Front Cover
 Author Guidelines
 Table of Contents
 Dennis J. Miller of Michigan State...
 Chemical Engineering at South Dakota...
 Newton's Laws, Euler's Laws, and...
 New Laboratory Course for Senior-Level...
 Does Your Department Culture Suit...
 Applications of the Peng-Robinson...
 Ideas for Creating and Overcoming...
 Use of Engineering Design Competitions...
 Challenges in Teaching 'Colloid...
 The Chemical Engineer's Toolbox:...
 'Old Dead Guys' - Using Activity...
 Numerical Problems and Agent-Based...
 Using a Readily Available Commercial...
 Editorial: Are the Steam Tables...
 Back Cover

Chemical engineering education
http://cee.che.ufl.edu/ ( Journal Site )
Full Citation
Permanent Link: http://ufdc.ufl.edu/AA00000383/00179
 Material Information
Title: Chemical engineering education
Alternate Title: CEE
Abbreviated Title: Chem. eng. educ.
Physical Description: v. : ill. ; 22-28 cm.
Language: English
Creator: American Society for Engineering Education -- Chemical Engineering Division
Publisher: Chemical Engineering Division, American Society for Engineering Education
Publication Date: Spring 2009
Frequency: quarterly[1962-]
annual[ former 1960-1961]
Subjects / Keywords: Chemical engineering -- Study and teaching -- Periodicals   ( lcsh )
Genre: serial   ( sobekcm )
periodical   ( marcgt )
Citation/Reference: Chemical abstracts
Additional Physical Form: 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
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 01151209
lccn - 70013732
issn - 0009-2479
sobekcm - AA00000383_00179
Classification: lcc - TP165 .C18
ddc - 660/.2/071
System ID: AA00000383:00179

Table of Contents
    Front Cover
        Page i
    Author Guidelines
        Page ii
    Table of Contents
        Page 81
    Dennis J. Miller of Michigan State University
        Page 82
        Page 83
        Page 84
        Page 85
        Page 86
        Page 87
    Chemical Engineering at South Dakota School of Mines and Technology
        Page 88
        Page 89
        Page 90
        Page 91
        Page 92
        Page 93
        Page 94
        Page 95
    Newton's Laws, Euler's Laws, and the Speed of Light
        Page 96
        Page 97
        Page 98
        Page 99
        Page 100
        Page 101
        Page 102
        Page 103
    New Laboratory Course for Senior-Level Chemical Engineering Students
        Page 104
        Page 105
        Page 106
        Page 107
        Page 108
        Page 109
        Page 110
        Page 111
        Page 112
    Does Your Department Culture Suit You?
        Page 113
        Page 114
    Applications of the Peng-Robinson Equation of State Using MATLAB
        Page 115
        Page 116
        Page 117
        Page 118
        Page 119
        Page 120
        Page 121
        Page 122
        Page 123
        Page 124
    Ideas for Creating and Overcoming Student Silences
        Page 125
        Page 126
        Page 127
        Page 128
        Page 129
        Page 130
    Use of Engineering Design Competitions for Undergraduate and Capstone Projects
        Page 131
        Page 132
        Page 133
        Page 134
        Page 135
        Page 136
    Challenges in Teaching 'Colloid and Surface Chemistry' - A Danish Experience
        Page 137
        Page 138
        Page 139
        Page 140
        Page 141
        Page 142
    The Chemical Engineer's Toolbox: A Glass Box Approach to Numerical Problem Solving
        Page 143
        Page 144
        Page 145
        Page 146
        Page 147
        Page 148
        Page 149
    'Old Dead Guys' - Using Activity Breaks to Teach History
        Page 150
        Page 151
        Page 152
    Numerical Problems and Agent-Based Models for a Mass Transfer Course
        Page 153
        Page 154
        Page 155
        Page 156
        Page 157
        Page 158
        Page 159
    Using a Readily Available Commercial Spreadsheet to Teach a Graduate Course on Chemical Process Simulation
        Page 160
        Page 161
        Page 162
        Page 163
        Page 164
        Page 165
        Page 166
    Editorial: Are the Steam Tables Dead?
        Page 167
        Page 168
    Back Cover
        Page 169
Full Text

Chemical engineering education

o Dennis J. Miller

u ... of Michigan State University

Ideas for Creating and Overcoming Student Silences (p. 125)
I Woods, Sheardown
RandomThoughts: Does Your Department Culture Suit You? (p. 113)
48Richard M. Felder

LUse of Engineering Design Competitions for Undergraduate and Capstone Projects (p. 131)
o Kundu, Fowler
c 'Old Dead Guys'-Using Activity Breaks to Teach History (p. 1501
3 Holles
.a! ' Using a Readily Available Commercial Spreadsheet To Teach Graduate Chemical Process Simulation (p. 160)
V m Clarke, Giraldo
c CI Newton's Laws, Euler's Laws, and the Speed of Light (p. 961
o C
� , Whitaker
> 3 Challenges in Teaching 'Colloid and Surface Chemistry'-A Danish Experience (p. 1371
= E Kontogeorgis. Vigild
c W
Z _-c The Chemical Engineer's Toolbox: A Glass Box Approach to Numerical Problem Solving (p. 143)
a) U
D .- Coronell, Hariri
C o
0 v Numerical Problems and Agent-Based Models for a Mass Transfer Course (p. 153)
-, 2 Murthi, Shea, Snurr
7 D_ New Laboratory Course for Senior-Level Chemical Engineering Students (p. 104)
_ -c Aronson, Deitcher. Xi, Davis
S3 Applications of the Peng-Robinson Equation of State Using MATLAB (p. 1151
U Nasri. Binous
E Editorial (p. 167)

South Dakota School of Mines and Technology

Author Guidelines for the



The laboratory experience in chemical engineering education has long been an integral part
of our curricula. CEE encourages the submission of manuscripts describing innovations in the
laboratory ranging from large-scale unitoperations experimentsto demonstrations appropriate
for the classroom. The following guidelines are offered to assist authors in the preparation of
manuscripts that are informative to our readership. These are only suggestions, based on the
comments of previous reviewers; authors should use their own judgment in presenting their
experiences. A set of general guidelines and advice to the author can be found at ourWeb site:

c Manuscripts should describe the results of original and laboratory-tested ideas.
The ideas should be broadly applicable and described in sufficient detail to
allow and motivate others to adapt the ideas to their own curricula. It is noted
that the readership of CEE is largely faculty and instructors. Manuscripts must
contain an abstract and often include an Introduction, Laboratory Description,
Data Analysis, Summary of Experiences, Conclusions, and References.
* An Introduction should establish the context of the laboratory experi-
ence (e.g., relation to curriculum, review of literature), state the learning
objectives, and describe the rationale and approach.
* The Laboratory Description section should describe the experiment in
sufficient detail to allow the reader to judge the scope of effort required
to implement a similar experiment on his or her campus. Schematic dia-
grams or photos, cost information, and references to previous publica-
tions and Web sites, etc., are usually of benefit. Issues related to safety
should be addressed as well as any special operating procedures.
If appropriate, a Data Analysis section should be included that concisely
describes the method of data analysis. Recognizing that the audience
is primarily faculty, the description of the underlying theory should be
referenced or brief.The purpose of this section is to communicate to the
reader specific student-learning opportunities (e.g., treatment of reac-
tion-rate data in a temperature range that includes two mechanisms).
* The purpose of the Summary of Experiences section is to convey the
results of laboratory or classroom testing. The section can enumerate,
for example, best practices, pitfalls, student survey results, or anecdotal
* A concise statement of the Conclusions (as opposed to a summary) of
your experiences should be the last section of the paper prior to listing

Chemical Engineering Education
Department of Chemical Engineering
University of Florida * Gainesville, FL 32611
PHONE and FAX : 352-392-0861
e-mail: cee@che.ufl.edu

Tim Anderson

Phillip C. Wankat

Lynn Heasley

James 0. Wilkes, U. Michigan

William J. Koros, Georgia Institute -I i,. ,...'

John P. O'Connell
University of Virginia

C. Stewart Slater
Rowan University

University of Colorado
Jennifer Curtis
University of Florida
Rob Davis
University of Colorado
Pablo Debenedetti
Princeton University
Dianne Dorland
Thomas F. Edgar
University of Texas at Austin
Stephanie Farrell
Rowan University
Richard M. Felder
North Carolina State University
H. Scott Fogler
University of Michigan
Jim Henry
University of Tennessee, Chattanooga
Jason Keith
Michigan Technological University
Steve LeBlanc
University of Toledo
Ron Miller
Colorado School of Mines
Susan Montgomery
University of Michigan
Lorenzo Saliceti
University of Puerto Rico
Stan Sandler
University of Delaware
Donald R. Woods
McMaster University

Vol. 43, No. 2, Spring 2009

Chemical Engineering Education
Volume 43 Number 2 Spring 2009

88 Chemical Engineering at South Dakota School of Mines and Technology
Kenneth M. Benjamin and Robb M. Winter

82 Dennis J. Miller of Michigan State University
Daina M. Briedis with Jane L. DePriest

113 Does Your Department Culture Suit You?
Richard M. Felder

125 Ideas for Creating and Overcoming Student Silences
Donald R. Woods and Heather Sheardown
131 Use of Engineering Design Competitions for Undergraduate and Cap-
stone Projects
Sumit Kundu and Michael W Fowler

150 'Old Dead Guys'-Using Activity Breaks to Teach History
Joseph H. Holles
160 Using a Readily Available Commercial Spreadsheet To Teach a Graduate
Course on Chemical Process Simulation
Matthew A Clarke and Carlos Giraldo

96 Newton's Laws, Euler's Laws, and the Speed of Light
Stephen Whitaker
137 Challenges in Teaching 'Colloid and Surface Chemistry'-A Danish
Georgios M. Kontogeorgis and Martin E. Vigild

143 The Chemical Engineer's Toolbox: A Glass Box Approach to Numerical
Problem Solving
Daniel G. Coronell and M. Hossein Hariri

153 Numerical Problems and Agent-Based Models for a Mass Transfer
Manohar Murthi, Lonnie D. Shea, and Randall Q. Snurr

104 New Laboratory Course for Senior-Level Chemical Engineering Students
Mark T Aronson, Robert W Deitcher, Yuanzhou Xi, and Robert J. Davis

115 Applications of the Peng-Robinson Equation of State Using MATLAB
Zakia Nasri and Housam Binous

167 Editorial

CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engineering
Division, American Societyfor EngineeringEducation, and is editedatthe 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 0 2008 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 ifnotified 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).


, educatorr

Dennis J. Miller

of Michigan State University

Dennis with post-doctoral associate Navin Asthana in 2006.

Dedicated and resolute. If taken without energy, in-
novation, and relationships, these attributes suggest
routine, even monotony, in life. But for Dennis Miller,
professor of chemical engineering at Michigan State Uni-
versity (MSU), life is anything but monotonous. His love of
discovery and creative spirit energize him to constantly seek
new opportunities both professionally and personally, and his
dedication and resolve have led to a life that is full of diverse
experiences and accomplishments. With these traits, Dennis
Miller is exemplary in how a typical kid from Toledo, Ohio,
can become a respected and accomplished teacher, researcher,
and community servant.

Dennis has been a faculty member in the Department of
Chemical Engineering and Materials Science at MSU in East
Lansing, Michigan, since completing his doctorate in 1982.
He has had the same "job" for his entire academic career.
During that time, Dennis has been successful in cultivating his
passion for teaching and research, while maintaining a hefty
measure of service in the academic and local communities.
He has balanced career, family, and faith-all while trying to
keep a healthy perspective on time and resource challenges.
His energy, enthusiasm, and selfless commitment in all as-
pects of life have earned him the affectionate title of "The
"Energizer Bunny" among family and friends. His passion
� Copyright ChE Division of ASEE 2009
Chemical Engineering Education

for "doing"-and doing things well-is contagious, and has
benefited his students, colleagues, family, and the progress
of his career.
"Dennis is an exemplary, complete faculty member," says
Martin Hawley, professor and chairperson of the MSU Depart-
ment of Chemical Engineering and Materials Science. "He
has a high-level and high-quality research program involving
graduate students and post-docs, and he collaborates quite
effectively with his colleagues. Dennis is also an outstand-
ing educator. He incorporates new ideas related to his own
experiences, is willing to try new approaches, and requires
high standards in student work."

Dennis has a strong family background. He was born in
Toledo, Ohio, to Fred and Dorothy Miller, who still live in the
same house to which they moved when Dennis was six months
old. His father attended the University of Toledo from 1946-
1949 on the GI Bill and graduated as an electrical engineer.
That started a tradition for the Miller family. Dennis and his
two brothers all are engineering graduates of the University
of Toledo. Fred Miller worked for Toledo Edison for his entire
career (1949-1987) and was involved in a variety of jobs that
culminated with the engineering of the safety systems for the
Davis-Besse Nuclear Power Plant in Oak Harbor, Ohio, about
20 miles southeast of Toledo.
The opportunity to observe the nuclear plant construction
during his high school and early college years triggered
Dennis's interest in science and engineering. His AP chemistry
teacher at Thomas A. DeVilbiss High School, Ethyl Molnar,
helped to ignite his passion for chemistry because she chal-
lenged her students to think through problems; his high school
math teachers demanded systematic effort and correct answers
and helped Dennis begin to think like an engineer.
Following his high school graduation, Dennis proceeded
immediately to the University of Toledo (which was nearly
as close to his house as his high school) to study chemical
engineering. His favorite courses were kinetics and transport
phenomena, clearly evidenced by the direction his career has
taken. "I had an excellent experience as an undergraduate,"
Dennis remembers. "The professors were great, especially
Ken DeWitt, James Lacksonen, and Joe Boston, and the
classes were small, and so there was a lot of interaction."
Dennis was able to couple his coursework with a student
internship at Owens-Illinois Glass Company, where he worked
on a research project with Millard Jones, another University
of Toledo faculty member and a consultant for Owens-Illinois.
Dennis worked on heat transfer in glass bottle manufacturing.
This involved bench-scale experimentation, computer model-
ing, and pilot plant testing, which provided good exposure
to the research environment. This experience, along with the
support of his college professors, was influential in encourag-
ing Dennis to go on to graduate studies.
Vol. 43, No. 2, Spring 2009

Above: Early evidence of a lifelong love of fishing. Dennis
displays a trophy walleye taken from Georgian Bay, Lake
Huron (1967). Below: Graduation day at
the University of Florida.

As a teenager, Dennis spent many hours working on cars,
where he fine-tuned his appreciation for problem solving and
developed skill in working with his hands. He and his friends
took apart and assembled VW Beetles, and, most infamously,
two Triumph Spitfires. One of the Triumphs had significant
front-end damage and the other was smashed in the back. After
filling the garage floor with car parts for months at a time and
visiting every foreign car shop and junkyard in town, Den-
nis successfully assembled the two wrecks into one working
vehicle that ended up serving him well through college. The
Triumph experience, however, was not without trouble. The
serial number of the car used for the tide was on the damaged
car body that was disposed of, so when Dennis sold the car,
the serial number did not match the one on the title. Dennis
had to do some serious explaining to the buyer and the police
that the car wasn't stolen.
That same Triumph was also the victim of a practical joke
by Steve Le Blanc and other chemical engineering classmates
at the University of Toledo, who lifted and wedged the light
vehicle sideways between two other parked cars, leaving only
inches at the front and rear of the Triumph. When Dennis left
the engineering building that evening, he was trapped between
the two other cars with no way to move his Triumph. Only by
pleading with his thoroughly amused "friends" was the car
finally rescued from its predicament.
Of all Dennis's hobbies and interests, his favorite as a youth
and as an adult has been fishing. His father's fascination with
the sport meant that most family vacations involved angling in
some way, from Alaska to the Florida Keys, and many places
in between. When salmon were first planted in the Great Lakes
in 1967, Dennis and his father quickly joined in this exciting,
new sport-fishing adventure. That excitement has persisted to
the present, and Great Lakes and inland lake fishing remain an
integral part of what Dennis does for enjoyment, relaxation,
and fellowship. He shares his interest with family and friends;
if anyone even mentions fishing, Dennis is the first in plan-
ning where and when. Dennis jokingly boasts about the time
that he caught a salmon barehanded. That sounds impressive
until you hear the real story! The spawning run was so thick
on Michigan's Platte River that a poor salmon trapped itself
between the Miller boat and the shore. Dennis simply jumped
out of the boat and scooped up the 15-pound fish.

After working the summer of 1977 at the Exxon Research
and Development Laboratory in Baton Rouge, La., Dennis
headed to graduate school at the University of Florida in
Gainesville for a change of scenery. "I wanted to go to a dif-
ferent part of the country for graduate school and at that time,
the University of Florida was in the process of expanding its
faculty and research efforts," says Dennis. He chose to work
with Hong Lee, who had just arrived at Florida from Westvaco
Corp. "As Hong's first student, I spent a lot of time setting up
the lab and assembling equipment, which was something I

was pretty comfortable with," says Dennis who helped build a
high-pressure thermobalance for coal hydrogasification stud-
ies and constructed an enclosure around it in case something
exploded. Ultimately, their kinetics work on the role of alkali
carbonate catalysts in gasification fueled Dennis's broader
interest in catalysis, kinetics, and alternate energy sources
that drives his current research.
Lest the reader think that Dennis suddenly neglected his
hobbies, he also balanced the rigorous demands of graduate
studies and research with outside activities that included salt-
water fishing and playing beach volleyball and softball with
the department's graduate students and younger faculty. Among
the latter was a long-haired assistant professor shortstop named
Tim Anderson, who has remained a lifelong friend.
The graduate experience in Horida included another compo-
nent that strongly influenced Dennis's future - good teaching
experiences as an assistant to both Professors Lee and Ray
Fahein. "I taught a good part of the transport phenomena
course one year for Dr. Fahein because he was experiencing
some health issues," says Dennis. "That really perked my
interest in teaching. I enjoyed interacting with students and
seeing them get interested in the course material."
After receiving a Ph.D. in chemical engineering in 1982 and
with encouragement from Ray Fahein and John O'Connell,
Dennis applied for both academic and industrial positions.
"As graduation neared, job interviews and plant trips had
been scheduled, but the '82 recession led to hiring freezes at
many companies. In the end, Michigan State offered a bal-
ance of teaching and research, along with plans for significant
department growth that sounded promising. Don Anderson,
the chair of the chemical engineering department at that time,
was a real advocate for young faculty members."

The early years at MSU were full of the typical heavy work-
load and stresses of an assistant professor's job. "I most en-
joyed being in front of students in the classroom, but I knew
I had to develop a research program to stay in the academic
world," says Dennis. "Those years were definitely a struggle
in terms of research funding, but enough came through for
promotion and tenure."
The early toils were shared by a fellow assistant professor,
Daina Briedis, who had also started working at Michigan
State in 1982. They became friends through shared hours
of commiseration about the life of a young faculty member,
racquetball matches at the local gym, and teaming up in mixed
doubles beach volleyball, where the couple even advanced as
far as winning 2nd place in a tournament. The strong friend-
ship led to a permanent "arrangement," and Dennis and Daina
were married in 1985.
While Dennis's original work focused on carbon gasification
chemistry and pyrolysis, by 1985 the focus of the work done in
Dennis's research program shifted to catalytic conversions of
Chemical Engineering Education

Clockwise from lower left:
A chemical engineering wedding; Dennis
along with colleagues Ned Jackson (left)
and Carl Lira (2nd from left), and Michigan
Governor Jennifer Granholm, during her
visit to MSU chemical engineering follow-
ing the awarding of $7 million for Michi-
gan 21st Century Jobs Fund; with UICT
professor G.D. Yadav at the Miller home
during one of his visits to MSU.

renewable feed-
stocks. "Having
the Michigan Bio-
technology Insti-
tute come to East
Lansing brought
a number of pio-
neers in the field
to MSU," Den-
nis recalls. "They
started talking
about sugars, or-
ganic acids, and
alcohols as chem- '
ical feedstocks, so
we started looking
at the types of catalytic conversion chemistry we could do
with those molecules."
Dennis may have been a few years ahead of the curve. "At
a couple of Catalysis Society meetings in those years, people
would ask why we were wasting our time looking at obscure
compounds like lactic acid," says Dennis. "It seemed that
most people were studying single crystal surfaces in high
vacuum or surface reactions of simple hydrocarbons, so our
work appeared somewhat unwieldy because we were dealing
with multiple reaction pathways, carbon deposition on the
catalyst, and closing the material balance."
His research efforts took a positive turn in 1989 when he
partnered with James E. (Ned) Jackson, a physical organic
chemist and, at that time, assistant professor in the MSU
Department of Chemistry. Ned and Dennis enjoyed im-
mediate success in securing research funding from the U.S.
Department of Energy (DOE) and the U.S. Department of
Agriculture (USDA). A prolific partnership was born. "Ned
and I are a great team because we complement each other so
well. He studies mechanisms; I study kinetics and transport
phenomena. He is a thinker; I am a doer," says Dennis. To-
gether the two have published more than 20 papers, garnered
several million dollars of research funding, have 10joint patents,
and have studied numerous chemical systems in-depth. Much
Vol. 43, No. 2, Spring 2009

i of the work has focused on aqueous phase hy-
drogenation. "Most biorenewable feedstocks
are water-soluble, and they need to be deoxy-
genated en route to becoming replacements for
petrochemicals, so aqueous phase reactions are
a natural," says Dennis.
The Miller-Jackson collaboration is now
approaching 20 years of research with no end
in sight. Ned is now a professor of chemistry.
\i king with Ned has been a real professional and personal
benefit for me," says Dennis. "It's a marriage, in a sense, be-
cause we know each other's strengths and weaknesses so well
and we can take advantage of that to maximize our productiv-
ity." Ned agrees. "Our collaboration has been a continuous
learning experience. It's been very healthy for me and my stu-
dents to learn about not only large-scale chemistry but also the
economics and even politics of the massive flows of chemical
matter that we transform and traffic through the world," says
Ned, who believes that chemistry students should learn more
about the significance of the field in (and between) natural and
human environments. "Hopefully the learning exchange has
gone the other way too, with engineering students gaining some
appreciation of the rules governing reactions at the molecular
scale, to bolster their insights into transport, reactor design,
thermochemistry, stoichiometry, kinetics, and economics."
With the blossoming of the ethanol industry and emerg-
ing interests in renewable feedstocks, the Miller research
group has expanded significantly in the past 10 years to
include efforts in reactive separations and, more recently,
biofuels. \ li. lugan State is a national leader in biorefinery
development, and it also is, and always has been, an excel-
lent place to collaborate on research," says Dennis. "I have
been fortunate to have the chance to work with a number of

Clockwise from
right: On vacation
at the family's lake
cottage; coaching
girls' volleyball at
Lansing Christian
School; the Miller
family posing
in front of a 12th-
century Roman
Bridge during a
2007 mission trip
to Spain.

--" 1

--.. . , . .. . . .. . . . ... . , .

.--r . r. '.,, .-"7" ..... - � - ..,r '" - - -:
... . .. a.. . . ..

outstanding individuals across this campus and within the
College of Engineering, and those partnerships have nearly
always led to synergies that outweigh any possible advantages
of working alone." Colleagues Carl Lira, Ramani Narayan,
Kris Berglund, and Robert Ofoli in chemical engineering, and
Harold Schock in mechanical engineering along with Jackson
create combined expertise that makes proposals competitive
in most venues."
In addition, Dennis has worked with a group of postdoctoral
associates from the Mumbai (India) University Institute of
Chemical Technology (UICT). "They have been great col-
leagues and have generated many ideas and intellectual prop-
erty," explains Dennis. These former students of M.M. Sharma
and G.D. Yadav have really jump-started the reactive distillation
program in Dennis's lab. Dennis maintains close contact with
UICT, having visited there twice and having hosted Professor
Yadav at MSU during the 2001-2002 academic year.
Today Miller's research group, which includes six graduate
students and three postdoctoral associates, is active in multiple
research projects funded by DOE, USDA, private industry,
and national laboratories.
Besides research accomplishments and his advancement
through the faculty ranks, Dennis finds even more satisfaction
in educating students. \ ly early experiences in teaching at

the University of Florida are what stimulated me to consider
an academic career," says Dennis. "The university is all about
students, and my responsibility in educating them is equally,
if not more, important as advancing knowledge through re-
search. I ascribe to the motto of Michigan State-Advancing
Knowledge. Transforming Lives. And I believe I can help
influence the lives of our undergraduates."
Dennis's love of teaching has garnered him awards in
education. These include the Martin Best Paper Award in the
Chemical Engineering Division of ASEE, the Amoco Foun-
dation Excellence in Teaching Award (MSU), the Michigan
State University Teacher-Scholar Award, and five Withrow
Teaching Excellence Awards (1991, 1994, 1995, 1996, 2000)
given by the college for outstanding instruction in engineer-
ing. The reason for these awards and esteem is clear: Dennis
has been an early adapter of the principles of active learning
and engaging students in the classroom. He has a friendly,
collegial manner, but also sets high expectations. His office
door is always open for student questions and conversations,
and they are not afraid to talk with him.
One student notes, "Dr. Miller's office hours are worth it
because you actually get something out of them. He really
takes the time to help his students understand. After the office
hours of some other professors, I've left just as confused as
when I came in. Dr. Miller really puts things into ways that
I can understand. He knows how to connect with students,
Chemical Engineering Education

.. ... :2

which makes us enjoy him as a teacher." Another student has
this perspective: "I really enjoyed taking ChE 210 (Transport)
with Dr. Miller because he doesn't alienate his students by
making them feel stupid. He takes the time to explain con-
cepts slowly and thoroughly to make sure that every student
understands completely."
Every year engineering undergraduate students work in
Miller's research laboratory. "This gives students background
in research, so they can make an intelligent choice of whether
they would like to go on for graduate studies," says Dennis.
One of the students, a junior who worked in the pilot plant
during the summer of 2008, writes, "When I worked with Dr.
Miller, I gained so much practical work knowledge. It was a
hands-on internship where I really got a better understanding
of what chemical engineers do. Also, Dr. Miller took the time
to explain the organic chemistry behind the experiments, so I
actually understood what was going on in the reactors."
His dedication to improving the student learning environ-
ment is also evident in Dennis's long years of service on the
college's and department's curriculum committees. He helped
steer the college and his department through the transition
from quarters to semester, and has been a strong advocate of
many curricular innovations. He was the first faculty member
in chemical engineering to develop a freshman seminar course
that included hands-on activities, unique problem-solving sce-
narios, guest speakers, and a variety of contemporary issues.
This course contributed to a dramatic increase in enrollments
in chemical engineering at MSU at a time when enrollments
nationwide were plummeting. He and his colleagues both at
MSU and in India at UICT developed a course in "green" en-
gineering that was several years ahead of its time. This course
has become a mainstay of the chemical engineering program
and has broad appeal across the College of Engineering for
both graduate students and undergraduates.
Dennis shares his enthusiasm for chemical engineering and
education through many outreach activities. He has been an
instructor numerous times in the MSU Summer High School
Institute, a program designed to educate high school students
about the principles of engineering. He is active as a volun-
teer in middle school and high school classrooms and can
often be seen heading to a high school chemistry class with
his Dewar flask of liquid nitrogen and a boxful of hands-on
demos tucked into his briefcase.

