48 Sc a l ed Sk e t ches for Vi s u a li z in g Surface Ten s i o n ....... 39 (4),328 Solvent R ecovery by Condensation: An App lic at ion of Pha se Eq uilibrium and Sensitivity Analy s i s .. ..... .. 38 (3),2 16 Th e Sherr y Solera: A n App li catio n of P art ial Differ e nce Eq u a ti o n s .. .. ................... .. ... .. .... .. .. 36( 1 ),48 D a ta Ana l ys i s M a de Easy With D a tafit... .. .. .... . .......... 40 (1),60 De c i s i o n Ana l ys i s for Eq uipm e nt Selection .... ... .... .. 39 (2) I 00 Demon st r a ti o n a nd Assessme nt of a Simpl e Vi scos ity Experim e nt for Hi g h School Science Cla sses ........ .. .. 40 (3),2 11 De s i gn Experience : Multidi sc iplinary D es i gn of a P otable Water Treatment Plant A Freshman .... ..... ... 39 ( 4 ), 296 D esign in Chemica l En g in eeri n g at Ro seHulman In s titut e of T ech n o l ogy Freshman .. .. .. ..... .... .. 38 (3),222 D es i g n of a Fuel Pro cessor Sy s tem for Generatin g H ydroge n for A ut omotive App li ca ti o n s .. ........ ......... 40 (3),2 39 De s i g n Pr o bl e m A T woH o ur : Coffee on Demand .. .. .. 36 ( 1 ), 54 De s i g n P rojec t : Biodie se l Production Us in g AcidCatalyzed Transe s terifi ca ti o n of Yellow Gr ease 329

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Plant .. .................. .. ... ... .......................... ........... .... 40 (3),2 15 De s i g n Proje c t Curricula An Int e rnational Comparison of Final-Year .. ................. .... .... .. ..................... .... .. 40 ( 4 ),27 5 De s i g n Proje c ts of th e Futur e ...................................... .. .... 40 (2),88 De s ign Proj ec t s, Web-Ba se d D e liv e r y of ChE ..... .. ... .... 39 (3), 194 De s i g n Throu g h the Inve s tig a tion of Commercial Be e r T eac hin g Produ c t ... .......... ...... .... .... ..... ......... 36 (2), 108 Determinin g Self-Similarity Transi e nt Heat Tran s fer with Constant Flux, A Method for ...... ... .. ..... .. ... ... ... ... 39 ( 1 ),42 Determinin g the Flow Characteristics o f a Power Law Liquid .. ... ...... .... ... .. ..... .. .............. .. ... .. .. .......... 36 (4),3 04 D eve lopin g M e t acog niti ve Engineering T ea m s .... .... ...... 38 (4),3 16 Developm e nt a nd Implementation of a n Educational Simulator : Gluco s im .................. ............ .. ...... ...... .. 37 (4),30 0 Developm e nt of Cross-Disciplinary Projects In a ChE Undergraduate Curriculum .............. .......... ........ 38 ( 4 ),296 Differenti a l Equations, Scaling of: Analysis of the Fourth Kind ," .. .. .. ...... ........ .. ... .. ... .. .. ................. .. ...... 36( 3),232 Diffu s ion Experiments, Inexpen s ive and Simple Binary Molecular ... ...... .. ...... ... .. .. .... ... .. ... ................ .. 36(1 ),6 8 Diffusivitie s in the Classroom, Using Molecular-Lev e l Simul a tions to Determin e ...... .. .... ... ................. .. .. ... 37 (2), 156 Dis c hargin g Ves se l s, Compressible Flow Analysis . .... 38 (3), 1 9 0 Di sc ussion of the M et hod: Conducting the Engineer's Approach to Pr ob l em Solving ................... 38 (3),203 Di sso lv ed Ox yge n a t a Copper Rot a tin g -Di sc Electrode, Redu ctio n of ...... .... .... .......... ... ... ... ........ 39(1 ), 14 Di s till a tion Case Study Using Mathem a ti ca to Teach Proce ss Units, A .... .... ................ ... ... .. ... ... .................. 39(2 ), 116 Divi s ion Program Chemical Engineering ....................... 36 (2), I 28 Departmental Articles California Berkel ey, University of ...... .. ....... ............... 37 (3), 16 2 Columbia University ....................................... .. .. ... ...... 40 ( I ),8 Illinoi s Institute of Te c hnolo gy .... .. .. ... .. .. .... .. .. .... ... 39 ( 1 ),2 Kansa s State University .. ... .. .. ..... .. .. .. ... ..... ......... .... 36(1 ),2 Mar y l a nd Baltimore County U niver s it y of .................. 37 (2),82 Oklah o ma University of .. .... .. ..... .. ............ ....... 38 (3), 16 2 Ri ce University .... .... .. ....... .. ... ..... .. .. .. .. .. ................. 38 (2),88 Rowan University .. ... .. ..... .. ..... .. .. .. .. .. .. .. ..... .. ........ 39 (2),82 Sh e rbrook e, U niv e rsity of ... .. .... .. .... .. .. .... ....... ...... 40 (3), 146 Tulane University ..... ........ .. .. .. .. .. .... ... ... 36 (2),88; 40 (2),80 Vanderbilt University .... .. .. ........ .. .. .... ....... .. ............... .. 37 ( I ),2 Wa s hin g ton University ... .. ......................... ... . ........ 39 (3), 1 70 Doct ora l Student 's Per s pective Te ac hin g a nd M e ntorin g Trainin g Pro gra m s at Michi ga n State University: A .... ......................................... ... ............. 38 ( 4 ),25 0 Drawin g the Connections Betw ee n Engineering Science and Engineering Practi ce ............................... 39(2 ), I 10 Drug Deliver y for Chemical En g in eers, An Introduction to .. .. ............. .. ......... ............................... 36 (3), 198 Dru g Di scovery to Manufa c turin g, Bi oc h e mi ca l Engineering Tau g ht in the Context of ....... ....... .. .. ... 39 (3),2 08 Durbin-W a t so n Statistics to Time-Seri esBased R egress ion Mod e l s, On the Application of .. ......... ... ..... 38 ( 1 ),22 Du st Explosion Apparatus Suitable for Use in Le c ture D e mon s tration s, A .................... ... .. ......... .... ........... ... 38( 3 ), 188 Dynami c Simulation to Converge Complex Proce ss Flow Sheets, Use of ... .................................... 38 (2), 142 330 E Earth's Carbon Cycle C h em i ca l E n g ine e rin g Course Material The ....... ........................................ .. ............. 36( 4 ),296 Economic Ri sk A n a l ys i s: Usi n g Analy ti ca l a nd Monte Carlo Techniques ......... ....... ......................................... 36 (2),94 Economics a n d Business Stra t eg i es, A Lesson in Engineering: G as Station Pricing Game .......... .......... 36 (4),278 Educator Articles Davi s, Rob e rt H .; U niv ers ity of Co l orado .................. 37 (2),88 Doh e rt y, Mike; UC Santa Barbara ...... ... ....... ........ 38 (3) l 68 D ora i swa m y, L.K. ; Iowa Sta t e Un i ve r si t y ... .............. 36 (3), 1 78 Eckert, C hu ck; Georgia In stit ut e of Technology ............ 38 ( I ),2 Gast, Alice; Massachusetts In sti tut e of Technology .... 39 (2),88 Hesk e th Robert ; R owa n U ni ve r si t y .... ..... .... .... ...... ... 37 ( 1 ),8 Kin g, C. Jud so n ; UC Berkeley ............ .... .. ......... .... 39 (3), 17 8 L e Bl a n c, Steve ; University of Toledo .. ..... .. . .... ... 36 (2),82 Mont go mery Susan; U ni vers it y of Michi ga n .. ..... 40 (3), 154 Rhin e hart R. Ru sse ll ; Oklahoma State U ni versity .. ... 39 ( 1 ),8 S e ider Warren ; U ni vers it y of Pennsylvania .. .... ... .... 36 ( I ),8 Shuler, Michael L.; Cornell U ni ve r s it y ... .... .... ... .... 38 (2),82 Schulz, Kirk; Mi ssiss ippi State U niv ers it y .. .... ... .... .. 40 ( 1 ),2 Stuve Eric M .; U ni ve r si t y of Washington ... .. .. .. .. .... 40 (2),74 Electrochemical Method Metal Recovery from Wastewater with an ..................................................... 36 (2), 144 Electrodialysis Exploring the Potential of ........................ 37 ( I ),52 Electrolyte Th er m ody n a mic s, Teaching .... .. ....... ............. 38 ( I ),26 Energy Balances o n th e Human Body: A H a nd s -On Exploration of Heat Work a nd Power.. ............ ... .. ..... 39 ( I ),30 Energy Co n s umpti on vs. E n ergy Requirement ..... .... .. .... 40 (2), 1 32 Energy Source: An Illu strat ion of C h E Thermodynamic Co nc e pt s, Biomass as a Sustainable .. .... .................. ... 40 (4),259 E nh a n c in g the Undergrad u ate Comp utin g Ex p er i e n ce ... 40 (3),23 1 Engineering Analysis in the C h em E Car Competition ..... 40 ( I ),66 Engineering Science a nd Eng ine eri n g P rac ti ce, Drawing the Co nn ect ion s Between .. .. ... . .. ... . .. .... .. .. .. ... 39 (2), 110 Engines Hi g h-P erformance: Fast Cars Acce lerat e L ea rnin g .. .. .. ... ..... .. .... ..... .. ...... ... .. .... . .. ..... 37 (3),208 Environmental Engineers Throu g h Development of a New Course Introdu c in g Molecular Biolo gy t o ........ 36 (4),258 Environmental Imp ac t Assessme nt: Teaching the Principles and Practices b y Means of a Role-Playing Case Study .. . .. .. .. .... ... .. ..... .. .. ..... ... ... ... .... ... .. 39 ( I ), 76 E qu a tion s (of C h a n ge) D on't Change, But the Profession of E n g in eer in g D oes ..... ....... ... .. .... ... .. .. 37 (4),242 Equations of Stat e a t the Graduate Level Molecular-Based .. .. ................... ....... ................. ......... 39 (4),250 Equations of St a t e for Th er m o ph ys i ca l Properties Choosing and Eva luatin g ... .. .. ... ... .. ..... .. .... .... ...... ... 37 (3),236 Equilibrium St age Model for an Azeotropic Systems in an L aboratoria l Distillation Column, Validating the ........................ .............. ... .... ............... .... .. .... .. .... 40 (3), 1 95 Eq uipm e nt Se l ectio n Decision A n a l ys i s for ....... ..... ... 39 (2),100 Evolutionary Operation Method to Optimize Gas Absorber Operation Usi n g the: A Stati s tical Method for Pro cess Imp roveme nt .. ... ....... .. ............. .. 38 (3),204 Examining Value a nd B e h av i ors in Organizations: Aspects of Engineering P rac ti ce ... ...................... ...... 36 ( 4 ),3 1 6 Excel/VBAB ased P rogra mmin g and Probl em Solving Chemical Engineering Education

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Co u rse, Co mput e r S c i e n ce or S pr eads h eet E n g in ee rin g: A n ............. ... ..... .. ............... ........ .. ....... 39 (2), 1 42 Exce pti o n s t o th e L e C h a t e li e r Prin ci pl e ........ .... ... .... 37 (4),290 E xc it e m e nt a n d Int e r es t in M ec h a n ica l P a r ts, Pr ess u re fo r Fun : A Co ur se M o dul e fo r In c r eas in g C h E Stud e nt s' .. .. .. .. .. .. .... ........ ......... .. .. .. . .. .. .. .. .... 40 ( 4) 29 1 E xe r c i se fo r P rac ti c in g P rogra mmin g in th e C h E C urri c ulum C a l c ul a ti o n of Th er m ody n a mi c P ro p e rti es Us in g th e R e dli c h-K wo n g Eq u at i o n of St a t e ... .. .. .. .... .... ... .... .... ........ .... .. .. .. .. .. .. ... ... 37 (2), 1 48 Ex p e rim e nt A g it a ti o n a nd A era t io n a n Aut o m a t e d Did ac ti c .... .... ... . .. .... .. .. .. .... ... .. 38 (2), 100 Ex p e rim e nt A N o nlin ear, Multi Inpu t, Multi Output Pro c e ss Co nt ro l L a b ora t o r y .................................. ....... 40 ( I )5 4 Ex p e rim e nt A Quadrupl eT a nk P rocess Co n tro l .. .... .. .. 38 (3), 1 7 4 Ex p e rim e nt A Simpl e Open-End e d Va p o r Di ff u s i o n ... .. 38 (2) ,1 22 Ex p e rim e nt fo r Tran s p o rt Ph e n o m e n a, A n Easy H e at and Ma ss T ra n s f er .. ............. .................. 36 ( I ), 5 6 Ex p e rim e nt w ith Multipl e A s p ec t s A n Ag it a ti o n ..... .. 40 (3) ,15 9 Ex p e rim e nt a l A ir Pr ess ur e T a n k S ys t e m s fo r P rocess C o ntr o l E du ca ti o n .... ... ... ... ... .. .. .. .. .... .. .. ..... .. 40 ( I ),24 Ex p e rim e nt a l D es i g n P e r so n a li ze d Int erac t ive T ake -H o m e Exa min a ti o n s fo r St u de nt s St u dy in g ..... 37 (2). I 36 Ex p e rim e n ta l D es i g n int o th e U n i t Opera t io n s L a b ora t o r y, In corpora tin g ......... ... ... ... .. .... .. .. ... .. 37 (3), 1 96 E x p e rim e nt a l In ves ti ga ti o n a nd P rocess D es i g n in a S e ni o r L a b ora t o r y Ex p e rim e nt ................. ................ 40 (3) 225 Ex p e rim e ntal Proj e ct s for th e Pro cess Co nt ro l L a b ora t o r y ...... .... ... .. .... .. .. .. .. .. .. .. .. .. .. .. .... 36 (3) 1 82 Ex p e rim e nt a ti o n a nd M a th e m a ti ca l M o d e lin g: Coo kin g P o t a t oes .... .. .. .. .... ... .. . .. .. .. .. .. .. ... .... 36 ( I ),56 Ex p e rim e nt s Across th e A tl a nti c P erfo rmin g Pr ocess Co nt ro l .... .. .. .... ... .... . .. .... ..................................... 39 (3).232 Ex p e rim e nt s, In ex p e n s i ve a nd S imple Bin ary M o l ec ul ar Di ff u s i o n .............. . ... .. .. .. .. .. .. .. . .... 36 ( I ) 68 Expe rim e nt s a n d Oth e r L eam in g Ac t ivit i es Us in g Na tu ra l D ye M a t e ri a l s ......... .. .... .. ... ............. 38 (2), 132 E x p e rim e nt s w ith a F i xe d-B e d Ca t a l y ti c R eacto r. ............. 36 ( 1 ),34 E x pli c it M o d e l s, S e n s iti v it y A n a l ys i s in C h E E du ca ti o n: P a rt I. Introdu c ti o n a nd Appli ca ti o n t o .. ............. ..... 37 (3),222 E F ac t o r s Influ e n c in g th e S e l ec ti o n of C h e mi ca l E n g in ee rin g as a Ca r ee r. .... .. .. .. .. .. . .. . .. ..... 37 (4),268 F ir s t-S e m es t e r Co ur se F oc u s in g o n Co nn ectio n Co mmuni ca ti o n a nd P re p ara t io n A S u ccessfu l Introdu c ti o n to Ch E .. .. ....... .. ........ .... .. .... .. 39 (3),222 F i xe d B e d Ca t a l y ti c R ea ct o r Ex p e rim e nt s w i t h a ... .. ..... 36 ( I ),3 4 Fl ex ibl e Pil o t-S ca l e S e tup fo r R ea l-Tim e Studi es in Pro cess Sy s tem s E n g in ee rin g A .............................. .... 40 ( 1 ),4 0 Flow Chara c t e ri s ti cs of a Pow e r La w Liquid D e t e rminin g the .... ..... .. .... .... ... ................ .... ...... 36 ( 4) 30 4 Fluid M ec h a ni cs, W a t e r D ay : A n Ex p e ri e n t i a l Lec tur e for ... .. .. ..... .. .... ............. .. .. ..... .... .... ... 37 (3) 1 70 Fluid-Mi x in g L a b ora t o r y fo r C hE U n de r grad u a t es .. .. .. 37 (4) 296 Fluidi ze d B e d A d so rpt io n L a b orato r y Ex p erime n t... .. ... 38 ( I ), 1 4 F luidi ze d B e d P o l y m e r Coa tin g Ex p e rim e nt ... .. ... ... .. 36 (2), 1 38 Fo r th e S a k e of Ar g um e nt : If th e Co n ve nti o n a l L ec tur e I s D ea d Wh y i s it Ali ve a nd Thri v in g .. ..... ... .. ... .. .. .. 40 (2) Fr ee C o nv ec ti o n A Computation a l M o d e l for T eac hin g. 38 ( 4 ),272 F a ll 2006 Fr e n c h FrySh a p e d P o t a t oes, Op t imum Cooki n g o f : A C l assroo m Stud y of H eat a n d M ass T ra n sfer .. .. ..... 37 (2), 1 42 F r es hm a n D es i g n Ex p e ri e n ce : Multidi sc iplin a r y D es i g n of a P o t a bl e W a t e r Tr ea tm e nt Pl a nt A .. .. .. 39 ( 4 ), 2 96 F r es hm a n D es i g n in C h e mi c al E n g in ee rin g a t R os eHulm a n In s titut e of T ec hn o l ogy ... ............. .. .. .. . 38 ( 3 ),222 F r o nti e r s of C h e mi ca l E n g in ee rin g : a Ch e mi ca l E n g in ee rin g Fr es hm a n S e min a r. .... .... .... ... .... .. .. .. 37 ( l ),2 4 FTIR Sp ec t rosco p y: A n Ex p e rim e nt fo r th e U n de r gra du a t e L a b ora t ory K i n e ti cs of H y d ro l ys i s of Acet i c A nh y dr i d e b y In-Situ .... .. . .. .. ... .... .... ..... 39 ( 1 ), 5 6 F u el P rocessor S ys t e m for Ge n era tin g H y d roge n fo r A ut omo ti ve A ppli ca ti o n s D es i g n of a ... ... .... ........ 40 (3),239 F u e l Ce ll : A n Id ea l C h E U n de r gra du a t e E x p e rim e nt. ...... 38 ( I ),38 Futur e Dir ec ti o n s in Ch E Ed u ca ti o n: A New P a th to G l o r y .. ....... .. ....... ..... .................. .... ........ .. .... .. 37 ( 4 ), 2 8 4 G G as P e rm ea ti o n Co mput a ti o n s with M a th e m a tic a ... .. .... 40 ( 2 ), 140 G as Se p ara ti o n Memb ra n e Ex p e rim e nt s, A Simpl e A n a l ys i s fo r. ... . .. .. ... .. .. . .. .... .. .... .. .. .. ... ... .. .. 37 ( 1 ), 74 Gas Se p arat i o n Us in g P o l y m ers, T oo l s fo r T eac hin g .. ... 37 ( I ), 60 Gas Statio n P ri c in g G a m e : A L esso n in E n g in ee rin g Eco n o mi cs a n d Bu s in ess S t ra t eg i es .... .... .. ... .. .... 36 ( 4 ),278 Gasifica ti on S e ni o r D es i g n P rojec t T h at Int egra t es L a b oratory E x p er im e nt s a n d Co mput e r Simul at i o n A Tir e .................... .... .... . .. .. .. .. .. ... .. . .... . ... 40 (3), 20 3 G e n e S ub c l o nin g fo r Ch e mi ca l E n g in ee rin g Stud e nt s, L a b ora t o r y E x p e rim e nt 0 11 ................ .... .. ............... ... 38 (3),2 1 2 Gibb s E n e r gy Co n s i dera ti o n s R e d uce t h e R o l e o f R ac h fo r d -Ri ce A n alys i s, Co mputin g Ph ase E quilibri a: 36 ( 1 ),76 G i ll esp i e A l go ri th m a nd MA T LA B In trod u c in g th e Stoc h ast i c Si m ul a ti o n of Che mi ca l R eac ti o n s Us in g t h e .. .... .. .. .. ............. .. ... .... .. .... .. .... .... .. .. 37 ( 1 ), 1 4 Gl u cos i m: D eve l o pm e nt a n d I m pl e m e nt a ti o n of a n Ed u ca ti o n a l Simul a t o r ... .... .... ..... .. .. .. .. .. .. . .. .. 37 ( 4 ), 300 Gra du a t e Co ur se o n Multi -Sca l e M o d e lin g of S of t M a tt e r A .. . ...... ... .. ........................... .. ... 38 ( 4 ),2 4 2 G ra du a t e Co ur s e s, R e fl ec ti o n s o n Proj ec t-B a s e d L ea rn i n g in .... ... .. ...... ... .. .... ........ .... .. .. .. .. .. 38 ( 4 ),2 6 2 Gra du a t e C urri c ulum o n Int egra ti ve Bi o int e r fac i a l E n g in ee r i n g Mul t idi sci plin ary .. .......... ..... ... .... . .. 40 (4),2 51 Grad u a t e E du ca ti o n: A ovel A p p r oac h fo r D esc ribin g Micromix i ng Effec t s in H omoge n eo u s R eac t o r s ........ 36 (4 ) 2 50 Grad u a t e Ed u ca ti o n: I n t rod u c in g M o l ec ul a r Bi o l ogy to Env i ro nm e n ta l En g in ee r s Th ro u g h D eve l o pm e nt of a New Co ur se .. ... .. ... ... ... .. ... ... .. 36 ( 4 ), 25 8 Gra du a t e -L eve l C o u rse in Ti ss u e En g in ee rin g, T eac hin g A ................. ..... .. .. .... ... .. .. ... ... .. .... 39 ( 4 ), 272 Gradu a t e -L e vel-Equiv a l e nt Curri c ulum in Ch e mi ca l P ro du c t E n g in ee rin g, A ..... .. .. . .. ... .. .. ..... .... .. ... 39 ( 4 ),2 64 G ra du a t e L eve l M o l ec ul a r B ase d E qu a ti o n s of St a te a t th e ...... .... .. ..... ......................................... ... .. .. ... 39 ( 4 ),2 50 G r a du ate P rogra m s P rod u c t iv i ty a nd Qu a lit y In d i ca tor s fo r Hi g h ly R a n ked C h E .. .. ..... .. ... .... .. ........ .... .. 37 (2),94 Grad u ate S t u de nt s th e R o l e of J o urn a l A rti c l es in R esea r c h T eac hin g E nt e r i n g .. .... ... ......... ........ .... .. 40 (4),2 4 6 G ra du a t e Th e rmod y n a mi cs C o ur se in C h e mi ca l E n g in ee rin g D e p a rtm e nt s A c ro ss th e U nited State s A Sur vey of th e .. .... .. ...... ..... ... .. .. .. .... ... ......... 39 ( 4 ),2 5 8 33 1