Dennis views the balancing of priorities in life as coming in
seasons. "First there is education, then establishing oneself in
the professional community. When you are raising children,
your family must be a priority because most of us only get
one chance to do that," says Dennis. He and Daina have two
daughters (Mara, 20, and Anna, 15).
Dennis's and Daina's involvement in their church communi-
ty has helped establish the foundation of their priorities. Among
Vol. 43, No. 2, Spring 2009

other activities, Daina and their two daughters participate on the
church's worship team, and Dennis has taught Sunday school
and is a member of the church's leadership team. He has also
led or participated in two major mission trips with adults and
youth-to Renosa, Mexico, and to Camp L'Arcada Banyoles,
Spain-the latter of which included the whole family.
A major stress relief for the family has been their traditional
summer escapes to a small Northern Michigan lake cottage.
That is the place where work is truly left behind, and time is
spent enjoying all kinds of water sports, visits from extended
family, youth retreats, and (of course) fishing.
Another pastime Dennis still enjoys is volleyball, which he's
coached at the middle school, junior varsity, and varsity levels at
his daughters' school. "These kinds of activities help me feel con-
nected not only with my own kids, but with other young people
who, in a few short years, will be the ones sitting in our university
classrooms. I love coaching volleyball, and it also helps me to be
aware of how kids this age think. Although," he quips, "I don't
think I will ever understand teenage girls completely."
A dual-career family life has offered its share of challenges
and true tests of communication and time-management skills.
Daina and Dennis both consider themselves fortunate to work
in an environment where administration and colleagues under-
stand the importance of family and where faculty schedules,
as grueling as they can be, allow some measure of flexibility.
This has enabled the couple to share responsibilities of home
and family, particularly when their daughters were young. In
addition, both Dennis's and Daina's parents provided continual,
active support and encouragement. "We couldn't have gotten
through those early years without them," affirms Dennis.

Dedication and resoluteness have gotten Dennis to this point
in his career. He prefers to emphasize relationships over the
job. "The key to academic success for me is to build genuine
long-term relationships with as many people as possible," says
Dennis. "It doesn't matter if they are students, colleagues,
program managers, or funding agents - valuing people, treat-
ing them respectfully, being responsible, and working really
hard for them is a sure route to success."
Ned Jackson, Dennis's longtime collaborator, amplifies
this point. "The greatest pleasure in working with Dennis is
that the better I know him, the more I admire him," says Ned.
"He is a man of integrity, humility, and creativity; one who
seeks to make a real difference by bettering the world and
the life of those around him." Ned believes this is evident in
the calm passion Dennis brings to his research and his teach-
ing, his deep caring for his students, his dedication to honest
and thorough experimentation and reporting, and the zest he
radiates for all these parts of his work. "His ego is not built
on having to be more 'right' than others, but in sharing his
unique talents to map out the way as we all stumble, imper-
fectly, toward deeper knowledge." 0

r[l]o department

Chemical Engineering at . ..

South Dakota School of Mines

and Technology

T he year was 1921, and the South Dakota
Board of Regents (SDBOR) authorized
a degree program in chemical engineer-
ing at the South Dakota School of Mines -a
new field that had been birthed from applied
chemistry a few decades earlier. A vision had
emerged to bring this growing field to the Great
Plains. Dr. Andrew Karsten (1922-1960), the
first professor of chemical engineering at the
South Dakota School of Mines (as the institu-
tion was named at this time), single-handedly
brought the school's chemical engineering
program into existence. Dr. Karsten would then
shape and sustain the department for the next
20 years, along with chemistry colleagues Drs.
G.G. Osterhof and G.W. Bond.
In 1935 several Master of Science (M.S.) Where it a
programs were authorized by the SDBOR,
including one in chemical engineering. During
the early years, the Department of Chemical Engineering was
the sole source of M.S. graduates on campus, establishing a
culture of graduate education in the program. In 1943 South
Dakota School of Mines was renamed the South Dakota
School of Mines and Technology (SDSM&T) to signify this
institution's expansion from its mining heritage to a broad array
of engineering and science offerings. Dr. Warren E. Wilson,
the fifth President of SDSM&T (serving in the role from 1948
to 1953), urged the chemical engineering program to become
accredited, and this prompted the hiring of R.L. Sandvig,
who would lead the department in the decades to come. A
new Chemistry and Chemical Engineering building designed
by chemistry and chemical engineering faculty Osterhof and
R. Heckman (1953-1977), respectively, was dedicated in
1957. It included a state-of-the-art chemical engineering unit
operations laboratory-a crowning achievement for Karsten.
In classic pioneering fashion the laboratory was designed and
fabricated by chemical engineering students with the help of

11 began: The Chemistry and Chemical Engineering Building,
photographed shortly after its completion in 1957.

their mechanical engineering colleagues. The unit operations
laboratory would become a popular Parents' Day visitation
spot in the years to come. Accreditation was achieved and the
department has enjoyed accreditation status ever since.
During the '70s, faculty to join the department (with
their years of service in parenthesis) included L.G. Bauer
(1973-2002), W.A. Klemm (1975-1990), and J.M. Munro
(1977-2005). In addition, the biology program was integrated
into the department structure, which planted the seeds for
the development of the biochemical engineering emphasis
within the chemical engineering program. Faculty members
Sookie Bang (1985-present) and Kent Fish (1969-1995)
were brought onto the team. With the retirement of Sandvig
in the late '80s came the close of an era that saw Karsten,
Sandvig, and Heckman provide continuity and bold, visionary
leadership over nearly seven decades, 1922 to 1987.

� Copyright ChE Division of ASEE 2009
Chemical Engineering Education

Leading the way:
(Left to right) Russell
F. Heckman, early
faculty and one of
the building's design-
ers; Andrew Karsten,
the first ChE profes-
sor at the school and
a key player in the
department's cre-
ation; and Robert L.
Sandvig, integral to
the accreditation of
the department and
its chair for many
pivotal years.

The '90s saw a renaissance of the chemical engineering
curriculum at SDSM&T. Bauer, D.J. Dixon (1993-present),
Munro, J.A. Puszynski (1991-present) and R.M. Winter
(1988-present) pursued the development of the next gen-
eration of the curriculum determined to provide SDSM&T
chemical engineering graduates with a modem, industrially
relevant education, including an emphasis on design and
controls. Soon after, our Industrial Advisory Board agreed
that the time was ripe for the chemical engineering program
to develop a biochemical engineering emphasis. In this regard,
the chemical engineering and biology team found Cargill,
Inc., to be particularly interested in developing a unique
undergraduate curriculum that would produce graduates with
a practical knowledge of bioprocesses at the Bachelor of Sci-
ence level. Over the next several years faculty P. Gilcrease
(2002-present), T. Menkhaus (2005-present), and R. Sani
(2006-present) developed this biochemical engineering
emphasis, which integrates topics relevant to bioprocessing
across the ChE curriculum, and also immerses the students
in hands-on, open-ended biochemical engineering labora-
tory experiences. With the arrival of Dr. Ruch (2003-2008),
the 10th president of SDSM&T, came a restructuring of the
university that resulted in the formal creation of the Depart-
ment of Chemical and Biological Engineering. The growth
and vigor seen over the last 15 years would be the springboard
for the request and approval of the Ph.D. degree in chemical
and biological engineering (CBE) and the hiring of faculty
K. Benjamin (2007-present) and R. Shende (2008-present),
with a third faculty member yet to be hired. Over the last
20 years research has become an indispensable vehicle for
education and infrastructure development. The core areas of
research broadly include biochemical engineering, energy,
and nano- and macro-materials.
Vol. 43, No. 2, Spring 2009

The faculty of the CBE department at SDSM&T is com-
posed of chemical engineers, biochemical engineers, biolo-
gists, and microbiologists, by training. Among the nine faculty
members, seven have had industrial experience, allowing our
department to provide an applied dimension to our teach-
ing and research, in addition to engineering and scientific
Professor and Chair David Dixon has a long history at
SDSM&T. He is an alumnus of the department, having re-
ceived both his B.S. and M.S. degrees in chemical engineering
from the school. He obtained his Ph.D. in chemical engineer-
ing from the University of Texas at Austin. Dixon joined the
faculty at SDSM&T in 1993 and has served as chair of the
CBE department since 2006. His teaching interests include
thermodynamics and numerical methods, and his research
interests center on supercritical fluids, polymers, and envi-
ronmental and biochemical engineering. Recently, he has
also been appointed site director for the new National Sci-
ence Foundation Industry/University Cooperative Research
Center (NSF I/UCRC), the Center for BioEnergy Research
and Development.
Professor Robb Winter arrived in the CBE department in
1988. He obtained his Ph.D. in chemical engineering from the
University of Utah. Winter's research centers on understand-
ing how molecular-level chemical phenomena, particularly at
interfaces, influence bulk materials properties for composite
and thin film systems. The research is largely experimental,
and is aided by use of an interfacial force microscope-one
of few available in the country. Winter was also instrumental
in the creation of the Composites and Polymer Engineering
Laboratory (CAPE) on campus. In addition to research,

The faculty of the Department of Chemical and Biological Engineering,
from left to right, front row: Rajesh Shende, Sookie Bang, Pat Gilcrease, Rajesh Sani, and Robb Winter;
back row: Dave Dixon, Jan Puszynski, Ken Benjamin, and Todd Menkhaus.

Winter has helped shape the educational environment in the
department by creating the polymer/materials emphasis for
students within the undergraduate ChE curriculum, and by
helping bring National Science Foundation (NSF) Research
Experience for Undergraduates (REU) and Research Experi-
ence for Teachers (RET) sites to the SDSM&T campus.
Professor Jan Puszynskijoined the CBE department in 1991.
He obtained his Ph.D. in chemical engineering from the Insti-
tute of Chemical Technology in Prague. Puszynski's research
foci include heterogeneous (gas-solid) combustion, nanoener-
getic powders, densification of nanocomposites, and ceramic
synthesis. His research spans experimental investigations as
well as mathematical modeling and simulation. Puszynski has
played integral roles in both undergraduate and graduate educa-
tion in the CBE department and on the SDSM&T campus. He
led the incorporation of Aspen software across the undergradu-
ate curriculum, and has helped in the formation of two Ph.D.
programs on campus, in nanoscience and nanoengineering and
in chemical and biological engineering.
Sookie Bang, professor of biology in the CBE department,
has been at SDSM&T since 1985. She holds a Ph.D. in mi-
crobiology from the University of California, Davis. Bang's

research interests are focused on environmental/molecular mi-
crobiology and biotechnology, with current emphasis on deep
underground geomicrobiology and the use of extremophiles
for biomass degradation. Her teaching interests include gen-
eral and molecular biology and industrial microbiology. Bang
has been consistently devoted to introducing undergraduates
to the research environment, as evidenced by the fact that
she has had NSF/REU recipients nearly continuously from
1995-2008, many from disciplines outside biology.
Associate Professor Patrick Gilcrease has been a member of
the SDSM&T CBE faculty since 2002. He obtained his Ph.D.
in chemical engineering from Colorado State University.
His research activities include biomethane production from
coal, biomass pretreatment, fermentation, and biocatalysis
of solid substrates. Gilcrease's teaching activities comple-
ment his research well, as he has been the lead force behind
the development of biochemical engineering curriculum and
laboratories within the CBE department. He also serves as
advisor of the AIChE student chapter, which was just selected
as an Outstanding AIChE Chapter for 2007-2008.
Assistant Professor Todd Menkhaus joined the CBE de-
partment in 2005. Prior to that, he completed his Ph.D. in
Chemical Engineering Education

chemical engineering at Iowa State University. His major
research area is bioseparations, and his teaching interests span
separations and biochemical engineering as well as develop-
ing and delivering new bioseparations courses as part of the
CBE curriculum. Menkhaus is active in integrating teaching
and research, highlighted by his roles as acting director of
the NSF RET program at SDSM&T and as advisor for the
ChE Car Team.
Rajesh Sani is an assistant professor of biology within the
CBE department. He joined the CBE department in 2006,
and received his Ph.D. in environmental biotechnology from
the Institute of Microbial Technology at Punjab University,
Chandigarh, India. Sani's current research interests include
thermophilic bioprocessing for bioenergy and biomediated
transformations of metals and radionuclides. His teaching
interests include microbiology, environmental engineering,
and biochemical engineering.
Assistant Professor Ken Benjamin joined the CBE faculty
in 2007. Prior to arriving at SDSM&T, he completed a post-
doctoral rotation at SUNY-Buffalo and received his Ph.D.
in chemical engineering from the University of Michigan.
Benjamin's teaching interests include thermodynamics and
process modeling. His current research areas involve mo-
lecular and mechanistic modeling, with a focus on catalytic
reactions for biorefinery and bioenergy applications, and
reactions and materials processing in environmentally benign,
tunable solvents.
Assistant Professor Rajesh Shende
became a member of the CBE faculty in
2008. He holds a Ph.D. in chemical en-
gineering from the Institute of Chemi-
cal Technology at the University of 1 J/1 li '
Mumbai, India. Shende's research
portfolio is very broad, and covers ,
areas such as sustainable energy ' l
(including solar), alternative fuels, . .-2!.
nanostructured materials, thin / i ,,
films and MEMS, and sensors pR
and therapeutics. His teach- Ws o
ing interests include reactor A - 3
design, transport phenomena,
and nanomaterials. ,
There are two additional /
members of the CBE de-
partment whose contribu-
tions are integral to the success
and dynamics of our environment. Linda
Embrock, the CBE department secretary, is the pri-
mary contact within the department for all of our students
and visitors, and her tireless work ensures that our department
functions productively. Also, Ivan Filipov (M.S. chemical
engineering; Bourgas Professor, Assen Zlatarov University) is
the CBE department instrumentation and laboratory special-
Vol. 43, No. 2, Spring 2009

.A-/,. Fhe first building on campus, completed in
1 386. Center: An early document outlines the
school's inception.

, ist. Many students, both undergraduate
S l and graduate, owe their enjoyable and
productive laboratory experiences in large
part to Filipov's continued efforts.

' ,, Undergraduate ChE education at SDSM&T
is driven by several principles and themes, chief
among them being computer applications, inte-
grated design, and choice. To develop a desired
proficiency with computers and computer applica-
tions, freshmen students take Introduction to Engi-
neering Modeling -a course focusing on computer
applications relevant to chemical engineers, including
design software for creating process flowsheets and
piping and instrumentation diagrams, programming in
Microsoft Excel and Visual Basic, as well as the proper
use of specialized mathematical and engineering software such
as MathCad, Polymath, and AspenPlus and AspenProperties.
To emphasize the importance of process design and simulation
to our undergraduate students, we have integrated the use of

I , _ il ,l i l , i * ., I f . .. * -lll. ** I I, . t / , -/,, ' ./ / l l ' l- . .. l. l/ l l'll
,,/ , . ,l . l l ,,tl'- l. ,, l l ,, l.l ' I t , ,/, / ,, 1 t'llll''' Ill ,I' l- 1/ 1'1 .
, l .* i.I, - .", ,. 1 ,I i 'l. '_ -' *hI . l i , I- ,i l i , i
I. I . .l . * i .I . /It Ii. . 1o 1

AspenPlus simulation software in nearly every ChE under-
graduate course. 13] This feature has helped our graduates serve
more effectively as practicing process engineers.
An additionally large component in our undergraduate
education is the Integrated Design Project philosophy. In
addition to the aforementioned integration of AspenPlus
simulation software throughout the curriculum, the Integrated
Design Project philosophy has one other main objective-the
development of design projects that emphasize the strong
linkage and interdependency of the individual ChE courses.
This philosophy is a modified continuation of the original
Integrated Design Project,�11 which guided students through

a three-year design project. We are currently revisiting this
concept to consider how to most effectively implement such
a "long-term" cohesive design project.
One last feature of our practical, design-based curriculum is
the requirement that students take two process control courses.
The first is taken during the junior year, and is a combination
lecture/lab course that focuses more of the practical aspects of
process control. The second course is taken during the senior
year, and emphasizes the mathematics behind control theory.
The solid foundation in controls provided by these courses com-
plements the training our students receive in process design, and
positions them well to function effectively in industry.
Chemical Engineering Education

The emphasis on design is likewise carried through our
laboratory courses. The Materials, Automation, Processing,
and Simulation Laboratory (M.A.P.S), funded by the Dow
Coming Foundation, exists to help teach design skills through
the laboratory environment and experience. Conventional
chemical engineering laboratory courses and projects involve
conducting a "cookbook" experiment and performing sub-
sequent engineering calculations to determine a parameter,
or an optimal set of operating conditions. In the M.A.P.S.
paradigm, however, students are asked to design a process to
meet strict operating specifications using the methods learned
in lecture classes, then build or assemble the equipment to
meet their design, and finally to test their design by operating
the process, taking relevant measurements, and conducting a
critical review and comparison. Example M.A.P.S. laborato-
ries include heat exchangers and heat exchanger networks,
gas absorption,[41 piping networks, and tank-level control.
Also, it should be mentioned that this open-ended approach
to laboratory experiments is employed in all department
laboratory classes. Other unique characteristics of the ChE
laboratory courses includes the total number required for
the B.S. degree (6-spread out from the freshman through
the senior year), the availability of pilot-scale equipment for
experiments (and the need to modify equipment for experi-
ments), and the integration of automated process control into
many laboratory experiments. 51
The last component of our educational philosophy is that
of choice. Students in our program can add specialization to
their degree, by selecting curriculum options that emphasize
materials/polymers, environmental engineering, or biochemi-
cal engineering. (It is worth noting that the ChE department
is the founding member, and plays a continued, integral
part, of the environmental engineering degree program on
our campus.) Students in the materials/polymer concentra-
tion take advantage of SDSM&T's Composite and Polymer
Engineering Laboratory (CAPE), a 9,500-plus-square-foot
facility that houses state-of-the-art equipment for cutting-
edge research and development of polymer and composite
processing, prototyping, and tooling. For those concentrat-
ing on biochemical engineering, the Cargill Biochemical
Engineering Laboratory (established with generous support
from Cargill, Inc.) provides students access to state-of-the-art
bioprocessing equipment at the bench and pilot scale, such
as fermentors, centrifuges, and chromatography for analysis
and purification. In addition, all ChE majors are required to
take a microbiology course, and topics particularly relevant
to bioprocessing (such as stirred tank design and the use of
plate and frame heat exchangers) have been integrated into a
number of core ChE courses.

Students in the SDSM&T chemical engineering program
have participated in many opportunities to enrich their for-
mal engineering education. They maintain an active student
Vol. 43, No. 2, Spring 2009

The steady and planned growth of

the CBE research enterprise culmi-

nated in the formation of the Ph.D.

program in chemical and biological

engineering in 2007. The program

currently supports 10 Ph.D. students,

with the ultimate goal of growing to

20-25 students by 2010.

chapter of the American Institute of Chemical Engineers
(AIChE) and aChE Car Competition team- a multi-disciplin-
ary team including environmental, metallurgical, mechanical,
and electrical engineering, and computer science, students.
At regional and national AIChE meetings, SDSM&T ChE
students participate and compete with peer ChE students
from other universities in such activities as research paper
presentations, process designs, and the ChE Car Competition.
As noted previously, the AIChE Student Chapter was desig-
nated one of 15 AIChE Outstanding Student Chapters for the
2007-2008 school year. ChE students have been recognized
for outstanding academics by receiving national scholarships
and fellowships from AIChE and Tau Beta Pi, the engineer-
ing honor society. During Summer 2007, Travis Walker, a
ChE junior, was selected as the AIChE representative for the
Washington Internships for Students of Engineering (WISE).
In 2008, AIChE Student Chapter President Ben Bangasser
was awarded the Dr. Harry West Student Paper Award from
the AIChE Fuels and Petrochemicals Division. The ChE Car
Team has competed in the regional AIChE Student Chapter
Competitions every spring over the 10-year history of the
competition. Additionally, they have qualified and participated
as one of the top 31 teams in the national ChE Car Competi-
tion numerous times.

Graduate education in chemical engineering has been part
of the department since 1935, when the Master's program was
added. In 1986, the Ph.D. program in materials engineering
and science was formed on campus, which provided a natural
mechanism for facilitating Ph.D. research for CBE faculty in-
volved in polymer/materials research. Then, in 2005, the Ph.D.
program in nanoscience and nanoengineering was started on
campus, which augmented the existing department research
in nanocomposites, nano-structured materials, and combus-
tion synthesis of ceramic and intermetallic powders. During

Current research activity in the CBE

department at SDSM&T covers a

range of areas, including bioenergy,

biofuels, polymers/nanocomposites,

combustion synthesis of ceramic

and intermetallic powders, biochemi-

cal engineering and bioseparations,

bioremediation and extremophiles,

nano-structured materials, catalysis

and reaction engineering, and

molecular modeling.

the past 10 years, the diversity of research in the department
has grown considerably. The steady and planned growth of
the CBE research enterprise culminated in the formation of
the Ph.D. program in chemical and biological engineering
in 2007. The program currently supports 10 Ph.D. students,
with the ultimate goal of growing to 20-25 students by 2010.
The SDSM&T CBE program is different in nature from what
one finds most often in chemical and biological/biomolecular
engineering (i.e., CBE) departments across the country. Gen-
erally, CBE departments require Ph.D. students to take the
core chemical engineering graduate courses for their degree,
and provide elective courses in biology, microbiology, bio-
technology, etc., to supplement the training of those students
focusing on biological-related dissertations. In our CBE Ph.D.
program, students are required to take both chemical engi-
neering and biology/biological engineering graduate courses
to fulfill their degree requirement. At a minimum, SDSM&T
CBE Ph.D. students will take two courses from the follow-
ing biological engineering topics: biochemical engineering,
industrial microbiology and biotechnology, metabolic engi-
neering, biocatalysis, bioseparations, and molecular biology.
This structure ensures that the SDSM&T CBE Ph.D. gradu-
ate has the foundation and skill set to be proficient as both a
chemical and biological engineer.

Over the years, outreach to both our local and global com-
munities has been a continuous theme. The goal of drawing
more women into chemical engineering was a major thrust
begun in the '70s by Sandvig. This initiative, which received
a majority of its funding from the Dow Corning Corporation

and Dow Chemical, USA, was a great success, resulting in
a steady and persistent increase of female students pursing a
degree in chemical engineering at SDSM&T-from 2 percent
to 35 percent. The '80s and '90s saw several interrelated ac-
tivities to provide Native American middle and high school
students and their teachers with insight to the opportunities
that a chemical engineering degree can afford. Dow Chemi-
cal, USA, provided the majority of the funds for one initia-
tive- the Dow Chemical Native American Studies Workshop
for High School Teachers. The National Science Foundation
All Nations - Alliance for Minority Participation program
supported three initiatives, the Native American Summer
Engineering Bridge program, the SDSM&T - Oglala Lakota
College AISES Leadership initiative, and the Native American
Summer Research Program. These programs were envisioned
and developed to inform Native American students and teach-
ers of opportunities in engineering and science in general. The
result of these efforts has been a growing number of Native
American students pursing engineering and science degrees at
SDSM&T. In the '90s and '00s as the research efforts within
the department grew, National Science Foundation support
was sought and acquired to develop a Research Experience
for Undergraduates (REU) site within the Department of
Chemical and Biological Engineering. This site was success-
fully expanded to a sister international site at the Mongolian
University of Science and Technology in Ulaanbaatar, Mon-
golia, where REU research assistants investigated topics in
materials and environmental. To provide the regional K-12
community with opportunities to enhance their chemical en-
gineering and science skills and knowledge, an NSF-funded
Research Experience for Teachers (RET) site was established.
It too was expanded internationally, to Pontifica Universidad
Cat61lica De Valparaiso in Valparaiso, Chile. Both efforts have
been timely, with the recent realization of the importance of
globalization and the development within the United States
of a globally competent society.

The research environment of the SDSM&T CBE depart-
ment is vibrant and growing, and holds more promise with
the recently formed Ph.D. program in chemical and biological
engineering. Simultaneous with the new Ph.D. program was
the creation of the Center for Bioprocessing Research and
Development, a 2010 Research Center of the State of South
Dakota. The focus of CBRD is on research that leads to new
technologies for processing plant-derived lignocellulose mate-
rials into biomaterials such as ethanol and key building-block
chemicals. In 2008, the department was awarded status as the
lead site for a National Science Foundation Industrial/Univer-
sity Cooperative Research Center (NSF I/UCRC), formally
tied the Center for BioEnergy Research and Development
(). Further, the biologi-
cal-research component of our department has received an
additional significant boost from another recently awarded
Chemical Engineering Education

Envisioning future growth: The new addition to the Chemical and Biological Engineering/Chemistry building
is scheduled to be completed in 2011.

NSF center-the Deep Underground Science and Engineering
Laboratory (DUSEL)-to be located in Lead, South Dakota,
approximately 50 miles from the SDSM&T campus. In the
area of polymers and materials, department researchers take
advantage of the school's Composite and Polymer Engineer-
ing Laboratory (CAPE), a 9,500-plus square-foot facility for
advanced research and development of polymer and composite
processing, prototyping, and tooling. Current research activity
in the CBE department at SDSM&T covers a range of areas,
including bioenergy, biofuels, polymers/nanocomposites,
combustion synthesis of ceramic and intermetallic powders,
biochemical engineering and bioseparations, bioremedia-
tion and extremophiles, nano-structured materials, catalysis
and reaction engineering, and molecular modeling. Current
funding in the department exceeds $1MM per year, with an
average level of support of more than $200K/faculty.

The Department of Chemical and Biological Engineering
at SDSM&T, coming from humble beginnings, has survived
and thrived with the pioneer spirit so alive in the Great Plains.
The Department of Chemical and Biological Engineering has
entered the 21st Century with tremendous momentum and
Vol. 43, No. 2, Spring 2009

promise, with a vibrant curriculum, an emerging research
program, and now on the horizon a new building to be com-
pleted in 2011. We are fortunate that the vision and tenacity
of Drs. Karsten, Sandvig, Bond, and Osterhof has propelled
us to where we are today, and we look forward to making
continued contributions to chemical engineering research and
education locally, nationally, and globally.

1. Dixon, D., J. Puszynski, and L. Bauer, "Introduction of Design and
AspenPlus Across Chemical Engineering Curriculum," American
Institute of Chemical Engineers (AIChE) Annual Meeting, Miami
Beach, FL, November 1998
2. Dixon, D., J. Puszynski, J. Munro, and L. Bauer "Use of Simulation Soft-
ware Packages as a Teaching Tool in the 4-Year Chemical Engineering
Integrated Design Project," American Institute of Chemical Engineers
(AIChE) Annual National Meeting, Dallas, TX, November 1999
3. Dixon, D.J., L.G. Bauer, and J.A. Puszynski, "Professional Simulation
Packages as Effective Teaching Tools in Undergraduate ChE Curricu-
lum," presentation, 2000 ASEE Annual Meeting, St. Louis, MO, June
18-21, 2000
4. Munro, J.M., D.J. Dixon, and J.A. Puszynski, "Integrating Design Into a
Gas Absorption Laboratory,"American Institute of Chemical Engineers
(AIChE) Annual National Meeting, San Francisco, November 2003
5. Dixon, D.J., and J.A. Puszynski, "Introducing Process Controllers
Throughout the ChE Laboratory," American Society of Engineering
Education (ASEE) Annual Meeting, Montreal, Canada, June 2002 1

r1,] 1 curriculum
-- U s__________________



University of California at Davis * Davis, CA 95616

Truesdell11] tells us that Newton listed his three laws
of motion as:
Newton (1642-1727)
I. Every body continues in its state of rest, or of uni-
form motion straight ahead, unless it be compelled
to change that state by forces impressed upon it.
II. The change of motion is proportional to the motive
force impressed, and it takes place along the right
line in which the force is impressed.
III. To an action there is always a contrary and equal
reaction; or, the mutual actions of two bodies upon
each other are always directed to contrary parts.
Truesdell[2] also tells us that Newton never presented these
ideas in the form of equations, and because of this there are
differences to be found in the literature. In this work we choose
"motion" to mean mass times velocity, my, and we choose
"motive force" to be represented by f. This leads to

Newton I:

my = constant, f = 0

while the second law takes the form

Newton II:

d (mv)

Here the "change of motion" has been interpreted as the
time rate of change of the momentum, my. Often a precise
definition of v is not given in the discussion of Newton's

first and second laws, and we will return to this matter in
subsequent paragraphs. Clearly Newton's first law is a special
case of Newton's second law, and one can wonder why it was
stated as an independent law. Physicists[3 5] have pointed out
that Eq. (1) was deduced earlier by Galileo (1564-1642), thus
Newton was motivated to elevate this result to the position
of a "law."
Newton's third law for two interacting bodies can be ex-
pressed as

Newton III:

f 12 -f21

in which f12 is the force that body #2 exerts on body #1, and
f21 is the force that body #1 exerts on body #2. The most
dramatic success of these laws was their use, along with
the law of... ii i.,ii.. .i attraction, to justify Kepler's three

Stephen Whitaker is a professor emeritus
at the University of California, Davis. His
interests in engineering education are
directed toward avoiding leaps of faith by
building upon material studied in prereq- -
uisite courses. He has received various
departmental teaching awards in addition .
to the Tau Beta Pi Outstanding Teacher
Award (College of Engineering), the Magnar
Ronning Award for Teaching Excellence
(UC Davis), the Distinguished Teaching
Award (UC Davis), the Engineering Alumni
Distinguished Teaching Award (College of Engineering), and the
Warren K. Lewis Award (AIChE).

� Copyright ChE Division of ASEE 2009
Chemical Engineering Education

empirical laws of planetary motion. In a careful statement
of Newton's laws, one often notes that they are valid in an
inertial frame. This naturally leads to the question: What is
an inertial frame? The answer is that an inertial frame is a
frame in which Newton's laws are valid! We can only escape
from this circular argument by noting that an inertial frame
must be determined by experiment.[6] In Newton's case, the
verification of Kepler's laws indicated that the sun and the
"fixed stars" represented a good approximation of an inertial
frame for the study of planetary motion.
If we think about applying Eq. (2) to the motion of a body,
we must wonder what is meant by the velocity, v, since all
parts of a body need not have the same velocity. Physicists
often deal with this problem by arguing that Eq. (2) applies to
"mass points" that are small enough so that their motion can be
described by a single velocity. The statement that something is
"small" always leads to the question: Small relative to " hiit '
Feymnan, et al.,1 touch on this problem by considering the
cloud of N mass points illustrated in Figure 1. One can ap-
ply Newton's second law to the ih mass point in the cloud
to obtain

-(mV) = bl +Tf (4)
dt - - I

Here we have used b to represent the body force exerted on
the ith mass point by the large, spherical body located outside
the cloud in Figure 1. The force exerted by the jth mass point
in the cloud on the ith mass point in the cloud is represented by
f , and this force obeys Newton's third law as indicated by
f = -f (5)
-lJ -ji (5)

To obtain Newton's second law for the cloud of mass points,
we sum Eq. (4) over all the mass points in the cloudV81

d I1N
Kmv(CM) = Tb

We now identify the total external force acting on the cloud
of mass points as
f=Eb (11)

so that Newton's second law for a cloud of mass points is
given by

Newton II:


Feymnan, et al.,[91 describe this situation by saying M\: it in's
law has the peculiar property that if it is right on a certain
scale [the mass point scale], then it will be right on a larger
scale [the cloud scale]." While this is a satisfying result, it
does not explain "how small" a particle must be so that Eq. (2)
can be applied with confidence. For rigid bodies the velocity
v at any point r is given by10�1

Y (L) = IYc + U-X (E c) (13)

in which w represents the angular velocity. Here we see that
a single velocity can be used to describe the motion of a rigid
body whenever aX (r - r c) is small compared to cM , thus
the constraint associated with the "mass point" assumption
is given by

x(r- rc )< VCM (14)

For deformable bodies, one must replace Eq. (13) with the
more general representation


r .. Td.

d I1N I1N
-t mv = blI
dt 1 1-1 -1

I-N j-N
1=1 J=l

and make use of Eq. (5) to simplify this result to the form

d N
- > mv
dt 1-1


The mass of the cloud is given by
m= mi

while the center of mass, r , and the velocity of the center
of mass, vcM, are defined by

1 I-N
iCM =m-lmlr,
inM n111 1- 1

1 I-N
v =m mv,
-CM 1

The second of these definitions allows us to express Eq. (7)
in the form

Figure 1. Cloud of mass points interacting with a body.


Vol. 43, No. 2, Spring 2009

and then examine the velocity gradient tensor in terms of
its symmetric and skew-symmetric parts.u11 In this case, the
restriction"12 is obviously given by

S(7V) dTi << vcM (16)
,I rCM
however, the associated constraint would require a more detailed
analysis of the fluid deformation. If one accepts Eq. (12) as
Newton's second law instead of Eq. (2), no constraint need
be imposed.

While Newton's laws seem to be suitable for the study of
mass points and clouds of mass points, they cannot be applied
directly to the motion of a moving, deforming, continuous
medium.E13 Regardless of what words are used to describe the
laws of mechanics used by chemical engineers, those laws are
indeed the laws proposed by Euler that can be stated as
Euler (1707-1783)
L The time rate of change of the momentum of a body
equals the force o. i1,, on the body.
II. The time rate of change of the angular momentum of a
body equals the torque o. 11,, on the body, where both
the torque and the moment are taken with respect to the
same fixed point.
In addition to these two laws, we accept the Euler cut
pi imciplel '1 that can be stated as:
Not only do the laws of continuum physics apply to distinct
bodies but they also apply to any arbitrary body that one
might imagine as being cut out of a distinct body.
To understand how Euler's laws are related to Newton's
laws, we need to express Euler's laws in precise mathemati-
cal form. This will allow us to demonstrate that they contain
Newton's laws provided that we restrict ourselves to non-
relativistic phenomena.
For the body occupying the material volume, 6 m(t), illus-
trated in Figure 2, Euler's laws are given by�15l

Euler I: f pydV= f pbdV+ f tdA (17)
V t) Vm(t) m(t)

Euler II:d f x pydV= f x pbdV
V it) V it)

f rxt .. d\(18)

To be clear about Euler's two laws, we need to say that the
velocity, y, is determined relative to an inertial fame and that
the position vector r is determined relative to some fixed point
in an inertial frame. As mentioned earlier in connection with
Newton's laws, one identifies an inertial frame by experiment.
It is important to remember that these two axiomatic state-
ments for linear momentum and angular momentum apply
to any arbitrary body that one imagines as being cut out of
a distinct body.
Given Euler's two laws of mechanics and the Euler cut
principle, we need to know how they are related to Newton's
three laws. To explore this problem, we consider a body of
mass m illustrated in Figure 3, and we locate the center of mass
of that body in terms of the position vector defined by

CM - I pdV (19)
mes m
U tt

Chemical Engineering Education



Figure 2. Moving, deformed body.

\- -Eulerian cut

Figure 3. Motion of a body.

For a sphere of uniform density, the center of mass would be
located at the geometrical center of the sphere; however, the
definition of r CM is completely general and Eq. (19) is appli-
cable to any arbitrary body that is cut out of a distinct body. The
velocity of the center of mass is defined in a similar manner

CM I f pydV (20)
Vm (t)

and one can use a special form of the Reynolds transport
theorem[161 to prove that
CM-= dt (21)

The definition given by Eq. (20) can be used to express the
first term in Eq. (17) as

enough" so that VCM can be replaced by L we see that Eq. (24)
is identical in form to Eq. (2) for a mass point. The similarity
in form (not content) of Euler's first law and Newton's second
law has encouraged many to think that Newton's laws and
Euler's first law are essentially equivalent. This is a line of
thought that should be discouraged.

To clarify the different perspectives of physicists and chemi-
cal engineers, we apply Euler's first and second laws to the
special case of three interacting bodies in a vacuum. This
situation is illustrated in Figure 4 where we have shown two
distinct small bodies, three Eulerian cuts (material volumes),
and a distinct large body. For Cut I and Cut II, Euler's first
law yields

d d
d j pydV = d(m M)
V t


As a matter of convenience, we designate the total force
acting on the body by


CutII: d f p2v2dV

f Plb12dV

f plbl3dV
V (t)

f 2b21d+ f p2b23dV
v (t) v (t)

f f pbdV
v (t)

f t(n)dA
a (t)

so that Eq. (17) can be represented in the simplified form
given by

Euler Result I:

d ( )=
dt�mYC f

(23) The application of Cut III treats the two small bodies as a
single body for which the time rate of change of momentum
is balanced by the applied external force. This leads to

CutIII: d f plvldV
dt Vt


f P2dV
V (t

This is identical in form to Newton's second law for the cloud
of mass points illustrated in Figure 1, and if the body is "small

f pbl3dV+ f p2b23dV

Figure 4. Three-body process.

Vol. 43, No. 2, Spring 2009



/----fj'2 . .

cut III

Cut III /

The similarity inform

(not content) of Euler's first law

and Newton's second law

has encouraged many to think

that Newton's laws and

Euler's first law are essentially

equivalent. This is a line

of thought that should be


Substitution of Eqs. (25) and (26) into Eq. (27)
leads to

Given that Euler's first law contains all that is available in Newton's
three laws, one must wonder why physicists do not move forward one
century and accept Euler's first law as their axiom for mechanics. The
answer would appear to be associated with Euler's second law that
we examine in the following paragraphs.

In the absence of any surface forces, we can express Euler's second
law as

dt f r x pvdV
dt t

fr xpbdV
V (t\

and for the three Eulerian cuts, or control volumes, illustrated in
Figure 4 we have

Cut I: - f 1xpydV= f rxp1b12dV
d V (t) V (t)

Cut II:- f rxp2v2dV= f rxp2b21dV
V (t) V (t)

f r xplbl3dV (33)
V' (t)

f r xp2b23dV (34)
v (t)


f P12dV+ f 2b21dV= 0
V (t) V (tl

Cut III:

and it will be convenient to identify these two body
forces as

d fEl xpy vdV + E rxp2 2dV
V t V t)

f r xp bl3dV-
V (t)

f r2 p2b23dV
V (t)

12 =f plbl2dV,
V Yt

f21 =f 2b21dV (29)
V Yt)

Use of Eqs. (33) and (34) in Eq. (35) leads to a constraint on the body
forces given by

At this point we repeat Eq. (24) as

Euler Re sult I:

dt (cml)

f xp 1b12dV
V (t)


f L P2b21dV= 0
V (t)

And note that Eqs. (28) and (29) lead to

Euler Result II:

f12 f-21

Eq. (30) yields Newton's second law for the cloud
of mass points illustrated in Figure 3, and if Eq. (30)
is applied to a single mass point it yields Newton's
second law as given by Eq. (2). Eq. (31), which was
derived by applying Euler's first law to the process
illustrated in Figure 4, is identical to Newton's third
law. Here we see that Euler's first law can be used
to obtain all three of Newton's laws; however, the
inverse is not true, i.e., one cannot use Newton's laws
for mass points or for a cloud of mass points to obtain
Euler's first law. Euler's laws are based on the Euler
cut principle and the assumption that the material
under consideration can be treated as a continuum,
and these constructs are not to be found in Newton's
treatment of mechanics.[171

The position vectors can be expressed in terms of the position vectors
locating the centers of mass according to


and this leads to

(rcM)Ix f p1b12dV
Vi (t)

(cM )2x f P2b21dVA
V t

f rl X p1bl2dV

f -i2 xp2b21dV

Next we make use of Eqs. (28) and (29) to express this result in the

(I - CM) x f+ f p lbl2dV+ f ixp2 dV =0 (39)
V t) V (t)

Chemical Engineering Education

r2 = (cM)2 +f2

In the appendix we demonstrate that the last term in this result
can be neglected when the following constraint is satisfied:

o(il) +o(2)
0 C'M) - CM )2 1


Under these circumstances, Euler's second law leads to

(-CM)I - (CM)21 X f12= 0 (41)
and there are three ways in which this result can be satisfied.
We list the three possibilities as
1. (icMi)- IcM) =0 (42)
2. f12 = 0 (43)
3. (1cmi)I - ('") and f2 are parallel (44)

Since the first two possibilities can not be generally true,
we conclude that the interaction force between two bodies
must be parallel to the vector (rM)1 - (rCM)2. We express this
result as

Euler Result III: f12 = 2 (cM ) -i (M )2 (45)

in which 2 12 is some scalar parameter of the interaction force
law. Eq. (45) indicates that the interaction force between two
bodies subject to the constraint given by Eq. (40) must act
along the line of centers, i.e., it is a central force.
In this analysis we have shown that Euler'sfirst law contains
Newton's three laws, while Euler's second law provides what
is known as the central force law for the case of mass-point
mechanics. Given the power and economy of Euler's laws,
one can wonder why Newton's three laws are not discarded
in favor of Euler's two laws. The answer lies in the fact
that the central force law, given by Eq. (45), represents a
non-relativistic phenomenon. Since forces are propagated at
the speed of light, the force that one body exerts on another
cannot lie along the line of centers when the relative velocity
between the two bodies approaches the speed of light. Because
of this, physicists prefer to view mechanical phenomena in
terms of Newton's laws and make use of the central force
law as a special case that can be discarded when relativistic
phenomena are encountered. Engineers, on the other hand,
are rarely involved in relativistic phenomena and what is a
special case for the physicist is the general case for the en-
gineer. Because of this, engineers uniformly formulate their
mechanical problems in terms of Euler's two laws and the
Euler cut principle.

Physicists, who begin teaching chemical engineering
students about the laws of mechanics, are committed to a
Newtonian perspective because it is consistent with relativistic
mechanics and mass points. This perspective will not change.
Vol. 43, No. 2, Spring 2009

Physicists prefer to view mechanical

phenomena in terms of Newton's laws

and make use of the central force law

as a special case that can be discarded

when relativistic phenomena are en-

countered. Engineers, on the other

hand, are rarely involved in relativistic

phenomena and what is a special case

for the physicist is the general case

for the engineer.

Chemical engineering faculty teach chemical engineering
students about Euler's laws of mechanics, regardless of what
words they use to describe these laws. Chemical engineering
faculty need to take responsibility for the development of a
smooth transition between the perspective of physicists and
the perspective of engineers. In the absence of such a smooth
transition, our students will be confronted with a discontinu-
ityl18] and will never be completely confident in the laws of
mechanics that they have been given.

The author would like to thank the reviewers for thoughtful
and helpful comments.

i t) surface area of a material volume, m2
b total body force per unit mass, N/kg
b, i=1,2,...,N, body force exerted by a large, external body on
the ith mass point, N
b12 body force per unit mass exerted by body #2 on body #1,
b21 body force per unit mass exerted by body #1 on body #2,
f force, N
f12 force exerted by body #2 on body #1, N/kg
f2 force exerted by body #1 on body #2, N/kg
f force exerted by the jth mass point on the ith mass point in a
cloud of mass points, N
m mass of a body or mass of a cloud of mass points, kg
m mass of the ith mass point, kg
n unit normal vector
r position vector, m
rcM position vector locating the center of mass, m
t time, s
tn) stress vector, N/m2

v velocity of the ith mass point, m/s
v velocity, m/s
v(M velocity of the center of mass, m/s
6m(t) volume of a body (material control volume),

Greek Letters
p total mass density, kg/m3
p total mass density of the ith body, kg/m3
co angular velocity, rad/s

1. Truesdell, C., Essays in the History of Mechanics,
Springer-Verlag, New York, p.88 (1968)
2. Truesdell, C., Essays in the History of Mechanics,
Springer-Verlag, New York, p. 167 (1968)
3. Feynman, R.P, R.B. Leighton, and M. Sands, The Feyn-
man Lectures on Physics, Addison-Wesley Publishing
Company, New York, I, p. 9-1 (1963)
4. Huggins, E.R., Physics 1, WA. Benjamin, Inc., NewYork,
p. 109 (1968)
5. Greider, K., Invitation to Physics, Harcourt Brace Jova-
novich, Inc., New York, p. 38 (1973)
6. Hurley, J.P, and C. Garrod, Principles of Physics, Hough-
ton Mifflin Co., Boston, p. 49 (1978)
7. Feynman, R.P, R.B. Leighton, and M. Sands, The Feyn-
man Lectures on Physics, Addison-Wesley Publishing
Company, New York, I, p.18-1 (1963)
8. Marion, J.B., Classical Dynamics of Particles and Sys-
tems, Academic Press, New York, p. 68 (1970)
9. Feynman, R.P, R.B. Leighton, and M. Sands, The Feyn-
man Lectures on Physics, Addison-Wesley Publishing
Company, New York, I, p. 19-2 (1963)
10. Landau, L.D., and E.M. Lifshitz, Mechanics, Pergamon
Press, New York (1960)
11. Aris, R., Vectors, Tensors, and the Basic Equations of
Fluid Mechanics, Prentice-Hall, Inc., Englewood Cliffs,
NJ, p. 89 (1962)
12. Whitaker, S., "Levels of Simplification: The Use of As-
sumptions, Restrictions and Constraints in Engineering
Analysis," Chem. Eng. Educ., 22, 104 (1988)
13. Serrin, J., "Mathematical Principles of Classical Fluid
Mechanics," in Handbuch der Physik, Vol. VIII, Part 1,
edited by S. Flugge and C. Truesdell, Springer Verlag,
New York, page 134 (1959)
14. Truesdell, C., Essays in the History of Mechanics,
Springer-Verlag, New York, page 193 (1968)
15. Whitaker, S., Introduction to Fluid Mechanics, R.E.
Krieger Pub. Co., Malabar, FL (1981)
16. Aris, R., Vectors, Tensors, and the Basic Equations of
Fluid Mechanics, Prentice- Hall, Inc., Englewood Cliffs,
NJ, p. 87 (1962)
17. Truesdell, C., "A Program Toward Rediscovering the
Rational Mechanics of the Age of Reason," in Essays in
the History of Mechanics, Springer-Verlag, New York
18. Whitaker, S., "Discontinuities in Chemical Engineering
Education, Chem. Eng. Educ., 33, 18 (1999)
19. Birkhoff, G., Hydrodynamics: A Study in Logic, Fact, and
Similitude, Princeton University Press, Princeton, NJ, p.
20. Stein, S.K., and A. Barcellos, Calculus and Analytic
Geometry, McGraw-Hill, Inc., New York, p. 691 (1992)

Deciding when some quantity is "small enough" so that it can be dis-
carded is not always an easy task. Here we consider the simplification
that led from Eq. (39) to (40) and the central force law represented by
Eq. (45). We begin with Eq. (Al)

(MM)1 -(CM )2�X f12+ f .f XPlbl2dV

and use the following nomenclature

1cM Ic 2 = -
f12 F

f r X 1b12dV
V (t)

f 2 x P2b21dV
V (t)

0 (Al)




f 2 xp2b21dV
V (t)

to express Eq. (Al) as
RxF+D=0 (A3)

Here we would like to know when the vector D can be discarded in order
to simplify this result. A plausible intuitive hypothesis[19] associated with
this simplification is given by




however, we cannot discard D as being small compared to RxF since
Eq. (A3) requires that D and RxF be the same order of magnitude. This
type of problem has been considered before,[12] and we will follow the
procedure suggested in that earlier work. This requires that we decompose
F into a part that is parallel to R and a part that is perpendicular to R as
indicated by[201

F= F + -F
parallel part perpendicular part


On the basis of this decomposition, we see that Eq. (A3) provides the
two results given by

Rx F =0

RxF, +D=0



This allows us to estimate as F

F O )


in which 0 indicates an order of magnitude estimate. If F is small rela-
tive to F , and if small causes give rise to small effects, we can replace F
with F and Eq. (A6a) leads to the central force law given by Eq. (45). To
develop the conditions that must be satisfied in order that F� be negligible
compared to F , we consider the inequality given by

F_ > F,


In terms of the estimate given by Eq. (A7) this leads to

Chemical Engineering Education

F o(D)
F >01)
O (R)


and because of the constraint given by Eq. (A8) we can ex-
press this result as

F o> ()


Making use of the definitions given by Eqs. (A2) this inequal-
ity can be arranged in the form

0 f XPlb12dV
V "t)

f i2xp2b21dV

O(L12)O�(jrM), _(CM)j

On the basis of Eqs. (29) we obtain the two estimates

f r1x Plb12dV
V t

O(-l)f12, f 2 xp2b21dV
V t


and use of these [along with Eq. (31)] in Eq. (All) leads to
the constraint given by


0r - rEC)21
O -C Icm \-C 2


1 (All)

Vol. 43, No. 2, Spring 2009


i] 1= laboratory




University of Virginia * ( hi.. i/..i.. ,il//.., VA 22904

The career diversity for chemical engineers has changed
dramatically over the last 30 years. For example, more
than 75% of chemical engineering positions in 1975
were with companies involved in production of commodity
fuels and chemicals.J1l By 2003, only 25% of the careers for
chemical engineers were in these industries,11l while biotech
and electronics/materials industries employed approximately
15% and 10%, respectively, of chemical engineers.[2] These
trends are expected to continue with a growing emphasis on
the development and production of more complex materials
including biologically active and nanostructured materials.[3]
The responsibilities of today's chemical engineer are
evolving as a result of the changes in the industries that
employ them. Chemical engineers are now more involved in
the synthesis and development of new products and devices.
Twenty- five years ago, only 15% of the graduating chemical
engineers were in product development, whereas more than
50% of recent graduating chemical engineers are working in
this area.31] Also, the need for chemical engineers to be able to
effectively interact with scientists from a range of disciplines
such as materials science, biology, and medicine is increasing
as a result of evolving employment opportunities.[4]
Even with the dramatic changes in career diversity and
responsibilities for recent graduates, the chemical engineering
curriculum has changed little over the last 40 years.3, 5] Much
of the focus remains with large-scale process equipment such
as distillation towers and heat exchangers, and many of the
examples used in courses continue to come from the petroleum
refining and bulk chemical production industries. A grow-
ing number of leaders in chemical engineering believe that

chemical engineers need to be taught more about product and
process synthesis rather than large-scale chemical engineer-
ing equipment.ElJ Furthermore, it has been argued that more
time needs to be spent in chemical engineering education on

Mark T. Aronson is an associate professor in the Department of Chemi-
cal Engineering at the University of Virginia. He received his B.S. in
chemical engineering from the University of Virginia, and his M.S. and
Ph.D. in chemical engineering from the University of Pennsylvania. He
spent 17 years in R&D with DuPont before joining the faculty at the
University of Virginia in 2005. His current research interests include
polymer structure/property relationships and the use of polymer com-
posites for military blast and ballistic applications.
Robert W. Deitcher is a graduate student in the Department of
Chemical Engineering at the University of Virginia. He received his
B.S. in chemical engineering from the University of Delaware in 2000
and began a career in the manufacturing division of Merck. While at
Merck, he received an M.E. in chemical engineering from Leigh Uni-
versity. He returned to academia full time in 2005 to pursue a Ph.D.
His research project focuses on the measurement, modeling, and
prediction of protein retention and unfolding in hydrophobic interac-
tion chromatography.
Yuanzhou Xi is a graduate student in the Department of Chemical
Engineering at the University of Virginia. He received his B.S. and M.S.
in chemical engineering from Tsinghua University. He also received
an M.S. from the University of Virginia. His Ph.D. research project is
focused on heterogeneous catalysis and reaction engineering.
Robert J. Davis is a professor and chair of the Department of Chemi-
cal Engineering at the University of Virginia. He received his B.S. in
chemical engineering from Virginia Tech and his M.S. and Ph.D. in
chemical engineering from Stanford University. Prior to joining the
faculty at UVa in 1990, he worked as a postdoctoral research fellow in
the Chemistry Department at the University of Namur in Belgium. His
research interests include synthesis, spectroscopic characterization,
and kinetic evaluation of solid catalysts.

� Copyright ChE Division of ASEE 2009
Chemical Engineering Education

atomic- and molecular-scale phenomena, and on the transla-
tion of fundamental science to engineering principles.J6
Because of these changes and needs, the Chemical Engi-
neering Department at the University of Virginia (UVa) de-
cided to overhaul its senior-level laboratory course to provide
students with experiences and opportunities to learn concepts
and develop skills required for success in today's changing
world. The objectives of this paper are to communicate the
overall concept of the new laboratory course, provide an over-
view of each experiment, and describe student feedback from
the course. Details about each experiment can be obtained by
corresponding with the author.
The objectives of the new 3-credit-hour laboratory course,
based on a full course load of 15 to 18 credit hours per se-
mester, are to:
- Provide students with experiences that are more
relevant to the contemporary chemical engineer.
- Engage students in
* . w1 , .ii. - of process steps.
* relationships between molecular structure and
macroscopic properties.
* translation offundamental science to engineering
D- Provide students with an opportunity to develop team-
work skills in an environment similar to industry.

These objectives were accomplished by first developing
three 4-week-long experiments in Bioprocess Engineering
(protein synthesis and purification), Catalysis and Energy
Conversion (catalytic production of hydrogen coupled to
fuel cells), and Polymer Synthesis and Characterization
(structure/property relationships of advanced materials). A
class structure was then developed to reflect a real-world
chemical engineering environment. Sharing of information
and ideas was accomplished by having small teams of stu-
dents work together as part of a larger
team on each experiment. Knowledge J
and experimental results were commu-
nicated between the smaller sub-teams
using different types of written reports
and an oral presentation.
The three experiments were set up
in a new laboratory facility in Wils-
dorf Hall that opened in the fall of
2006. This state-of-the-art laboratory, ip
dedicated to undergraduate chemical
engineering, has over 2,000 square
feet of space, walk-in hoods, and
abundant natural light (Figure 1). The
major investment in the new laboratory
space, and the equipment required for
the three new experiments, represent a Figure 1. New 2,

Vol. 43, No. 2, Spring 2009

high-level commitment to undergraduate chemical engineer-
ing at UVa.
This space also is used for the junior-year laboratory course
for chemical engineering students at UVa during the prior
semester. The emphasis of this laboratory course is on more
traditional unit operations experiments with heat exchangers, a
distillation column, a fluid flow demonstrator, and equipment
for agitation and mixing.
Moving into a new laboratory facility made it easier to
implement the new senior-level course in a single semester.
This also provided the opportunity to benchmark the new
course to the old course of more traditional unit operation
experiments including a gas absorption column and a fixed-
bed reactor.

Each of the three 4-week-long experiments is designed
for division into three or four separate parts. Teams of six to
eight students divide themselves into three or four sub-teams
to work on the different parts of an experiment (two to three
students per sub-team). A member of the teaching team is as-
signed to each experiment and is responsible for supervising
the experiment and evaluating the students (teaching team
consists of one faculty member and two graduate research
assistants). Each teaching-team member spends 15-20 hours
per week on the course, which includes two 4-hour lab peri-
ods/week, experiment preparation, grading, and office hours
to answer questions.
The first week of each 4-week-long experiment is a planning
period that is used by each teaching-team member to explain
his or her experiment to a student team. The students also
use this time to divide themselves into sub-teams and to
become familiar with their part of the experiment. The final
three weeks are used to run the experiments to accomplish
the objectives of the experiment. The schedule of required

000-square-foot laboratory facility in Wilsdorf Hall for under-
graduate chemical engineering at UVa.

reports and oral presentation for each experiment is shown
in Table 1.
The total equipment cost for the three experiments was in
excess of $400,000. Major equipment costs for the Biopro-
cess Engineering experiment included the 5-liter fermenter
($45,000), liquid chromatography workstation ($62,000),
and the ultra filtration apparatus ($6,000). The major
equipment costs for the Catalysis and Energy Conversion
experiment were the plug flow reactor system ($55,000), gas
chromatograph ($40,000), and fuel cell system ($20,000).
The two big expenditures for the Polymer Synthesis and
Characterization experiment were for the dynamic me-
chanical analyzer ($65,000) and the differential scanning
calorimeter ($55,000).
The summer prior to the first offering of the new laboratory
course was spent by the instructor and five undergraduate
students setting up equipment and working out the details of
each experiment. Assistance was obtained during this time
from other faculty members with expertise in the areas of the
particular experiments. General course material, experimen-
tal procedures, and background information were prepared.
Relevant journal articles and reference materials were placed
on a Web site developed for the new course.