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" Gree nin g" a Design-Oriented Heat Tran sfer Co ur se .... 39 (3),2 16 G r ee n E n gi n ee rin g into a Desi g n-Oriented H ea t Tran sfe r Course, Assessin g th e In co rporation of ... ... 39 (4) ,3 20 Green Eng in eering into a Material and Energy Bal a nce Course In corporat in g .... .. .. ..... ..... .. .. .. .. ...... ..... ........ 38 (1) 48 Group Learnjng, Introdu ctio n to Synthe s i s, Re s ourcefulnes s, and Effectiv e Communication in Biochemical Engi n eering ......... .. .. .. ........ ................ 37 (3) 174 Gro up Work T e aching Engineering in a Modern Cla ssroo m Setting : Miling Room for .......... .. .... .. .. .. 39 (2), I 64 H Hand sOn Laboratory in the Fundament a l s of Serruconductor Manufacturin g, A .... ..... ....... .. ..... .. ...... .. 36(1 ), 14 Heat Transfer Visualization Tools Java Ba se d ................ 38 ( 4) ,2 82 Heat a nd Mass Tran s fer Experiment for Transport Phenomena An Easy ........ .............. .. .. ...... ................... 36( l ) 56 Heat a nd Mass Transfer Optimum Cooking of French Fry-Shaped Potatoe s: A Classroom Study of ................................. 37 (2), 142 Heat Tran sfer Analysis a nd the Path Forward in a Student Project o n the Splend a Sucralo se Pro cess ..... 39 (4),3 1 6 Heat Tran sfe r Course, As sess in g the In co rporation of Gr ee n Engineering into a De s i g n Oriented ............. ... 39 ( 4 ),320 Heat Tran sfe r Cour se, Greenin g" a De s i g n-Oriented .... 39 (3),216 Heat Tran sfe r Problems Spre a d s h ee t Solution s to Two-Dimensional .. ... .. ..... .. .... .... .. .... .... ..... ......... 36 (2) 160 Heat Work and Power ; Energy Bal a nce s on the Human Body: A Hands-On Exploration of .................... .... ...... 39 ( I ),30 High School Science Classes Demonstration a nd As sess m e nt of a Simpl e Viscosity Experime nt for .... 40 (3) 211 High-Performance Engine s: Fast Car s A cce lerat e Le a rnjn g .... .. ... .... ...... ............... ........ .. ... .. .......... ... 37 (3),208 High-Performance Learning Environment s ................. .... 38 ( 4) ,286 High School Outreach into ChE Co ur ses, Incorporating. 37 (3), 1 84 Holistic Unit Operations Laboratory A .................... ..... .. 36 (2), I 50 Homo ge neou s Reactors A Novel Approach for D esc ribin g Micromixing Effect s in .......... .. .. .. ........ .. .. 36 (4),250 Hydrogen for Automotive Application s, De s ign of a Fuel Processor System for Generatin g ...... ......... ........ 40 (3),239 Hydroly s i s of Acetic Anhydride by In-Situ FTIR Spectro sco py : An Experiment for th e Under g raduate Laboratory Kinetic s of .. .. .... ............. .. 39(1 ) 56 Hyper-TVT: Development and Implementation of an Int eractive Learning Environment. ............................. 40 (3),175 I Improving Coh e rence in Technical Writin g .......... .. .......... 38 (2) 116 Impro v in g Thought with Hand s", On .. .. ......... .... ........ .. 36 (4) 292 ln corporating Computational C h emistry into the ChE Curriculum .................................... .............. ... ......... 40 (4),268 In co rp orat in g Experimental Design int o the U nit Operations Laboratory ............................................... 37 (3), 1 96 In corporat in g Green Engineerin g into a Material and Ener gy Bal a nce Course ........... ..... ......... ........ .... ... ..... 38 ( 1 ),48 In co rporatin g High School Outr eac h into ChE Courses .. 37 (3), 1 84 In co rporatin g Molecular and Cellular Biolo gy into a ChE De g ree Program ......................... .. ................. ... 39 (2), 124 In co rporatin g Nonide a l Rea c tor s in a Junior Level Course Using Computational Fluid Dynamk s .. .. .... .. 38 (2), 1 36 Indu s tri a l Training in Chemical En g ineerin g Ed u cat ion 332 The Rol e of ...... ............................ .......... ....... .. ..... .. ..... 40 (3), 1 89 Indu s tr y for a Meanin gfu l Course Project, Partn er in g With ... .. ...................................... .. .... .... .... .......... 40 ( I ),32 Innovative Can W e Teach Our Students to be .. .. ... .. .. ..... 36 (2), l I 6 Inn ova tiv e Method for Developin g Comm uni cat ion Skills in E n gineering Student s, An ............................. 38(4 ),3 02 In s tant Mess ag ing : Expand in g Your Offi ce Hour s ... .. ..... 39 (3), l 83 Integratin g Biologi ca l S ys tem s in the Pro cess D y narru cs a nd Control Curriculum ........ .... ................. 40(3 ), 1 8 1 Inte gra tin g Biolog y a nd ChE a t the L owe r L eve ls .......... 38 (2), 10 8 Int egra t e d Chemkal Re ac ti o n Engineering Lab Experime nt An ............. .. .... .. .. .... .. ..... .... .... ..... .. 38 (3) 228 Int egra tin g Kjnetic s Characterization a nd M a terial s Proce ss ing in the Lab Experience .............................. 36 (3),226 Integration Technique to Trace Pha se Equilibri a Curve s, Use of an ......................... .. ....... .. ... .. .. ... .. .. ..... 36(2) 134 Interactive Le a rning E n viro nm ent, Hyper-TVT : Development and Implementation of an .................... 40 (3) 175 Intern a tion a l Comparison of FinalY ea r D es i g n Project Curricula, An .................................... ........ ....... ..... .... 40 ( 4 ),275 Internet Re so urce s for Chemical E n g ine ers .................. ... 36 (2), I 00 Inter-Rat e r Reliabilit y I ss u e in Assessing L ear nin g Outcome s, Rubric D eve l opment a nd ........................ 36 (3),2 1 2 Introducin g the Stocha s ti c Simulation of Chemical R eactions Using the Gille s pie Algorithm and MATLAB ...................................................................... 37 ( I ), 1 4 Introduction to ChE First-Semester Course Focus in g o n Co nn ec tion Communication, a nd Pr e paration A Successful ... ............... .. ... .... ... .. ...... .. ... .. ....... 39 (3),222 Introduction to Dru g D e li ve r y fo r Chemical Engineers An .... .. .. .. .. .... .. .. .. .. ......... ... ... ...... ... 36 (3), 19 8 Introductor y ChE Courses, Port fo li o Assessment in ........ 36 (4),3 10 Intr o ductor y Cherrucal Rea c ti o n Engineering Course Micromjxing Experiments in the ............................ ...... 39 (2),94 Inve s tigation into the Propa ga tion of Baker 's Yea s t: A Laboratory Experiment in Bio c hemi ca l Engineering 38 (3), 1 96 l J avaBased Heat Tran sfe r Vi s u a li zation To o l s ..... .. .. ........ 38 ( 4 ),282 Journal Articles in R esea r c h, Te ac hjn g Entering Graduate Student s th e Rol e of .. .. .. .. ... .. .. .. ..... ........ ...... 40 ( 4 ),2 46 K K-12 Stud e nt s, Biomedical and Biochemical Engineering for. ....... ......... ........................... ... .............. .... ............. 40 ( 4 ) 283 Kin e ti cs and R eac t or D esign, Modeling of Chemica/ ....... 37 ( 1 ), 44 Kinetic s Experim e nt for th e Unit Op era tion s L a boratory A ......... ..... .... ........................ .. ............ ............. ..... 39 (3),238 Kinetic s of Hydrol ys i s of Acetic Anhydride by In-Situ FTIR Spectro sco py : An Experime nt for the Under g raduat e Laboratory .................. .. .. ... .. ................. 39 ( 1 ) 56 L L-Ly s in e Produ c tion in the Senior Laboratory A Batch Fermentation Experim e nt for. ..... .... ....... .. ... .. .. .. .. .. 37 (4 ),262 L a b-Ba se d Unit Ops in Micro e l ec tronic s Proces s ing ...... 37 (3), 18 8 Laborator y E xerc ise Usi n g a Commercial Movie for an Educational Ex peri e n ce; Alternative: ... 37 (2), 15 4 Lab E x p e ri e n ce, Int egra tin g Kin et i cs Characterization and Chemi c al En g ineering Educati o n