The Bioprocess Engineering experiment involves the
production of recombinant green fluorescent protein (GFP)
from genetically transformed E. coli cells.J81 GFP is well-
suited for use in this type of experiment for several reasons:
its fluorescent nature allows students to detect its presence
visually; the concentration of GFP can be measured in a
protein mixture due to a unique absorbance peak at approxi-
mately 304 nmn; and the extremely hydrophobic nature of GFP
enables a straightforward purification strategy.[9] Because
of this, laboratory experiments for undergraduate chemical
engineering students have been developed for the production
and purification of GFP.10111]
Information from published experiments with GFP has been
used to develop an experiment that can be run in a 4-week time
period with 4 hours/week of experimental time. A working cell
bank of transformed cells, created by faculty and graduate stu-
dents in preparation for this course, is used as inoculum. Students
determine the effect of different process parameters on the growth
of E. coli cells and protein expression using a 5-liter fermentation
vessel (Figure 2a) in the upstream part of this experiment. Cen-
trifugation, mechanical cell lyses, tangential flow ultra filtration
(Figure 2b) and liquid chromatography (Figure 2c) are used in

(a) (b)

Figure 2. Pho-
tographs of the
major pieces of
equipment in the
Bioprocess Engi-
neering experi-
ment including
(a) 5-liter Sar-
tortius BIOStat
CTPlus� fermen-
ter, (b) GE Health-
care QuixStand�
benchtop ultra
filtration appara-
tus, and (c) AKTA
Purifiers liquid

Chemical Engineering Education

Schedule of required reports and oral presentation for each 4-week experiment.
End of Week Required Report/Presentation Comments
1 Planning Report Team report with separate sub-team grades
2 Oral Presentation Team presentation to teaching team member
3 Progress Report Individually prepared report
4 Final Report Team report that integrates work and results of each sub-team. A peer-evaluation
process is used to adjust individual grades.r]

Figure 3. Block
diagram of
the BioProcess
with the flow of
materials out-
side each box
and sub-team
objectives listed
inside each

the downstream part to recover and purify the
GFP product.
A block diagram of the Bioprocess En-
gineering experiment (Figure 3) illustrates CO + H20
the flow of material through the experiment
and highlights the objectives of each major Helium as
part of the experiment. carrier gas
The combination of fermentation, cell
disruption and separation, and liquid chro-
matography enables students to evaluate
and understand the overall process used
to make a protein product. This helped the Figure 4. Bloc
students develop an appreciation that a with the flow
successful process-development team must
work both cooperatively and independently
to develop an optimized, multi-step manufacturing process.
Representative examples of student feedback from this
experiment are:
- "This experiment fit in very well with biotech courses
and tied them ...,- i,, , "
- "Enjoyed seeing the process from fermentation .-/. *,h.
downstream processing to final purified product."
D- "Enjoyed applying my coursework to actual experi-
mentation. "
- "I liked this experiment because it introduced me to
the field of biochemical engineering without having to
take the biochemical engineering electives."

The Catalysis and Energy Conversion experiment is moti-
vated by an interest in hydrogen as an alternative fuel source
and the potential technical and environmental advantages of a
fuel cell to convert hydrogen's chemical energy into electrical
L nL I __. '. The block diagram (Figure 4) shows the flow of mate-
rial and the objectives of the major parts of this experiment.
Pure CO and H20 are converted to CO2 and 1-H over a copper
alumina catalyst (BASF, Selectra Shift 4P+E14]) in the reversible
water-gas shift (WGS) reaction experiment shown in Eq (1).[131
CO + H20 -O CO2 + H2 (1)

The reaction is conducted in a fixed-bed reactor located in a
BTRS-Jr reactor system (Autoclave Engineers). Liquid water
Vol. 43, No. 2, Spring 2009

H2 Production Energy
o maximize CO u maximize power Electric
conversion H2 + CO2 generation Power
and H2 yield H p determine effect b
obtain scale-up of CO cone. on
data 02 fuel cell H20
i performance r
Obtain scale-up

k diagram of the Catalysis and Energy Conversion experiment
of materials outside each box and sub-team objectives listed
inside each box.

enters through an HPLC pump and is vaporized before being
fed into the reactor. Helium is used as a carrier gas to minimize
the temperature increase from the exothermic WGS reaction.
The concentration of CO and CO in the reactor effluent is
determined using an HP 6890 Series gas chromatograph. This
information, along with the inlet flow rates to the reactor, is
used by the students to determine the CO conversion and H
yield for a range of operating conditions. These data are used
to identify the process conditions that result in the highest
CO conversion and largest H2 yield. Students also compare
their experimental CO conversion values to their calculated
equilibrium CO conversion values to determine whether the
reaction is kinetically or thermodynamically limited.
ANafion proton exchange membrane (PEM) fuel cell is used
to convert the chemical energy in H2 to electrical energy.[JsI
Fuel (H2) is fed into the anode side of a PEM fuel cell where it
is converted into protons and electrons in the presence of the
anode catalyst. The protons diffuse through the membrane and
the electrons travel to the cathode through an external circuit.
At the cathode catalyst, oxidant (0 2, either from air or pure 02
gas) reacts with the protons and the electrons to form H2O and
heat. Eq. (2) is a summary of the reactions that occur on the
anode and cathode sides of a PEM fuel cell.

Anode: H2 -+ 2H' + 2e -
Cathode: 0.502 +2e +2H+ - H20
Overall: H2 +0.502 - H 0

. Cell Disruption Liquid
Fermentation Fermentation and Separation G Chromatography
Fermentation broth with GFP and Pure GFP
rmentation provide material GFP in E. coli > remove GFP other > purify GPF product
for separations cells from E. coli cell. proteins protein
Soptimize P separate GFP - otm
Inoculum conditions from cell debris o ntions
with GFP conditions
wvithrr GF obtain scale-up >optimize ,* i
modified da obtain scale-up opnditionsmize obtain scale-up
clsdata conditions dt
cells data
>obtain scale-up

The fuel cell part of this experiment is based on published
laboratory experiments with PEM fuel cells.E16 17 The tem-
perature of the fuel cell is varied from room temperature
to 80 �C. Pure H2 or H2 mixed with a small amount of CO
(<100 ppm) is passed through a heated humidifier before
being fed to the anode side of the fuel cell. The moisture
maintains a high proton conductivity of the electrolyte
membrane. Likewise, pure 02 or air as oxidant is passed
through a humidifier before being fed to the cathode side of
the fuel cell. The flow rates of both streams to the fuel cell
are controlled by digital mass flow controllers (OMEGA,
model FMA6500).
An Agilent Electronic Load (model 6060B) is connected
between the anode and cathode sides of the fuel cell. This
instrument is used to vary the external load on the fuel cell
from 0 Q to 1,000 Q and to measure the voltage and current
of the fuel cell.
Figure 5 is a plot of fuel cell voltage as a function of current
density at three different fuel cell temperatures. Each curve in
this figure, which is referred to as a polarization curve, was
obtained by varying the external load on the fuel cell over
the range of 0 Q to 1,000 Q.
Students are able to determine the optimum conditions for
operating the fuel cell by examining fuel cell performance
over a range of temperatures, pressures, and gas flow rates.
Fuel cell efficiency, defined as the electric power generated
divided by the product of the rate of reactant utilization and its
Higher Heating Value, is calculated under the optimum condi-
tions. This information is used by the students to scale-up their
results from a single fuel cell data to a fuel cell "stack," i.e.,
fuel cells connected in series, which is capable of producing
enough energy for an average-size home.
Students observe that a CO concentration in H2 as low as 10
ppm can significantly affect the performance of a PEM fuel
cell, which illustrates why it is important for the WGS reaction
to be run with a very high CO conversion value. In addition,
they appreciate why the H2 produced in the upstream part of
this experiment as currently configured cannot be fed directly
to the PEM fuel cell since the lowest CO concentration in the
reactant stream leaving the reactor is approximately 20,000
ppm. A new type of fuel cell made by BASF, that can tolerate
a CO concentration as high as 30,000 ppm, is currently being
evaluated for use in this experiment.181

Figure 6. Structural
representations of the
(a) isocyanate and R
(b) hydroxyl reactive '
groups, and (c) ure- C
thane linkage. O


Representative student comments from this experiment are:
- "I learned a great deal in this lab, having no previous
experience with fuel cells."
- "Enjoyed the real-life application with the fuel cell."
- "I really liked the design problem."
- "Enjoyed applying what we learned in class to real
- "Enjoyed learning about fuel cells and seeing the dif-
ferent factors that affect them."
- "Reactor experiment was practical and related many of
the basic chemical engineering concepts to practice."


Polyurethane is a polymer that contains urethane linkages
formed by the reaction of a diisocyanate containing two
or more isocyanate groups (NCO) with a glycol molecule
or a low-molecular-weight diol containing two or more
hydroxyl groups (OH).[19] Figure 6 includes structural
representations of these different chemical groups where
R and R' are two different carbon chains (R is usually
aromatic, R' is usually aliphatic).

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Current Density (A/cm )

Figure 5. Effect of temperature on fuel cell performance.
Experimental conditions: H2 flow rate 30 ml/min, 02 flow
rate 30 ml/min, anode side pressure 10 psig, cathode side
pressure 6 psig. Data obtained from student experimental


R -R'

R'-OH 0
(b) (c)

Chemical Engineering Education

Polyurethane polymer chains are composed of alternating
"soft" segments and rigid "hard" segments. The soft segments
are formed by the reaction of high-molecular glycol molecules
with diisocyanate molecules. The number average molecular
weight i \ In i of the glycol molecules used to make a polyure-
thane polymer is usually between 1000 and 2000 (i.e., Mn
of R' is between 1000 and 2000). A typical soft segment of a
polyurethane polymer contains between two and four glycol
molecules that are joined together with urethane linkages.
The hard segments are formed from the reaction of diiso-
cyanate molecules with a low molecular weight diol, such
as 1,4 butanediol, that is typically referred to as the chain
extender. The hard and soft segments are joined end-to-end
with urethane linkages. For this reason, polyurethane poly-
mers are usually classified as block copolymers. A schematic
representation of a polyurethane polymer chain is shown in
Figure 7.

The students are given the assignment in the Polymer
Synthesis and Characterization experiment to produce a soft,
energy-absorbing polyurethane polymer for use in applica-
tions including the soles of shoes and personal protective
equipment. This objective is accomplished by the students
synthesizing polymers from several different prepolymers
and chain extenders and then measuring the performance
properties of the polymers. Figure 8 is a block diagram to
illustrate the flow of materials and information through this
experiment, and to summarize the objective of each of the
four sub-teams.
The students synthesize polyurethane polymers by adding
the appropriate amount of chain extender(s) to a prepolymer
with a known mass and isocyante concentration (%NCO) in
a plastic cup. After mixing with a disposable stir-stick, the
mixture is poured into heated sample molds and allowed to
cure at 80 �C for 16 hours. The %NCO value of each prepoly-
mer is measured by the students using a
titration technique.

soft segment segment soft segment hard segment soft segment

nrumn glycol molecule
- chain extender
* urethane linkage

Figure 7. Schematic representation of a polyurethane polymer chain showing
the soft segments (long chain glycol molecules connected with urethane groups)
and hard segments (chain extender connected with urethane groups).

mers ar
this exp
are prej
of 4,4'-
after all

different polyurethane prepoly-
e obtained from ITWC, Inc., for
)eriment.Y201 These prepolymers
pared by reacting polyether- or
er-based glycols with an excess
Diphenylmethane diisocyanate
An excess of MDI is used so that
d diisocyanate molecules remain
the glycol hydroxyl groups have
been consumed. The amount
of excess diisocyanate is
quantified with a parameter
referred to as %NCO, which
is simply the wt% of NCO
in the prepolymer (prepoly-
mers used in this experiment
have NCO values between 6
and 12 wt%). Based on the
%NCO, the amount of chain

Figure 8. Block diagram
of the Polymer Synthesis
and Characterization
experiment to illustrate
the flow of materials
(solid lines) and infor-
mation (dotted lines)
through this experiment.
The objectives of each of
the four sub-teams are
listed inside each box.
Data synthesis is accom-
plished by the four sub-
teams working together.

Vol. 43, No. 2, Spring 2009

Polymer synthesis
DSC recommendations
polymers > determine Tg T
. and identify __ _ _ __ _ _ _
other thermal

Polymer Poly- DMA Data Synthesis
Synthesis urethane develop
Prepolymer ) develop polymers > measure E', E, E" relationships
E", and Tan 8 E between polymer
synthesis plan as a function ----------- structure --
Chain Extender and algorithm of temperature Tan 8 physical properties:
> synthesize and frequency and performance
polymers properties
A-- ^ -- ------- - - ------ - - -

Analytical and Polyurethane
Testing hardness with optimized
physical properties
Measure %NCO -----------------
Polyurethane hardness, and % rebound
polymers % rebound

%NCO value
. . . . . . . . . . . . . . . . . . . . . . . . . . . . .-

extender required to react all the isocyanate groups to form
the final polymer can be determined.
Students use two different chain extenders (1,4 butanediol
and diethylene glycol) to react the NCO groups of the prepoly-
mers to form the final polyurethane polymers. Synthesizing
polyurethane polymers with different types of soft and hard
segments, and with different hard-segment concentrations,
enables the students to test polymers with a wide range of
rheological properties and thermal transitions and to observe
a range of performance properties.
A Shore SRI Resilometer, commonly referred to as a Bay-
shore Resilometer, is used to measure the % rebound of the
polyurethane polymers following ASTM procedure D2632.
Polymer hardness is measured using hand-held durometers
obtained following ASTM procedure D2240. "A" and "D"
scale durometers are used so that polymers with a wide range
of hardness values can be characterized.
A TA Instruments Q1000 differential scanning calorimeter
(DSC) is used to determine the effect of polyurethane compo-
sition changes on the glass transition temperature (T ). DSC
also is used to identify any other higher-temperature thermal
transitions in these materials. The rheological properties of
the polyurethane samples, including elastic (E') and viscous
(E") modulus, are measured as a function of temperature
and frequency using a dynamic mechanical analyzer (DMA)
manufactured by TA Instruments (Model Q800). The energy
damping coefficient, Tan 6, which is the ratio of E" to E', is
calculated using the measured moduli values.
The students are challenged to use all of their measurements
to develop an understanding of the relationships between
molecular structure, rheological properties (i.e., E' and Tan
6), and performance properties (i.e., % rebound and hard-
ness) of their polyurethane samples. They are then expected
to communicate their understanding to the polymer synthesis
team to help decide which prepolymer and chain extender(s)
to use in their second batch of polymers to obtain a material
with the best combination of energy absorbing and hardness
properties for the stated end-use of the material.

Representative student comments from this experiment are:
- "This lab really allowedfor all the sub-teams to come
.., ti-., and I .1,. l,,i that that was very helpful."
N "Learning about the challenges of polymer synthesis
was very . t,, "
- "Enjoyed how the sub-teams relied on feedback from
other sub-teams .,. .,,, h..,,t the experiment."
- "Learned a great deal including the application of tech-
niques and end-use tests."
- "This experiment really gave us a good idea of how
polymers are made."

Student feedback regarding the new laboratory course was
obtained from the online course evaluation that is adminis-
tered by the school and by a custom questionnaire that was
administered at the end of the semester. The online course
evaluation provided comparisons of student feedback from the
old and new laboratory courses. The questionnaire provided
an opportunity to obtain quantitative information about how
well the objectives of the new laboratory course were met,
how students enjoyed the organization of the new laboratory
course, and how students felt about each of the three experi-
ments that make up the new laboratory course.
The online course evaluation consists of 20 general ques-
tions about the course and the instructor. Students respond
to each of the questions on a scale of 1 to 5 where 5 is the
most favorable. Overall ratings for the course and instructor
are calculated based on responses to the 20 questions by all
the students. The overall course rating for the last two years
of the old laboratory course was 4.03 and 4.05 (out of 5)
indicating a good course rating. The overall course rating for
the new laboratory course was 4.48 indicating a significant
increase in course satisfaction by the students for the new
course compared to the old course.
For the custom questionnaire, a response scale of 1 to 5 was
provided for each statement, where 1 is strongly disagree and

Summary of student responses to the statements that they were provided on the custom questionnaire
about how well the course objectives were met
Statement Strongly Agree Neutral or
Agree Disagree
1. Collectively, the three 4-week-long experiments provided me with educational opportuni- 68% 32% 0%
ties that are relevant to today's practicing chemical engineer.
2. The three 4-week-long experiments taught me about the:
a. integration of process steps. 36% 56% 8%
b. relationship between molecular structure and macroscopic properties. 16% 60% 24%
c. translation of fundamental science to engineering principles. 28% 68% 4%
3. Dividing my lab team into smaller sub-teams provided an opportunity to develop teamwork 48% 44% 8%
skills in an environment similar to what I might experience working in industry.

10 Chemical Engineering Education

5 is strongly agree. Students were also encouraged to add individual comments about
each statement. Included in Table 2 is a summary of student responses to the three state-
ments about how well the course objectives were met.
Responses to the first statement clearly indicate that the students felt the new labora-
tory course taught them about technologies that are relevant to the modem chemical
engineer. Individual comments indicated that the students enjoyed discussing the details
of the experiments during job interviews.
Responses to the second statement indicate that the students learned something about
the integration of process steps and how material learned in basic science classes can be
applied to engineering-related problems. The connection between molecular structure and
macroscopic properties was not made apparent to a number of students, however. Even
so, individual comments indicated that the students appreciated the different learning
opportunities they were provided during the course ("Learned more in this course than
any other course that I have taken here."). Most students felt that the team/sub-team
structure was challenging, but felt that this experience helped prepare them for what
they will experience working in industry based on responses to the third statement and
on individual comments included with this statement. In particular, students commented
that they enjoyed the opportunity to be part of smaller sub-teams that worked together
to achieve a common goal.
Feedback from the students indicated that a successful multi-week experiment does
not depend on whether or not the students had prior coursework related to the subject of
the experiment. For example, students who had not taken any bioengineering electives
appreciated the opportunity to learn about the field during the Bioprocess Engineering
experiment, while students working toward a bioengineering concentration enjoyed
being able to apply their classroom knowledge to hands-on experiences. Furthermore,
although an elective course in polymers is currently not offered at UVa, students were
able to learn enough about the subject, and the details of polymer rheology and thermal
transitions, to have a productive and enjoyable laboratory experience in polymers.
An overall observation by the instructor is that students stayed much more focused and
engaged with the new laboratory course throughout the semester compared to students
during the old laboratory course. It is the instructor's belief that the primary reason for
the change in student attitude and interest is that the students find the three 4-week ex-
periments that make up the new laboratory course more interesting and relevant to what
they might do as chemical engineers after graduation than the traditional unit operations
experiments that were used in the old laboratory course.

The authors gratefully acknowledge the financial support of Virginia's Equipment
Trust Fund that provided funds to purchase most of the equipment for the Bioprocess
Engineering and Catalysis and Energy Conversion experiments. Also, the authors grate-
fully acknowledge the Office for Naval Research for funds that were used to purchase the
major pieces of equipment for the Polymer Synthesis and Characterization experiment
through its Defense University Research Instrumentation Program (DURIP), contract
N00014-06-1-0853. Finally, the technical support of Steve Longacre from ITWC, Inc.,
throughout the development of the Polymer Synthesis and Characterization experiment
is noted and gratefully acknowledged.

1. Cussler, E.L., "A Different Chemical Industry," Chem. Eng. Educ., 40, 114 (2006)
2. AIChE, , 2004 (AIChE Department of Career Services)
3. Varma, A., "Future Directions in ChE Education: A New Path to Glory," Chem. Eng. Educ., 37, 284
4. Rugarcia, A., R.M. Felder, D.R. Woods, and J.E. Stice, "The Future Direction of Engineering Educa-

Feedback from

the students

indicated that a



experiment does

not depend on

whether or not

the students

had prior


related to the sub-

ject of the experi-

ment. For exam-

ple, students who

had not taken any



appreciated the

opportunity to

learn about the

field during the




Vol. 43, No. 2, Spring 2009

tion, Part 1. A Vision for a New Century," Chem. Eng. Educ., 34, 16
5. Armstrong, R.C., "A Vision of the Curriculum of the Future," Chem.
Eng. Educ., 40, 104 (2006)
6. Davis, M.E., "Adapting Chemical Engineering Education to Increasing
Job Diversity," Philips Lecture, Oklahoma State University (2004)
7. Kaufman, D.B., and R.M. Felder, "Accounting for Individual Effort
in Cooperative Learning Teams," J. Eng. Educ., 89, 133 (2000)
9. Yakhnin, A.V., L.M. Vinokurov, A.K. Surin, and Y.B. Alakhov, "Green
Fluorescent Protein Purification by Organic Extraction," Protein Ex-
pression and Purification, 14, 382 (1998)
10. Komives, C., S. Rech, and M. McNeil, "Laboratory Experiment on
Gene Subcloning for Chemical Engineering Students," Chem. Eng.
Educ., 38(3) 212 (2004)
11. Fisher, H.E., and C.S. Mintz, "Use ofthe Green Fluorescent Protein as
an Educational Tool," J. of Industrial Microbioloogy & Biotechnology,
24, 323 (2000)
12. Tullo, A.H., "A Fuel Cell in Every Car," Chem. and Eng. News, 79,

13. Keiski, R.L., 0. Despons, Y.E Chang, and G.A. Somorjai, "Kinetics of
the Water-Gas Shift Reaction Over Several Alkane Activation and Wa-
ter-Gas Catalysts," Applied Catalysis A: General, 101, 317 (1993)
14. Ilinich, 0., W Ruettinger, Z Liu, and R. Farrauto, "Cu-A1203-CuAl204
Water-Gas Shift Catalyst for Hydrogen Production in Fuel Cell Ap-
plications: Mechanism of Deactivation Under Start-Stop Operating
Conditions," J. Catalysis, 247, 112 (2007)
15. Ashley, S., "On the Road to Fuel-Cell Cars," Scientific American,
March, 62-69 (2005)
16. Lin, J.-C., H.R. Kunz, J.M. Fenton, and S.S Fenton, "The Fuel Cell:
An Ideal Chemical Enginieering Undergraduate Experiment," Chem.
Eng. Educ., 38(1) 38 (2004)
17. Fowler, M.W, and A. Lam, "PEM Fuel Cell Test Station and Labora-
tory Experiment," Chem. Eng. Educ., 38(3) 236 (2004)
19. Oertel, G., Polyurethane Handbook, 2nd Ed., Hanger Publishers,
Munich/New York (1994)
20. J

Chemical Engineering Education

Random Thoughts ...



North Carolina State University
If you are like most faculty members, your salary is paid
by your university and you're subject to policies dictated
by the Provost and Dean, but your department is your
academic home. Cultures can vary dramatically from one
department to another, and how much you look forward to
coming to work every day can depend significantly on how
well you are temperamentally suited to your department's
culture. Just for the fun of it, fill out the questionnaire on
the next page to gauge how you perceive that culture. For
the questionnaire to be most useful, you should complete it
before continuing to read. Go ahead-I'll wait.

Finished? Look back at the bottom row. The more (a) an-
swers you circled, the more your department can be character-
ized by words such as collegial and supportive; the more (b)
answers, the more words like individualistic and competitive
would apply. It's not that one type of department is good and
the other is bad-they're just different. (I'm partial to col-
legial, but that's just me.)
Your comfort level at work depends on how compatible
your personality is with the culture-collegial or individual-
istic-of your department. If you are strongly collegial, you'd
probably be more comfortable in a collegial department than
in an individualistic one; if you're strongly individualistic you
might or might not be comfortable in a collegial department,
but there is a good chance that your collegial colleagues would
not be particularly comfortable with you. If either you or your
department is somewhere near the balance point between
collegial and individualistic, there's a reasonable chance that
things will work out-and if they don't, it will likely be for
reasons other than a culture incompatibility.
While I haven't attempted a rigorous validation of the ques-
tionnaire, to get a feeling for how it works I asked several of
my friends on engineering faculties to complete it. Four of
them in the same department-the department head, a full
professor, an associate professor, and an assistant professor
in his second year-respectively registered a-b scores of
14-3, 15-2, 14-3, and 15-2. In another department, the scores
submitted by two professors (full and associate) were 12-5 and
9-8. Individual profiles from the other raters - all in different
Vol. 43, No. 2, Spring 2009

departments- were 10-7, 11-6, 12-5, 12-5, and 0-17. In short,
all but one department fell in a range from very collegial to
fairly collegial, and that one showed up as virtually devoid
of collegiality. I'm familiar with the departments in question
and consider all of those ratings to be accurate.
If you are a department head and would like to increase your
department's level of collegiality, have the faculty complete
the questionnaire anonymously and use common (b) responses
as prompts for change. If you see widely varying scores from
different respondents, it could signal a problem such as the
existence of cliques or the exclusion of women and minorities
from full participation in department activities, and you should
try to find out what's going on. If you are a faculty member,
postdoctoral fellow, or graduate student looking for a new
academic position, complete the questionnaire with your ideal
department in mind before you go on your first interview trip.
You should probably stop short of asking the search committee
to fill out the questionnaire, but you might casually introduce
some of the questions in your discussions with department
faculty. The correspondence-or lack of it-between your
responses and theirs could tell you a lot about how suitable
the department is for you and vice versa.

My thanks go to Dave Clough of the University of Colorado,
who gave me the idea for this column in a recent conversation,
and to Rebecca Brent and other colleagues who completed
early drafts of the questionnaire and offered excellent sug-
gestions for improvement.

� Copyright ChE Division of ASEE 2009

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 edu/felder-public>.

Academic Department Culture Assessmentt
For each of the 17 questions, circle the letter next to the description
that most closely matches your perception of your department.
1 a Research collaborations among department faculty members are common and fluid (the col-
laborators are different from one project to another).
b Intradepartmental research collaborations are uncommon. When they exist, they usually
involve the same faculty members year after year.
2 a Most graduate students identify themselves first as belonging to their department, second as
members of their advisor's research group.
b Most graduate students identify themselves first as members of their advisor's research
group, second as belonging to their department.
3 a Informal interactions between senior faculty and junior faculty are common.
b Informal interactions between senior faculty and junior faculty rarely occur.
4 a Laboratory space and equipment are often shared by students working for different advisors.
b Sharing space and equipment across research groups is rare.
5 a Groups of faculty members frequently go out for lunch together.
b Groups of faculty members rarely go out for lunch together.
6 a Individual faculty achievements and honors are routinely acknowledged and celebrated.
b Faculty achievements and honors usually go without notice within the department.
7 a Faculty members and their partners/families periodically socialize with one another.
b Social interactions among faculty members and partners/families almost never occur.
8 a New faculty are routinely mentored in research and teaching by senior colleagues.
b Mentoring of new faculty does not routinely occur.
9 a The whole faculty gathers regularly for refreshments and conversation.
b Gatherings of the faculty for refreshments and conversation rarely occur.
10 a Graduate students are frequently co-advised by two or more department faculty members.
b Co-advising of graduate students within the department rarely occurs.
11 a Relationships among faculty members are almost always cordial and cooperative.
b Relationships between many faculty members are often distant or competitive.
12 a The department's teaching program quality is a source of pride or concern to the faculty.
b The department's teaching program is seldom a topic of conversation among the faculty.
13 a Dissertation defenses are almost always amicable.
b Dissertation defenses often include hostile questions from members of other research groups.
14 a Graduate students generally choose research advisors after they begin their graduate studies.
b Graduate students commonly commit to advisors before their first semester.
15 a Faculty meetings are generally peaceful.
b Faculty meetings are often contentious.
16 a The Department Head provides performance feedback to new faculty annually or more often.
b The Department Head does not regularly provide performance feedback to new faculty.
17 a Retired faculty members regularly participate in department activities.
b Retired faculty members rarely participate in department activities.
*Add the number of circled a's and b's in their respective columns.
t All rights reserved by RichardM. Felder, North Carolina State Unmverstty,
114 Chemical Engineering Education

MR! t class and home problems



National Institute of Applied Sciences and Technology
The Peng-Robinson equation of state (PR EOS) was sug-
gested in 197601] to satisfy the following objectives:

1. Parameters of this EOS should be defined in terms of the
critical properties and the acentric factor.
2. Reasonable accuracy near the critical point, particu-
larly for calculations of the compressibility factor and
liquid density.
3. A single binary interaction parameter, which should be
independent of temperature pressure and composition, is
needed for the mixing rules.
4. PR EOS should be applicable in natural gas processes.
The PR EOS provided results similar to the Soave-
Redlich-Kwong EOS, although it is generally superior in
estimating the liquid densities of many materials, especially
nonpolar ones.
The authors start by using the PR EOS to predict several
pure-component properties, such as liquid and gas molar vol-
umes for propane. The vapor-liquid isobaric diagram is then
computed for a binary mixture composed of n-pentane and
n-hexane at pressures of 2 and 8 bar. We compute the extent
Vol. 43, No. 2, Spring 2009

* 1080 Tunis, Tunisia
of reaction in the case of the high-pressure ammonia synthesis
in the next section. Finally, the adiabatic flash computation
problem is presented and we conclude with several remarks
concerning the use of MATLAB in chemical engineering.[2]

Housam Binous is a full-time faculty mem-
ber at the National Institute of Applied Sci-
ences and Technology in Tunis. He earned
a Diplome d'ingenieur in biotechnology from
the Ecole des Mines de Paris and a Ph.D.
in chemical engineering from the Univer-
sity of California at Davis. His research
interests include the applications of com-
puters in chemical

Zakia Nasri is a Ph.D. student at the National
Institute of Applied Sciences and Technology
L 'in Tunis. She earned a Master's degree and a
Diplome d'ingenieurin industrial chemistry from
the National Institute of Applied Sciences and
Technology in Tunis. Her research interests
are in applied thermodynamics and petroleum

� Copyright ChE Division of ASEE 2009

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.


The Peng-Robinson equation of state[3 5] is

RT a (1

(V-b) v(v+b)+b(V-b)

5G.- --I------- ----------I----7I-------I-------------------

1D . ---1-:15K
-2 -
.0 - .................... 36 ..15 J(........... ... ... ...... ...

-20 ....... ------------------iI -------I ------- --------------

0 200 40 6] ) 800 1000 120D 1400 160D
Volume, cm3/mol

Figure 1. Isotherms for propane with spacing of 10 K.


b= 0.07780-

a =0.45724R 1+ m 1- T

Volume, cmrimol

Figure 2. Isotherm at 313.15 K (shaded areas are equal)

Chemical Engineering Education

MATLAB Commands for Obtaining the Isotherms
% propane's critical temperature and pressure and acentric factor
Tc = 369.9;
Pc = 42.0;
Omega= 0.152;
% universal gas constant
R = 83.14;
% b and m for the PR EOS
b = 0.07780*R*Tc/Pc;
m = 0.37464 + 1.54226*Omega - 0.26992*Omega^2;
for i=40:10:90
% molar volume
% temperature
% reduced temperature
Tre = T(i)/Tc;
% a for the PR EOS
a = 0.45724*(R*Tc)^2/Pc*(l + m*(l - sqrt(Tre)))^2;
P=R*T(i)./(v - b) - a./(v.*(v + b)+b*(v-b));
Pv= [ Pv P'];
% plotting isotherms for T varying from 313.15 to 363.15 K
figure (2)
hold on
axis([0 1600 -40 60])
xlabel('Volume in cm3/mol')
ylabel('pressure in bar')
title('Isotherms for propane')



m= 0.37464 1.54226)- 0.26992L2 (5)

In Figure 1, we show isotherms (of the P/V relationship)
obtained for propane at temperatures varying from 313.15 K
to 363.15 K. Propane's critical temperature and pressure and
acentric factorm51 are:

T=369.9 K, P =42.0 bar and co=0.152.

These isotherms are obtained using the MATLAB com-
mands given in Table 1.
In Figure 2, one can read the vapor pressure as well as the
liquid and gas molar volumes at different temperatures using
the bold dots. These pure component properties are found by
imposing that the two shaded areas in Figure 2 are equal; the
MATLAB syntax for such an operation is given in Table 2.
The isotherm oscillates in a specific region and the PR EOS
fails to describe real substances in this region. To fix this
problem James Clerk Maxwell (1875) proposed to replace the
isotherm in this region with a horizontal line positioned so that
the areas of the two shaded regions are equal. The reason for

MATLAB Commands for Obtaining the Liquid and Gas Molar Volumes
function f=Pressurel(v,T)
% propane's critical temperature and pressure and acentric factor
Tc = 369.9;
Pc = 42.0;
Omega= 0.152;
% universal gas constant
R = 83.14;
% b and m for the PR EOS
b = 0.07780*R*Tc/Pc;
m = 0.37464 + 1.54226*Omega - 0.26992*Omega^2;
% reduced temperature
Tre = T/Tc;
% a for the PR EOS
a = 0.45724*(R*Tc)^2/Pc*(l + m*(l - sqrt(Tre)))^2;
f=R*T./(v - b) - a./(v.*(v + b)+b*(v-b));

function f=equations31(x,T)
% three algebraic equations, which solution gives the molar volumes
f(1)=-quad(@(v) Pressurel(v,T),x(1),x(2))+...
feval(@(v) Pressurel(v,T),x(1))*(x(2)-x(1))...
+quad(@(v) Pressurel(v,T),x(3),x(2))...
-feval(@(v) Pressurel(v,T),x(2))*(x(2)-x(3));
f(2)=feval(@(v) Pressurel(v,T),x(l))-feval(@(v) Pressurel(v,T),x(3));
f(3)=feval(@(v) Pressurel(v,T),x(2))-feval(@(v) Pressurel(v,T),x(3));

% using fsolve to get the molar volumes
X=fsolve(@(x) equations31(x,T(i)),[100 260 800])
% plot the bold dots in figure 2
h=plot(max(X),feval(@(v) Pressurel(v,T(i)),max(X)),'b.')
h=plot(min(X),feval(@(v) Pressurel(v,T(i)),max(X)),'b.')

where the solutions of this system of three non-linear algebraic equations, min(X) and max(X), are the
liquid and gas molar volumes. Once the vapor pressure and liquid and gas molar volumes are computed, it is
straightforward to get the bold dots using the following two lines of MATLAB� code:

h=plot(min(X),feval(@(v) Pressurel(v,T(i)),max(X)),'b.')

Vol. 43, No. 2, Spring 2009

Using the


equal area

rule, one can

get estimates

for the vapor

pressure as

well as the

liquid and

gas molar

volumes from

the depicted


this equality is that the area in the P-V diagram corresponds to mechanical work and the change
of free energy, AA(T,V), is equal to that work. This change of free energy is independent of the
path because A(T,V) is a state function. Thus, this work should be equal if one takes the hori-
zontal line drawn by Maxwell as a transformation path or the isotherm obtained using PR EOS
as an alternative transformation path. The flat line portion of the isotherm now corresponds to
liquid-vapor equilibrium. Using the Maxwell equal area rule, one can get estimates for the vapor
pressure as well as the liquid and gas molar volumes from the depicted isotherms.
The values of the vapor pressure, calculated using the PR EOS, are then plotted vs. temperatures
in Figure 3. These points agree with the curve calculated using the modified Antoine equation
obtained from HYSYS 3.2, a major process simulator by Aspen Technology, Inc. ( hyprotech.com>), and given by

Pat = exp 52.3785- 3.4905510 -6.108751n(T)+1. 11869 10 T2 100 (6)

with T in Kelvin and Pa' in bar.

The vapor-liquid isobaric equilibrium diagram for the binary mixture composed of n-pentane
and n-hexane can be computed using the PR EOS. The liquid and vapor mole fractions are re-
lated by
yI = KIx with = 1 or 2 (7)

where K is the equilibrium constant.
The PR EOS is part of a family of equations called cubic because the compressibility factor,
Z, is a solution of the following cubic equation written for a multicomponent mixture where we
have used the mixing and combining rules,
Z3-1-B)Z2 (A-3B2-2B)Z (-AB+B2+B3)=0 (8)



W 310s 32 33D 34 350 30 3M
Temperature, K

Figure 3. Vapor pressure vs. temperature for propane.

Eyl A or T ZXxxxA J
J-1 11 jli

n-pentane vapor or kquid mole fraction
Figure 4. Isobaric VLE diagram for n-pentane/n-hexane
mixture at 2 and 8 bar.
Chemical Engineering Education

A =(AA) (1- k,)


A =0.45724a - and B =0.07780 i
T 2 T

For each component, we define the reduced pressure and temperature by P = P/PC and
T = T/T, and a is given by an equation similar to Eq. (3) for the pure component case. The
binary interaction parameter, k , is obtained from HYSYS 3.2 or assumed to be equal to zero if
not available. The equilibrium constants are obtained using the (p- ( method as follows,

K = -for i= 1 to C (13)


BA 2 y lJ yA BI Z+ 1-+- B
S=exp Z -1)- In Z -B) A -- B )BIn B)B (14)
B 2V2B A B Z , (I- [)B

A similar expression is obtained for the liquid phase fugacity coefficient, 0 , by replacing the
gas phase compressibility factor, Z, with its liquid phase counterpart, Z1 . These two compress-
ibility factors are the largest and smallest roots of Eq. (8), respectively. We perform several flash
calculations to obtain both the bubble-point and the dew-point curves using the famous Rachford
and Rice equation given by:
z (K -1) 0 (15)
-1 ( =K -1)

where z is the mole fraction of component i in the feed. The MATLAB commands for the VLE
data determination are given in Table 3 (next page).
Figure 4 is obtained for pressures of 2 and 8 bar. These results agree with those given by
DISTIL by Hyprotech Ltd. One advantage of the PR EOS is that one can compute VLE data for
low, moderate, and high pressures with the same code. According to Figure 4, one could assume
that the binary mixture is ideal at low pressures since both n-hexane and n-pentane are nonpolar

Nitrogen and hydrogen react to form ammonia, N2 +3H2 NH3. This reaction is favored
by low temperatures and high pressures. Kinetic considerations, however, oblige us to use high
temperatures. Thus, reactors are operated at very high pressures to get a reasonably high con-
version of reactants. High gas-phase pressures imply significant deviation from ideality and the
need to take into account the fugacity coefficients. 51 In fact, the equilibrium constant depends
on K as follows:

K av,
a =H

YNH3 1
N p2

X(2-X) 1K

1 X05 31 X)5P v
2 2

Nitrogen and


react to form


This reaction is

favored by low


and high




however, oblige

us to use high


Thus, reactors

are operated at

very high

pressures to get

a reasonably


conversion of


Vol. 43, No. 2, Spring 2009

MATLAB Commands for Obtaining the VLE Data

function f=flash(x)
global z
% critical temperature and pressure and
acentric factor
% for n-pentane and n-hexane
Pc=[33.75 30.32];
Tc=[196.45+273.15 234.748+273.15];
w=[0.25389 0.3000];
% pressure is set equal to 2 bars
% reduced temperature and pressure
% m, a, Ai, Bi, Aij, A, B for the PR EOS
mr0.37464 + 1.54226.*w-0.26992.*w.^2;
for i=1:2
for j=1:2
for i=1:2
for j=1:2
for i=1:2
for i=1:2
for i=1:2
for j=1:2
Alsum=[0 0];
for i=1:2
for j=1:2
Avsum=[0 0];
for i=1:2
for j=1:2
% liquid and gas phase compressibility fac-
Zv=max(roots([1 -1+Bv Av-3*Bv^2-2*Bv -

continued next column

TABLE 3, continued

Av*Bv+Bv^2+Bv^3])); Zl=min(roots([1 -1+B1
Al-3*Bl^2-2*Bl -Al*Bl+Bl^2+Bl^3]));
.-........cients phiv=exp((Zv-1).*Bp/Bv-log(Zv-
By) ...
% equilibrium constant
% the system of five algebraic equations
for i=1:2
for i=1:2
end f(5)=0;
for i=1:2

global z
clear sol
% flash calculation using fsolve and a zero-
order collocation method
z=[0.0001 0.9999];
options = optimset('Display','off');
[X]=fsolve(@PT1,[0.01 0.9 0.01 0.9 360],op-
tions); xO=X;
for i=1:100
z=[0.01*i l-0.01*i];
% plotting bubble curve
hold on
% plotting due curve
axis tight
xlabel('vapor or liquid mole fraction')
ylabel('temperature in K')
grid on

Chemical Engineering Education

MATLAB Commands for Ammonia Synthesis Problem
function f=ammonia(x,T,P)
Zv=x(5) ;
% critical pressure for hydrogen, nitrogen
and ammonia
Pc=[13.16 33.94 112.77];
% critical temperature for hydrogen, nitro-
gen and ammonia
Tc=[33.44 126.19 405.55];
% acentric factor for hydrogen, nitrogen and
w=[0.0 0.0206 0.2582];
% reduced temperature
% reduced pressure
% Parameters for the Soave-Redlich-Kwong
Equation of State
% m, a, Ap, Bp Av, Bv, Bl, Al
for i=1:3
for j=1:3
for i=1:3
for j=1:3
for i=1:3
% Equilibrium constant versus temperature
Ka298 = exp(16.5*1000/(8.314*298.15));
a = 24.619 - 0.5*27.318 - 1.5*26.879;
b = (3.75 - 0.5*(0.623) - 1.5*(0.435))*10^-
c = (-0.138 + 0.5*(0.095) + 1.5*(0.033))*10^-
d = (0.5*(2.871) + 1.5*(0.87))*10^-9;
K=Ka298*exp(a/8.314*log(T/298.15) +
b/(2*8.314)*(T-298.15) ...
+ c/(6*8.314)*(T^2-298.15^2) +
d/(12*8.314)*(T^3 - 298.15^3) + ...
1/8.314*(46100 + (298.15)*a +
b/2*(298.15^2) + ...
c/3*(298.15^3) + d/4*(298.15^4))*(l/T-

continued next column

TABLE 4, continued
% fugacity coefficients for vapor phase
phiv=exp((Zv-1) .*Bp/Bv-log(Zv-Bv)...
% system of algebraic equations
*phiv(1) 1.5*phiv(2)^0.5...

% temperature is 800 K
% calculation using fsolve and a zero-order
collocation method
X0=[0.2 0.1 0.4 0.9 0.9 0.9];
for P=10:100:1600
if(i==l) X=fsolve(@(x) ammonia(x,T,P),XO
else X=fsolve(@(x) ammonia(x,T,P),[yl(i-
1) y2(i-l) y3(i-l) Xe(i-l)...
Z(i-1) Kv(i-1)],options);
% plotting the extent of reaction versus
pressure at 800 K
figure (1)
axis tight
xlabel('Pressure in bars')
ylabel('Extent of reaction at T=800K')
% plotting the correction coefficient, Kv,
versus pressure at 800 K
figure (2)
axis tight
xlabel('Pressure in bars')
ylabel('Kv at T=800K')

Vol. 43, No. 2, Spring 2009

where Kv is given by:

K INH (17)
�N H

a1 = ylP (18)

The extent of reaction, X, is defined by the following equation: N =N +v X where N and N0 are the number of moles of spe-
cies I at time t and initially, respectively, and v is the stoichiometric coefficient. The unknowns in this type of problems are five:
the mole fraction in the gas phase, the extent of reaction, and the gas-phase compressibility factor. Once again, the calculation
uses the built-in functionfsolve to solve five nonlinear algebraic equations simultaneously. The MATLAB commands, which
allow the determination of the five unknowns, are given in Table 4 (previous page).
In Figure 5, we plot Kv vs. pressure at a temperature of 800 K. Values of Kv are significantly different from unity, which
means that this factor must be taken into account at high pressures. The extent of reaction at equilibrium versus pressure, for
the same temperature, is represented in Figure 6. The extent of reaction approaches unity at high pressures, in agreement with
LeChatelier's rule.

A quaternary mixture, at 33.016 bar and 37.778 �C, is composed of 0.41% hydrogen, 5.71% methane, 70.97% benzene, and
22.91% toluene. This mixture is sent to a stabilizer to remove hydrogen and methane. The feed pressure is decreased adiabati-
cally from 33.016 bar to 11.232 bar by valve and pipeline pressure drop. To find the vapor-phase fraction, the temperature, and
other relevant variables, one needs the following expression for the departure function from ideality for the enthalpy in order
to compute enthalpyE51:

1 Z+ ( B d RT)2 (RT)2
HD =RT(Z-1)-+ Log Z--1 T- A--- -AT--- (19)
2 B RT Z+ 1- B dT P P

This problem has been solved using a tedious iterative technique.61] The unknowns in this problem are the mole fractions in the
two phases, the temperature, the vapor phase fraction as well as the compressibility factors. We have 12 nonlinear algebraic
equations to solve simultaneously. These equations are three equilibrium relations, three component mass balances, two
summation rules, two cubic equations of the compressibility factors, the enthalpy balance, Hfeed =Hv+(1-4)HL, and the
Rachford and Rice equation. The MATLAB commands, which allow the determination of the 12 unknowns, are based on the
optimization toolbox functionfsolve. The code is similar to the one presented in the previous section except for the code for
the calculation of the enthalpy. This code is presented in Table 5 and uses the symbolic computation capability of MATLAB to
compute the temperature derivative term in Eq. (19).

0 -g6 ..... ... - .. ...... ............ ........... ........... .................... ..... ..... ........... . .......... ......

M\ -- - - - - -- - -- - - -- - - -- - - -- - - - ------------ --------.. -. ., .- -. ---- --- -- -

. ........................ ............ . ........

o8 .......... . .. .. . . ............ ... .... .. . ........... ......... ............ .... .
0& 61!75 ....... .... ......... ........ . . .. ....

., ..-.-..... - .-.- .. ... -- . .-.- .. . .. . ..... ... - . -.... ... .-. ...... . -i ... ...-.-.- .-.. - . . . . ... . ........... .......... .......... ............. .......... . ........... .....
0L55 ........... .... .............. ....... . . . ....................... ........

200400 M o tU 1200 1W Pre ssure O 1r
Prwessure, bar
Fgr5.Kfrtamoisyteiratoat80KFigure 6. Extent of reaction for the ammonia
Figure 5. K for the ammonia synthesis reaction at 800 K. synthesis reaction at 800 K.


Chemical Engineering Education

MATLAB Commands for Obtaining the Feed Enthalpy
% defining symbolic variables
syms TF af AP Abf BP ZF
% critical pressure and temperature (in psi
and �R) and acentric factor
% for hydrogen, methane, benzene and toluene
Pc(l) = 190.8; Tc(1) = 59.7; w(1) = 0.0;
Pc(2) = 673.1; Tc(2) = 343.9; w(2) = 0.0;
Pc(3) = 714.2; Tc(3) = 1012.7; w(3) = 0.2116;
Pc(4) = 587.8; Tc(4) = 1069.1; w(4) = 0.2415;
% feed pressure in psi
% feed composition
z(1)= 0.0041; z(2) = 0.0571; z(3) = 0.7097;
z(4) = 0.2291;
% various terms of the Peng-Robinson EOS
for i=1:4
for i=1:4
for i=1:4
% binary interaction parameters obtained from
k(l, 1) = 0; k(2, 2) = 0; k(3, 3) = 0; k(4,
4) = 0;

k(2, 1) = k(l, 2); k(3,
= k(1, 4);
k(2, 3) = k(3, 2); k(3,
= k(4, 2);
k(l, 2) = 0.20200; k(l,
k(l, 4) = 0.28510; k(3,
k(4, 2) = 6.4900*10^-2;
for i=1:4
for j=1:4

1) = k(1, 3); k(4, 1)

4) = k(4, 3); k(2, 4)

3) = 0.2851;
2) = 3.9999*10^-2;
k(4, 3) =

for i=1:4
for i=1:4
for j=1:4
for i=1:4
% computing enthalpy

Ac(l, 1) = 29.088; Ac(2, 1) = -0.192*10^-2;
Ac(3, 1) = 0.4*10^-5;

continued next column

Vol. 43, No. 2, Spring 2009

Ac (4,

19.875 ; Ac(2,
-36.193; Ac(2,
-34.364; Ac(2,

2) = 5.021*10^-2;

3) = 48.444*10^-2;

4) = 55.887*10^-2;

for i=1:4
2*z(i) ...
4*z(i) ...
2*z(i) ...


We find a feed enthalpy equal to -29913 kJ/kmol. The va-
por-phase fraction and temperature are 0.0367 and 38.126 �C,


It is the authors' experience that teaching and understand-
ing applied thermodynamics can be very tedious and abstract
if the lectures do not show how results of a flash distillation
or vapor-liquid diagrams can be obtained. The study of such
problems usually involves solving nonlinear algebraic equa-
tions, which is readily performed by the MATLAB function,
fsolve. Little programming skill is required by the student,
who gets acquainted with the basic MATLAB commands in
a few days.71 MATLAB can be used in other chemical engi-
neering problems such as process dynamics and control, fluid
mechanics, heat transfer, and chemical reaction engineering.
With his student Zakia Nasri, Dr Binous has also performed
similar computations using Mathematica.81


We have shown through simple examples how one can
take advantage of the numerical and graphical capabilities
of MATLAB to perform properties estimation for pure com-

TABLE 5, continued

ponents and VLE calculations for binary mixtures. In addi-
tion, we have performed high-pressure chemical-equilibrium
calculations. An example of an adiabatic flash computation
was also presented. Similar computations were performed
by the author using Mathematica.[91 These classic problems
are junior- and senior-level study material at the National
Institute of Applied Sciences in Tunis. The students excel in
these types of problems despite the fact that they do not have
prior knowledge of MATLAB and Mathematica.

a activity of species i [bar]
c number of components
HD departure from ideal enthalpy [cal/mol]
k binary interaction parameter
K equilibrium constant
P critical pressure [bar]
P reduced pressure
Psat vapor pressure [bar]
R universal gas constant [cal/(mol. K)]
T critical temperature [K]
T reduced temperature
x liquid mole fraction
y vapor mole fraction
Z compressibility factor

z mole fraction in the feed
v stoichiometric coefficient
(| vapor phase fraction
Pl, v fugacity coefficients
co acentric factor

1. Peng, D.Y., and D.B. Robinson, "A New Two-Constant Equation of
State," Indust. and Eng. ( ....... Fundamentals, 15, 59 (1976)
2. Binous, H., MATLAB File Exchange Center, com/matlabcentral/fileexchange/authors/11777> (2006)
3. Tester, J.W, and M. Modell, Thermodynamics and its Applications,
3rd Ed., Prentice Hall, Upper Saddle River, NJ (1996)
4. Prausnitz, J.M., R.N. Lichtenthaler, and E.G. deAzevedo, Molecular
Thermodynamics of Fluid-Phase Equilibria, 3rd Ed., Prentice-Hall,
Englewood Cliffs, NJ (1998)
5. Sandler, S.I., Chemical and Engineering Thermodynamics, 3rd Ed.,
Wiley, New York (1999)
6. Henley, E.L., and J.D. Seader, Equilibrium-Stage Separation Opera-
tions in Chemical Engineering, Wiley, New York (1981)
7. Davis, T.A., MATLAB Primer, 7th Ed., CRC Press, Boca Raton, FL
8. Nasri, Z., and H. Binous, "Applications of the Soave-Redlich-Kwong
Equation of State Using Mathematica," J. ( I..... .of Japan, 40(6),
9. Binous, H., Mathematica Information Center, com/infocenter/search/?search_results= 1;search_person_id= 1536>
(2006b) 1

Chemical Engineering Education

MR classroom
----- --- s___________________________________________



McMaster University * Hamilton ON L8S 4L7

Fifty minutes of teacher talk with passive student lis-
tening is relatively ineffective in developing student
learning. By creating silences, teachers can encourage
productive, active, student learning. Likewise, by overcoming
silences, students can change from passive listeners to active
talkers/discussers of their learning.
In this paper we consider creating and overcoming silences.
Ideas are given for creating silences for individual active
activities and creating silences, via wait times, to provoke
facilitated class discussion. Then suggestions are given on
how to overcome student silence via peer discussion and on
overcoming the silence between teacher and students. But first
consider the research upon which these ideas are based.

The fundamental research for creating and overcom-
ing silences is extensive and is related to Chickering and
Gamson's1ll summary of seven features to improve learning,
Ramsden's[21 research on developing deep learning, and the
concept of 20-minute student attention spans.4 7, 9 12]
Chickering and GamsonE11 suggest that the seven ideas to
improve student learning are: 1) prefer active to passive; 2)
prefer cooperation to competition; 3) use clear time-on-task;
4) expect success; 5) have good teacher-student interaction;

6) provide prompt feedback; and 7) account for individual
student-learning preferences. Ramsden's[21 research sug-
gests that deep learning is promoted by good teaching, clear
goals and standards of assessment, an emphasis on student
independence, a social climate fostering good relationships
among the students, openness to students, and vocational rel-
evance, while negative impact results from a heavy workload
and a large amount of formal lecturing without freedom for
individual or group study. Hake's[3] research-comparing the
performance on standardized, validated tests of 6,000 first-

Donald R. Woods is a professor emeritus of chemical engineering at
McMaster University. He received his B.Sc. from Queen's University,
his M.S. and Ph.D. from the University of Wisconsin, and worked for a
seven different industries before joining McMaster University in 1964.
His research interests are in process design, cost estimation, surface
phenomena, problem-based learning, assessment, improving student
learning, and developing skill in problem solving, troubleshooting,
group work and teamwork, self-assessment, change management,
and lifetime learning.
Heather Sheardown is a professor in the Department of Chemical
Engineering, adjunct professor in the Department of Pathology and
Molecular Medicine, and holds an adjunct appointment in the Depart-
ment of Chemical Engineering at the University of Ottawa. She is an
expert in polymeric biomaterials, wound healing, and drug delivery, and
has a particular interest in the development of biomaterials and delivery
systems for ophthalmic and vascular applications.

� Copyright ChE Division of ASEE 2009

Vol. 43, No. 2, Spring 2009

year physics students, some of whom received interactive
engagement activities in class vs. some that received tradi-
tional lecture-showed that students who received interac-
tive-engagement learned twice as much as those receiving
traditional lectures.
After 20 minutes of teacher talk, boredom sets in, and
student recall of information presented after 20 minutes is
greatly reduced.14 7 912] Indeed, Liebman"131 suggests that the
attention span is as low as 8 to 10 minutes. McKeachieE141
reports that immediately after 50 minutes of straight teacher
talk, students can recall about 70% of the content presented
in the first 10 minutes but only 20% of the content in the
last 10 minutes. To overcome this and to improve student
learning, after 10 to 20 minutes of teacher talk, instructors
can introduce activities to engage students actively in the
learning process. Princes151 reviews such options. Two ideas
for active learning that are the focus in this paper are, 1) to
use silence for individual student activity related to their
learning; and 2) for the teacher to remain silent and allow
wait time and then facilitate class discussion. Such activities
also apply some of the Chickering-Gamson11l principles to
improve learning: using active instead of passive, using co-
operation instead of competition, providing prompt feedback,
and providing clear time-on-task.
Ramsden'sE21 research has shown the importance of the
social climate in the class on the development of deep learn-
ing. Ideas presented in this paper address how to develop a
strong social climate in class and how to improve the quality
of teacher-student interaction.
In section 2, we consider how to create silences for individual
work. In section 3, we explore creating silences, or wait times,
as a prelude to full class discussion. Then in section 4, ideas are
given for overcoming student silences via peer activities and, in
section 5, overcoming silences between teacher and students.
Finally, in section 6, a measure of the effectiveness of these
approaches is given. Each is considered in turn.

After 20 minutes of teacher talk, instructors can create
silences by asking students to do individual work such as
writing reflections (section 2.1), solving a problem (section
2.2), or answering a test question (section 2.3).