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M a t e ri a l s Pr ocess in g in th e ............... ......................... 36 (3),226 L a b E x p e rim e nt A n In tegrated C h em i ca l R eact i o n En g in ee rin g ... . .. ..... .... .. .................... .. . ..... ........ 38 (3),228 L a b ora t o r y A B a t c h F e rm e nt a ti o n Ex p e rim e nt fo r L-Ly s in e Produ c ti o n in th e S e ni o r .... ... ......... ........ 37 ( 4 ),262 L a borator y E x perim e nt E x p e rim e nt a l In ves ti ga ti o n a nd Pro cess D es i g n in a S e ni o r ...................... ... .. . ...... 40 (3),225 L a b o rat o r y in th e F und a m e nt a l s of Se mi co ndu c t o r Manu fac tu r in g A H a nd sOn . .... .. . .... ... .. ..... .. . 36 (1 ), I 4 L a b o rator y Ex p e rim e nt o n G e n e Sub c l o nin g fo r Ch e mi ca l E n g in ee rin g Stud e nt s .... .. ..... .. .. ..... .... 38 (3),2 1 2 Laborator y E x p e rim e nt P e m Fu e lCe ll T est St a ti o n a nd 38 (3),236 L a borat o r y S k ill s in C hE Stud e nt s Buildin g Mole c ul a r Bi o l ogy ........ ................ ..................... .. 39 (2), 1 34 L a b o rat o r y t o Suppl e m e nt C o ur ses in Pro cess Co ntr o l A. 36 (1),20 L a borator y Stru c tur e En c oura g in g R ea li s ti c Co mmunic a ti o n a nd Cr e ati ve E x p e rim e nt Pl a nnin g .. .. ..... .............. 37 (3),2 0 2 L ear nin g En v ironm e nt s, Hi g h-P e r for m a n ce .. . .. ..... .. 38 ( 4 ),286 L ea rnjn g P e d agog i es in Fluid M ec h a ni cs a nd H ea t Tran s f e r C o mbin i n g .............. .. .............. .... .... .. .. .. 39 (4),280 L ea rnin g Thr o u g h Simul a ti o n : S tud e nt E n gage m e nt... ... 39 (4),288 L ec ture D e m o n s t ra ti o n s A Du s t Exp l os i o n A pp ara tu s Suitable fo r U se in .. .. .... .. .. .. ..... ... ..... .. .. .. ....... 38 (3) 1 88 Letters to the Editor .. .. ... ..... 36 ( I ), 5 9 ; 37 ( I ), 45 ;(2), 1 2 4 ;(3),2 0 7 L e Chateli e r Prin c ipl e, E x c epti o n s t o the .. .. .. .... .. ....... 37 ( 4 ),29 0 Liquid Diffu s ion C oe ffi c i e nt s, M ass Tra n sfe r Experiment: D e t e rminati o n o f . .. . .. ...................... 36 (2), 156 L owe r L eve l s Int eg r a tin g Bi o l ogy a nd C h E a t th e ....... .. 38 (2) l 08 M Makin g Room fo r Group W o r k: T eac hin g E n g in eer in g in a Mod e rn Cl ass ro o m Settin g .... .. ... ................ 39 (2), 1 6 4 Manu fa cturin g, Bi oc h e mi ca l E n g in ee rin g T a u g ht in th e Conte x t of Dru g Di sco ver y a nd ...... .... ... . .. .. ... .... 39 (3),2 0 8 M a themati ca, G as P e rm e ation Co mput a ti o n s w ith ..... .. 40 (2), 1 40 M ass Balanc e Probl e m An Op e nE nd e d .. .. . .. .. ..... .. 39 ( 1 ),22 M ass Tran sfe r a nd Ce ll Gro w th Kin e ti cs in a Bior e a c tor ... ....... ... .. .... .. .. .. .. . .. .. .. .... .... ...... 36 (3),2 1 6 M ass Tran sfe r Ex p e rim e nt : D e t e rmin a ti o n of Liquid Diffu s i o n Coe f fic i e nt s .. ...... ... .. .... .................... . 36 (2), 1 56 M ass Tr a n sfe r Ex p er im e nt for T ra n s p o rt Ph e n o m e n a, A n E asy H ea t a nd ............. .... ... ............... .. .. .. .... .... 36 ( I ), 5 6 Material s Pro cess in g in th e L a b E x p e rien ce, Int eg ratin g Kineti cs Ch arac t e ri za tion a nd ..... ...... .... ...... .... ... .. 36 (3) 226 MathCad C o n s tru c tion a nd Vi s u a li za tion o f VL E E n ve l o p es in ............. ... ... .. .. .. .. . .. ..... ............. .... 37 ( 1 ),20 M a thCad in U nd e r gra du a t e R eac ti o n E n g in ee rin g, Numeri ca l P ro bl e m S o l v in g Us in g ... .... .. .................. .. 40 (1) 1 4 Mathem a ti c a t o T eac h Proce ss U nit s: A Di s till a ti o n C ase Stud y, Us in g .... .. .. .... ..... ......... ...... .... . ... ..... 39 (2), 11 6 M a th e m a tic a l M e th o d s in Ch E Simil ari t y S o luti o n C omput e r-F ac ilit a ted .. ..... ............ ........... . .. ... ... 40 (4),307 M a them a ti ca l Mod e lin g: Cookin g Potatoe s, E x perimentation a nd ....... ..... .. .. .. .. ... .... . 36(1 ) 26 M a themati c al Mod e lin g a nd Proce ss Control of Distribut e d P a ram e t e r S ys t e m s : The One-Dim e n s i o n a l H ea t e d R od ...... ................ .. . .. 37 (2), 1 26 MATLAB Int ro du c in g th e St oc h as ti c Simul a ti o n of Fa/12006 Ch e m R eac ti o n s Us in g th e Gill es pi e Al go rithm a nd ... 37 ( 1 ), 1 4 M cCabe -Thi e l e M o d e lin g S p ec i fic R o l es in th e L ea rnin g P rocess, P rocess Simul a ti o n a nd .................... .... .. 37 (2) 1 32 M ec h a ni ca l T es tin g of C o mm o nUse P o l y m e ri c M a t e ri a l s with a n In-H o u se -BuiltAppar a tu s .. .. .. ... 40 ( 1 ) ,46 M e mbr a n e S c i e nce and T ec hn o lo gy in the 2 1 s t Century ... 38(2 ), 94 Ment o rin g T ra inin g Pro gra m s a t Mi c hi ga n St a t e U ni ve r s it y: A D oc t ora l S tud e nt 's P e r s p ec ti ve, T eac hin g a nd .. .. .. . . ... .. .. ............................. .. 38 ( 4 ) 2 50 M e t acog niti ve E n g in ee rin g T ea m s, D eve lopin g .............. 38 ( 4 ),3 1 6 Mi cro mi x in g Ex p e rim e nt s in th e Introdu c t o r y Ch e mi ca l R eac tion En g in ee rin g C o ur se ... .. . .. .. ... 39 ( 2 ), 94 Mi x in g Writin g w ith Fir stY ear E n g in ee rin g: A n U n s t a bl e S o luti o n . .... .. .. .. .. .. .. .. .... .................. 37 ( 4 ),2 4 8 M ec h a ni ca l P a rt s, Pr ess ur e fo r Fun : A Cour se M o dule for In c r eas in g ChE Stud e nt s' E xc itement a nd Int e r es t in .. ... ...... .. ... . .. .. ... ... .. .... .. ..... .. ... .. 40 ( 4 ), 291 Membranes in ChE Education A n a l ys i s of M e mb ra n e P rocesses in th e Int ro du c tion t o-C h E Co ur s e ....... .. .. .... ............... ....... .. .... ... ... 37 ( 1 ),33 C om p e ndium o f Op e nE n de d M e mbran e P ro bl e ms in th e Curri c ulum ........... ..... ....... . .. .. ... .. .. ... 37 ( I ), 46 E x pl o rin g th e P o t e nti a l of El ec trodi a l ys i s ...... ... ... .... .. 37(1 ), 5 2 M e mb ra n e Proj ec t s with a n Indu s tri a l F oc u s in the C urri c ulum ......... .... ... .. .... .... .......... .... ............. ... 37 ( I ),68 Pr ess R o S ys tem: A n Int e rdi sc iplin ary R eve r se O s mo s i s P ro j ec t fo r Fir s t-Y ear E n g in ee rin g Stud e nt s ..... ... 37 ( I ),3 8 Simpl e A n a l ys i s for G as S e p a ration M e mbrane Ex p e rim e nt s, A .... .. . .. .. .. .... ... .... .. ... .... .... ... 37 ( 1 ) 7 4 T oo l s for T eac hin g G as Se p ara ti o n Us in g P o l y m e r s .... 37 ( 1 ), 60 M e mb ra n e Sc i e n ce a nd T ec hn o l ogy in th e 2 1 s t C e ntur y .. . .. .. ........ .. .... .. .. .. .. ... .... .. ..... 38 ( 2 ), 94 Memb ra n e P ro bl e m s in th e C urriculum A C o mp e ndium of Op e n -E nd e d .... ........ ... ... .. ... ... ... .. .. 37 ( 1 ) ,46 M e t al R ecove r y fr o m W as t ewa ter with a n E l ectroc h e m ka l M e th o d .. .... ......... ... ............. .. .. 36 (2), 144 M e th od for D e t e rminin g S e l fSimil a rit y T ra n s i e nt H ea t T ra n s f e r with Co n s t a nt Flu x A .... ...... .... ...... .. 39 ( 1 ) ,42 Mi c romi xi n g Effec t s in H o m oge n eo u s R eac t o r s, A No ve l Ap p roac h fo r D esc ribin g ........ .. ......... ..... .. .. .. .......... 36 ( 4 ),2 50 Mode lin g of C h e mi ca l Kin et i cs a nd R eac ti o n D es i g n .. .. 37 ( I ),4 4 M o d e lin g in a P rocess D y n a mi cs a nd C o ntrol Co ur se, Bi o m o l ec ul a r ....... .. .. .. ..... .... .. ...... ..... .. .. ... ... ... ..... 40 ( 4 ),2 97 M o d e rn C l ass ro o m S e ttin g, Makin g Room for Group W o rk: T eac hjn g En g in ee rin g in a ...... ...... .. .. .. ...... .. 39(2 ), 164 M o l e B ala n ces S ys t e m a ti ca ll y Put Y o ur Intuiti o n t o R es t: Wri te ........................................ ... ... .. .. .. .. .... 38 ( 4 ),3 0 8 M o l ec ul a r a nd Ce llul ar Bi o l ogy int o a ChE D eg r ee Pro g r a m In co rp o ratin g .. .. .. . ... ...... .. .. ........ .......... 39 (2), 1 2 4 M o l ec ul a r-B ase d Equ a t io n s of St a t e a t th e G ra du a t e Leve l .. .. .. ... .. .. .. . .. .......... .. .... ... .... .... 39 ( 4 ),2 50 Mol ec ul a r Di ff u s i o n E x p e rim e nt s, In ex p e n s i ve and Simpl e Bin ary ........................... .. ............ .... ... .... .... .. 36 ( 1 ), 6 8 Mol e cul a r-L e v e l Simul a tion s to Determine Diffusivities in th e Cl ass room U s in g .. .... ..... ....... .... .. .. .... ..... ... 37 ( 2 ), 156 M o le c ul a r Biolo gy to Environment a l En g in e er s Through D eve l op m e nt of a ew Co ur se, Introdu c in g ........ .. .. 36 ( 4 ),2 5 8 M o nt e Car l o T ec hniqu es: 333

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Economic Risk Analysis, Using Analytical and ......... .. 36 (2),94 Movie for a n Educational Experience : An Alternative Laboratory Exercise, Using a Commercial ..... ........................... 37(2) 154 Multidisciplinary Design of a Potable Water Treatment Plant A Freshman Design Experience: .... ... ............. 39( 4 ),296 Multidisciplinary Graduate C u rricu lum on Integrative Biointerfacial Engineering ... ..... .. .... .. ... ........... ........ 40 ( 4),251 Multidisciplinary Projects Collaborative Learning and Cyber-Cooperation in ............................. ... ........... 37(2) 114 Multidisciplinary Team Projects Evaluating: Rubric Development for Assessment of Undergraduate Research ..... .. .. .. .. . .. ... .... ........ ........ .... ................ 38(1),68 Multi-Scale Modeling of Soft Matter A Graduate Course on ........................ ...................... ... 38 (4),242 N Nanostructured Materials Synthesis of Zeolites .... ........... 38 (1),34 Natural Convection A Simple Classroom Demonstration of ..... ................. ... ...... .. .......... ............... 39(2) 138 Natural Dye Materials, Experiments and Other Learning Activities ............................................ ...... 38(2) 132 Next Millennium in Chemical Engineering Crystal Engineering: From Molecule s To Products .. 40 (2), l I 6 Different Chemical Industry A. ...... .......... ................. 40(2 ), 114 Inside the Cell: A New Paradigm for Unit Operations and Unit Processes .............................. .. ... ...... .. ... 40 (2), 126 Next Millennium in Chemical Engi n eering, The ......... 40 (2),99 Teaching Engineering in the 21st Century with a 12thCentury Teaching Model : How Bright is That... ... 40 (2), I I 0 Vision of the Curric ulum of the Future, A .................. 40 (2) 104 Nonideal Reactors in a Junior-Level Course Using Computational Flu id Dyn a mic s, Incorporating .... ...... 38 (2) I 36 Non lin ear Multi-Input, Multi-Output Proce ss Control Laboratory Experiment, A .................. .. .. ............... ... 40 ( I ),54 Numerical Methods Increasing Time Spent on Course Objectives by Using Computer Programming to Teach .... .... ... ... .. ... ................... ... ..... ...... ..... ........... 37(3),214 Numerical Problem Solving Using MathCad in Undergraduate Reaction Engineering .. ....... ......... ..... .. 40 ( 1) 14 Numerical Problems A Separation Processes Course Using Written-Answer Questions to Comp l ement ... 36(2) 130 _Q Office Hour s, Instant Messaging: Expanding Your ......... 39(3 ), 183 On Improving Thought with Hand s" ............... .. ..... .. ..... 36(4 ),292 On the Application of Durbin-Wat so n Statistics to Time-Series-Based Regres s ion Model s ..... .. ..... ........ ... 38( I ),22 One-Dimensional Heated Rod: Mathematical Modeling and Process Control of Distributed Parameter Systems ....... .. ... ..... .......... ... .......... ....... 37(2), 126 Open-Ended Mass Balance Problem An ........... ...... ... ..... 39(1) 22 Optimum Cooking of French Fry-Shaped Potatoes: A Classroom Study of Heat and Mass Transfer ..... ... ..... 37 (2), 142 :e Paradox of Papermaking The .............. .... .. .. ............... 39(2) 146 Partial Difference Equat i ons, The Sherry Solera: An Application of .......... .... .... .. .. ........ 36 ( I ),48 334 Particle Demonstration s for the Classroom and Lab ....... 37(4 ),274 Particle Technology Novel Concepts for Teaching ......... 36( 4 ),272 Partnering with Industry for a Meaningful Course Project... .......... ............... ... ........ ..................... 40(1 ),32 Performing Proces s Control Experiments Across the Atlantic ... .... . ........ .. .... ... ... .. .. ... ...... ...... ... ........ .. 39 (3),232 Pem Fuel-Cell Test Station and Laboratory Experiment. 38 (3),236 Per so nalized Interactive Take-Home Examinations for Students Studyin g Experimental Design .. ........... 37 (2), 136 Plantwide Flow Sheets Common Plumbing and Control Errors in ......................................................... 39 (3),202 Potato Cannon : Determination of Combustion Principle s for Engineering Freshman The .. ... .. ... .. 39(2 ), 156 Product De s ign Through the Investigation of Commercial Beer Teaching .. ..... ......... ....... ................ 36(2 ), I 08 Phase Equilibria, How Gibbs Energy Considerations Reduce the Rol e of Rachford-Rice Analysis: Computing: . ..... ..... ... ... ..... 36 ( 1 ),76 Phase Equilibria Curves, Use of a n Inte gratio n Technique to Trace .. .. .................................................. 36(2) 1 34 Pha se Equilibrium and Sensitivity Analysis, Solvent Re cove ry by Condensation: An Application of .. ... .. 38(3 ),2 I 6 Pha se Equilibrium More User-Friendly, Making .... ........ 36(4 ),284 Pillar s of Chemical Engineering: A Block-Schedu l ed Curriculum ......................... .... ... ... 38 ( 4),292 Pilot-Scale Setup for Real-Time Studies in Process Systems Engineering A Flexible .................. .. ....... .. ..... 40( l ),40 Plant Design Project: Biodie se l Production Using AcidCatalyzed Transesterification of Yellow Grease ...... 40(3 ),2 15 Polymer Coating Experiment Fluidized Bed .. ....... ....... 36(2 ), 138 Polymeric Materials with an In-House-Built Apparatus Mechanical Te s tin g of Common-Use .... ............. .. ... ... 40(1 ),46 Portfo li o Assessment in Introductory ChE Courses ......... 36 (4),310 Potable Water Treatment Plant A Freshman Design Experience: Multidi sc iplinar y Design of a .... ........ .. 39 (4),296 Power Energy Balanc es on the Human Body: A Hand s-O n Exploration of Heat Work, and ................... 39 ( I ),30 Power Law Liquid Determining the Flow Character i stics of a ............................... .... .............. 36(4 ),304 Press RO System: An Interdisciplinary Reverse Osmosis Project for First-Year Engineering Students .......... .... 37(1) 38 Pressure for F un : A Course Module for Increasing ChE Students' Excitement and Intere s t in Mechanical Parts .. ... ... ... .... .. .. .............................................. ... ... 40( 4 ),291 Problem And Open-Ended Mass Balance .. ... .. ..... ........... 39 ( I ),22 Problem-Solving Skills Assessing: Part 2 ............... ....... 36 ( I ),60 Proce ss Control of Di s tributed Parameter Systems Case Study: The One-Dimen s ional H eated Rod Mathematical Modeling and ... .. .. ... .. ... ..................... 37(2) 126 Process Control Education Experimental AirPressure Tank Systems for ....... ... ... ..................... ..... .... 40(1 ),24 Proces s Control Experiment, A Quadruple-Tank ............. 38(3) 174 Process Control, A Laboratory to Supplement Courses in. 36 ( I ),20 Proces s Control Intuition Using Control Station Building Multi variable ........... ............................ ..... 37 (2), I 00 Proce ss Control Laboratory Experience Simulation and Experiment in an Introductor y .. .. .... .. ....... .... ... .. .. 37 (4),306 Proce ss Control Laboratory Experiment A Nonlinear Multi-Input, Multi-Output ..... .. .. .... ... .. ... .. ... .. ... ... 40 ( I ),54 Proce ss Contro l Laboratory Experimental Projects Chemica l Engineering Education

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for the ... ... .... ................. .. .......................................... 36 (3), 182 Process Control with a Numerical Approach Based on Spreadsheets Teaching .. .... ... ..................... ........... 36 (3) 24 2 Proces s Design in a Senior L abora tor y Experiment, Experimental Investigation and .................................. 40 (3),225 Process Dynamic s and Control Course, Biomolecul ar Modeling in a .... .............................. ... .. ...................... 40 ( 4 ),297 Proce ss D y namic s a nd Control Curriculum Integrating Biological Systems in the ........................................... 40 (3), 1 81 Proces s Flow Sheet s, Use of Dynamic Simulation to Converge Complex ........... .... .................................. 38 (2), 142 Proce ss Security in ChE Education .. ... .............................. 39(1 ),48 Process Simulation and McCabe-Thiel e : Modeling Specific Roles in the Learning Process ....................... 37 (2), I 32 Proces s Simulation Used Effectively in ChE Courses? I s .... ....... .. ............................................. ...... 36 (3),192 Proce ss System s Engineer in g, A Flexible Pil ot-Sca l e Setup for Real-Time Studi es in ..................................... 40 ( I ),40 Productivit y and Quality Indicator s for Hi g hl y R a nk ed ChE Graduate Programs ........ ............ ...... ............. ........ 37 (2),94 Profession of Engineering Doe s, Equations (of Change) Don t Change but the .................................................. 37 (4),242 Profes so r Returnin g as a ................................. .. .............. 37 (4),310 Project-Based Learning in Graduate Courses Reflections on ... .. ........ ................................... ... .. 38 (4),262 Project to Desi g n and Build Compact H eat Exchangers A ............................................................... 39 ( I ),38 Project on the Splenda Sucralose Process Heat Transfer Analysis and the Path Forward in a Student .............. 39 (4),3 16 Project VCM Process De s i g n: An ABET 2000 Fully Compliant .............. ....... ...... .. ... ..... ... ......................... 39 (1),62 Propagation of Baker 's Yeast: A Laboratory Experiment in Biochemical Engineering Inve s tigation into the ....... 38 (3) 196 Put Your Intuition to Re s t : Write Mole Balance s Sy s tematically .... .. .... .. ...... .. ....................... 38 ( 4 ),3 08 Q Quadruple-Tank Proce ss Control Experiment A ............. 38 (3) 174 R Rachford-Rice Analysis Computing Phase Equilibria: How Gibbs Energy Considerations Reduce the Rol e of.. ................ 36(1 ), 76 Rate Processes Teaching Coup l ed Tran s port and ........... 38( 4),254 Reaction Engineering, Numerical Problem Solving Using MathCad in Undergraduate .......... .. .................. .. 40 ( 1 ), 14 R eac t or D es ign Modeling of Chemical Kin e tics ............. .. 37 ( 1 ),44 Real-Time Studies in Proce ss Systems Engineering, A Flexible Pilot-S ca le Setup for ...... ................. ................ 40(1 ),40 Re a l-World Probl ems, R e l a tin g Abstract Chemical Th er modynamic Concepts to ...................................... 38(4 ),268 Recommendation Letter s, Value of Good ........ ...... .......... 37 (2), l 22 Redlich-Kwong Equation of State: An Exercise for Practicing Proramming in the ChE Curriculum Calculation of Thermodynamic Properties Using the ................... 37 (2) 148 Reduction of Di sso lved Oxygen at a Copper Rotatin g -Di sc Electrode ............................................... 39 (1 ), 14 Reflection s on Proj ectB ased Learning in Grad u ate Courses ....... ... .... ......... ....... ....................... 38 (4),262 Regre ss ion Model s, On the Applications of Durbin-W a t so n Fa/12006 Statistics to Times-Series-Based .......................... ......... 38 ( I ),22 Relating Abstract Chemica l Thermodynamic Concepts to Real-World Problem s ......... .. ................... ... ........... 38(4) ,2 68 R esearc h Proposal in Bio chemical a nd Biolo gica l Engineering Courses The ....... ..... ..... ......... ......... ... 40 (4),323 R esearc h T eac hin g Entering Graduate Students the Role of Journal Articles in .............................................. ..... 40 (4),246 R espiration Experiment to Introduce ChE Principles A. 38 (3), 182 R et urnin g as a Professor .................. .. .............................. 37 (4),3 10 Rever se Osmosis Project for First-Year Engineering Students, Press RO System: ......... .. .... .... ....................... 37( I ) 38 Ri sk Analysis: Us ing Analytical and Monte Carlo Techniques Economic ........................................ 36(2) 94 Role of Indu s trial Training in Chemical Engineering Education The ........... ..... .... .. .......... ................ .... 40 (3), 189 R ole-P l ay in g Case Study Environmental Impact Assessment: Te ac hin g the Principle s and Practices by Means of a ........... ... .......... ............ ........................... 39(1)76 R ose -Hui man In s titut e of Technology Freshman Design in Chemical Engineering at ............................ 38 (3),222 Rubric Development and Inter-Rater Reliability Issues in Assessing Learning Outcomes ................................ 36(3) ,2 1 2 Rubri c D eve lopment for Assessment of Undergraduate R esearc h Evaluating Multidisciplinary Team Projects .. .... ...................................... .... .... ... ... .. .. ..... 38( I ),68 Random Thoughts Changing Times and Paradigms .......... ........................ 38 ( 1) ,32 Death By PowerPoint ................................ .................. 39(1) ,28 Educator For All Seasons An ..................................... 38(4 ),28 0 Effective Efficient Professor, The .............................. 36 (2), 114 FAQs. V. De s ignin g Fair Tests ............ ... ...... .. ...... ... .... 36 (3),2 04 FAQs. VI. Evalua tin g Teaching and Converting the Masses ................. ... .................................... ..... 37(2 ), 106 Fond Farewell A. .................................................... ... 39(4 ),279 How to Evaluate Teaching ........ ................................. 38(3) ,2 00 How to Survive Engineering School ............................ 37 ( 1 ),30 How to Teach (A lm os t ) Anybody (Almost) Anything ........ .. .. ... ... .... .... ............................... ... 40 (3) 173 Incontrovertible Lo g ic of the Academy, The .............. 37(3),220 Learning By Doin g .. ... ......... ..... .... .... .... .. ....... .......... 37(4),282 Screens Down Everyone: Effective Uses of Portable Computers in Lecture Classes ............. ... ......... ...... 39(3),200 So You Want to Win a CAREER Award ... .. ............ ..... 36(1) 32 Speaking of Education-III ................................... .. ..... 36(4) ,282 Speaking of Everything-II ... ....... ... .................... ....... 39 (2),93 The Way to Bet ....................... .... ....... ......................... 40 ( 1 ),32 We Hold These Truth s To Be Self-Evident... .. ...... ..... 38(2) 114 What 's in a Name ......................................... ............. 40 (4),28 1 Whole New Mind For a Flat World, A ................. ... ..... 40 (2),96 s Scaled Sketches for Visualizing Surface Tension ............ 39(4) ,328 Scaling of Differential Equations: "A n a lysi s of the Fourth Kind ....... ... .. ........ ...... .......... .... .... ........ ...... 36(3) ,232 Self-Similarity Transient Heat Transfer with Constant Flux A Method for Determining ........................... .. ... .. 39 ( I ),42 Semiconductor Manufacturing, A H ands-O n Laboratory in the Fundamentals of ................................................. 36(1) 14 Semiphysical Modeling to ChE Students Using a 335