2.1 Writing reflections
A reflection is a comment about what has been ex-
perienced in the past: knowledge, attitudes, feelings,
or reactions to what was done or felt. The reflec-
tion could be free writing, prompted free writing, or
perhaps a structured checklist. Here are some example
details about the format and the timing.
Format: For prompted free writing, provide lined
worksheets that have a title and a place for name
and date. Table 1 is an example. This may include a
prompt that can be given verbally or can be written on
the form. Example prompts include:
"I discovered ..", "The most important idea was.
S. ," "The most ti,.,. i, 'ii. idea was . . .," "Now
I realize that. . .". The prompts could stimulate: a
comparison of the present experience to past experi-
ence (corresponding to revised Bloom's cognitive
taxonomy level 2 understand)"15 16]; an evaluation of
the experience (revised Bloom's level 5); a creation
of something new based on the integration of past
and present experience (revised Bloom's level 6116]);
or attitudinal comments and change (Krathwohl's
attitudinal taxonomy level 41171). As a side note, for
the cognitive domain, Bloom, et al.,i151 published a
taxonomy or structured list representing increasing
level of difficulty in learning in the cognitive domain.
This has been revised by Anderson, et al.[161 Such a
classification is extremely helpful in analyzing the
degree of difficulty expected in a task. For example,
on an exam students should be given a chance to dem-
onstrate an ability to do tasks of varying levels, rather
than assigning only tasks at Bloom's level 6. Similar-
ly, students can use such a taxonomy to monitor their
growth. For the affective domain, a similar taxonomy
has been developed.[171
A further example of a prompted format, applying
Bloom's level 5 evaluate, is a listing of the topics plus
a rating for each. An example is given in Table 2.
Another example of a prompted format (that com-
bines Bloom's levels 2, 3, and 4-understand, apply,
and analyze) is Larkin's checklist format in the con-
text of physics.["18 In this example, the reflective tasks

Chemical Engineering Education

Example Reflections
Reflection Name I Date
"Now I realize that... I need to study the text before I come to class. I thought I could pick up most of
the ideas from lectures but in this course I need to come to class prepared."
Reflection Name Date
"I discovered that . . you can'tpush on a rope. This sounds simple, but I now realize this really helps
me to solve pulley problems."

are to write down an equation, and then, for each
symbol, identify its kind (number, vector, tensor), the
sign and direction, the units, the typical magnitude,
and the meaning in words. Students are also asked to
compare each concept with other similar quantities
with which it might be confused.
Timing: two to three minutes; be specific:
"Please take out the reflection worksheet and write
reflections for the next two minutes. For this reflec-
tion, please use the prompt 'I discovered. 'Any ques-
tions? OK, time is running. Quiet please."

2.2 Individual problem solving
Individuals are asked to solve a simplified problem.
Usually we design the problem to test the student's
comprehension of the most challenging parts of a
concept. An example might be to plot, on log-proba-
bility paper, some particle-size data and determine the
geometric average and geometric standard deviation.
Instead of giving the students 50 data points, however,
only two data points are given so that the task can
be done within the allowed two minutes. The timing
and instruction details are the same as for reflections,
described above.

2.3 Individual response to test questions
An example of this approach is used by Mazur.111l
Instead of formally talking at the beginning of class
time, Mazur posts reading that the students are
expected to do before class. In the first activity each
student is silently to solve multiple-choice questions.
The time allowed is one minute. The test can be pro-
jected onto a screen.

All of the three examples listed require that the student si-
lently does the task alone. What options are available to provide
closure for this individual activity, or, is closure needed?
In our experience, closure is indeed needed. After any of
these silent activities, three actions can be used.
A first action is to share the experience. Whenever
students are given an individual task, we have found that
most want to tell someone about the activity. Two options
include: a) a leader summary where the teacher asks for
feedback from the students and records ideas from students,
which usually takes about 10 minutes of class time for a class
of 30 because most students want to ensure that their ideas are
noted by the instructor; b) ask students to "Turn to a neighbor
andsay 'That was miii, t. i... i, it. activity because.. .'and talk
to your neighbor for the next 90 seconds. You need not share
what you wrote. You may be more comfortable talking about
the ease with which you did the task. Any questions? OK,
noise level up." For the problem-solving or test activity, the
prompt might be "Convince your neighbor that your answer
is correct." This provides prompt feedback to each because
the instructor can a) provide the correct answer and then have
further peer dialogue; b) collect responses to the questions (via
clickers, or a show of hands) and then elaborate on the correct
answer and the reasons why one might mistakenly select the
other answers. In collecting the responses, do not stop after
the "correct" answer has been received. Rather, continue with
a prompt such as "OK, we are ci ll.. i, it . answers, what other
answers are there to this? " Or "Are you sure we have all the
possible answers here? "
A second action is to follow this activity with applause.
Applause helps to close the activity; applause suggests that
this is a desired classroom activity, and encourages students
to come prepared for class, and to do the individual activity

Example Reflect-Rate Form
Rate the ideas Already Would Might Not my
do this work work style
Create silences for individual reflections
Create silences for individual activities
Create wait times after posing questions
Overcome silences for diad 'Tum to a neighbor..."
Overcome silences for diad TAPPS
Overcome silences with small group activity
Use ombudspersons
Use written feedback at the end of each class
Ask them to reflect in class
Know the names of your students
Overcome silences between you and students
What conclusions do you draw from your responses?

Vol. 43, No. 2, Spring 2009

Instruction is a two-way street.
Teachers should seek feedback
throughout the semester about the
quality of the teaching/learning.

to the best of their ability. Applause nurtures even the wrong
answers being presented.
A third activity is to collect, mark, and return the written
responses to the students or to ask them to use this as evidence
in a weekly reflective journal in which they self-assess their
learning journey. Suggestions about self assessment via reflec-
tive journals are given by Woods and Sheardown.[191
Creating silent times for individual student activity is an
excellent "active" addition to the classroom.

An approach to encourage active learning in the classroom
is for the instructor to pose a question and solicit student
response and a "lively discussion" from a "full class" of
about 30 students. (If the class is larger than 30, then a large
class-of say 200-can be divided into groups of about 30
so the instructor engages in discussion with one particular
group at a time.)[20 21] When an instructor poses a question to
prompt classroom discussion, inevitably the students know
that if they are silent, the instructor will answer his/her own
question. To combat this, after a question has been posed, al-
low a silent wait time. How long is a wait time? The research
evidence is not clear. Rowe's r%. al..'-- - I identified a wait
time of 1 second. Whitman and Schwenk[241 discuss using a
wait time of 3 to 5 seconds. Woods, et al.,[9] talk of a wait
time of 30 seconds. Gedalofo201 suggests 7 to 10 seconds.
Huntsberger 251 distinguishes between a 3- to 7-second wait
time (if the question is addressed to an individual) and a wait
time of "several minutes" (if the question is asked to a group
in general). Rg i , -1 notes that an average wait time faculty
allow is 2-3 seconds. Increasing wait times will significantly
increase the number of student responses and Rogers says
that the literature actually suggests 17 seconds as the optimal
wait time. Rasmussen 211 recommends a wait time of 10 to 15
seconds. Whether the wait time is 1 or 30 seconds is not the
issue. The importance is to recognize and cope effectively with
the phenomena "as a question poser." Here are some options.
Explain that often when a question is asked that the students
know if they are silent that the teacher will rephrase the ques-
tion or answer the question. One might say "I really want you
to think about and answer the questions I pose. There will be a
silent wait time to give you a chance to create a response to the
question. I really want to .. al, ideas from you." Then, when
an answer or response comes in, acknowledge it by writing
it down and with applause. Continue gathering ideas beyond

the right answer. Do not criticize the ideas when they come
in. Gather the student's ideas. If no student response is given
after a wait time of 20 to 30 seconds, then invoke "Turn to a
neighbor and say 'How would you respond to this question?'
Noise level up for 2 minutes." Then at the end of two minutes
say "Please share with us what you talked about."

An effective learning environment engages students actively
in the learning, uses cooperation not competition, provides
prompt feedback, and creates a good social climate. After 20
minutes of teacher talk or when the students seem confused or
their eyes glaze over, ask pairs of students or small groups to
talk. The talking should be on task. For diads a useful prompt
is "Turn to your neighbor and say ...
* 'Did you understand that?'"
* 'Summarize what's happened so far.'"
* 'Do you believe that?'"
* 'The key point so far is.. .' "
* 'A practical application of this stuff is . .
* 'Let's compare lecture notes that we have taken so far ...'"
* 'So what's that all about?' "
* 'Please explain that to me in simple terms.' "

Instead of using diads, a small group of three to five students
could be used. The size is dictated mainly by the classroom
configuration. If the students are unfamiliar with group dis-
cussion, the talking-stick approach can be used. An object,
such as a stick, pen, or paper, is given to the speaker, who
talks briefly and then passes the stick to the right so that, in
turn, all have a chance to talk. If one prefers not to talk, they
can pass. The ground rule is that only the person holding the
stick can talk at a time.
Diads could also solve problems using the Whimbey Talk
Aloud Pairs Problem Solving, or TAPPS. Here each person
has a specific role. One person plays the role of the talker/
problem solver: Verbalize thoughts, focus on being accurate
(instead of rush! rush! time pressures), have clear communica-
tion so that others can follow and understand-this is the role
of the talker/problem solver when given a written problem
statement. The other person plays the role of the listener;
his/her role is not to solve the problem, but to encourage
verbalization, to encourage a focus on checking and double
checking, and to ensure that he/she comprehends the other's
approach. The listener is not to correct or make value judg-
ments about the other's efforts. Typically this activity would
last 5 to 15 minutes. Then, each should write out reflections
about what he/she discovered. Brief diad discussion of the
process is useful. Then, the people reverse roles. Feedback
forms can be used to help each see how the roles are being
played. More is given by Woods.[27]
Chemical Engineering Education

Two basic ideas are given: how to break the silence to get
feedback about the learning and how to establish connections
with students to improve the social climate.
5.1 Overcoming silences to monitor the quality of the teach-
ing and learning
Instruction is a two-way street. Teachers should seek feed-
back throughout the semester about the quality of the teach-
ing/learning. Some options include the use of class ombud-
spersons, clickers, red cards, half-minute papers, and a wide
variety of ideas given by Angelo and Cross.[28] Ombudspeople
are a team of volunteers from the class who provide feedback
to the instructor throughout the year about the quality of the
teaching and learning. Clickers refers to a method to receive
anonymous response to questions via audience response sys-
tems, referred to as clickers.[29] In red cards, each student is
given a display card that they can hold up whenever they are
confused. A half-minute paper asks students to anonymously
respond to such questions as "What was the muddiest point in
this class? What was the most important point?" The papers
are then collected to provide feedback to the teacher about
that particular class.

5.2 Overcoming silence between students and instructor to
improve the social atmosphere
Here are ideas on how to improve the social atmosphere
and to have quantity and quality time between faculty and
students: know and call students by name; celebrate their
successes; help them network with visitors to the department,
including seminar speakers; critique their resumes; build trust
and be willing to confidentially hear about their concerns and
personal problems; personalize feedback on assignments;
come early to class and stay late; take time to chat in the
hall; walk with them between classes; attend events that they
think are important and where you are comfortable (such
as convocation and the iron ring ceremony for engineering
students); create special events (such as a Christmas carol
sing-song with a class band); invite them to your home; and
be willing to share personal experiences, attitudes, and val-
ues. Invest time in explaining your role and their role in the
teaching and learning process. This includes explanations in
the course syllabus/outline and time spent in class explain-
ing your choice of learning environment. Here is an example
from a course syllabus:
The process of teaching and learning is a two-way street. I
want you to do well and succeed in the course and in your
career. Here is what you can expect from me: clear indica-
tion of the objectives, support and encouragement, sharing
of experience, prompt feedback, respect and trust, response
to your ",,, , . and a caring environment in class.
Here is what I expect from you: participation and success in
all activities, feedback on how best I can help you, helping
to create a caring environment in class, and respect and
Vol. 43, No. 2, Spring 2009

trust in me and your colleagues. In this class I use ombud-
spersons to provide input about how best I can create the
best learning environmentfor you.

In another example, there was a dramatic improvement in
student performance in problem-based learning when up-front
explanation and preparation time for this new learning envi-
ronment was increased from two hours to six hours.[30]
In summary, many simple things can be done to break the
silences between students and teacher.

We have used these approaches in our classes for the past 15
years. One measure of effectiveness is to compare the student
response to the Course Perceptions Questionnaire (developed
and validated by Ramsden'21) for straight lecture-style courses
vs. student response to our courses that use silences as de-
scribed in this paper. For straight lecture-style courses the
responses were 18 to 20 whereas for our courses the responses
were 28 to 32. A larger number is desired.

Silences can be created to allow individual students to
actively engage in reflection and adaptation of new ideas.
Silences, or wait times, should be created after a teacher poses
a question to the class. Such wait times encourage students
to participate in discussion instead of waiting for the teacher
to answer his/her own question.
Silence between students can be overcome by using a
variety of diad and small-group activities in class to actively
engage students in the learning process. Ideas are given on
how to overcome the silence between students and faculty.
Research evidence supporting these suggestions is given.

1. Chickering, A.W., and Z.E Gamson, "Seven Principles for Good Prac-
tice in Undergraduate Education," AAHE Bulletin, Mar 3-7, 1987
2. Ramsden, P., "How Academic Departments Influence Student Learn-
ing," HERDSA News, 4, p 3-5 (1982)
3. Hake, R.R., "Interactive-Engagement vs. Traditional Methods: A Six-
Thousand-Student Survey of Mechanics Test Data for Introductory
Physics Courses, "Am. J. Phys., 66, 64-74 (1998)
4. Burns, R.A., "Information Impact and Factors Affecting Recall," in:
Annual National Conference on Teaching Excellence and Conference
of Administrators, Austin, TX, May 22-25, 1985 (ERIC Document
No. ED 258 639)
5. MacManaway, L.A., "Teaching Methods in Higher Education-In-
novation and Research," Universities Quart. 24(3), 321 (1970)
6. Davis, B.G., "Personalizing the Large Lecture Class," in Tools for
Teaching, Jossey-Bass, San Francisco (2001)
7. Caldwell, J.H., WG. Hewitt, and A.O. Graeber, "Times Spent in Learn-
ing: Implications from Research," The Elementary School Journal,
82(5), 471 (1982)
8. Felder, R.M., D.R. Woods, J.E. Stice, andA. Rugarcia "The Future of
Engineering Education II, Teaching Methods That Work," ( ..... i .
Educ., 34(1) 26 (2000)
9. Woods, D.R., C.M. Crowe, T.W. Hoffman, and J.D. Wright, "How

Can One Teach Problem Solving?" Ontario Universities Program for
Instructional Development Newsletter, Kingston, Ontario, Canada,
May 1977
10. Anderson, J.R., "Cognitive Psychology and Its Implications," 4th Ed.,
W.H. Freeman, New York (1995)
11. Mazur, E., "Are Science Lectures a Relic of the Past?" Physics World
9, 13-14; online at php?function=search&topic=8> (1996)
12. Liebman, J.S., "Promote Active Learning During Lectures," ORMS
Today, online edition, 23(6) (1996)
13. McKeachie, WJ., Teaching Tips: Strategies, Research, and Theory for
College and University Teachers, 10th Ed., Houghton Mifflin, Boston,
MA (1999)
14. Prince, M., "Does Active Learning Work? A Review of the Research,"
J. of Eng. Educ., 93(3), 223 (2004)
15. Bloom, B.S., et al., Taxonomy of Educational Objectives-the Clas-
sification of Educational Goals, HandbookI, Cognitive Domain, David
McKay, New York (1956)
16. Anderson, L.W., D.R. Krathwohl, P.W Airasian, K.A. Cruikshank,
R.E. Mayer, P.R. Pintrich, J. Raths, and M.C. Wittrock, A Taxonomy for
Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy
of Educational Objectives, Addison Wesley Longman, Inc., (2001)
17. Krathwohl, D.R., et al., Taxonomy of Educational Objectives-the
Classification of Educational Goals, Handbook II, Affective Domain,
David McKay, New York. (1964)
18. Larkin, J.H., "PS Corner," J. College Science Teaching, p. 468, May
19. Woods, D.R., and H.D. Sheardown, "An Approach to Developing
Students' Skill in Self-Assessment: A Paper," #832, ASEE Conference,
Salt Lake City, June 2004

20. Gedalof, A.J. "Teaching Large Classes," STLHE Green Guides, Society
for Teaching and Learning in Higher Education, c/o Center for Leader-
ship in Learning, McMaster University, Hamilton, Ontario L8S 4K1
21. Rasmussen, R.V., "Practical Discussion Techniques for Instructors,"
Alberta Association for Continuing Education, 12(2) 38 (1984)
22. Rowe, M.B., "Wait Times and Rewards as Instructional Variables,
Their Influence on Language, Logic, and Fate Control," J. Res. Sci.
Teaching, 11, 81 and 291 (1974)
23. Rowe, M.B., "Pausing Principles and Their Effect on Reasoning in
Science," in New Directions for Community Colleges, 31, p. 27 Jossey-
Bass, San Francisco (1980)
24. Whitman, N., and T.L. Schwenk, A Handbook for Group Discussion
Leaders: Alternatives to Lecturing Medical Students to Death, 2nd
Ed., Whitman Associates, Salt Lake City, UT (1983)
25. Huntsberger, J.P, Effective Questioning Techniques, Science Education
Center, University of Texas at Austin, Austin, TX (1985)
26. Rogers, R.L., "The Seven Habits of Highly Effective Medical Educa-
tors," (2006)
27. Woods, D.R., "Chapter 5, Implementing PBL, Section MPS 4, p. MPS4-
5 and 4-6", in Preparing for PBL, ca/pbl/pblbook.pdf> (2006)
28. Angelo, T.A., and K.P Cross, Classroom Assessment Techniques, 2nd
Ed., Jossey-Bass, San Francisco (1993)
29. Caldwell, J.E., "Clickers in the Large Classroom: Current Research and
Best Practices Tips," CBE Life Sciences Education, 6(1) 9 (2007)
30. Woods, D.R., "Helping Your Students Make the Most From Their PBL
experience," chapter in Management of ( l', .. implementation of
PBL in engineering, E. de GraffandA. Kolmos, eds., Sense Publishers,
Rotterdam (2007) 1

Chemical Engineering Education

MR classroom
----- --- s___________________________________________



for Undergraduate and Capstone Projects

University of Waterloo * Waterloo ON, Canada, N2L 3G1

Providing high-quality undergraduate education is the
goal of any engineering school. As part of this, the use
of final-year design projects or capstone projects is a
useful tool to engage students and enhance the undergradu-
ate experience. At the University of Waterloo Department
of Chemical Engineering many engineering students choose
to do design projects and capstone projects as part of their
involvement with various technical competition teams. Re-
cently, many team entries have included hydrogen fuel cell
technology such as "Challenge X-Crossover to Sustainable
Mobility," a competition sponsored by GM, the USDOE, and
Natural Resources Canada, in which students designed and
built a full-size hydrogen fuel cell vehicle. Students have also
entered into the H2U Hydrogen Facility Design Competition
sponsored by the U.S. National Hydrogen Association as
well as others. Although all of these design competitions are
multidisciplinary and involve members from all departments
and other faculties, chemical engineering students have typi-
cally held leadership roles because of the applicability of the
competition subject matter. Further, faculty advisors have also
come from the Department of Chemical Engineering.

Undergraduate design projects and upper-year capstone
projects offer many valuable benefits to students. As well as
being an opportunity for applying concepts learned during

Sumit Kundu is a Ph.D. candidate at the
University of Waterloo. His research focus-
es on the chemical degradation of fuel cell
materials and chemical degradation mod-
els. Sumit currently teaches an introductory
course for chemical engineers and is an
Engineer in Training with the Professional
Engineers of Ontario. Sumit is also actively
involved with the chemical engineering
graduate student organization.

Michael Fowler is an assistant professor
Sin the Department of Chemical Engineering
at the University of Waterloo with research
Interests in fuel cell system design and
reliability, fuel cell materials durability,
and green power systems. The University
of Waterloo is one of Canada's leading
comprehensive universities with extensive
graduate and undergraduate programs.

� Copyright ChE Division ofASEE 2009

Vol. 43, No. 2, Spring 2009

a student's previous classes, these projects are also used by
many schools to help the students develop "soft skills" such
as leadership, communication, and project management.11
2] Studies of undergraduate research, which shares many
similarities with design work, found that students were able
to develop professionally by acquiring research and other
technical skills. They were also able to gain a greater sense of
what science and engineering research work entailed, which
changed their attitudes toward such work and helped clarify
career plans. A separate survey study by Kardash131 echoes
some of the above points. This study was able to further detail
the skills gained by undergraduate researchers, finding that
the ability to understand concepts in one's field, observe and
collect data, and write a research paper all improved after the
research experience. Making design projects available to first-
year engineering students is thought to lead to lower attrition
rates since students can see the applicability of course material
which they may otherwise characterize as "boring."[41
Technical competitions can also provide the framework for
design projects. Competitions, such as the Chem-E-Car com-
petition, involve a significant design and analysis component151
and can be complemented with presentations and reporting to
also encourage development of communication skills. A study
by Padgett[61 found that when a design competition is used,
student motivation can be very high and it is believed that
undergraduate education may improve through a better reten-
tion of course concepts. Further, students learn team-building
skills121 and younger students have been observed to develop
an interest in undergraduate research after participation.1, 81
There are also benefits to participating professors and
graduate students. Faculty and graduate students who serve as
supervisors for undergraduate researchers gain valuable men-
toring experience that can be later translated to other jobs.191
Some of the challenges with undergraduate research include
extra start-up time and effort required. Also, since students
come from a variety of different backgrounds their abilities
can be varied. Undergraduate schedules tend to be variable
as they attempt to balance lab work as well as social lives,
schoolwork, and exams. Thus, work output and motivation can
be variable.[31 Further, graduate students involved as mentors
will have less time to focus on their own thesis work.
This paper will examine the benefits and challenges of
using competitions for undergraduate design projects and up-
per-year capstone projects through the use of a case study of
students participating in the Hydrogen Ambassador Competi-
tion. Experiences as they relate to undergraduate and graduate
students, as well as faculty advisors and the department and
faculty as a whole, will be explored from the perspective of
the authors-one of whom participated as a graduate student
and the other as a faculty advisor-as well as from surveying
undergraduate student participants. The aim is to show that
the use of competitions can benefit all parties and is worth
the extra effort.

In 2005 a Hydrogen Ambassador Competition was an-
nounced as part of the Hydrogen and Fuel Cells Exhibit at
the Hanover Fair, one of the largest trade shows in Germany.
The goal of the competition was to develop an idea for the
commercial use of fuel cells in an application that could be
developed and marketed today. If accepted, the idea and any
prototypes could be shown at the 2006 Hanover Fair. The
project began with three students-two graduate students
from the Department of Chemical Engineering and a 4th-year
student from the Department of Electrical Engineering who
was going to use the competition submission as a capstone
project. These students formed the core of the team and to-
gether they developed the idea of entering a fuel cell-powered
diver propulsion vehicle. A diver propulsion vehicle is any
kind of external propulsion aid for an underwater diver. Over
the course of the project a number of other ChE undergradu-
ates were added to the team to complete the project, which
also extended to other events beyond the Hanover Fair.

Figure 1. Overall fuel cell DPV system.

Figure 2. Completed prototype of the fuel cell-powered
diver propulsion vehicle.
Chemical Engineering Education

The design of a fuel cell-powered diver propulsion vehicle
(DPV) involved many technical challenges for the students
participating. The main thrust of the project was to take an
existing battery-powered DPV and replace the battery with a
fuel cell while keeping the same size and basic functionality
of the unit. A fuel cell is an electrochemical device similar
to a battery. Unlike a battery, which contains a finite amount
of reactants, a fuel cell can be continuously supplied with
reactants and therefore theoretically generate electricity for
as long as a user may want. The benefit of using a fuel cell
in the DPV is that is would have near-instantaneous refilling
times as compared to the 8-hour recharge times of the battery,
and offer longer range. Some of the impediments are that the
weight is higher and the cost is significantly higher at the
current stage of fuel cell technology development. Neverthe-
less, such a product would certainly be accessible for wealthy
diving enthusiasts or military interests.
To acquire the necessary materials to develop a prototype,
team members contacted manufacturers of stock DPVs and
fuel cells. A DPV was obtained from DAKA corporation and
a fuel cell stack from Hydrogenics corporation. The fuel cell
was sized to meet the requirements of the DPV motor. To fund
the rest of the project, and to assist in travel funding, group
members submitted proposals to an undergraduate engineer-
ing endowment fund (Waterloo Engineering Endowment Fund
-WEEF), and sought financial support from the Department
of Chemical Engineering, Department of Electrical Engineer-
ing, and the Dean of Engineering's office. Materials, fittings,
and other equipment were also used from the faculty advisor's
research lab, and the faculty advisor also provided funding
for smaller components.
Figure 1 is a schematic of the fuel cell system that needed to
be designed. It includes features such as compressed-air and
hydrogen reactants, pressure sensors, DC/DC converters, an
electrical control system, temperature management, and safety
features, as well as other auxiliary systems. Component selec-
tion and packaging was possibly the most challenging aspect
of the project since components needed to not only be suitable
for the demands of the fuel cell system but also fit into the
same space occupied by the battery in the DPV. This involved
extensive design work and the fabrication of several frames and
mounts. The design of the control system was also a challenge
since functionality of the system and safety considerations were
of importance. Finally, the testing work was centered around
evaluating the fuel cell stack received from Hydrogenics as
well as creating testing apparatuses for the fuel cell system at
different levels of development. Although this task was not as
challenging technically, it required many practical electrical,
mechanical, and workshop skills as well as experience with
compressed gasses, specifically hydrogen.
Ultimately, the final prototype shown in Figure 2 was exhib-
ited at the fuel cell exhibit at the Hanover fair. This included
a small booth in the same area as other hydrogen ambassador

When surveyed, undergraduate competi-
tion participants highlighted the hard
and soft skills gained through partici-
pation as part of the positive benefits.
Technical skills such as programming
and building hardware as well as gain-
ing experience with new technology
were specifically mentioned as were soft
skills such as project management and
oral communication skills.

competitors and fuel cell companies as well as a live interview
on the main stage. While at the fair, government officials
also toured the booth for the DPV and the project was also
featured on a number of fuel cell and hydrogen-related news
Web sites. The project was also presented as a poster at the
Toronto Green Energy Fair at the University of Toronto and
was featured in a University of Waterloo Faculty of Engineer-
ing Annual Report, which is read by alumni.

Undergraduate Experience
The hydrogen fuel cell DPV project for the Hydrogen
Ambassador's Competition had many of the characteristics es-
sential to creating a positive undergraduate design experience
for both younger undergraduate and final-year capstone proj-
ect participants. It should be noted here that undergraduates
receive no extra credits for participating in the competition
and students doing capstone projects within the competition
are only marked on their selected design project and not on
any extra work that they may also do.
Over 35 participants from several competitions including
the Hydrogen Ambassador Competition were surveyed. They
were asked to reflect on the perceived benefits and chal-
lenges of working on a project centered on a competition as
well as to give their opinions on how the project work for a
competition differed from project work done for credit. A list
of the questions and typical responses is provided in Table
1 (next page).
First, the organizational structure of the team was particu-
larly well suited to meeting the needs of all the undergraduate
participants. The graduate students at the core of the team
were able to supervise the overall project and day-to-day lab
activities, and to divide tasks among all the students. This
provided necessary control for safety aspects, as well as the
ability to teach necessary technical skills to the undergradu-
ates. Furthermore, the tasks themselves could be divided to

Vol. 43, No. 2, Spring 2009

meet the needs and interests of the individual students. Un-
dergraduate participants generally wanted more experience
with hands-on aspects of the project, and had a great desire
to actually work with the fuel cell technology. Undergraduate
could therefore be given "mini" projects such as the design
and fabrication of tank mounts, hydrogen management
components, the sizing and selection of components, or the
testing of the system. These projects had a very narrow
scope and could be done in the allotted time and around
the undergraduates' other commitments. When surveyed,
undergraduate competition participants highlighted the
hard and soft skills gained through participation as part of
the positive benefits. Technical skills such as programming
and building hardware as well as gaining experience with
new technology were specifically mentioned as were soft
skills such as project management and oral communication
skills. Finally respondents also described being exposed to
a multidisciplinary team as a positive benefit.
Undergraduates using the project as the basis of their cap-
stone project also had a positive experience. As a requirement,
capstone projects had to be broader and more complicated than
the projects given to younger, undergraduate participants; this
was easily accommodated. One such project was performed
by a core team member who focused on the design and setup

of the DPV control system. This applied skills in detail con-
trol system development as well as hardware selection and
integration. Other capstone projects included the design and
construction of a hydrogen management and water knockout
system, and testing of the fuel cell systems. All students were
also involved in the overall project design, sponsorship re-
cruiting, and testing. Once the initial events associated with
the project were complete, other projects such as further
design iterations of the control software were initiated. These
projects were also of sufficient size and scope to be used as
capstone projects for students even after the completion of
the original competition.
There were certain benefits that were unique to the use of a
competition for undergraduate design projects apart from the
obvious travel to the Hanover Fair-although the potential
for travel to an international conference was certainly a very
strong motivator for participants in this competition. Through
the fund-raising activities students had an opportunity to
interact with members of undergraduate funding organiza-
tions, departments, and the Faculty of Engineering and thus
develop communication and project-management skills, as
well an introduction in dealing with media organizations. The
experience of being part of a competition with real awards and
recognition was also a much more satisfying experience than

Chemical Engineering Education

Survey Questions and Typical Responses
Question Typical Responses
Were the projects that you did with the team technical in nature? Did Projects were mostly technical in nature and related to the design and
you apply concepts learned in courses? building of components. Tasks also extended to economic analysis and
public outreach. In all technical and economic cases, course concepts
were applied.
Were team projects organized and did they have clear objectives? Due to the structure of the competitions there were clear objectives
Could projects be completed in a school semester? that each team was required to meet that enhanced the organization of
tasks. Since the teams themselves designed the tasks to meet the objec-
tives, they could usually be completed in the required time frame.
List some of the main benefits of participating on a project team for Respondents benefited from experience with new technologies, job
competition. opportunities, development of new skills, and the acquisition of real-
world experience.
List some of the main drawbacks of participating on a project team for All respondents unanimously identified the large time commitment
competition? involved as a drawback since it takes away from time needed to spend
on classwork.
Is participating on a project for a competition different from other Survey respondents all thought that competitions were different. They
noncompetition projects? generally thought that projects for competitions had more stringent
deadlines, real consequences to failure, and that the idea of winning
was highly motivational and lacking in other class-based projects.
What skills have you gained from your experiences? Technical skills: CAD, fuel cell system design, mechanical design,
electrical design, system controls, computer programming. Nontechni-
cal skills: time and project management, teamwork, marketing, oral
and written skills.
Did you receive any academic credit? The majority of respondents received no academic credit, 14% partici-
pated as part of a capstone project.
Did participation increase your appreciation for engineering? All respondents agreed that their appreciation for engineering had

capstone projects which only lead to academic credit. This was
primarily because of the unique experience of teambuilding
and camaraderie that comes from competing and winning as
a group. The competition aspect also adds more "flair" to the
project, and creates a better and more memorable experience.
Survey respondents described these real rewards, the desire
to win, and tangible consequences for failure as a positive
motivating force that was not present in other design projects
for credit. Many students desire exposure to new and innova-
tive technologies, and in this case being able to work with a
hydrogen fuel cell stack provided this experience. Therefore
students generally applied themselves more and hence were
able to gain more from the academic experience.
Despite the many benefits of the project there were several
challenges when applying this particular contest to undergrad-
uates. Only a certain type of student is capable of carrying out
the projects. As indicated by Smith,f1] the participants must be
more driven and resourceful and be able to work in a diverse
team with more of an organizational structure as compared to
smaller group work. Since the scope of the project as a whole
was large, the most successful students were those who could
work independently and on a team, simultaneously. From the
perspective of undergraduate participants, the most common
challenge was that time spent on the competition project
meant less time spent studying as well as challenges when
transferring work from one participant to another. The timeline
of the competition was also a concern in this case study, as
initial proposals for the Hydrogen Ambassador Competition
were required before the official start of capstone projects
(this was one reason why graduate students initiated entry
into the competition). Also, undergraduates were challenged
by missing a week of classes to attend the conference during
the school term.

Graduate Experience
The graduate experience in the project was also unique.
Since the project was initiated with a team that included
graduate students, there were ample opportunities to develop
leadership and project-management skills. Also, some of the
tasks required increased focus and skill that normally only a
graduate student with more experience would possess. One of
the challenges of participation was that the competition was
not an extension of a specific student's research project, but
was instead a side project with limited prospects for academic
credit or recognition in the realm of research. As such, many
of the benefits from the participation depended on the value
that the students attributed to them. For the graduate students
involved in the DPV project the extra work created by the
project was offset by the travel opportunity to Germany and
participation in an industry-focused international conference
in the fuel cell field. The graduate students also benefited
from increased exposure to the department and faculty, which
eventually lead to participation in the Engineering Annual

Report. Most importantly, the graduate students benefited
from having a separate experience from their thesis work,
which added value to their resumes and increased their
marketability in the workplace. In this case participation in a
system-integration project provided a broader understanding
of fuel cell engineering and the challenges associated with
fuel cell engineering.

Faculty Advisor and Departmental Experience
From a faculty perspective it can be difficult to see the
benefits to supporting students in a competition of this na-
ture, especially graduate students since there is little value
added to specific publishable research. Undergraduate design
projects can sometimes assist specific research projects in
the lab simply by providing extra labor. With projects based
on competitions, however, the goals of the design are often
separate from the research interests of the advisor. As such,
one challenge is the time commitment needed to help manage
the project as there is little recognition in merit reviews and
no teaching relief to the advisor. Nevertheless there are many
reasons to participate.
If the professional development and education of both un-
dergraduates and graduate students is valued then participation
in the Hydrogen Ambassador Competition had many benefits.
The most important one was that the educational experience
of the student team members was enhanced. A project of this
nature excites undergraduates and thus assists in graduate
recruitment and placement of graduates in the industry. Of the
students involved with the DPV, two were already graduate
students with fuel cell-related research; one went on to work
in the fuel cell industry, a second went on to graduate studies
in fuel cell research, and another continued graduate studies
in the green energy field (other members are still continuing
their undergraduate education). Another benefit was that the
prize of going to the fuel cell exhibit within the Hanover Fair
placed the lab in a high-profile industry event that allowed for
increased exposure of the lab and its research aims to potential
industry partners. A final benefit is that the DPV platform can
be used for future capstone projects. This is important because
often there is little budget to support capstone projects and
thus project with high equipment costs are generally not fea-
sible. Ultimately it becomes a decision based on what values
faculty advisors have and what role they feel they play in the
education of their students.
At the departmental and faculty level the main benefits for
financially supporting the participants of this project is the
increased international exposure of the institution. For this
project in particular, the exposure was at a trade show where
potential student co-operative education employers would be
present, and thus able to see the quality of work by students
at the university. To this end the participants also distributed
information about the Waterloo engineering program and co-
opertive education program at a display booth. New students

Vol. 43, No. 2, Spring 2009

to both the graduate and undergraduate program often com-
ment that their university decision was based on exposure to
one of the student team projects at some event.

This paper has shown that engineering design competitions
can be effectively used as an educational tool to give under-
graduate students project design opportunities as well as used
for capstone projects. The use of competitions meets all the
requirements of a good project, and provides a valuable inter-
disciplinary experience. For the DPV, the projects had focused
topics with clear objectives and gave students experience
with an exciting technology. The project had a large-enough
breadth to accommodate a number of students, adequate
possibilities for true partnership among all the participants,
and potential for completion within a reasonable time frame.
There were also many benefits for graduate-student involve-
ment including the development of leadership skills and a
wider exposure to the technology. For the faculty advisor,
department, and faculty, support of this design competition
provided a strong educational opportunity for a number of
students as well as good exposure for the institution.

1. Kentish, S.E., and D.C. Shallcross, "An International Comparison of
Final-Year Design Project Curricula," Chem. Eng. Educ., 40(4) 275
2. Mackenzie, L., and S.J. Masten, "Design Competitions: Does 'Multidis-
ciplinary' Contribute to the Team-Building Experience?" 26th Annual
Frontiers in Education Conference Proceedings, 1, 276-279 (1996)
3. Kardash, C., "Evaluation of an Undergraduate Research Experience:
Perceptions of Undergraduate Interns and Their Faculty Mentors," J.
of Educ. Psych., 92, 191 (2002)
4. Kartam, N.A., "Integrating Design into Civil Engineering Education,"
International J. for Eng. Educ., 14, 130 (1998)
5. Lewis, R.S., A. Moshfeghian, and S.V. Madihally, "Engineering
Analysis in the Chem-E- Car Competition," Chem. Eng. Educ., 40,
66 (2006)
6. Padgett, W.T., 'Teaching Design Through Design Competition," 27th
Annual Frontiers in Education Conference Proceedings, 1, 1477-1480
7. Avanzato, R., "Mobile Robotics for Freshman Design, Research, and
High School Outreach," 2000 IEEE conference on Systems, Man, and
Cybernetics, 1, 736-738 (2000)
8. Marchman, J., and W. Mason, "Freshman/Senior Design Education,"
International J. for Eng. Educ., 13, 143 (1997)
9. Pfund, C., C. Pribbenow, J. Branchaw, S. Lauffer, and J. Handelsman,
"The Merits of Training Mentors," Science, 311, 473 (2006)
10. Smith, L., "Social Engineering," Poster presentation at the 17th
NACCQ, (2004) O

Chemical Engineering Education




A Danish Experience

Technical University of Denmark * DK-2800, Lyngby, Denmark

Seven years ago we were asked, as one of our first
teaching duties at the Technical University of Denmark
(DTU), to teach a 5-ECTS-point course entitled Col-
loid and Surface Chemistry. The topic is both exciting and
demanding, largely due to its multidisciplinary nature. Several
"local" requirements posed additional challenges. The course
is part of the international program of the university, typically
at the start of the M.Sc. studies (7th-8th semester) and can
be taken by students of different M.Sc. programs (advanced
and applied chemistry, chemical engineering, or petroleum
engineering). B.Sc. students toward the end of their studies
can also take the course. Also, due to the multidisciplinary
nature of the course topic, a wide variety of industries in
Denmark has shown interest in the course, which has led to
development of a separate industry course.
In this article we report on our experience from the first
years of teaching the course and how teaching methods and
course material have been adapted to meet the aforementioned
challenges, as well as feedback and course evaluation from
students. First, we present the learning objectives of the course
followed by a discussion of the teaching methods used over
the years. The most challenging topics covered in our course
are highlighted as well as a discussion of the textbooks em-
ployed. Supplementary initiatives (e.g., link to a laboratory
course) are briefly presented followed by our assessment of
the current status and some suggestions.
Vol. 43, No. 2, Spring 2009

The time allocated for a typical 5-ECTS-point course at
DTU is one four-hour block a week during a 13-week semes-
ter, followed by an examination. We have been during the last
three years using the textbook of Pashley and Karaman1ll as
part of the course material. Self notes from the teachers are

Georgios Kontogeorgis is a professor in the
Department of Chemical and Biochemical En-
gineering at DTU, Denmark. He is a graduate
of the Technical University of Athens (Greece)
and has a Ph.D. from DTU. His teaching and
research interests are thermodynamics, colloid
and surface chemistry, and chemical product
design. He is the author of 100 articles in the
field of chemical engineering. He is the study
co-ordinator of the M.Sc. program Advanced
and Applied Chemistry.
Martin E. Vigild is a professor in the Depart-
ment of Chemical and Biochemical Engineer-
ing at DTU, Denmark. After graduating from
DTU he obtained a Ph.D. degree in polymer
chemistry from the University of Copenhagen
(Denmark). He was post doc at the University
of Minnesota before returning to the DTU.
His research is focused around polymer
nano technology, colloid and surface chem-
istry, and chemical product engineering. He
founded the Industrial Polymer Research
Consortium at the Danish Polymer Centre.
� Copyright ChE Division of ASEE 2009

also used; they are available to the students via the intranet
system at DTU, called Campusnet. We have found it particu-
larly difficult to find a suitable textbook that could fulfill the
course requirements and be appealing to different audiences
and the increasing number of students (Figure 1), and a discus-
sion of the three textbooks used in the lifetime of this course
is provided in Table 1. Further discussion on textbooks and
teaching in Colloid and Surface Chemistry has been provided
by Woods and Wasan.E111 The comments shown in Table 1 are
based on the opinions of both the students and the teachers.
We have, however, considered other textbooks as well,4-10]
but we have not found them suitable for our course.
The course is evaluated with a four-hour written "open
book" exam (i.e., all material available).
From the beginning of the academic year 2007-8, DTU
adopted learning objectives as a standard part of all course
descriptions in the course catalogue. The overall target of
the course is to present to the students the most important
principles and phenomena related to colloid systems and
surface chemistry. These areas have important and extensive
applications in the understanding and design of processes such
as adhesion, lubrication, cleaning, enhanced oil recovery, and
waste-water and air purification, as well in the understand-
ing and design of products such as detergents, cosmetics,
pharmaceuticals, polymer-containing items, and food.
There are also numerous applications in nature, e.g.,
fog, water droplets, and capillary phenomena.
The specific learning objectives of the course are for
students to be able to:
* Calculate surface and liquid-liquid interfacial
tensions with various theories
* Use different theories for. 1,1,,. the solid-
liquid and solid-solid interfacial tensions and c
employ them in i -,,,, and adhesion studies .
* Recognize the various mechanisms of adhesion i
and use various methods (Zisman's plots, theo-
ries) for its assessment
* Describe the most important theories in surface
* Use the Gibbs equation for adsorption calculations

* Explain the creation of micelles (CMC) from surfac-
tants and tell how CMC can be measured and how it
depends on salt, temperature, and chain .", it,
* Relate the adsorption in gas-solid and solid-liquid
surfaces and use the Langmuir and BET theories for
adsorption calculations
* Calculate the molecular weight and shape of colloidal
* Describe the most important (van der Waals and dou-
ble- layer) forces between colloidal particles and their
differences in relation to the intermolecular forces
* Explain the most important parameters in colloid
force-theories (zeta potential, Debye thickness, Ha-
maker constant) and perform calculations with those
* Describe the DLVO theory for the stability of colloidal
particles as well as compare the various mechanisms
for steric stabilization
* Describe the stabilization mechanisms in emulsions
(and foams) and design emulsions using various semi-
empirical tools (HLB, Bancroft rule, etc.)

These learning objectives, which are presented using active
verbs, focus on the abilities or competencies the students must
possess after they have completed the course.

Chemical Engineering Education

Figure 1. Students in the course over the years.

Books on Colloid and Surface Chemistry Used in Our Course in the Period 2000-2006
Book Used in period Comments by students Comments by teachers
ShawR1 2000-2003 Detailed presentations. Extensive presentation of numerous topics. Includes
Boring layout. exercises-not worked-out problems. No presentation
No applications, of modern theories for interfacial tensions.
Goodwin13 2004 Too condensed. Advanced textbook, requires previous knowledge of
Too high-level. colloids and interfaces.
Pashley and Karamand1 2005-2006 Somewhat too brief, no details; Very interesting industrial case stories and worked-out
easy to read, though. laboratory exercises.
Does not include chapter on colloid particles charac-


Due to the multidisciplinary nature of the subject as well
as the varying interests of the students, among other reasons,
we have found it necessary from the start of the course to
(i) The applications of colloid and surface chemistry in
various fields-especially chemical industry- including
paints, adhesives and detergents, petroleum industry
(especially the surface phenomena), materials with
emphasis on polymers, cosmetics, agrochemicals, and
food colloids (Figure 2)

(ii) The links between the most important topics and con-
cepts as well as their interrelations

One of the positive features of the currently used textbookVl
is the large number of "industrial stories" presented. The
book, however, includes numerous applications "hidden"
throughout the text and we felt it necessary to summarize
those applications for the students.
We have found that presentations of key concepts and tools
are extremely helpful in promoting understanding of the
coursework as well as in assisting in practical applications.
Equally useful is a summary of the key equations, considering
the variety of topics covered.
The key concepts of broad importance covered in the
course are:
1. The estimation methods for surface and interfacial
tensions, especially theories for the latter based on
intermolecular forces and their applications to , i >
and adhesion

2. D, 1,1,,, h1,, between ">11..,11 ' laws and concepts
and theories-specific equations, but also a demonstra-
tion of the major applications of the general laws
especially of surface chemistry
3. The equivalency interrelation of the Gibbs adsorption
equation with the adsorption theories and two-dimen-
sional equation of state (surface pressure-area plots)
4. The structure-property relationships in surfactants
and the complexity of the various factors o ff.
micellization and the value at CMC
5. The similarities/differences (both in terms of physics
and equations) of the adsorptions at various inter-
faces: gas-liquid, liquid-liquid, liquid-solid, solid-gas,
and how information from one type of interface, e.g.,
solid-gas, can be used in analyzing data in liquid-
solid/liquid interfaces
6. The complexity of adsorption on solids-differences
between gas, surfactant, and polymers
7. The complexity of solid surfaces and cautiousness need-
ed in the interpretation of - ,, ii, ,, ii, ....- phenomena
8. How a variety of properties/measurements for col-
loidal particles (kinetic, optical, theological) can yield
important information for the particles-especially
their molecular weight and shape
9. The similarities but also important differences be-
tween intermolecular and interparticle/surface forces
10. The essential concepts of the electrical and van der
Waals forces between colloid particles-especially
Zeta potential, double-layer thickness, and Hamaker
11. The DLVO theory for colloidal stability, how

ants in

Figure 2. Selected ap-
plications of Colloid and
Nanoporous materials Surface Chemistry.

Vol. 43, No. 2, Spring 2009

stability can be modified (qualitatively), and the
"other" non-DLVO stabilization mechanisms due
to hydration and steric forces; a bit on kinetics of
o , , L I , 1,1 . ,

12. Basic tools for studying emulsion stability and link

In addition, in a short course with emphasis on applications
we have found it difficult to include lengthy derivations such
as those in surface thermodynamics (for the Gibbs adsorption
equation) and those related to charged interfaces. The final
results were, of course, thoroughly discussed also via numeri-
cal examples exercises, both in the classroom and homework
problems. Table 2 shows the various types of exercises used,
fulfilling different goals, covering aspects from very simple,
straightforward demonstrations all the way to more complex
synthetic problems-including a few inspired from industrial
applications and projects.

The weekly 4-hour segments for a 5-ECTS-point course
at DTU present a challenge but also a gift for planning the
learning activities. Obviously it is impossible to give a straight
4-hour lecture. On the other hand, the sessions offer the op-
portunity to spend time with students and incorporate more
dialogue and interactive learning activities, where the stu-
dents will become active participants and not simply passive
listeners (as in a traditional lecture). We have experimented
with different teaching methods in this environment and
have arrived at the conclusion that variation and mixture of
various methods can give a positive learning environment.
It is very important, however, to explain to students what to
expect, because unnecessary roadblocks to learning occur
when student expectation is not met. In the following section
we discuss various elements which have been tested in our
teaching of this course.

Chemical Engineering Education

Different Categories of Exercises Used in Class or Homework Problems
Exercise Category Some Examples
1. Simple calculations; Adsorption from solution- role of solvent * Competitive adsorption of surfactants on solids * Vapor pressure of
Demonstrations based on droplets via the Kelvin equation * Estimating surface tension via capillary rise * Avogadro number from Brown-
few experimental data ian motion data * Free energy, enthalpy, and entropy changes in micellization from CMC-temperature data *
Debye lengths of single and mixed salts (for aqueous colloids) * Zeta potential via electrophoresis and Huckel/
Smoluckowski equations * Hamaker constants for colloidal particles in various media * Heat of adsorption from
adsorption data * Spreading of liquids and works of adhesion and cohesion * Molecular weight (MW) of proteins
from sedimentation (equilibrium or velocity) data
2. Derivations Molecular weight equation from gravity or centrifugal measurements * Stokes-Einstein equation and Brownian
distance * The maximum of the work of adhesion from Zisman plot * Link of critical and solid surface tensions
from interfacial theories * Contact angle via combining Young equation and interfacial theories * CPP (critical
packing parameter) of spherical micelles, and the aggregation number of SDS (Sodium Dodecyl Sulphate) * From
adsorption theories to surface tension/concentration equations and vice versa-derivation of the two-dimensions
ideal law * The general equation for the Debye length as a function of valency, temperature, and medium and
specific cases for aqueous solutions at 25 �C * CCC (Critical Coagulation Concentration) via the DLVO theory
and surface potential at CCC
3. Group contribution Surface and interfacial tensions of liquid-liquid interfaces, e.g., water-alkanes (aliphatics and aromatics), glycol-
(GC) methods; alkanes, mercury-water, or hydrocarbons via the Fowkes, Girifalco-Good, and Hansen theories * Estimation of the
Estimations via theories dispersion part of the surface tension of water * Surface tensions via Parachor and corresponding states methods
* Surface tensions via Hamaker constants * Resistance of adhesive points in presence of liquids via the Owens-
Wendt theory * Solid surface tensions via contact angle data and a theory, e.g., Owens-Wendt * HLB (Hydro-
philic-Lipophilic Balance) of surfactants for use in emulsions via the GC method of Davies-Rideal
4. Inspired from industrial Adhesion in silicon-epoxy coatings via the van Oss-Good theory * Stability of Alumina particles in various media
problems using Hamaker constants alone * Composite and individual adsorptions of solid pigments in paints via Langmuir's
equation * Kinetics and creaming of emulsions * Stability (electric vs. steric) of latex paints and kinetics of
5. Requiring graphical so- MW of biomolecules (proteins) via surface pressure-area data * Kinetics of aggregation via particle-time data *
lutions and extrapolations MW of polymers from osmotic pressures * MW of colloid particles via sedimentation coefficients * Adsorption,
area/molecule, and CMC from surfactant solutions from surface tension-concentration data * Adsorption of gas on
solids from volume-pressure data using Langmuir and BET --+ calculation of specific area of solid * Adsorp-
tion of compounds from solution on solids from adsorption-concentration data --+ calculation of area of adsorbed
6. Combined and general Characterization and wetting of polymer surfaces, e.g., nylon, PET, and Teflon (critical surface tension, Zisman,
contact angle, theories, work of adhesion) * Stability of colloids (potential-distance, potential energy-distance
curves, Debye length, zeta potential, Schulze-Hardy rule, and CCC * Kinetics of aggregation of (hydro)sols (half-
life time, Phase Inversion Temperature for emulsions, stability ratio)

A central component in the course is the variety of teach-
ing methods/approaches employed. Such variety has been
considered necessary both for enhancing understanding and
for making best use of time within the 4-hour modules used
at DTU. The teaching methods we use include:
* Traditional elements such as lectures and problems

* Active individual and group work

* Specialfeatures to raise interest of students

(i) Traditional elements: short lectures with exercises
solved by the individual student, with an appropri-
ate choice/balance between exercises suitable for
in-class work and homework.

(ii) Active individual work or group work on selected
topics (see later). Active discussion during the ex-
ercise section is absolutely necessary and we find
it necessary that both the teacher and teaching
assistant are present.

(iii) Specialfeatures designed to spur and raise the
student interest in the topic: these include "the
question of the day" (Table 3), guest lecturers
and company visits (e.g., a visit to Novozymes for
surfactant-enzyme-based detergents or a guest
lecture related to the link of fuel cells with colloid
stability). The question of the day was an initiative

"The question of the day" (Autumn 2003)
Day Question
1 How can mosquitos walk on water?
2 Do detergent companies cheat us?
3 What is common for the leaves of lotus and wings of
4 Why is it so difficult to paint Teflon?
5 How do you make good bread-or, what is gluten?
6 Why were PEG (polyethylene glycol) solutions used for
the conservation of the wooden VASA ship in Stock-
holm, Sweden?
7 Why is the sky blue but the sunset red?
8 What do milk, mayonnaise, and shampoos have in
9 Why - where - what about enzymes?
10 In which three ways can you measure the molar mass
of colloids?
11 When is a colloidal suspension stable-above or below
the critical coagulation concentration?
12 What is the most important thing you have learned
about colloidal and surface chemistry, and how is it
relevant to you in practice ?
13 Why do plastic paint buckets always have dusty lids?
14 Why does the bathroom mirror always steam up?
15 What makes a no-stick frying pan no-stick?

aimed at; ',,,ii*, one simple and relevant question
to which all students could more or less directly
relate, as a headline for each 4-hour session.

For the group-work sessions, suitable topics have been
chosen, e.g., electrokinetical phenomena, electric double
layer, and colloid stability. In small groups the students are
encouraged to read short parts of the textbook and slides and
then discuss the topic among themselves, answering well-
defined but general questions given in advance. A discussion
in plenum would follow. For example, in the case of "elec-
trokinetical phenomena as used in colloid chemistry," these
questions "to inspire the group work" can be:
* What are they?

* How do they work?

* Which of them is the most important in your opinion?
* What do they measure?

* What do they tell us and how are they used in practice?
* What are the limitations?

We soon realized that a 5-ECTS-point course cannot cover
both the theoretical and the experimental aspects of Colloids
and Interfaces and thus a laboratory exercise course, which
runs during January (duration: three full weeks) following
the theory course, has been established. Despite the fact that
one might have expected a laboratory course to have been as
popular (if not more so!) than a theory course, in practice we
have observed the opposite, for reasons not entirely clear to
us. To make the laboratory course more attractive to students,
we have tried to illustrate the "evident" links between theory
and laboratory courses as well as a clear illustration of how,
in colloid and surface science, theory and experiments go
hand-in-hand and little can be said and done without well-
defined and planned experiments. Theories and concepts are,
of course, useful in this planning and in understanding the
results. Table 4 (next page) summarizes these links.


Student satisfaction with the course has been high despite
the difficulties associated with finding an appropriate textbook
for our needs. Greater satisfaction with the course material
evident in recent years could be attributed to the availability
of extensive slides from the lecturers in the form of Power-
Point presentations with Notes. Our experience from teaching
Colloid and Surface Chemistry in a mixed student audience
with different expectations, interests, and directions has been
presented. We have discussed curriculum, textbooks, and
learning objectives emphasizing the "unifying concepts" that
can enhance understanding. Despite the numerous textbooks
available, we feel that only a few cover both topics in substan-
tial detail and at a level suitable for undergraduate students.