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Brine-Water Mixin g T a nk Experiment T eac hin g ... .. 39 (4),3 0 8 Sens i tivity Ana l ysis in ChE Education : P a rt I. Intr o. and App li cation to Exp licit Model s ....... .. ....... .... .. ... ... 37 (3), 111 Sens iti vity Ana l ysis in ChE Ed u ca tion: P a rt 2. App li c ation t o Implicit Mod e l s .. ... .. ... ... .... ....... 37 (4),254 Sen s itivit y Ana ly sis Solvent R ecovery by Condensation: An App li ca tion of Pha se Equilibrium a nd .... ... ........ 38 (3),2 1 6 Separation Proce sses Cour se: Us in g Writt e n-An swe r Qu es ti o n s to Comp l ement Num er i ca l Problem s ........ 36 (2), I 30 Separation Pro cesses, Using Vi s ualization and Computation in the A n a l ysis of .... ... ............... .. .. 40 ( 4 ),3 1 3 Senior D es i g n Project That Inte gra t es Laboratory Experiments and Computer Simul at ion A Tir e Ga s ifi cation .. ...... .. .... ........................ .... ....... .. ..... 40 (3) 203 Sherry Solera: An Ap pli cation of Partial Difference Equation s, The .... .... .. .... ......... ........ .. ..... ... ... ... . 36(1 ),48 Similarity Solution Computer-Facilitated Mathematical Methods in ChE ................. ......... ... .... .. ...... .... .... 40 (4),307 Simple Cla ss room Demon s tration of Natural Conve c tion A ....................... .. ... ........... ....... .. ... ... 39 (2), 13 8 Simp l e Op e n-End e d Vapor Diffu s i o n Experiment, A .. 38 (2), 1 22 Simulation a nd Experime nt in an Introductor y Proc ess Co ntr o l Laboratory Exp er i e nc e .. .. .. ..... .. ... ........... 37 (4),3 06 Sim ul a tion : Stud e nt Engagement Learning Throu g h .. .. .. 39 (4),288 Soft M a tt e r A Graduate Cours e on Multi -Sca l e Mod e lin g of ......................... .... .. ... .. .. .................. ... ... 38 ( 4 ),242 Softw are Tool s for ChE Educ a tion Student s' Evaluation s, Use of ........................ .............. .. .... .. .. 36 (3),236 Solid s Product Engineering Desi g n Proje ct, A ... ... ... ... .. 37 (2), l 08 Solvent R ecovery by Conde n sation: An Applic a tion of Pha se Equil ibrium and Sensitivity Ana l ysis ...... .... 38 (3),2 16 Sorption Separations Using a Commercial Simulator t o T eac h ... .. .... .. ....... .. ... ... .... ...... .. .... .. .. .. .............. 40 (3) 165 Sp l enda Sucralo se Proces s, H ea t Transfer Ana l ys i s a nd th e Path Forward in a Student Project on th e .... .. .. .. 39 (4),3 1 6 Spre a d s h ee t Engineering An Excel/VBA-Based Pro gra mming a nd Problem Solvin g Course: Computer Science or .......... .................. .... ........ ... .. 39 (2), 14 2 Spread s heet S o luti ons to Two-Dimen s ional Heat Tran s fer Problems ... ... .. ....... .................. .... .. .. .. ...... 36 (2), 160 Spread s heet s, Teaching Proce ss Control wit h a Numerical Approach Ba se d on ..... ... ...... .. .. ..... ... ... ... .. .. .... .... 36 (3),242 Spreadsheets a nd Visual B as i c Applications as T eac hin g Aids for a Unit Op s Cour se, Us in g .. ... ....... ........ .. ... 37 ( 4) ,3 16 Stati s tic s, A n Undergrad u ate Course in App li ed Prob a bility a nd .... .... ........ .... ...... ......... .. .. ..... .. 36 (2), 17 0 St oc h as ti c Modeling of Thermal D ea th Kin e ti cs of a Cell Popul a tion R evisited ..................... .. ................ .. 37 (3),228 Stocha s tic Modeling Using a Web Module to Teach ... .. 39 (3),244 Stocha s tic S imul ation of Chemical R eac tion s Us in g th e Gille s pie Algorithm and MATLAB Introducin g the ... 37(1 ), 14 Student Motivation Survivor Cla ssroo m: A Method of Activ e L ear ning That Addres ses Four Type s of .. .. ... 39 (3),228 Stud e nt s, T eac hin g ChE to Bu s in ess a nd Science ... .... ... 36 (3) 222 Students' Evaluat i ons, Use of Softwar e To o l s for ChE Education ...... ...... .... .................................. .. ............. 36 (3) 236 Succe ssf ul Introduction to ChE Fir stS e me s ter Course Focu s ing o n Co nn ection, Comm uni cat ion and Preparation A. .... .. ... .. . .. ... ............... .... .... .. 39 (3),222 Summer School 336 Course in Biopro cess Engineering Engaging th e Im ag in a tion of Students Us in g Experiences Outside th e C l assroo m A ...................................... 37 (3), 1 80 In cor p ora ting Experimental D es i g n int o the Unit Op era tions Laborator y .... . .... .... ... .. .. .. . .. 37 (3), 196 In co rp orat in g Hi g h School Outreach int o ChE Courses .. ... .... ......................................... ........... .. 37 (3), 184 In c re as in g Tim e Sp e nt on Course Objectives b y Using Computer Pr ogram min g to T eac h Numerica l Method s ... .... ... ......... ........... ............ 37 (3),2 1 4 Introducti o n to Bioch em i ca l Engineering: Synthesis R eso ur ce fuln ess, a nd Effect i ve Comm uni cat ion in Group L ear nin g ... .. .. .. ... ... ..... ..... .. ................. 37 (3), 1 74 L a b-B ase d Unit Operations in Mi croe l ec troni cs Proce ss in g ................. ... .. ......................... .. ..... ... 37 (3), 1 88 P ass in g it On: A Laboratory Structure Encourag in g R ea li st ic Communication a nd Creat iv e Experiment Plannin g . .. ...... .... .. .. ... ... ....... ....... 37 (3),2 02 Water Da y: A.n Exper i ential L ec ture for Fluid Me c hanic s .. .. ........ .... .. ..... .... .. ........... ... ... .. .. ...... 37 (3), 17 0 Survivor C l assroom: A M e thod of Active L ear nin g Th a t Addresses Four Types of Student Motivation .... 39 (3) 228 Survey of the Gradu a t e Thermodynamics Course in Chemical E n gineering Departm e nt s Across th e United States A .. ... .. .. ..... .. . .. .... ... .... ............. 39 (4),258 I T a nk Sy s t e m s for Proc ess Control Ed u cation, Experimental Air-Pressure ... .... .... ...... .. . .. ... ... ... 40 ( I ),24 T eac h Our Student s t o be Inn ovat iv e? Can We .... ... .... 36 (2), 11 6 T eac hin g ChE to Business a nd Science Students .. .......... 36 (3),222 T eac hin g Coupled Transport a nd R a t e Pro cesses .. ..... .. .. 38 (4),254 T eac hin g Electrolyte Thermodynamics ............ ................ 38 ( I ),26 T eac hin g Engineering Courses with Workbook s ............... 38 ( I ),74 T eac hin g En t ering Gradu a t e Student s the Role of Journal Art i cles in R esearch ....... .. .......... .. ............. ............. 40 (4),246 T eac hin g Free Convection, a Computational Model for.. 38(4 ),272 T eac hin g a Graduate-Lev e l Course in Ti ss ue Eng in eering ..... ...... .... .. ... ....... ... .. ... ......... .. ... .. 39 ( 4) 272 Teaching a nd Mentorin g Trainin g Pro gra m s at Michi ga n State U ni vers it y: A Doctoral Student's P e r spec ti ve .. .. ... .. .. .. .. .... ... .... .. ........ .. 38 ( 4) ,2 50 T eac hin g No nid eal R eac t o r s with CFO T oo l s .. .. .. ... ... 38 (2), 154 Te ac hin g P a rticle Te c hnolo gy, Novel Concepts for. .. ... 36 (4),272 T eac hin g Proce ss Control with a Numerical Approach Ba se d on Spr ea dsheet s ... .. .. .... ... .. ... .. ... ... .. ... .. 36 (3),242 Te ac hin g Semiphysical Modelin g to ChE Students Using a Brine-Wat e r Mixin g T a nk Experiment .......... 39 ( 4) 308 Teachin g Tip s : El eva tor Talks ..... ..... ...... .. .... .......... ...... ..... 40 (3) Teachin g Tip s .... .. ... ... .. .. ..... .. ................ 38 (2), 1 2 1 40 ( 4 ),327 Teachin g Turbul e nt Th e rm a l Co n vec tion, A New Approach to ..... ..................... .. .... .. ... .. .... .... ... .. 36 (4),264 T ec hnic a l Writin g, Impro v in g Coherence in .... .. .... ... 38 (2), I I 6 T ec hni ca l Writin g, Top T e n W ays to Imp rove . .. ... . ... 38 ( 1 ),54 Test Re s ults for Assessment of T eac hin g and Learnin g, Using .... ..... ..... .. .. ... ... .... ...... .... .... .. .. .. .... .... ..... .. 36 (3), 1 88 T es t Station a nd Laboratory Experiment Pem Fu e l -Cell 38 (3),236 Th e rmal Convection, A New Approach t o Tea c hin g Che mi ca l Engineering Ed u ca tion

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Turbulent .. ....... .............. .... ... ........... ........................ 36 (4),264 T h erma l D eath Kinetics of a Cell Population R evisited, Stochastic Modeling of.. ............................................. 37 (3),228 T h erma l R ad i a ti on, Comp ut er Evaluat i on of Exchange Fac t ors .. ................................................. 38 (2), 126 Thermodynamic Co n cepts, Biom ass as a Su sta inable E ner gy Source : An Illu stratio n of ChE ...... .. ............... 40 ( 4 ),2 59 Thermodynamic Properties Us in g the R ed li c h-K wong Eq. of State A n Exercise for Practicing Programming in ChE Curriculum Calcu l ation of.. ................................ 37 (2), 148 Thermodynamic s Course in Chemical Engineering Departments Across the United States, A Survey of the Graduate .......................... .. ...... .. ....................... 39 (4),258 Thermodynamic s, Teaching E l ectrolyte ............................ 38 ( 1 ),26 Thermodynamic s, Use of ConcepTests a n d In s t a nt Feed b ack in ........................ ........ ................................... 38 ( I ) 64 Thermophysical Prop er ti es, C h oosi n g a nd Evaluating Eq uation s of State for ...................... .. ......................... 37 (3) 236 Tire Gasification Senior Design Project That Integrates Laboratory Experime nt s and Computer Simulation, A .............. .. .................................. ...... 40 (3),203 Tissue Engineering, Teaching a Graduate-Level Co ur se in .... .. ... ............. ......................... .... ...... .. 39 (4),272 Tools fo r Teaching Gas Separation Usi n g Polymers .......... 37 ( I ) 60 Top Ten Ways to Improve Technic a l Writing .................... 38 ( I ) 54 Transesterification of Yellow Grea se, Plant De sig n Project: Biodiesel Production Usi n g Ac id -Catalyzed. 40 (3),2 1 5 Transport Ph e nom e n a, An Easy H eat a nd Mass Transfer Experime nt for ............................................... 36 (1 ), 56 Troubleshooting Skills in the Unit Operation s Laboratory Developing ...................... ... ............ .... ..... 36 (2), 122 Two-Dimensional Heat Transfer Problems Spreads h eet Solutions to ...... .. .................. ... .. ... .. ........ 36 (2), 160 II Undergraduate Curr i culum, Devel o pment of CrossDisciplinary Projects in a C h E .................................... 38 (4),296 U nit Ops Course Us in g Spreadsheets a nd Visual Ba s i c A ppli cat i o n s as Teaching Aids for a .... ...................... 37 (4),3 1 6 Un it Operations Laboratory A Holi s tic ........................... 36 (2), 150 U nit Operation s Laboratory A Kinetic s Experiment for the .... ...................... ......................................... ... 39 (3),238 Unit Operation s Laboratory, A Virtual ........................ .... 36 (2),166 U nit Operations Laboratory, An Automated Di s tillation Column for the ............................................................ 39 (2), 1 04 U nit Operations Laboratory Developing Troubl eshoot in g Skills in the .............. .... .................... 36 (2),122 U nit Operations Laboratory, In corporating Experimental Design into the ...... .... ..................... ............................ 37 (3), l 96 Un it Ops in Microelectronics Proces s ing, Lab-Based ..... 37 (3), 1 88 U nit Ops L abora t ory, Community-Based Pr esenta ti ons in the ......... .... ................ .. ............................... .. .......... 39 (2), 160 UOP-C hul a l ongkorn University Indu str ial-Univ ers it y Joint Program .... .. ... ....... ... .. .... ........................ 38 ( 1 ),60 Use of ConcepTe s ts and Instant Feedback in Thermodynamics .... ... .......... .... .............. ... .................... 38 ( I ),64 Usi n g a Commercial Simulator to Teach Sorpti on Separations ................................................. ... ..... ........ 40 (3), 165 Using a Web Module to Teach Stochastic Modeling ....... 39 (3),244 Usi n g Mathematica to Teach Proce ss Un it s: A Fall 2006 Di s tillation Case Study .... .. .................................... .... 39 (2), 11 6 Using Small Blocks of Time for Active Learnin g a nd Critical Thinking .................................................. 38 (2), 15 0 Using Spreadsheets and Visual Ba s ic App li cations as Teaching Aids for a Un it Ops Co ur se .... ... .. ................ 37 (4),3 1 6 Using T est R esu lt s for Assessment of Teachin g and Learning ...... ....... ................. .... ............ .. ........... ... 36 (3), 1 88 Using th e Evo luti o n ary Operation Method to Optimize Gas Absorber Operation: A Statistical Method for Proce ss Improvement ................................................. 38 (3),204 Usi n g Visua li zation a nd Comp ut atio n in the A n a l ys i s of Separation Proces ses .................... .... ... .. .. .. ...... .. .. .. 40 (4),313 y Validating The Eq uilibrium Stage Mode l for an Azeo t ropic System in a Laboratorial Distillation Column .. ... .. .. .. .. ........ .... .... .. .. .. ... .. ... .... ......... 40 (3), 1 95 Value of Good R ecommendation Letters ........... ... ........... 37 (2), 1 22 Vapor Diffu s i on Experiment A Simple Open-Ended ...... 38 (2), 1 22 YCM Pro cess De s ign : An ABET 2000 Fu ll y Compliant Project ......................................................... 39 ( I ),62 Virtua l Laboratory Web-Ba se d Y RFor m ............ .. ......... 36 (2), 102 Virtua l Unit Operations L a boratory, A ............................. 36 (2), 1 66 Viscosity Experiment for Hi g h School Science Classes, Demon s tration and Assessment of a Simp l e .... ........... 40 (3),2 11 Visual B as i c App li ca ti o n s as Teac hin g Aids for a Un it Ops Course, Usi n g Spreadsheets and .................... .. ... 37 (4),316 Visualizing Surface Tension .. .......................................... 39 (4),328 Visualization Tools Java-Based Heat Transfer ................ 38 (4),282 YLE Envelopes in Mathcad, Construction and Visualization of .. .... .................. .. .. .... .. ....... .. ......... 37 ( I ),20 Vulnerability Analys i s, ( BLEVE ) Boiling-Liquid Expanding-Vapor Explosion : An Int roduction to Consequence and .. ............. .. ..... .. .. .. .. .. .... .... 36 (3),206 w Wastewater wit h a n Electrochemical Method Metal R ecovery from .. .. .... ... .... .. ... .. .... .......... .. . 36 (2), 144 Water Day : An Experien ti al Lecture for Fluid Mech ....... 37 (3), 1 70 Web-Based Delivery of ChE Design Projects .................. 39 (3), l 94 Web-Based YR-Form Virtual Laborator y ........................ 36 (2), 102 Web Module to Teach Stochastic Modeling, Using a ...... 39 (3),244 Work and Power Energy B a l a n ces o n the Human Body: A Hands-On Exp l oration of Heat ................................ 39 ( I ),30 Writing with First-Year Engineering: An U n stable Solution Mixing .......................... ... ......... ................. 37 (4),248 Written-An swe r Questions to Compleme nt Numerical Problem s Case Study : A Separation Processes Co ur se .... ........... ... .. ... .. .. .......... ..... ...... .......... .... ........ 36 (2), 1 30 y Yellow Grease, Pl a nt De s i g n Project: Biodie sel Produ c tion Using Acid-Catalyzed Tran ses terification of ...... .. .......................................... 40 (3),2 15 z Zeo lit es Nanostructured Materials Synthesi s of.. .. ... .. ..... 38 (1 ),34 337

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Author Index A Abbas, Abderrahim ..................... 36 (3),236 Abra h a m Martin A. .. .... .. ........ 34 (2),272 Abu-Khalaf Azi z M ... ................ 36 (2), 1 22 Adhan ga l e, Par ag .... ..... .. .. .. ..... ... 37 (2), I 56 Akers William H ................ ...... 39 (4),3 1 6 A lb a rr a n Carlos Pon ce de L eo n .... 39 ( 1 ) 14 A l-B astaki Nader ... .... ............. 36 (3),236 A lm eida, Paulo I g n ac io F. ..... .. 38 (2),100 Alves, Manu e l A .......... .. ............. 38 (2), 154 Ang, Sion g ... ................. ... ......... 36 (3), 1 82 April G C .... .. ... ........ ... .. .. ........... 38 ( 1 ),8 Ang, Siong .... ............. ....... .. .... 38 (3), 174 Arce, P e dro E .................... .. .. .... 38(4 ),286 Armstrong Robert C. ............... .. 40 (2), 104 Arnold, D.W. ...... .................. .. .. ... ... 38 ( 1 ),8 Ascanio G a briel ... ... ..... .. ..... ....... 37 ( 4 ),296 Assaf-Anid Nada M .. 38 ( 4 ),268; 40(4 ),259 B. B a ber T y li s ha M ..... ... .... .. .... 38 (4),250 Badino Jr. Alberto C. ........... ... .... 38 (2), 100 Balakotai a h Vemuri ........ ........... 36 (4),250 Balcarc e l R Robert... .... ... ... ... .... 37 ( 1 ),24 Barna Bru ce A .. ........ .. .... ... 36 (2),94 Barritt Amber M .................... .... 39 (4),296 Bayles Tar y n ..... .... .... ... .. 37 (2),82;(3), 1 84 Beene Jason D ... .... ... .......... .. .. .. 38 (2), 1 36 Bennewitz Marlene Roeckel von38(4) 302 B e n ya hia Farid ............................. 39 ( 1 ),62 Bernardo Fernando P. ... .......... 39 (2), 1 I 6 Be ss er Ronald S .... .... .... .. ... .. 36 (2), 160 B ev ia Fran c is co Ruiz .. ........ .... 36 (2), 156 Bh a tia Surita R. ............... .. ... .. .. 36 ( 4 ),3 10 Biernacki, Jo se ph J... ........ .... ... 39 (3), 1 86 Binou s, Housam ....... ....... .. ....... 40 (2), 140 Biro! Gulnur ... ....... ... .. ...... ....... 37 (4),300 Blau Gary ................ .................. 37 ( 4 ),3 10 Blaylock Wayne ......... ............... 38 (2) 122 Bonet Josep .. ... ......... .... ....... ..... 36 (2) 150 Bowman Christop h er .......... .. ..... 37 (2),88 Bowm a n Frank M ...... ... .. ....... .... 37(1 ),2 4 Braatz Richard D ... ... 36(3 ), l 82 ; 38 (3)17 4 Brauner Ne im a ... .. .. ...... .. ....... 37 (2), 148 Brazel C.S .................. .. .. ... .. ... ... 38 ( 1 ),8 Brenn er, James R .. .. ... .. .... ... ....... 40 ( 1 )60 Brent Rebecca .. .. .. 36 (3),20 4 ; 37 (2), 106; ..... ( 4 ),282; 38 (3),2 00 ; 39 ( 1 ),28;(3),200; ........................................ .. .. 40 (3), 17 3; Briedi s, D a ina ... .. .. ... .. ... .. 38 (4),25 0 Brown Gar y .. .. .... .......... .. .. ... 39 (4),280 Bru c e David A ....... .. .... 39 (2) 104 ;(3),238 Bullard Li sa G ........ .... .... .. ..... .. 39 (3), 194 Burke y, D a niel .. ........ ........... .... 39 (3), 1 83 Burme s ter Jeffre y A ..... .. .. .. .... 40 (3),2 11 Burrow s, Veronica .. ..... ... ....... .. 38 (2), 1 32 Butler Justin T. .. ..... .... ...... .... 39 (2), 104 338 .c Caicedo, A. Ar go ti .............. .. ....... 37 (3),228 Carmona Ximen a Garci a .. .. ....... 38 (4),3 0 2 Carney, Michael .. ...... ...... .. ...... 36 (2), 1 8 Carter. Rufu s .................... ......... 39 (4),296 Case Jennifer M .. .... 36 ( 1 ),42; 39 (4),288; 40 (4),29 1 Caspary, David W. ....................... 37 (4),262 Ca s t a ld i M a rco J. .. ... 38 (4),268; 40 (3),2 0 3; .............. ......... ............... ... ... (4),2 59 Cecc hi Joseph L. .. ... .. .... ...... ... 37(3 ) 208 Center Alfred M ...... .... .. .. .... .. 36 (4),278 Chakraborty Saikat .. .. 36 (4),2 50 ; 37 (3), 16 2 Chang Chih -Hun g .. .. .. . .. .. .. .... 37 (3), 188 C h ang Jan e P. ...... ................ .. ... 36 ( 1 ), 1 4 Chauhan, Anuj .... .. .. .. .. .. . .... 39 (4),296 Chen, B e i .............. ............ ......... 38 ( 1 ),34 C h en Wei-Yin ........... ....... 37 (1),20;(3)228 C h en Xiao Don g ... ..... 36 ( 1 ),26; 38 (3) 196 Chi, Yawu ... ........... .... .... ..... ...... 38 ( I ),34 C hin Der-Tau .. .. ..... .. .. .. .. ...... 36 (2), 144 Chou, S.T ... ......... .... ... ....... ........ 37 (3),228 Choudhary Dev as hi s h ....... ........ 40 (4),3 1 3 Chuang Steven S.C .. ................. .. 38 ( I ),34 Churchill Stuart W. .. .. 36 (2), I 16 ; 36 (4),264 Cilliers, Jan .... .... ..... .. ... ..... .. 39 (2),100 <;:inar A li .. .. .... .. .. ........ .... .. .. 37 (4),300 Ciric, Amy ...... .. .. .. .. .... .. .... ... .. 39 (2), 164 Co h e n Claude ........ ..... ........... 38 (2),82 Coker, A. Kayode ..... .. ....... .... 37 ( 1 ),44 Coker, David T .. . .... .. .. ... ... .. 37 ( 1 ) 60 Colina, Coray M ...... .. 37 (3),236; 39 ( 4 ) 250 Colto n C l ark K ..... .. .. ..... ... 39(3 ),232 Cooper Dougla s J .. .... .. .. .. ... ... 37 (2) 100 Coronell, D a n .. ..... ........ ... . .. . 39 (2), 14 2 Corti David S .... .. .. ..... ...... 37 (4),290 Crittenden B arry .. .............. ....... .. 39 ( 1 ),76 Crowe Cameron M ........... 36(1 ),48;( 1 ),60 Cruz, A ntoni o J G ... .... .... .. ..... .. 38(2 ), 100 Cussler, Edward L. .. .. ... ..... .. ...... 40 (2), 114 Cut lip Michael 8 ..... .. .. ........... 37 (2), 14 8 D da Silva Dulce Cristina Martin s. 40 (3), 1 95 Dahm Kevin D ........ .. 36 (3), 19 2;(3)2 12 ; .... ... 37 ( 1 ),68;(2), l 32; 38 ( l ),68;(4),3 1 6 39 (2),94 Dal e, France s F. ... .... .. .. .... ..... .. 40 (3),2 11 Davis Richard A ....... ..... 37 ( 1 ),74; 39 ( 1 )38 Demirel Ya sa r. .... ..... ...... 38 ( 1 ),7 4 ;(4),254 Det a more Michael... .. .. .. .. .. ... 39 (4),272 DiBia s io David ... .... ... .... .. .. ... ... 37 (4),2 4 8 Di ckso n James M ... ... ... . ... ..... .. 36 ( I ),60 Dickson Ja s per L. ............ .. .. .. .. ... 37 ( 1 ),20 Dohert y, Mike ... .. ..... 38 ( 4 ),3 08 ; 40 (2), l l 6 Don oso, Carmen Gloria ... .... .. .. .. 38 (4),302 D oraz io, Luc as .. ... .. .. .. .. .... .. 38 (4),268 Doskocil Eric J .. ... ... ... .... .. .. 37 (3), 1 96 Dougherty, D a ni e ll e ... ............ 37 (2), 100 Doyle III Francis J .. ... .. .... .. .. 40 (3), 1 8 1 Dran off, Joshua S ..... .. ... . .. .... .. 36 (3),2 16 Drwiega Jack .................... .. ...... 39 (4),296 Du arte B e lmiro ........ ..... .. ......... 40 (3), 1 95 Dube S a n jay K .................. ...... 39 (4),2~8 Dueben, Reb ecca ...... .. . .. .......... 39 (4),280 Durand Alain .. .. .... .. ... .. .. .. .. .. 39 (4),264 E Edgar Thom as F. ............ .. ... ...... 40 (3 ) 23 1 E n g l a nd Rich ard ...... ... ..... ....... ... 39 ( 1 ),76 Erkey, Can .. .. .. .. .. ... .... ... .. ... .. ... 39 ( 1 ),56 Erze n Fetanet Cey l an ... .. .... ... ... 37 (4),300 Esp ino R a m o n L. .... .... ..... ...... 36 ( 4 ),3 16 Eva n s, Geoffery M .... ... ....... .. ... 38 (3), 1 9 0 E Fahidy Thom as Z ..... .. 36 (2), 170 ; 38 ( 1 ),22 Falconer John L. ......... ... ..... .. .. .... 38(1 ),64 Fan L.T .. .. .. .. .. ... .. .... ...... 40 (2), 1 32 Farrell, Stephanie .. .. ... 36 (2), 108 ;(2), 1 38; .. (3), 1 98;3 7 ( 1 ),52,68; 38 ( 2) 108 ;(3), 18 2 .. ..... ...... .................................. 39 ( 1 ),3 0 Farrio l Xavier .. ..... ..... .. ...... ... ... 36 (2), 150 Favre Eric .. ......... .. ................. .... 39 (4),264 Fe ld er Ri c hard M .. ....... 36 ( 1 ),32;(2), l 14 ; ....... ... (3),204;(4),282; 37 ( 1 ),3 0 ;(2), I 06; (3),220;(4),282; 38 ( 1 ),32;(2), 114 ; .... ........ (3), 200;( 4) ,2 80 ; 39 ( 1 )28;(2),82; .... .. .. ... (3),20 0 ;( 4 ),2 79 ; 40 ( 1 ),38;(2),96; ........................... (2), 110 ;(3),173;(4)28 1 Fenton James M .. ... .......... ..... .. 38 ( 1 ),38 Fenton, Suzanne S ........ ............. 38(1 ),38 Fe rn a nd ezTorr es, M a rfa J .... ...... 39 (4)302 Ferr i James K ..... .. ... ..... ... ..... 37 (3),202 Fishe r David W. .......... ...... .. .. ..... 37 ( 4 ),262 F l emi n g Patr i ck J .. ... .. .. ... .... .. 36 (2), 166 F l etc her Nathan W. .... ..... .. .. ..... .... 40 (1) 40 Floyd-Smith, Tamara M .............. 40 (3),2 11 F l y nn A nn Marie ......... 39 (3),2 1 6;(4) 3 16 Fog l er, H. Scott ... . .... .. ...... ... ... .. 40 (2),99 Fo nt Josep . .. ........... .. ... .. ...... 36 (2), 150 Fo rd La u ra P ... .. ... .. .. ... .. . 37 (3), 1 70 Forres t er, Stephanie E .. .... ... .. ... 38 (3), 1 9 0 Fo ut c h Gary L. .. .... .. .. .... .. ... ... 37 (2), 1 22 Fow l er Micha e l .... ........ .. ... ..... 38 (3),236 Franks, George V. .... .. .... .. .. .. 37 ( 4 ),274 Franses Elias I. .. ... ..... .. .. .. 37 ( 4 ),290 Fraser Dun ca n M .. ... 36 ( 1 ),42; 39 ( 4 ) 288 Franzen Stefan . .. ... .. .. ... ... .. 38 (4),242 Free m a n Benn y D ... .. ..... .... .. ... 37 (1) 60 Frey Dou g l as .... .. ... .. .. ... .. 37 (2),82 Fried l y, John C. ............................. 38 ( 1 ),54 Chem i ca l E n g in eer in g Educarion

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.G Gad ewa r Sa ga r B .. ... .. ... .. .. 38 (4),308 Gat z ke Edwar d P. ... .. ... ..... ... .. ... 40 ( I ),24 Ghann a m Mamd o uh .. .. ... .. .. .. 40 (3), 1 89 Glasser Benjamin L. . . ..... ... .... 38 ( 1 ) 1 4 Glennon Brian ............... .. ........... 38 (4) 296 Gra y, J effrey J ......................... .. .. 40 ( 4 ),297 Gold s tein Aaro n S ....... . .......... 38 ( 4) 272 Goiter P a ul .. .. ... . ...... . .. .. ...... 39 ( 4) ,28 0 Gon za l ez -F e rnand ez, Cam in o .. ..... 37 ( I ), 14 Good There s a .. .. ... .............. ...... 37 (2),82 Goodin g, C h ar l es H ....... 39 (2), I 04; (2), 1 28 Good so n Mike ... ... ... ...... . .. ..... 39 (3),232 Gorowara R a j eev L. .. ...... ... .. ..... 36 (3),226 Gubbin s, K e ith E .... .. 37 (3),236; 38 ( 4 ) ,24 2 ...................................... ....... 39 ( 4) 250 Gupta Santo s h K .. .... ...... ... 36 (4),304 H Haji Shaker ... .... .......... .... ........... 39 ( 1 ) 56 Han S a n g M ... ............ .. ...... ...... 37 (3), 208 Hardin Matt ... ..................... . ... 38 (3), 1 96 Harri so n R oge r G ................ ...... 40 (4) 323 H a rt John A. IV ............... .. ........ 37 (1) 20 Har vey R o b erta .................. .... .... 38 ( 4 ) 316 H aya ti 1... .. ................ ........ .. .. .. 37 (2), 10 8 H ec ht Gre go ry B ....... ...... .. ..... 38 (2), 10 8 H e nd a, R ed h o uan e ..... .. ..... .... .... 38 (2), 1 26 H e nd erso n T o m .. ...... ..... .......... 39 ( 4 ) ,280 Hen so n Mic h ae l A. ........... .. ...... 40 (3), 181 Hern a nd ez, R afae l .......... .. ... ....... 40 (3),2 1 5 H esket h R obert P. ......... 36 (2), 1 38;(3), 19 2; 36 (3), 198 ; 37 ( I ), 52 ; 37 ( 1 ) 68; 38 (3), 182 .. .. ... .. ... .. .... 38 ( I ), 48 ; 39 ( l )30;(2) 94 Hi ck n er Mich ae l A ........... .... ...... 36 (2) 94 Hill Priscilla 1 .... .......... .. .. ...... 40 (4) 246 Hilli e r James R ... .... .. ..... .. .... 36 ( 4 ),3 04 Hil e, Ll oyd . ........ ........... .. .... 38 (2) 121 Hin estroza Juan P ............. ... ..... 37 ( 4) 3 1 6 Holl a nd C h a rle s E ... ........ .. ........ 40 ( I ),2 4 Holl a r K at hr y n A ... .. .. .. .... .. 38 (2), 10 8 Houn s l ow M.J ................. .. ..... 37 (2) 10 8 Howe-Grant Mar y E ... .. .. ....... 38 (3) 16 8 Hren y a Christine M .. ..... .. . ... .. 40 (2) 99 Huan g, Yinlun .............. ... .. ... .. .. .. 39 ( 1 ) 48 Hubbe Mart y ..... .... . .. ... ... 39 (2), 14 6 Hudson Mary B et h .. ... . ... ... .. 40 (1) 32 Hummel Scott R. .. .. ... ......... ... 37 ( 1 ),38 Hun g, Franci sco .......... ... .. ...... .. 38 (4),242 I Ib ra him T a bleb H .......... ......... .... 36 ( 1 ),68 I veso n Simon M ........ 36 (2), 1 30; 37 (4),27 4 l Jacob y William A ....... .. .. ...... ...... 37 (2) 136 J effreys Trent .............. ...... .......... 40 (3),2 1 5 J e nnin gs, G. K a n e .......... .... ........... 37 ( 1 ) 24 Fa/12006 Jim e nez Laureano .. .. ...... .... ....... 36 (2), 15 0 Madiera Lui s M .. .. .. 38 (2), 154 ;(3) 228 Jo hn sto n B a rr y S .... .. .. .. .... .... 39 (3),232 M a dih a ll y, Sundararajan .... .. ..... 38 (2), 1 36; Jo n es, Paul. .. ..... .. ... .. ... .. ......... 40 (3),2 11 ..... .... .. .. ... ... .... ..... 40 ( I ), 66 ;( 4) ,2 83 Joo Yong L ak .... .. .. .. .. .. .. .... .... 40 ( 4 ),3 1 3 Ma ga lh a e s, Fern ao D .. 38 (3),228; 40(1 ),46 Josep h B abu ..... .. .. .. .... ... .. .... .. 36 ( I ),2 0 Malone Mike . .... .. ..... .. . ... 38 (4),308 Mar c h a l-H e u ss l e r Laurent .... .... 39 (4),264 K Kear Gareth ..... .. .. .. ........... .. .. 39 ( I ), 14 Keffer, D.J .. ..... ...... ..... .. .. 37 (2), 1 56 K ei th Jason .. ..... ............ .. .......... 38 ( 4 ),282 K e ntish Sandra E ........ .. .... ........ 40 ( 4 ), 275 Khilar K .C .................................. 36 ( 4 ),292 Kimura Sh o ............................. .. 37 (3), 1 88 Koch Mar ga ret ............ .. .. ... ........ 36 ( 4 ),3 04 Kolavennu Panini K .. .. ............ 40 (3),239 K o mive s, Cla ir e .... .. .. ... .. .. .. . 38 (3),2 1 2 Kopplin Li sa L. .. .... .... .. .. .. 36 (4),304 K o r e t sky, M il o D ...... .............. ... 37 (3), 1 88 Kourti Theod ora ........................... 36 ( I ),60 Kraft Marku s ................. 39 (3),232;(3) 24 4 Kr a ntz W illi am B ...... .. .. ........... .. 38 (2) 9 4 Kuhnell Da v id R ...... .. .. .. .... ... 39 (3),238 Kulprathipanj a, A nn .. ... ...... ..... 38 ( 1 ),6 0 Kulprathipanja Santi .. ... ...... ..... 38 ( I ),6 0 Kun z, H Ru sse ll .. .. .. .. .. .. ... ... 38 ( I ),38 Kwon K y un g C. .. .. .. 36 ( 1 ),68; 40 (3) 2 1 Mardone s, Ol ga Mora ............... 38 (4) 302 Mar Ol aya, M aria d e .. ... .. .. ..... 36 (2) 15 6 Marten Mark ..... .... ....... .. ........ ... 37 ( 2 ),82 Martfnez-Urreaga, Joaq u in ........... 37 ( 1 ) 14 Marwah a, Anirudha .................. .. 40 (3),2 15 M aso n Sarah L. .............. ........... 39 (4),328 M ay, Nico le .... ..... .................... 40 (4),259 M azyc k D avid ............................ 39 (4),296 Maz zo tti, M a r co ...... .. .. .. ........ .. 40 (3), 175 McCarthy Jo se ph J ............ ... .. .. 38 ( 4 ) 292 McCullough R oy L. .... .. .. ........... 36 (3) 226 M c D o n a ld Chri s t op h er I ...... ...... 39 (3),238 M cNe il Melanie A ..... 38 (3),2 1 2; 39 (2), 1 34 M cNe ill V i v i a n Faye .. ............. 39 (3),232 M e nd es, Ade li o M .. ...... .. . .. .. .. 38 (3) 228 M e nd es, Joaq uim G ..... ..... .......... 40 ( 1 ),46 Miaoliang, Zhu .... ..... .. .. .. .. .. 36 (2) 10 2 Michaud, Denni s J. ............ .. ....... 36 (3),226 Midou x, Noe l ................. .. .. .. ....... 39 (4),264 Mira Jose .. ........ .. .. .. ....... .. .. .... ....... 37 ( 1 ), 14 Mi sov ich Michael J ............. .... 36 (4) 284 Mi sse n R o n a ld W. ......... 37 (3),222;( 4) 254 L ........................ ......... .. .. ........ 38 (3) 2 1 6 Labadie Joseph A ...... ........... .... 36 ( I ),7 6 Mit c h e ll Bri a n S ............ .. .... ...... 39 (2), 160 Lacks D a ni el J ......................... .. 36 (3),242 La Clair Darc y .. ...... .. .. ... .. ........... 37 (3), 1 80 Lam A lfr ed ........... .. ....... .... .... .. 38 (3),236 Mo g h e, Prabh as V. .. . ... ... ....... 40 ( 4 ),2 51 Moh a n Marguerit e A ...... .. ........ 40 (4) 259 Monro e, Charles ... ....... ..... ......... 39(1 ) ,42 La n e A.M ........ .. ........ .. ... .. . .. ... 38 ( 1 ) 8 Moor S Scott ........ ....... .. ..... .. .... 36 ( 1 ) 54; Law Victo r J .............. .. .. .. ... .. . 39 (2), 1 60 .............. 37(1 ),38; (3), 202 L aw r e nc e B e nj amin J .................. 38 (2) 136 Moreira A nt on i o ... .. ..... ... ........ .... 37 (2) 82 L e bduska Li sa ................ .. ........ 37 ( 4 ),248 Morri so n Faith ........ ... ... ..... .. .... 39 (2) 110 Lee-Desa ut e l s, Rh o nd a .. ........... ... 40 ( I ),32 M os ba c h Seba s tian .. .. .... .... ... .. 39 (3),2 44 Lee-Parson s, Caro l y n W.T. .... .. 39 (3), 208 Legros, R o b ert .. .. .. .. .. .... .. . 37 ( 4 ),29 6 M os h feg h ian A li akbar ... .. .. .. .. ..... 40 (1) 66 M os t o P at ri c i a .. .. .. .. ....... ... .. .... 38 (2), 108 Le Va n M D o u g l as ....... .. ................ 37 ( I ) 2 Mou ra, Maria Jo se .... ... .............. 40 (3), 1 95 L ew i s Rand y S ............ 38 (2), 136 ; 40 (] ),66 Mu ske K en n e th R .. .. 37 ( 4 ),3 06 ; 40 (3),225 Li Grace X.M ........ .. .. .. . .. .. .. 38 (3), 196 Lin Jung-Chou ........ .. .. .. ............ 38 ( I ),38 N Linder Cedric ... .. ........... . .... .. .. 39 ( 4 ),288 Lipscomb, G. Glenn ..... 36 (2),82; 37 ( 1),46 Naraghi Mohammad H .. .. ...... 39 (3),2 16 Newman John .. .. .... .. ... .... .... .. 39 ( 1),4 2 Li u X u e .. .. .. ........ .. ... ............. ...... 38 (]),14 Newe ll H e idi L.. .... .... 36 (3),2 1 2; 38 ( 1 ),68 Lobban L a n ce L. ............ .. .. .. 38 (3), 162 .... ... . .. ................ .. .... ...... .. ..... ( 4 ),3 1 6 Lombardo Stephen J ........ ... ...... 38 (2), 150 Newell, James A ... .... .. 36 (2), 10 8;(3),2 1 2; L o n g, C hri sto pher E .................... 40 ( 1 ),24 ........... .. ....... 38 ( I ),6 8; (4) 3 1 6; 39 (3),228 Lone y Norma n W. ............ ... .. .... 37 (2), 126 Newman, Austin .......................... 37 (2), 15 6 Lou H e l en H ....... .... .. ... .. .. .... 39 (1 ),48 N i e hu es Patri c ia K .. ... .... .. .... ... 39 (3) 194 Luk s Kr aemer D .. ... .. ... .. .. .. ... 36 ( 1 ) 76 Luyben William L. .. 38 (2) 142 ; 39 (3) 202 Ng Ka M ............. ... .. .......... .. .. .. 36 (3),222 Nguyen Anh V. ........................... 38 (3), 190 Nollert, Matthia s U ...... 36 ( I ), 56 ; 40 ( 4 ) 323 M Maa se, Eric L. ... .... ... .. .. ..... ...... 40 (4),283 .Q Macedo, Euge ni a A. ........... .. .. ... 38 ( I ),26 O Con n or, Kim ..... .. . .......... 39 (2), 1 24 Machniew sk i Piotr M ............ .. 38 (3) 190 O Donnell, Br e nd a n R .................. 36 (2), 94 339

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Oerther D a ni e l B ... .... ................. 36(4 ),258 s Tellez C. ... ....... ....... ................. 36 (3),206 Oh Don g H ee ( Lindsey ) ........... 39 (4),3 1 6 S a dd aw i Salm a ... .. ..... .. .. ....... ... 36(1 ),3 4 Telotte John C. ......... ...... ........ 40 (3),239 Olivera-Fuentes Claudio G ... ... .. 39 (4),250 S a likli s, Edmond P. .. ... .. .......... .. 37 ( I ), 38 Thomas Mathew .... .... .. .. ... .. .. ... 40 (3),2 15 O'Rear, Edgar A .. .... .............. .. 38 (3), 1 62 Salman, Agba D ........... ........ .. 37 (2), 108 Thom so n William J ..... .... .. ..... ... 39 (4),28 0 Ortiz. Elizabeth Parra ..... .. ... ... 38 (4),302 S a nd a ll Orvill e C. .. ..... ...... .......... 37 ( 1 ),7 4 Ting, D a l e .......... . ...... .. .... ....... .. 36 (4),304 O s t a fin Agnes E ........ ....... .. .. .... 37 (3), 1 80 Santoro Marin a .................. ... .. .. 40 (3) 175 Toma s, Christopher ... .... ..... ..... .. 36 (3),2 16 Sarai va, P e dro M ... .......... .. .. ..... 39 (2) 116 Tummala Se s hu ........ .. ........... 36 (3),2 16 f Sauer Sharon G .. .. ......... .. .... .. 38 (3) 222 Turton Ri chard .... .. ..... .. .... ....... 40 (2),88 Palanki Srinivas ..... .. ....... . ...... 40 (3),239 Savage Phillip E ...... .. ...... ... ........ 37 (2),94 Panjapomp o n Chanin .... .. .... .. .. 40 ( 1 ),40 S ave lski Mariano J ... .... 36 (2), 108 ;(3), 192 ; ll Papadopoulo s, Kyriakos .. 36 (2),88;( 4) ,3 16 .. 37( I ),68; 38 (3), 182 ; 39(1 )3 0 ; 39(2) ,9 4 Uygun Karkut ........ ......... .. .. ... 39 ( 1 ),48 Park Y oo nKo ok ....... .... .. ... .. .. 36 ( 1 ),68 Sayari Abdelhamid ...... ......... ...... 38 ( 1 ),34 Park er, R o b e rt S ......... 38 (4),292; 40 (3), 1 81 Scarbrough Will J .. .. .. ....... ........ 40 (4) 291 y Parulek a r Satish J ....... 38 (4),262; 40(1 ),14 Schmedlen R ac h ae l.. .. .. .......... 39 ( 4 ), 272 van der Lee Jame s ..... .. .... .. ... .. 40 ( 1 ),54 Patel Dherme s h V. .. .. .. .. ... .. 37 (2), 10 8 Schmid Han s-Joac him .............. 36 (4),272 Va hdat Nader ... .. .. . .. .. ...... 40 (3) 2 I 1 Paulaiti s, Mich ae l E. .. .. .. .......... 36 (2), 1 66 Schmidt Hartl ey T .. .......... .. ..... ... 37 ( 3) 180 Va n Wie B e rni e .. .. ... ... .. .... ... .. 39 (4),280 Payne Greg ory ... ... .. .... .. .... .. ... .. 37 (2),82 Schmidtke David W. ...... ........... 40 (4),323 Var m a, Arv ind .. .. .. .... .... .. ........ 37 (4),28 4 P e dro sa, Cristiana ....... .. ... .... .. .. .... 40 (1) 46 Schmitz Ro ge r A ... .. ..... 36(1 ),34;(4) 296 Visco Jr. Don a ld P .... 36 (2), 1 34; 39 (4),258 Peep l es Tonya L. ....... .. .. ......... 37 (3), 1 74 Schowalter W.R .................. ... .... 37 (4),2 42 Pena J .A .... .. .. .. ... .. .. ... . ........ 36 (3),206 S c hreiber Loren B ... ............... .. 38 (4),286 .w Peretti St eve n W. ..... ....... .. .. .. ... 39 (3), 194 P e rkin s, Dou g la s M ............... .. .. 39 (2),104 Peukert Wolf ga n g ....................... 36(4 ),272 Pier so n Ha ze l M ........ .. ... ........... 39 (2), 156 Pilu so, Christina .......... .......... ....... 39(1 ) 48 Pinheir o, Maria Nazare Coelho ... 40 (3),195 Pinho, Simao P. ..... ....... .. ..... .. .. 38(1 ),26 Pitt Martin 1... .. .. .............. 37(2 ), 108 154 Plouff e, P.B ........ .. .. .. ......... .. .. 37 (3), 162 Prabhakar R ajeev ......................... 37 ( 1 ),60 Pri ce, Dou g l as M .. ... ... .. ........ 39 (2), 15 6 R Rao Go v ind ................ .. ............. 37 (2),82 Ra s teiro Maria G ....... ... .. .. .... .. 39 (2) 11 6 Rech S a bin e ....... ... .. 38 (3),2 1 2; 39 (2), 1 34 Reijen ga, J etse C. ............... ... .. 37 (2), 114 Reill y, Peter J ......... ................. 36 (3), 17 8 Rhode s, Martin ............. .. ........ .. 36(4 ),288 Rice Rob er t ... .... .. .. ..... ............ 37 (2), 100 Rice Richard W. ... .. ...... .. .. .. .. .. 39 (3),238 Rivera D anie l E .. .. .. .... .. .... ... .. 39 ( 4 )302 Ri ves, Christopher.. .... .. ...... ..... ... 36 (3),242 Robert s, Su sa n ............. ........... .. 39 (3),222 Robinson Janet E. ... .... .. ..... .. .... 37 (2), 154 Robinson K e n K. .... ... . .. .. ........ 36 (3),2 16 R oc h efort Skip ................. .. ...... 37 (3), 1 88 Rock straw, D av id A ..... .. ............. 39(1 ),68 Schulp John R ............. ......... .. 40 (2), 13 2 Schultz, Jerom e ......... .. ..... .. ..... 40 (2), 1 26 Scud e ri, Phillip .. ..... .... .. ...... ... 39 (4),280 S e lm e r Anders ....... .. .... ......... .. 39 (3),232 Sen Siddhartha .. ... .. .. .. .... ..... .... 39 (3),2 32 Shacham Mordechai .. ....... ...... 37 (2), 14 8 Sh aefe r Stac ey .. ... . .... .. .. ... ... 39 (3),2 16 Shaeiwitz Joseph A .. .. ....... ........ 40 (2), 88 Shallcros s, D av id C. ... 37 ( 4 ),268; 40 ( 4 ),27 5 Shambau g h Rob ert L. ................. 38 (3) 162 Shan er, Cyndi e .. ...... ............. .. 37 (3), 18 8 Shanley Ed S ........................ ..... 38 (3), 188 Sheardown Heath e r .. .. .............. 36 ( 1 ),60 Shonnard David R .. .. ................. 37 (4),262 Shulman Stacey ...... ... .. .. ...... .. 37 (3) 162 Sides P a ul J ........ ......... .. .. .. .. ... 36 (3),232 Siepe, Hendr y ... ... . ....... ......... ... 37 (2), 114 Sikavitsas Vassilios I. ... ... .. .... 40 (4),323 Silv e r s tein D av id L. ................. 37 (3),2 14 Simmon s, Christy M ........ .. .. .. ..... 36 ( 1 ), 68 Simon Laurent... .. .. .... ...... ........ 37 (2), 126 Sin Aaron .. .............. .. ....... ... .. 36 (4),278 Slater C. St ewart .......... 36 (2), 1 38; 37 (1 ) 8; 37 ( 1 ),52,68; 38 (1),48 Sloan Dendy .. .... .... ....... .... ... .. .. 38 (3) ,2 03 Smart, Jimmy L.. ...... 37 (2), 142 ; 38 (3),2 04 Smith Willi a m R .... ...... 37 (3),222;(4),254 S oro u s h Ma so ud ....... ...... ............. 40 ( 1 ),40 Wagner Wolfgang .. .... .. ... .. ... 39 (3),24 4 Walsh Frank .. .. ... .. ... .. .. ........ .. 39 ( 1 ), 14 Wang Chi-Hwa ... . .. .... .. ..... 37 (2), 114 Wankat Phillip .. 37 ( 4 ),3 I 0 ; 38 (1 ),2; 40 (3); .. ... .... ... .. ..... ... ..... ...... .. ... 40 (3), 1 65; W e i ss, Alvi n H .. ... ........... ... .... 36 ( I ) 74 Weiss Bri a n .. .. .. .. ........... ........ 40 (3),203 W es t Kate ....... ..... .. ................. 39(4 ),288 Wh ee l er, D ea n R. .... ... ........... ..... 39 (2), 138 Wheelock Thomas D ............. ... 36 (3), 17 8 White, Shannon H ............... .. .. 39 (3), 194 Whitrnire, D av id .............. ... ...... 38 (2), 1 22 Wiest, J .M ... ............................. .. .... 38(1 ),8 Wilcox Jennifer .. ..... ............. ... .. 40 (4),268 Wilken s, Bob ... ..................... ... 39 (2),164 Willey R ona ld .... .. .. .. 38 (3), 188;39 (3), l 83 Winter H H e nnin g .............. . .. 36 (3) 1 88 Wood Philip E .... ... ...................... 36 (1),60 W oo d s, Donald R. ............. 36 ( 1 ),60; 40 (2) W o rden R. Mark ....................... 38 (4),250 Wright Pamela .... ... .. ....... .... .. ..... 38 ( I), 14 y Yabo Dong .. ............................ .. 36 (2), l02 Ying Chao-Ming .. . .. .. ... .... 36 ( 1 ),20 Young Br e nt .. .. . .. .. ... .... .... 40 ( I ), 54 Young R a lph ...... ... ...... ... ......... 40 ( 1 ),32 Rodri g ue s, Alfrio ..... ... .... .......... 38 (2), 154 Rogers Brid ge t R ... ....... .... .. .. ..... 37(1 ),24 Roizard Christine .... .. ...... .. ..... 39(4 ),26 4 Roja s, Orl a ndo ... ......... .............. 39 (2), 146 Rollin s Sr., Derrick K ......... .. ...... 40 ( 4 ),29 1 Ro ss, Juli a M .... ........ ..... 37 (2),82;(3), 184 Roth Charles M .... .. .. ........ ........ 40 (4),25 1 Ruiz Joaquin ............................... 39 ( 1 ),22 Ru s li Effendi ..... 38 (3) 174 Ru sse ll John J Sotudeh-Gharebaa g h Rahrnat ... 36 (2), 100 Sousa Jo se M ... ........... .............. 38 (3),228 Spencer Jordan L.. .. .. ... ...... ... .... 40 (3), 159 Sriniva sag upt a, D ee pak ................ 36 ( I ),20 Stoynova, Ludmila ............... .. .. 39 (2), I 34 Streicher Sam a nth a ....... ... ..... .... 39 ( 4) 288 Subramanian Venkat R .. ........ .. 40 ( 4 ) 307 Sur es hkumar G.K. ... .. 36 (4),292; 38 (2), l 1 6 Svrc ek, William .......... .. .. ......... 40 ( I ), 54 z Zhang, Tengyan .... ..... .. .... .... .. .. 40 (2), 132 Zheng Hai s han .. .. ... .. ....... ..... .. 38 (4),282 Zydney, Andrew L. .. .... .... ..... .. 37 ( I ),33 Zy go ur akis, K yriacos .. ... ...... ... ... 38 (2),88 37 (3),2 08 I Ru ss um Jame s P. ... .. .. ... .. .. .. .... 36 (2), 1 34 Tanguy Philipp e A. ............ .. .. 37 (4) 296 340 Che mi ca l Engineering Educa t ion

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CEE's Annual Fall Graduate School Information Section Published in February, May, August, and November of each year for the past 40 years, Chemical Engineering Education (CEE) is the premier archival journal for chemical engineering educators. The schools listed in the following section have all demonstrated their support of CEE b y purchasing advertising in our annual Fall Graduate School Information issue. The fall advertising issue serves as the journal s primary means of revenue, enabling its ongoing service to the field. We are exceedingly grateful to all of our faithful advertisers. To sign up t o adve rtis e your school s chemica l engineering graduate program in the 2007 2008 Fall Graduate S c hool Information issue, pl ease fill out the information below a nd fax or m ai l this page to our edito rial office a t (352) 392-0861, Chemical Engineering Education, c/o Chemical Engineering Dept. University of Florida, Gainesville, FL 32611-6005 D ea dlin e for adver ti si n g is Jul y 1 of eac h year. If questions, write cee@c h e .ufl .e du School:-----------------------------------Contact per so n: __________________________________ Address: Fax number: e-mail: Fa/12006 ______________ Telephone number : ____________ 3 41

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342 INDEX Graduate Education Advertisements Akron U ni ve r s it y of ......... ................. ............. .. .. .. ........ 3 4 3 Alaba m a, U ni ve r s it y of ............ .. .. ............ .. ... .. ...... .. ....... 344 Alabam a Hunt sv ill e, U ni ve r s it y o f .......... .. Arizona, U n iver s it y of ..... Arkan s a s, U niver s it y of Auburn U ni ve r s i ty .. Bu c kn e ll U ni ve r sity .... 345 .. .. ........ .. .. .. 3 46 .............. 3 47 348 .. 432 Ca li fo rni a, B e rkel ey; U ni ve r s it y of ..... ..... ... .. ................ .. ...... 3 49 Ca l ifornia, Da v i s; U n iv e r s i ty of .... ..... .. ...... .. ..... 3 50 Ca li fo rni a, Ir v ine ; U ni ve r s it y of.. ... ... ....... .. .... ...... ... ..... .. .......... 3 5 1 Ca l ifornia Ri ve r s id e; U ni ve r s i ty of. .. .. ...... ...... .. .. ..... 3 52 Ca li fo rni a, Santa Barbar a; U ni ve r s it y of... Ca li fo rni a In s titute of Techno l ogy .. ... .......... .. Carn eg i eM e ll on U ni vers i ty ........... Ca se W es tern R e s e r ve Un i ve r s it y ......... .. .. ...... Cit y Co ll ege o f New Y ork .................. C l eve l a nd State Un i ve r si t y .. .. ........... .... 353 .......... .. .. 354 .... .. ........ 3 55 .... 438 Co l o rado Schoo l of Min es ..... .. .. .. .... ... ...... ..... 358 Co l orado S t a te U ni ve r s it y ............ ...... .. .. ... ..... .. .. .. .. ... ... 359 Co lumbi a U ni ve r s it y ...................... .. .. .. .. ...... 4 32 Co rn e ll Un i ve rsity .. .. .. .. .. .. .. .. .. ... ........ .... .... .. ....... ... .. .. 360 D artmo uth Co ll ege ......................... .. .. .. ......... 36 1 D e l awa r e, U ni vers i ty of. ................. .. .. .. .. ............. .. ..... .. ........ 362 D e nm a rk Tec hn ica l U ni ve r s it y of .. ........ .. Dr exe l U ni ve r si t y .............................. F l o rid a, U ni ve r s it y of ............... ....... Florida In s titut e of T ec hn o l ogy .......... .... .. Geor g ia In s titut e of Te c hn o l ogy .... .. .......... ... 363 ..... 364 .... . ... ....... 36 5 ..... .. .. .... ..... 366 .. .. ........... .. .. .. .. 367 H o u s ton U ni ve r s i ty of ...................... .. .. ............ .... 368 ....... 369 ....... 37 0 Illin o i s, C hi cago; U ni vers it y of .. .. .. .. .............. Illin o i s, Urba n a C hamp a i g n U ni ve r s it y of .. .......... Illinoi s In s titute of Te c hn o l ogy. .. .... .. . .. ...... .. 37 1 ... 372 ... 373 .. 374 I owa, U ni ve r s ity of .. .. ... I owa S t ate U ni ve r s it y Kan sas, Un i vers it y of .................. ... Kan sas Sta t e U ni ve r s it y ....... ....... .. .......... 37 5 K e ntu c k y, Uni v ers it y o f ... .......... .. . ................ .. .. ... 3 76 L ama r U n i ve r s it y ... .. .. L av a l Un i ve r s ity ........... ... ...... .... ........... ..... 433 377 .... 378 ... 379 L e hi g h U ni ve r s it y ..... L o ui s ian a State U ni versity M a in e, Univers it y of... ................ . .. ...... .. ....... 38 0 Manhattan Co ll ege .... .. .... 38 1 .... 382 ..... 383 M ary l and Baltimore Co unt y; U ni ve r s it y of . Ma ssac hu setts, Amher s t; U ni ve r s it y of Ma ss a c hu se tt s, Lowe ll ; U ni vers it y of .. ..... .. .. ........ ... .. .. .. 4 38 Ma ss ac hu se tt s In s titut e of T ec hn o l ogy ........ .. .. .. .. ...... 38 4 M cG ill U ni ve r s it y................. .. .. .............. ....... .. ... .. ....... 385 M c Ma s ter U ni ve r s ity ... .. .. .. .... .. .......... .. .. ..... .. ......... .. .. .. .... 386 Mi c hi ga n U ni ve r s it y of. .... .... .. .. .. ........... Minne so ta U ni ve r s it y of ........... ... ............. Mi sso uri Co lumbi a; U ni ve r s it y of ........... .. ...... .. ..... 387 388 389 Mi sso uri R o l la ; Univer s it y o f .. .. ... .. ..... .. .... ..... 390 M o na s h U ni ve r s it y ................... .. .... 433 Montana Un i vers it y of... .... ...... ... .. .. .. .. .. ...................... .... 434 New M exico, Univer s it y of .......... ...... ............ New M ex i co S t ate U ni ve r s i ty ....... .. .. .. ..... o rth Caro lin a Stat e U ni ve r s it y Nort h D akota, University of .. .. Nor th eas t e rn U ni ve r s it y ... ............... .. ............ 39 1 .... 392 ..... 393 .... .. .. 434 ............ ... 394 Northwe s t e rn U ni ve r s it y ....... .. .......... ........... .. .. 395 No tr e Dam e, Un i ve r s it y of ............ . .... .. ... ........ ............... 396 O hi o St ate Univer s it y...... ... .. .. ... .. .............. .. ... .. 39 7 ....... .. 398 ... .. 399 ... .400 .... ...... 40 1 ........ 402 ... 40 3 Ok l a h o m a, U ni ve r s i ty of ................ .. .. .. ...... .. .. Okla h o m a State Unive r s ity P e nn sy l va ni a State Un i ve r s it y ... Pol y t ec hni c Unive r s it y Prin ce t o n U ni ve r sity ..... .......... Purdu e U n ive r s ity .. .. . R e n sse l ae r P o l y t echn i c In s titut e Ri ce Unive r s ity .... ......... .................... R ochester Univer s it y of.. ........... ... .. .................. .... .. 404 .405 .406 R oseHui man In stitute of T ec hn o l ogy ......... .... ... .. .. .. ... .. . 435 R owa n U ni ve r s it y ................. .. .. ... .. . .. ... .... .... ................ 407 R ye r so n U ni ve r s ity ............................................. .. .. .. ...... .435 Sin ga por e, ational U ni vers it y of ... .. ..... ... ...... ...... .40 8 .. 40 9 Sin g apor eM IT Alliance Grad u a t e Fello ws hip .. South Caro lin a U ni versity of South Flo rid a, U n ive r s it y of Southern Ca li fornia U ni ve r s it y of .. .. .. .. ............ ..... .. .4 1 0 ..... .. .... .436 ... .41 1 State Uni ve r s it y of New York ..................... ... ..... .. .... 4 1 2 Steven s I nstitute .............. .... .4 1 3 T e nn es see, U ni ve r s it y of .4 1 4 T e nn essee Tech n o l ogica l U ni ve r s ity ......... .. ....... .. ......... .415 .416 .4 1 7 T exas a t A u s tin University of T exas A&M U ni ve r s it y T exas A&M Kin gsv ille T exas T ec h U ni versity .. Tol e d o, U ni ve r s it y of. .. ........ ... 436 ... 41 8 .. .4 1 9 Tuft s U ni ve r s it y ........................ .... . .. .............. ...... .420 Tulane U ni ve r s ity .. .. .. .. .. .. .. ... ... .. .42 1 Tul sa, U ni ve r s it y of ........... .......... .... .. .. .. ... . .. ... ........... ....... 422 Vanderbi lt U ni ve r s it y .................... .... ..... .. ... Vi ll ano va U ni ve r si t y .......... ... ......... .. ...... .. ... .. Vir g ini a, Un i ve r s it y of ....... ............ .. Vir g in i a T ec h ................................ . Wa s hin g ton U ni ve r s ity of.. ............. Wa s hin g t o n State U ni versity .......... ... .. Wa s hin g ton U ni vers it y .. .. .. .... . .. ........ .. .... . .42 3 ..... .4 37 .. .. ... .424 ... ...... .425 ... .426 .... ....... 427 ............ .. 4 28 Waterl oo Univer s it y of ................ .... ........ ... .... ..... ... .. ....... 4 37 We s t Vir g ini a U ni ve r s ity .. .. .. ..... .. ........ ....... .... .. .. . 429 Wi sco n s in Un i versity of .. .... ....... 430 W yo min g, U ni v er s it y of .... .................. 438 Y a l e U ni versi t y ........ .......... ......... .. .. . .. .. 43 1 Che mi cal Engi n ee rin g Edu ca 1i o 11

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Graduate Education in Chemical and Teaching and research assistantships as well as industrially sponsored fellowships available I n addition to stipends, tuition and fees are waived. PhD students may get some incent i ve scholarships The deadline for assistants h ip app l ications is Apri l 15t h Biomolecular Engineering G. G. C HASE Multiphase Proce sses Fluid Flow I nterfacial Phenomen a, Filtration Coalescence H.M.CH EU NG anocomposite Materials, Sonochemical Pro cessi n g, Polymerization in anostruc tured Fluid s, Supercritical Fluid Pro cess ing S. S. C C H UA NG Catalysis, Reaction Engi neering Environmentally Benign Synthesis, Fuel Cell J. R. ELLIOTT Mo l ecular Simulation, Phase Beha v ior Phy s ica l Properties Proce ss Modeling Supercritical Fluids E. A EVA NS Materials Proce ssing and CVD Modeling Pla s ma Enhanced Deposition and Crystal Growth Modeli n g L.-K. JU Bioproce ss Engineering Environmental Bioen g ineering S. T. L OPINA BioMateria l Engi n eering and Po l ymer Engineering B.Z. N EWBY Surface Modification Biofilm and AntiFou l ing Coatings Gradient Surfaces H .C. Q A MM A R Nonlinear Contro l Chaotic Processes, Engineering Ed u cation P.W AN G Biocatalysis and Biomaterial s (A djunct ) For Additional I nformation, Write Fall 2006 Chairman Graduate C ommittee Department of Chemical and Biomolecular E ngineering The U ni v er s i ty of A kron A kron OH 44325-3906 Ph o n e (330) 972-7250 Fax (330) 972-5856 www.c h emical. u akron.edu 343

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THE UNIVERSITY OF ALABAMA Chemical & Biological Engineering A dedicated faculty with state of the art facilities offer research programs leading to Doctor of Philosophy and Master of Science degrees. Research Areas : Biomaterials, Catalysis and Reactor Design, Drug Delivery Materials and Systems, Electrohydrodynamics, Electronic Materials Environmental Studies, Fuel Cells, lnterfacial Transport, Magnetic Materials, Membrance Separations and Reactors, Molecular Simulations Nanoscale Modeling Polymer Processing and Rheology, Self-Assembled Materials, Suspension Rheology For Information Contact : Director of Graduate Studies Department of Chemical and Biological Engineering The University of Alabama Box 870203 Faculty : G. C. April, Ph.D. (Louisiana State) D. W Arnold, Ph.D. (Purdue) C. S. Brazel, Ph.D. (Purdue) E. S. Carlson, Ph.D. (Wyoming) P. E. Clark, Ph.D. (Oklahoma State) W C. Clements Jr., Ph.D. (Vanderbilt) A. Gupta, Ph.D. (Stanford) D. T. Johnson, Ph D. (Florida) T. M. Klein, Ph.D. (NC State) A. M. Lane, Ph.D. (Massachusetts) M. D. McKinley, Ph.D. (Florida) S. M. C. Ritchie, Ph.D. (Kentucky) C.H. Turner, Ph.D. (NC State) J. M. Wiest, Ph.D. (Wisconsin) M. L. Weaver, Ph.D. (Florida) Tuscaloosa, AL 35487-0203 Phone: (2 05) 348-6450 An equal employment I equal educational opportunity institution 344 Ch e mi c al En g in ee rin g Edu c ati o n

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Chemical and Materials Engineering Graduate Prograni Pacu{ty and
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FACULTY/RESEARCH INTERESTS ROBERT G. ARNOLD, Profe s sor (Ca lTe c h ) Mi cro biologi ca l H azardous Waste Tr ea tm en t Merals Speciation and Toxicity Chemical and Environmental Engineering PAUL BLOWERS Associate Prof esso r ( Illinoi s, Urbana-Champaign) Chemical Kin etics, Ca tal ysis, Su jace Phenom e n a, Green Design at JAMES C. BAYGENTS A ssoc iate Profes so r ( Princeton ) Fluid M ec hani cs Transport a n d Colloidal Ph enomena, Bioseparations ARIZ(5NA WENDELL ELA, Associate Profe ss or (S tanford ) P article -Parti cle 111 e ractions Environm e ntal C h e mistr y JAMES FARRELL, Profes so r ( St a nford ) Sorption / desorption of Organi cs in Soils JAMES A. FIELD Professor ( Wa ge nin ge n U ni vers it y) Bi oremediation Mi c r obiology, Whit e R ot Fun gi, H aza r dous Wast e ROBERTO GUZMAN Professor (No rth Carolina St a te ) Affinity Protein Separations, P o l y meric Su r face Sci e n ce ANTHONY MUSCAT Associate Pro fessor ( Stanford ) Kin etics Swfa ce C h emistry Surface Engineering Semicond u c t or Pr ocessing, M icrocontamination KIMBERLY OGDEN, Profe sso r (Co lorado ) B ioreactors, Bioremediation, Organi cs R emov al from Soils THOMAS W. PETERSON, Professor a nd D ea n (Ca lT ec h ) Aerosols, Ha z ardous Wast e I ncineration, Mi croco 111amination ARA PHILIPOSSIAN Profe ssor (T u fts) Chemical / Mechani c al P olishing, Semiconductor Pr ocessing EDUARDO SAEZ Profe sso r (UC, D av i s) P olymer Flow s, Multiphase R eac t ors, Colloids GLENN L. SCHRADER, Profe sso r & Head ( Wi sco n s in ) Catalysis, Environm e ntal S u s t ainability, Thin Films, Kineti cs FARHANG SHADMAN, R ege nt s' Profes so r ( B e rk e l ey) R eaction Engineering, Kin e ti cs, Catalysis, R eactive Membranes Micro conta mination REYES SIERRA, Associate Pro fesso r ( Wa ge nin ge n U ni vers it y) Environmental B io t ec hn ology, Biotransfonnation of M e tal s, Green Engineering 346 For further infonnation http: / /lvww.chee.a r iwna.edu or wr it e Chairman Graduate Study Co mmitt ee Department of Chemical and E11viro11111e11tal E11gi11eeri11g P.O BOX 210011 The Un iv ers it y of A ri z ona T11cso11 ,A Z 85721 The Universi l y of Arizo n a i s a n equal o pportunit y e du ca li ona l in s ti1u1i o n / equal opport uni l)' e mplo ye r Wome n a nd minoriti es are enc o ura ge d 1 0 apply. TUCSON ARIZONA The D e partment of C hemi ca l a nd Environmental E n g in ee rin g at th e Un i ve r s it y of Ar i zo na o ff e r s a w ide range of re sea r c h opportunities in all major areas of c hemi ca l e n g ine er in g a nd e nvironm e nt a l engi n eering. The departm e nt offers a fully accre dit ed und e r gra duate de g r ee in c h e mical e ngin eeri n g, as well as MS a nd PhD de g ree s in both c h e mic a l and e n v ironm e ntal e n g ineerin g. A sign ifi ca nt portion of re searc h effo rt s i s d evo t ed to area s at the boundar y b e twe en chemica l and environmenta l engineering includin g e n v ironm e ntall y beni g n semicond u ctor manufacturin g, e n v i ronmenta l r e mediation e nvironmental biot ec hn o lo gy and no ve l water tr ea tment tec hn ologies. Financial support i s available through fellowships government and indu s trial grants and contract s, teaching and re sea rch assistantships. Tucson has an exce ll en t climate and many r ec r ea tional opportunities. ft is a growi n g modern c i ty that r e tains much of th e o ld South we st e rn atmosphere Chemical Engineering Educa t ion

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Graduate Program in the Ralph E. Martin Department of Chemical Engineering University of Arkansas The Department of Chemical Engineering at the University of Arkansas offers graduate programs leading to M.S. and Ph.D. Degrees. Qualified applicants are eligible for financial aid. Annual departmental Ph.D. stipends provide $20 000, Doctoral Academy Fellowships provide up to$25 000 and Distinguished Doctoral Fellowships provide \$30,000. For stipend and fellowship recipients all tuition is waived. Applications received before April 1 will be given first consideration Areas of Research [] Biochemkal engineering [] Biological and food systems [] Biomaterials [] Electronic material s proces s ing [] Fate of pollutants in the environment [] Hazardous chemical release consequence analysis [] Integrated passive electronic components [] Membrane separations [] Micro channel electrophore s i s [] Mixing in chemical processe s [] Phase equilibria and process design Faculty M.D. Ackerson R.E. Babcock R.R. Beitle E.C. Clausen R.A. Cross J.A. Havens C.N. Hestekin J.A. Hestekin J.W. King W A. Myers W R. Penney T.O. Spicer G.J. Thoma J.L. Turpin R.K. Ulrich For more information contact Dr. Richard Ulrich or 479-575-5645 Chemical Engineering Graduate Program Information: http: // www.cheg uark edu / graduate.asp F a ll 20 0 6 34 7

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348 AUBURN UNIVERSITY Chemical Engineering W. Robert Ashurst University of California, Berkeley Mark E. Byrne Purdue University Robert P. Chambers University of Ca lif o rni a, Berkeley Harry T. Cullinan Carneg i e In stitute of T echno l ogy Christine W. Curtis Florida State University Virginia Davis Rice Uni versity Steve R. Duke University of Illinois at Urb ana-Champaign Mario R. Eden Technical University of Denmark Ram B. Gupta University of Texas at Austin Thomas R. Hanley Virginia Tech Institute Gopal A. Krishnagopalan University of Maine Yoon Y. Lee I owa State University Glennon Maples Oklahoma State University Ronald D. Neuman Th e Institute of Paper Chemistry Timothy D. Placek University of Kentucky Christopher B. Roberts University of Notre Dame Arthur R. Tarrer Purdue University Bruce J. Tatarchuk University of Wisconsin Jin Wang University of Texas at Austin SAMUEL GINN COLLEGE OF ENGINEERING Auburn University 1s an equal opportunity educallonal institution / employer. Research Areas Alternative Energy and Fuels Biochemical Engineering Biomaterials Biomedical Engineering Bioprocessing and Bioenergy Catalysis and Reaction Engineering Computer-Aided Engineering Drug Delivery Energy Conversion and Storage Environmental Biotechnology Fuel Cells Green Chemistry Materials MEMS and NEMS Microflbrous Materials Nanotechnology Polymers Process Control Pulp and Paper Supercritical Fluids Surface and lnterfacial Science Sustainable Engineering Thermodynamics Ch e mi c al En g in ee rin g Edu c ation

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UNIVERSITY OF CALIFORNIA, BERKELEY The C h e mi ca l E n g ine e rin g Department at the U ni vers ity of Ca li fornia B e rk e l ey o n e of the preeminent departments in the field offe r s graduate programs l eading to the Master of Science and Doctor of Phi l osop h y. St ud ents a l so have the opportunity to take part in the man y cultural offerings of the San Fran cisco Bay Area and the recreational act i vities of Ca liforni a s n o rth ern coast and mountains. FACULTY Nitash P B a l sara A l ex i s T. B e ll Harvey W Blanch E lt o n J Ca irn s Jhih-W e i C hu Douglas S. Clark J ea n M.J. Frechet David B. Graves Enri qu e Iglesia A l exan d er Katz Jay D Keasling Ro ya Maboudian Susa n J. Muller John S. Newman John M Prausnitz Clayton J. R adke David V. Schaffer Rachel A. Sega lman FACULTY RESEARCH INTERESTS BIOCHEMICAL & BIOLOGICAL ENGINEERING Blanch, Chu, Clark Keasling Muller Prausnitz, Radke & Schaffer CATALYSIS & REACTION ENGINEERING Bell Iglesia, Katz & Reimer ELECTROCHEMICAL ENGINEERING Cairns, Newman & Reimer ENVIRONMENTAL ENGINEERING Bell Graves, Iglesia, Keasling, Newman & Prausnitz MICROELECTRONICS PROCESSING & MEMS Graves, Maboudian, Reimer & Segalman POLYMERS & SOFT MATERIALS Balsara Chu Frechet Muller Prausnitz Radke Reimer & Segalman ADJUNCT FACULTY An dr eas Acr i vos Brian L. Maiorella LECTURERS Moshe Ste rnber g Stacey L Zones Arnold L. Grossberg Paul 8 Plouffe P. Henrik Wallman PDP EXECUTIVE DIRECTOR Keith A l exa nder C h air: J effrey A Reim e r Starting in Fall 2006 the Department of Chemical Engineering will initiate an innovative new Product Develop ment Program (PDP) aiming to expose graduates of chemical engineering and related disciplines in the com plex process of transforming technical innovations into commercially successful products PDP students will gain exposure to real-world product development practice in a range of chemical process-intensive industries includ ing biotechnology microelectronics nanoscience and consumer products PhD certificate and Master s degree programs will be offered For more information call PDP Executive Director Keith Alexander at (510) 642-4526 or go to : http ://c heme berkeley.edu / PDP / overview.html F a /12006 FOR FURTHER INFORMATION, PLEASE VISIT OUR WEBSITE: http://cheme.berkeley.edu 3 4 9

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Ma rk Asta, Professor Ph.D., University of California, Berkeley, 199 3 Computational materials sciellce, surface and interface science, phase rransformalions, computer assisted materials design David E. Bl ock.Associate Professor P h .D., University of Minnesota 1992 l ndustrialfermelltatioll, bioprocessoptimiza rioll and artificial intelligellce methods Roger B Boulton Professor and Endowed Chair Ph.D ., U ni versity of Melbourne, 1976 Wille technology,Jermentatiion killetics, biochemical N igel D, Brownin g, Professor Ph.D., University of Cambridge, U.K., 1 992 Materials structure-property relatiollships at atomic-scale, atomic resolutioll and sensitivity imaging, electron microscopy S teph a ni e R. Dungan Professor Ph.D., Mas sac hu se tts In stit ute of Technology, 1992 Thermodynamics and transport ill micellar alld microemulsions systems, surfacta/11 illteractions with biological a11d food macromolecules Nae l E l-Farra ,Assistant Professor Ph.D ., University of California, Los A n geles 2004 Pro cess systems ellgilleering, with emphasis Oil process colltrol, dynamics alld design, computatio,111/ modeling, simulatioll Roland Faller, Associate Professor Ph.D. Max-Planck I nstitute for Po l y m er Re searc h 2000 Molecular 11wdeling of soft condensed matter Bruce C. Gates, Di st in g uished Professor Ph.D. University of Washington Seattle, 1966 Catalysis, surface chemistry, catalytic materials, IIOllOmaterials, kinetics, chemical reaction ellgineering Jeffery C, Gibeling, Professor Ph D ., Stanford University, 1979 Defomwtion, fracture and fatigue of metals, layered composites and bone Joanna R. Groza, Professor Ph.D ., P olytechnic Institute, Bu charest, 1972 Plasma activated sintering, processing of llanostmctured 11111terials, and microstruc tur e c haract e rization Brian G, Higgins, Profossor Ph.D., U n iversity of Minnesota 1980 Fluid mechanics and illlerfacial phenomena, sol gel processing, coatillg jiows David G. Howitt, Professor Ph.D., University of California Berkeley 1976 Forellsic and failure analysis, electron microscopy, ignitioll and comb u stio n processes in materials Alan P. Jackman, Professor Emeritus Ph.D ., University of Minnesota, 1968 Biochemical engineerillg, bioreactor design and kinetics, plant cell cultu res ellvirollmental engineering, modeling transport in the environme/11, environmelllal sorption process, bioremediarion Sa ngtae Kim, Assistant Professor Ph.D. University of Hou s ton 1999 Transport ki11etics in adva11ced oxides solid oxide fuel cell, gas separation, membrane reactors Tonya L. Kuhl, Associate Professor Ph.D. Unive111ity of California, Santa Barbara 1996 B ionmterials, membra11e interactions, intermolecular and intersurface forces in com ple x jiuid systems E nriqu e J. Lavemia, Professor Ph.D. Massachusetts In stit ute of Technology, 1986 Symhesis of structural nu1terials and composites, nanostrucfllred 111aterials and composites, thermal spray processing Ma rjorie L. Longo,A ssocia te Professor Ph .D. University of California, Santa Barbara 199 3 H ydrophobic protein design for active control, surfactant microstrucn,re, and interaction of proteins and DNA with biologi cal membranes Karen A. McDona ld Professor Ph.D. University of Maryland, College Park 1985 Biochemical engillee ri11 g, plant cell cult11res, cyanobacterial cultures A mi y a K. Mukherjee, Distinguished Professor D.Phil. University of Oxford I 962 Mechanical behavior, creep superplasricity, nanocrystalline metals a11d ceramics Zuhair A. Munir, Di stinguished Professor Ph D ., University of California, Berkele y, 1963 Sy111hesis and processing ofma reria/s ,fie ld effects i11 mass tra11sport, nanostrucrures, composites and FGMS simulation of field-activated symhesis A le xa ndra Navrots k y, Distinguis h ed Professor and Endowed C h air Ph D. U ni ve111ityofChicago 1967 Thermodynami cs of solid materials nanomaterials plwse equilibria and metastability, high-temperature calorimetry Ahmet N, Palazoglu Profe ssor Ph.D. Ren sse laer Polytechnic Inst it ute 1984 Process control, process desigll, automatic co11tro/, control systems Ronald J, Phillips Professor Ph.D., Massachusetts Institute ofTechnology, 1 989 Transport processes i11 bioseparations, Newto11ian and non-Newtonian suspension mechanics Robert L. Powell Professor and Chair Ph.D., Johns Hopkin s University, 1978 Rh eology, suspension mechanics, magnetic mona11ce inwging of suspe11sio11s S ubhash H. Risbud Professor Ph.D ., University of California Berkeley 1976 Semiconductor qua11tum dots, high superco11ducting ceramics, polymer composites for optics Dewey D.Y Ryu, Professor Ph.D. Massachusetts Institute of Technology, 1967 Bi ochemic al engineering biomolecular process engi11eering and biotech110/ogy Julie M. Sc h oe nung ,Associate Professor Ph .D., Massachusetts lnstituteofTechnology, 1987 Materials systems analysi s, pollution preve11tion alld waste minimizalioll, process econom ic s Sabyasacbi Sen Associate Professor Ph D ., Stanford Unive111ity 1996 Structure-property relatio11ship, glass, nwwcrysta/ line glass ceramic, high temperature liquids, quantum dots, spec tros copy, computer 11wdelin g James F. Shackelford, Professor Ph.D ., University of California, Berkeley, 19 7 1 Structure of materials biomaterials 11011destructive testing of engi11eeri11g materials J .M. Smith, Professor Emeritus Sc D. Massachusett s Institute of Technology 194 3 Chemical ki11etics and reactor desig11 Pieter Stroeve, Professor Sc.D., Massac h usetts In sti tute of Technology, 1973 Membrane separations, self assembly, colloid a11d surface science, 1111notec/111ology surface modification, biotech11ology Yayoi Takamura Assistant Professor Pb.D. Stanford University, 2004 Thi11 film growth and characterizatio11 pulsed las e r depositio11, 11ew mag11etic a11d e/ectro11ic materials for spintronic applications na11oscale pattemi11g tech11iques Stephen Whitaker, Profes sor Emeri tu s Ph.D. University of Delaware, 1 959 Multiphas e transport phe11ome11a 350 Department of Chemical Engineering & Materials Science IUCDAVISI The multifaceted graduate study experience in the Department of Chemical Engineering and Material s Science allows st udent s to choose research proj ects and thesis advisers from any of our faculty with expertise in chemical engineering biochemical engineering, and materials science and engi neerin g. Our goa l is to provide the financial a nd academ i c s upport for students to comp l ete a substantive re se arch project within 2 years for the M S. a nd 4 years for th e Ph.D. SAN FRANCISCO Davis is a small, bike-friendl y university town located 17 miles west of Sacramento and 72 miles northeast of San Fran c isco ENTO within driving distance of a multitude of r ec reational activities. HOE We also e,~ j oy close LOS ANGELES SAN collaborations with national laboratories, including LBL, IEGO LLN L and LOCATION: Sandia. Sacramento : 17 miles San Francisco : 72 miles For information about our program look up our web site at http : !l www.chms.ucdavis.edu. or contact us via e-mail at chmsgradasst@ucdavis.edu Chemical Engineering Education

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UNIVERSITY OF CALIFORNIA Graduat e Studi es in IRVINE Chemi c al Engin ee rin g and Material s S c ien c e and En g ineering for Chemical E n g in ee r i n g, En g in ee rin g, and Material s S ci e nc e Major s Offe ri ng degrees at the M.S. and Ph.D levels R esearch i n frontier areas in c h emical engineering, biochem i cal engineering, biomedical engineering and materials science and engineer i ng. Strong ph ys i ca l and life science and e ngin eeri ng groups on campus. F A C U LTY Nanc y A Da S il v a (California I nstitute of T ec hnolo gy) Jame s C. Earthman (Stanford Un i vers i ty) Stanle y B. Grant (Ca l ifornia I nstitute of T echnology) Juan Hong ( P urdue University) Henr y C Lim (No r thw es tern University) Martha L. Mecartne y (Stanford Univ e rsity) F a rghalli A Moh a med ( University of California, Berkele y) A li Mohraz ( University of Mi c hi ga n) Daniel R. Mumm (Northwestern University) Andrew J. Putn a m (University of Mi c higan) R e gina Ragan (Cal(fornia I nstitute of Technology) Frank G. Shi (California I nsti t ute of Technolog y) Vasan Venugopalan (Massachusetts I nstitute of Technolog y) Szu-Wen Wang (Stanford University) Albert F. Yee (University of California B erkeley) J oint A pp ointments: Nanc y L. A llbritton (Massachusetts I nstitute of Te c hnolog y) Stev e C. George ( University of Washington) G. Wesle y Hatfield ( Purdue University) Noo Li Jeon (University of I llinois) Marc Madou ( R (iksuniv e rsiteit) Roger H. Rangel (University of California, Berkele y) Kenneth Shea (The P ennsy l vania Stat e Un i versity) Lizhi Sun ( University of California, Los Ang e les) Ad i u n ct Ap p ointments Jia Grac e Lu ( H arvard University) The 1 ,5 1 0-ac r e UC Ir vine ca m pus is in O range County five miles from th e P acific O cean and 40 miles so u th of Los A n ge l es. Ir vine is one of the nation's fastest g r owing resident i a l industria l and business areas Nearb y beaches, mou n tain. and desert area r ec reation.a l a c tivities, and local c ultural activities make Ir vine a p l e asant city in which to liv e and study. For further information and application forms, pl e ase vis it htt p: // www.e n g. u c i .ed u / de p t/c h e m s / or co nta c t Department of Chemical Engineering and Materials Science School of Engineering University of California Irvine, CA 92697-2575 Fa/12006 Bi o m e dic a l En g in ee rin g Bi o mol e cular E n gi n ee r i n g B i o r eac tor E n g in ee rin g Bi o r e m ed i a ti o n C e rami cs C h e mi cal and Biolo g ical N a no s en s or Colloid Sci e n ce Combu s tion Co mpl ex F luid s Comp os it e Mat e rial s Co n tro l and Optimi z ati o n En v ir o nmental E n g ineer in g Fu e l Ce ll S ys t e m s Interf ac ial En g in ee rin g M a t e ri a l s Pr ocess in g M ec hani ca l Pro pe rti es Me t a boli c En g in ee rin g Micro e l ectronic s Pro cess in g and M o d e lin g Micro s tmctur e of Mat e r i al s Mult if unctional M a t e ri al s N an ocrys tallin e Materi al s Nano sca le El ec troni c D ev i ces Nucleation Chry s talliza ti o n a nd Gla ss T ra n s tion Proce ss P o l y m e r s Power and Propul s ion Mat e rial s Protein Engin e erin g Recombinant C e ll Tech nolo gy S e par a ti o n Pro cesses Sol-G e l Proc ess in g Two Ph as e Flo w Water Pollution Control 35/

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UNIVERSITY of CALIFORNIA Riverside Department of Chemical and Environmental Engineering Offering degrees at the M.S and Ph.D. levels in frontier areas of Chemical, Biochemical, Biomedical, Advanced Materials, and Environmental Engineering, we welcome your interest and would be delighted to discuss the details of our graduate program and your application. We have outstanding faculty, research facilities and well supported infrastructure, and offer competitive fellowship packages to qualified applicants RESEARCH AREAS Advanced Vehicle Technology Advanced Water Reclamation Aerosol Physics Atmospheric Chemistry Bioand Chemical Sensors Biomolecular Engineering Carbon Nanotubes Catalysis and Biocatalysis Electrochemistry Environmental Biotechnology MEMS/NEMS, Bio-MEMS Membrane Processes Molecular Modeling Nanostructured Materials Site Remediation Processes Sustainable Fuels and Chemicals Water/Wastewater Treatment Zeolites & Fuel Cells a., u t :::,
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UNIVERSITY OF CALIFORNIA SANTA BARBARA SANJOY BANERJEE Ph.D. ( Wat e rlo o) Environmental Fluid D y n a mi cs Multiphase Flows, Turbulence, Co mputational Fluid D y nami cs BRADLEY F. CHMELKA Ph D ( B e rk e l ey) M o l ec ular Materi a l s Science In orga ni c-O r gan i cs Co mpo s it es, Porou s Solids NMR Pol y m e r s PATRICK S. DAUGHERTY Ph D. (UT, Austin) Protein Engineering a nd D esign Library Technologies MICHAEL F. DOHERTY Ph D (Ca mbrid ge) De s ign and Synthe sis, Separations Pro cess D y namics a nd Co ntrol FRANCIS J. DOYLE III Ph D. (Ca lt ec h ) Process Co ntrol Systems Biology Nonlinear D y n a mi cs GLENN H. FREDRICKSON Ph D. (S t anford) Stati s ti ca l Mechanics Glasses Polymer s, Compos it es, Alloys G.M. HOMSY Ph D (Illinoi s) Fluid M ec hanic s, In s tabilitie s, P oro u s Media lnt erfac ial Flows, Co n vec ti ve H ea t Tran sfe r JACOB ISRAELACHVILI Ph D (Ca mbrid ge) Co ll oi dal and Bi o m o l ecu l ar Int erac tion s, Adhesion a nd Friction EDWARD J. KRAMER Ph D (Ca rn egieM e ll on) Fracture and Diffu s i o n of P o l yme r s, P o l y mer Surfaces and Interf aces L. GARY LEAL Ph D (S tanford) Fluid M ec h a ni cs Ph ys i cs a nd Rhe o l ogy o