Vol. 43, No. 2, Spring 2009


1. Pashley, R.M., and M.E. Karaman, Applied Colloid and Surface
( I...... , Wiley (2004)
2. Shaw, D., Introduction to Colloid & Surface ( ...... , 4th Ed., But-
terworth-Heinemann (1992)
3. Goodwin, J., Colloids and Interfaces with Surfactants and Polymers:
An Introduction, Wiley (2004)
4. Jonsson, B., B. Lindman, K. Holmberg, and B. Kronberg, Surfactants
and Polymers in Aqueous Solution, Wiley (2001)
5. Hamley, I., Introduction to Soft Matter. Polymers, Colloids, Amphiphiles

and Liquid Crystals, Wiley (2000)
6. Hunter, R.J., Introduction to Modern Colloid Science, Oxford Science (1993)
7. Hiemenz, PC., and R. Rajagopalan, Principles of Colloid and Surface
Science, 3rd Ed., Marcel Dekker (1997)
8. Israelachvilli, J., Intermolecular and Surface Forces, Academic Press (1985)
9. Barnes, G.T., and I.R. Gentle, Interfacial Science-An Introduction,
Oxford University Press (2005)
10. Myers, D., Surfaces, Interfaces, and Colloids: Principles and Applica-
tions, VCH, Weinheim (1991)
11. Woods, D.R., and D.T. Wasan, "Teaching Colloid and Surface Phe-
nomena," Chem. Eng. Educ., 30(3) 190 (1996) 1

What can/should be measured and what can be calculated in "Colloid and Surface Chemistry"?
Property Can we measure it? How? Can we estimate it? How? Comments/Importance
Surface tension of X (Du Nouy, Pendant Drop, Wil- X (Parachor, solubility parameters, Wetting, adhesion, lubrication,
pure liquids and helmy plate, capillary rise) corresponding states)
liquid solutions
Interfacial tension X (Du Nouy) X (many methods, e.g., Fowkes, Surfactants, ....
of liquid-liquid Hansen, Girifalco-Good)
Surface tension of X (Zisman plot, extrapolation from Wetting, adhesion, ....
solids liquid data, solubility parameters,
Interfacial tension X (many methods, e.g., Fowkes, Wetting, adhesion, character-
of solid-liquid and Hansen, van Oss-Good) ization and modification of
solid-solid interfaces surfaces, . . . (paints, glues, . . . )
Contact angle X (many goniometers and other X (combination of Young equa- Wetting, adhesion, character-
between liquid and methods) tion with a theory for solid-liquid ization and modification of
solid interfaces) surfaces, ....
Critical micelle X (change of surface tension or other Detergency, ....
concentration of properties with concentration)
Surface or zeta po- X (micro electrophoresis) Stability of colloidal dispersions
tential of particles
Adsorption of gases/ X (many methods) X (many theories, e.g., Langmuir, Stability, surface analysis
liquids on solids BET, Freudlich)
Topography of a X (AFM, STM) Surface analysis and modifica-
surface tion
HLB (Hydrophilic- X (group contribution methods, Design of emulsions including
Lipophilic Balance) solubility parameters) stability of emulsions and deter-
mining the emulsion type
Work of adhesion X (JKR, AFM) X (the ideal one via Young-Dupre Adhesion, detergency
and similar equations)
Interparticle forces X (surface force apparatus, AFM, X (DLVO theory) Stability of all types of colloids
and colloid stability and other methods for stability, e.g., (paints, food colloids, . . . )
Molecular weight X (many methods, e.g., ultracentri- Characterization of high-
of polymers and fuge and osmotic pressure) molecular-weight molecules
Creaming and X (Turbiscan) X (Stokes equation for dilute disper- Stability of colloids
sedimentation of sions)
suspensions and
Critical Coagulation X (series of experiments adding X (DLVO theory) Stability of colloids
Concentration salts in colloidal dispersions until
coagulation occurs)
Determining emul- X (HLB and Bancroftt rule) Emulsion design
sion type

Chemical Engineering Education



A Glass Box Approach to Numerical Problem Solving

Rose-Hulman Institute of Technology * Terre Haute, IN 47803

An introductory computer programming course has
been a permanent staple of the undergraduate en-
gineering curriculum ever since the appearance of
mainframe computers. While the principal programming lan-
guage that is taught has changed over the years, much remains
the same. The course is typically taken during the freshman
year, well before any of the core engineering courses. Students
wonder why they have to take the class when they're in it,
and this viewpoint is unfortunately reinforced in retrospect as
they are rarely if ever called upon to apply their programming
skills. When they are asked to solve numerical problems, a
commercial software package is typically used in a "black
box" fashion, thus perpetuating the notion that their computer
programming course was a waste of time.
Hardware and software advances and curricular adjustments
have improved this situation. Laptop computers are used in the
classroom to a greater extent. Access to computing facilities,
in general, is less of an issue than ever before. In addition,
the availability of programming languages such as MatlabN1
that come equipped with built-in solvers and graphics makes
it easier to apply computer programs to solve engineering
problems. The use of such software, however, is only effective
if one can broker a departmental or institutional arrangement
where a common numerical software package is used in re-
lated engineering courses. Another consideration is that many
commercial numerical software packages are designed to be
used in a "black box" mode. This can foster their use in a way
that does not require the user to understand the underlying
numerical algorithms. In an academic setting, this may not
meet all of the intended educational objectives.

Another approach taken to promote numerical problem
solving in the undergraduate engineering curriculum has
been to have the individual engineering departments teach
computer programming rather than farming out this task to
the computer science department. This arrangement offers the
advantage of being able to offer discipline-specific instruc-
tion and example applications. Nonetheless, the impact of a
more enlightened experience in the introductory computer
programming course quickly fades if the students do not
regularly apply their computer application skills in problem
solving. As the saying goes, "use it or lose it."

Daniel Coronell received his B.S. in
- r-* chemical engineering from the University
4 of Illinois, Urbana, and his Ph.D. in chemi-
- - cal engineering from the Massachusetts
Institute of Technology. After graduation,
he worked in the chemical, semiconductor,
and engineering software industries over
a period of nine years before joining the
Department of Chemical Engineering at
Rose-Hulman Institute of Technology, where
he is an associate professor.
M. Hossein Hariri received his B.S. in gas
engineering from Abadan Institute of Tech-
nology in Iran, his M.S. in gas engineering
from IITin Chicago and his Ph.D. in chemical
engineering from the University of Manches-
terin England. After graduation, he worked in
the petroleum industry and R&D in energy for
11 years and was an assistant professor at
IIT before joining the Department of Chemi-
cal Engineering at Rose-Hulman Institute of
Technology, where he is a professor.

� Copyright ChE Division of ASEE 2009

Vol. 43, No. 2, Spring 2009

The Department of Chemical Engineering at Rose-Hul-
man Institute of Technology has made similar modifications
to its curriculum to address the issues outlined above. Since
1996, all undergraduate students at Rose-Hulman have been
equipped with a laptop at the start of their freshman year. In
2002, the department inherited from its computer science
colleagues the task of teaching introductory programming to
students enrolled in chemical engineering. This two-credit-
hour course, Programming and Computation for Chemical En-
gineers, is taken in the spring quarter of the students' freshman
year. [2] It has included instruction on Microsoft ExcelF31 (~ 1/3)
as well as computer programming (~2/3). Excel's integrated
Macro language, Visual Basic for Applications (VBA), has
been used as a medium for teaching programming concepts
to the students.
The decision to use VBA was motivated by several factors.
First, the convenience and efficiency of using a single soft-
ware package for the entire course reduced the instructional
overhead. Since VBA is integrated with Excel, this also less-
ened the students' anxiety due to their familiarity with this
application. Assuming that the use of VBA would continue
into their chemical engineering courses, it circumvented the

After several years of teaching the

students how to program in VBA, it

was recognized that their programming

skills were still largely abandoned after

the freshman year.

need for faculty in the department to embrace an unfamiliar
software package. For example, Matlab was used in an earlier
version of this course, and ~1/2 of the faculty had rarely or
never used it before. Other important factors included the
results of a comprehensive survey conducted by CACHE[41
that suggested Excel was the most widely used software by
practicing chemical engineers. Lastly, it was recognized that
the programming elements in VBA (e.g., loops, decision
constructs) were sufficiently similar to those in other com-
mon programming languages. As such, it would not be too
difficult for students to subsequently learn how to program
in a different language if required.
After several years of teaching the students how to program
in VBA, it was recognized that their programming skills were
still largely abandoned after the freshman year. It is believed that
much of this is due to the relatively large investment in resur-
recting their VBA course material and programs for application

in subsequent coursework. This inevitably involves relearning
some aspects of VBA, especially if more than a quarter or two
has passed since they took their programming course. Most
students are reluctant to do so, thus creating an obstacle to the
objective of teaching them how to apply their programming
skills to chemical engineering problem solving.
The principal pedagogical challenge that remains is two-
fold. First, we simply need to increase the opportunities for
students to apply their computer application skills to nu-
merical problem solving while minimizing the instructional
overhead. The use of a common numerical software package
throughout the curriculum is a key part of a solution to this
issue. Additionally, to be most effective, the software must be
used by students in a manner that increases their understand-
ing of the numerical algorithms while minimizing the actual
programming effort.

A novel approach to address this challenge is being
evaluated with the students who have recently completed
the Programming and Computation for Chemical Engineers
course. The central idea is to compile the general-purpose
programs that the students developed in this course into an
Excel Add-In. This addresses the need to increase the numeri-
cal problem-solving opportunities by making the programs
more accessible. The programs appear as functions built into
their Excel application. This approach also addresses the
need for the students to understand the underlying numerical
algorithms. They will use their own programs in a transpar-
ent software environment. One may refer to this as a "glass
box" approach to numerical problem solving, in contrast with
the more familiar "black box" approach. The Excel Add-In
can also be continuously populated with more complicated
programs and numerical algorithms as the students move
up the curriculum. This Add-In, hereafter referred to as the
Chemical Engineer's Toolbox, is distributed to sophomore-
level students at the start of the fall quarter for use in their
introductory Material and Energy Balances course.
We envision that the students will use the Toolbox in a
couple of different ways that serve to improve their learning
of chemical engineering principles. For relatively routine
computing tasks such as interpolation or numerical integra-
tion, the availability of Excel functions that streamline these
calculations will enable them to spend more time learning
the fundamentals of the problem and less time setting up a
spreadsheet. In addition, as the students move up the cur-
riculum, the relatively simple programs that they developed
as freshmen can serve as templates or starting points for more
sophisticated numerical problem solving. For example, a
program that computes the specific volume using a simple
pure component equation of state may be modified to account
for nonideality or multiple components as an assignment in
a thermodynamics course.

Chemical Engineering Education


Before describing the Chemical Engineer's Toolbox, we of-
fer a summary description of the VBA programming environ-
ment and language. The VBA programs are developed using
the Visual Basic Editor, a graphical computer programming
package that is seamlessly integrated with Excel. It consists
of a multiple-pane window as shown in Figure 1. The two
panes on the left are the Project Explorer and the Properties
Window. The Project Explorer includes a listing of all open
workbooks and installed Add-Ins, both of which are referred
to as projects in VBA. Each project includes any associated
objects (e.g., worksheets), forms, and modules. A form is a
customized graphical user interface, or GUI, that is created
in the Visual Basic Editor and can be used to conveniently
facilitate input and output for a VBA program. A module is
simply a sheet onto which related VBA procedures are typed
and stored. The code contained in a module appears in the pane

to the right of the Project Explorer. The Properties Window
can be seen below the Project Explorer pane. This window
is used to specify the properties associated with objects con-
tained in a VBA project.

The VBA programming language contains all of the tradi-
tional structured programming constructs (loops, decisions,
etc.) and some aspects of object-oriented programming as
well. A detailed description of the VBA programming lan-
guage may be found in several recently published books.E5 71
VBA programs are referred to as procedures. There are
several different types of VBA procedures, and methods
to execute them. In Excel, the simplest approach is to use
VBA function procedures since the protocol for calling one
is identical to that of any of Excel's built-in functions (e.g.,
SUM, SQRT, MINVERSE). For this reason, the collection
of VBA programs in the Toolbox is comprised exclusively
of function procedures.

Ea] atpvbaen.xls (ATPVBAEN.XLAM)
E ChEToolbox (CHEToolbox.xlam)
rn B1 Microsoft Excel Objects
I . Modules
4 EOSTools
: MathTools
- MixtureTools
- VLETools
El VBAProject (Bookl)
i B Microsoft Excel Objects
S .-- I (Sheetl)
**r :.. (Sheet2)

i - Th:- :r too
rl l VBAProject (FUNCRES.XLAM)

ThisWorkbook Workbook -
ly,.utl ,.: : re.:.:,,:.,l I

,utoUpdateFrequency :0
ZhangeHistoryDuration: 0
ZheckCompatibility False
ConflictResolution 1 - xlUserResoluLion
)atel904 False
)isplayDrawingObjects-4104 - xlDisplay5hap,
DisplayInkComments :True
EnableAutoRecover True
EnvelopeVisible False
final False
ZorceFullCalculation False
-lighlightChangesOnScr False
[nactiveListBorderVisiblk True
[sAddin False
(eepChangeHistory True
istChangesOnNewShe False
Dassword ******
�ersonalviewListSetting True
: i ,,[i-,al hi- h i ii-,i : ir ,-, h .... ".


Zd I MixDensity

Option Explicit

Function MixDensity(rho As Range, frac As Range) As Double
'This function computes the density of a liquid mixture.
'The inputs include the densities of each component (rho) and the
'corresponding component mass fractions (frac).

Dim i As Integer, nsp As Integer, sum As Double

'Determine the number of species
nsp = rho.Count

'Perform summation
sum = 0
For i = 1 To nsp
sum = sum + frac(i) / rho(i)
Next i

HixDensity = 1 / sum

End Function

Function Hol2Mass (mrng As Range, yrng As Range) As Variant
'This array function computes the mass fractions of a mixture given the
'corresponding mole fractions and molecular weights for each species.
'The molecular weights are contained in the range variable mwrng.
'The mole fractions are contained in the range variable yrng.

Dim i As Integer, nsp As Integer, x0) As Double
Dim sum As Double

'Determine the number of species
nsp = mwrng.Count

'ReDim output vector
ReDim x(1 To nsp)

'Compute Sum
sun = 0
For i = 1 To nsp
sum = sum + yrng(i) * mwrng(i)
Next i


Figure 1. Visual Basic Editor used to create VBA programs in Excel.

Vol. 43, No. 2, Spring 2009


The initial version of the Toolbox is tailored to chemical engi-
neering students beginning their sophomore year of instruction.
It contains a collection of Excel functions that includes general
math tools as well as tools designed to solve problems specific
to their introductory Material and Energy Balances course. A
list of the Toolbox functions can be found in Table 1.

It is seen that some of the functions do not require specifica-
tion of a system of units (e.g., Trapezoid, LinearSys), while
others do (e.g., Pvap, BubbleT). For the units-dependent

trapezoidal rule typed in as cell formula

functions, the Toolbox uses the SI system. This simplifies
the coding of the VBA programs, but also requires the user
to ensure that the function inputs are in SI units, and to
convert the function output units if necessary. Note that the
interested student could easily modify their VBA programs to
accommodate additional systems of units. This type of creative
enhancement of their Toolbox functions is encouraged.

We next consider a specific Toolbox function to demonstrate
how it is applied to solve a problem and to illustrate some
important characteristics of the underlying VBA code. A VBA
function procedure that performs numerical integration using
the trapezoidal rule [see Eq. (1) below] is developed by the

trapezoidal rule VBA function call

A B I C 0 E i

-;x fix) intll
" 0 6 0
J 1 i 6 e. ; :?s6;i1
E 1 3O; 6 3a 9 09:01
6 1-71 6-88 11-17687
7 2.078 6.922 13.71644
8 2.526 6.958 16.82556
9 3.071 6.985 20.62503
10 3.733 6-999 2525373
11 4.538 6-996 30.88672
12 5.516 6.97 37.71609
13 6.704 6.913 45.9626
14 8.149 6.817 55.88252
15 9.905 6.671 67.72498
16 12.04 6.46 81.74233
17 14.636 6.167 98.13217
18 17.79 65.77 116.9568
19 21.623 5.244 138.0652
20 26.283 4.556 160.8992
21 31.948 3.665 184.1851
22 38.833 2.523 205.4873
23 A? 201 1 07 222.3169

S ecry | C D E


f(x) in
0 6 222.3169
1-157 6.786
1.407 6.834
1-71 6-88
2.078 6.922
2.526 6.958
3.071 6.985
3-733 6.999
4.538 6.996
5.516 6-97
6.704 6.913
8.149 6.817
9.905 6.671
12.04 6.46
14.636 6.167
17.79 65.77
21.623 5.244
26.283 4.556
31.948 3.665
38.833 2.523
48.201 1.07

Figure 3. VBA
code for the
trapezoidal rule

Chemical Engineering Education

Figure 2.
Comparison of
a trapezoidal
rule numerical
integration us-
ing a spread-
sheet with that
using a Chemi-
cal Engineer's
Toolbox VBA

Function trapezoid(xrng As Range, frng As Range) As Double
'This function performs a numerical integration using the trapezoidal rule.
'The independent variable is contained in the xrng object variable.
'The integrand is contained in the frng object variable.

Dim npts As Integer "Namber of discrete points
Dim i As Integer 'Loop index

'Determine the number of discrete points
npts = xrna.Count

'Initialize sumnation variable
trapezoid = 0

'Sum up areas of trapezoids representing integral
For i = I To npts - 1
trapezoid - trapezoid + 0.5 * (frng(i) + frng(i + 1)} * (xrng(i + 1) - xrng(i)
Next i

End Function

students in their Programming and Computation fi
Engineers course.

ft n-, f( Jx ) + f x
f f(x)dx 1) -- x))X -
xo2 2+

This simple computational task can be accomplish
a spreadsheet. In fact, the students are required to
the first part of the course. This serves to reinfor
of having a customized function available for this
streamlines the calculation and eliminates the poss
correctly implementing the trapezoidal rule formula
been programmed correctly. This is shown in Figur

Saturated Steam
H, = 2762 0 W/kg
T, 165 �C
P - 7 bar
m, = 200 kgr

Superheated Steam
H2=3101 64 g
T 320 �C
P, 7 bar
2"= -999 kg

Mass Balance
- m^ + m = ms

Energy Balance
=2 rh1, MH2 = r/3H3

or Chemical

example numerical integration is performed using a spreadsheet-
only implementation and again using the Toolbox function.

The corresponding VBA code for the trapezoidal rule
x1) ( function is seen in Figure 3. The students are taught to cre-
X1) 1 ate computer programs that are reusable, i.e., not specific to
a given problem. For example, the trapezoidal rule function
*d using only can be used to integrate using any number of discrete indepen-
do so during dent variable points that are equally or unequally spaced. In
ce the value addition, the students are encouraged to write programs that
purpose-it can be easily modified if necessary. An example would be to
ibility of in- expand the trapezoidal rule function so that it can perform
a once it has numerical integration using Simpson's 1/3 rule, as well. If the
e 2, where an code includes sensibly named variables and is sufficiently
, commented, this task is more easily accomplished.

Product Steam
H = 2953 8 kg
T3 - 250 �C
P3 = 7 bar
3 =999 kg,

Figure 4. Schematic illustration of the steam-mixing problem based
on problem 7.35b in Felder and Rousseau!8'

In the following section, we provide a couple of
example applications of the Chemical Engineer's
Toolbox. These are taken from Felder and Rous-
seau's textbook Elementary Principles of Chemical
ProcessesI81 to demonstrate how the Toolbox may be
used for problem solving in an introductory Material
and Energy Balances course.

The first example problem involves the adiabatic
mixing of two streams containing saturated and
superheated steam as shown in Figure 4. This cor-
responds to problem 7.35b in Felder and Rousseau,181

Functions in the Sophomore Version of the Chemical Engineer's Toolbox
Function Name Description
Trapezoid Performs numerical integration using the trapezoidal rule.
LinearSys Solves a system of linear equations.
Interp_l1 Performs linear or cubic interpolation in one dimension.
Interp_2 Performs linear or cubic interpolation in two dimensions.
NewtonRaphson Solves a single nonlinear algebraic equation using the Newton-Raphson method.
ModEuler Solves an initial value ODE using the modified Euler method.
Mol2Mass Converts mole fractions to mass fractions.
Mass2Mol Converts mass fractions to mole fractions.
MW_mix Computes the average molecular weight of a mixture.
Density_mix Computes the density of a liquid mixture.
V_VDW Computes the specific volume of a gas using the van der Waals EOS.
V_Virial Computes the specific volume of a gas using the virial EOS.
V_RK Computes the specific volume of a gas using the Redlich-Kwong EOS.
Pvap Computes the vapor pressure of a pure component using the Antoine equation.
BubbleP Computes the bubble point pressure and corresponding vapor composition using Raoult's law and the Antoine equation.
BubbleT Computes the bubble point temperature and corresponding vapor composition using Raoult's law and the Antoine equation.
DewP Computes the dew point pressure and corresponding liquid composition using Raoult's law and the Antoine equation.
DewT Computes the dew point temperature and corresponding vapor composition using Raoult's law and the Antoine equation.

Vol. 43, No. 2, Spring 2009

with some of the pressures and temperatures modified to
underscore the use of the Toolbox functions. The problem
requires the students to simultaneously solve material and
energy balances around the system by making use of saturated
and superheated steam tables.

I. 1'< , = nlr], . ;:._;i _l'. I I"1i, 1- : . , 1 F if . I - 1 7
,A B | C D E F C IH

3 Enthalpy of Stream 3
5 T, �C P, bar H, kJIkg
6 250 5 2961
7 250 10 2943
H. = ;9- :.i ;0

12 Enthalpy of Stream 2
14 T, �C
.00 : ,
16 P. bar .
1 i-

Solution ol Mass and Energy Balances (Ax = b)

A Matrix b Veclor
SMass 1 I ...

Figure 5. Toolbox-assisted solution to problem 7.35b in
Felder and Rousseau!.8

I-0 - & !=t.ut.t.i,I1 0;I:I I 8 : A " I . o f-:. E: Fe . i
A R | I | | Ei F | H |I

3 Benzene 0 1 E. k : l l l'3411 1 1 1 V1 .C, I DP
4 Eihylbenzene OJEl F ye.'. l3J6 *,j. 21. 09'1 X 1 04971731
5 Toluene 0 ::1 E. SZ'O . 13.J -IF ;71 19 E.9J xe_ 0 1949511
6 x W 0 3078761

3 x. A B C
10 Benzene 0[ J : J 6 924' 1 . I:i 1 . 19 e. I:% JF': TI
11 Eihylbenzene C0 ';- f '' 1Fa2 V 21) 0 x 0 7146.7J
12 Toluene 0 2:1 6 3E I iJJE. 2 9 .1i9 X O Ot.06;2 2
13 XT 0.217504
-C I
17 . A B C
13 Benzene 0 A6. 6 ~:j 1; - L1."_ ; _.1 19 E 1j0J JJ Z
19 Elhylbenzene 0 -E. 6 6-.. lJi . '4i 11 091 x 0 J.1 l
20 Toluene [0 :-J 6 a;sc. 1 :i7E. 19 1 .9: -I c 6Xi
21i x.r id oul

Figure 6. Toolbox-assisted solution to problem 6.58b in Felder and Rousseau.

This problem is particularly well-suited for application of
the Chemical Engineer's Toolbox since it requires repeti-
tion of many routine calculations. For example, the steam
enthalpies for streams 2 and 3 (H2 and 1H3 in Figure 4) must
be determined by two- and one-dimensional interpolation,
respectively, using the values available in the steam tables.
The interpolation tasks are conveniently performed using the
Interp_2 and Interp_l functions. In addition, the solution of
the material and energy balance equations are obtained us-
ing the LinearSys function. The Toolbox-assisted solution to
this problem is illustrated in Figure 5. Clearly, the solution
could have been obtained without the Toolbox, but having the
functions available minimizes the time spent performing rote
calculations and provides more time for the students to learn
the fundamental steps that lead to the solution. Additionally,
the underlying code that comprises the functions is fully ac-
cessible to the students.
The second example application of the Toolbox makes use
of the bubble point temperature function, BubbleT. Problem
6.58b in Felder and Rousseau81l involves the calculation of
the bubble point temperature of an ideal mixture of benzene,
ethylbenzene, and toluene. The students are asked to compute
the bubble point temperature at atmospheric pressure for three
different liquid mixture compositions by using Raoult's Law
and the Antoine equation.

EYlP =E1P 1x
1 1

log,,io = Al --1 (3)

This numerical problem consists of solving
a single nonlinear algebraic equation where
the unknown variable is the temperature, T.
Excel's Goal Seek utility is recommended
in the problem statement.
This problem represents an example where
the Toolbox may be used in a manner that
expands the students' learning opportuni-
ties beyond the original problem statement.
For example, the students can be asked to
create a Txy diagram by using the BubbleT
and DewT functions since they return the
temperature and phase composition. In this
example, the BubbleT function was applied
to solve for the bubble point temperatures
of three ternary mixtures specified in the
problem statement. BubbleT is an array
function (i.e., returns an array of numbers)
that computes not only the bubble point tem-
perature but also the corresponding vapor
composition. The required inputs include
the total pressure, liquid phase mole frac-

Chemical Engineering Education

tions, and the Antoine equation coefficients for each species.
The Toolbox-assisted solution to problem 6.58b is shown in
Figure 6. The additional function output consisting of the
vapor phase composition enriches the students' learning as-
sociated with the problem. Unlike the "black box" Goal Seek
approach, the students can also see the underlying numerical
algorithm (Regula-Falsi method as described in Appendix A
of Felder and Rousseau) implemented in the BubbleT func-
tion, providing them with a more fundamental understanding
of the solution technique. In addition, the BubbleT function
can serve as a basis for incorporating non-ideal effects when
the students learn more about vapor-liquid equilibrium in a
subsequent thermodynamics course.

The Chemical Engineer's Toolbox was developed as a
proactive approach to improve students' computer applica-
tion skills in the undergraduate chemical engineering cur-
riculum. The primary benefits of the Toolbox that enhance
student learning are its convenient access as an Excel Add-In
and the transparent "glass box" environment in which the

programs are created and stored. The students are provided
with the Toolbox at the start of their sophomore year for use
in their introductory material and energy balances course. It
is anticipated that additional VBA program modules will be
defined and created by faculty and students alike in courses
to follow in fluid mechanics, heat transfer, thermodynamics,
mass transfer, and reactor engineering.

1. The Mathworks, Inc., Natick, MA.
2. Coronell, D.G., "Computer Science or Spreadsheet Engineering?"
Chem. Eng. Educ., 39(2), 142 (2005)
3. Microsoft, Inc. Redmond, WA.
4. Edgar, T., "Computing Through the Curriculum: An Integrated Ap-
proach for Chemical Engineering," CACHE Fall 2003 Newsletter,

5. Billo, E.J., Excel for Scientists and Engineers: Numerical Methods,
Wiley, New York (2007)
6. Walkenbach, J., Excel 2003 Power Programming with VBA, Wiley,
New York (2004)
7. Kimmel, PT., S. Bullen, J. Green, R. Bovey, and R. Rosenberg, Excel
2003 VBA Porgrammer's Reference, Wiley, New York (2004)
8. Felder, R.M., and R.W Rousseau, Elementary Principles of Chemical
Processes, 3rd Ed., Wiley, New York (2005) 1

Vol. 43, No. 2, Spring 2009

MR! t classroom
---- --- s_____________________________________


Using Activity Breaks to Teach History

Michigan Technological University * Houghton, MI 49931
Teaching students in the classroom on a regular basis
quickly reveals the importance of activity breaks.
Activity breaks can be used for active learning ex-
ercises such as in-class teams, think-pair- share, or minute
papers.J1 The core elements of all active-learning methods
are student activity and engagement in the learning process.
These methods have been shown to have a positive effect on
student learning. [2]
An alternative focus of this active-learning activity break
can be to educate students about the history and personalities
of chemical engineering. Almost every lecture in a chemi-
cal engineering class contains references to the people and
their accomplishments that form the foundation for today's
students: Antoine equation, Gibbs' free energy, Arrhenius
equation, Reynolds number, McCabe-Thiele plot, Bode plot.
Why are these figures famous today? Because they came up
with solutions to important problems. While many of these
historical figures are at least vaguely familiar to us as instruc-

Joseph H. Holes is an assistant professor
of chemical engineering at Michigan Tech-
nological University. He received his B.S.
in chemical engineering in 1990 from Iowa
S State University and his M.E. and Ph.D.
from the University of Virginia in 1998 and
2000, respectively. His research area is
nanoscale materials design and synthesis
for catalytic applications with an emphasis
on structure/property relationships and in-
situ characterization.

SCopyright ChEDivision of ASEE 2009

tors, the students are usually completely unfamiliar with
them. By focusing on the history and personalities, chemical
engineering comes alive and the students become familiar
with the human side of our profession. These examples can
also be used to demonstrate to students the reasons why these
problems were so important and how their solutions led to
practical developments and applications. Since there is often
at least one historical figure mentioned in every class lecture,
they provide an opportunity to re-engage the students and re-
focus on the topic through the use of a historically focused
activity break.

When a historical figure is encountered during a class pe-
riod, it is often part of a derivation, and student attention is
waning. This provides an ideal opportunity for a historically
focused activity break. This break serves as a way to put an
exclamation point on a concept and to connect the person to
this concept. The students are first asked to guess when the
historical figure lived and did the work that bears his or her
name. As expected, a few wildly inaccurate guesses usually
result. Next, the students are shown a picture/portrait of the
historical figure. Slightly more accurate guesses are then
given. The guesses serve as a way to encourage participation.
Since no one is likely to know the answer, a wrong guess
does not demonstrate a lack of technical knowledge to their
peers. Finally, the students are shown a picture together with
biographical information about the historical figure. This in-
formation typically includes birth and death dates, institutions
attended, degrees earned and dates, major accomplishments,

Chemical Engineering Education

Biographies Used in Kinetics and Reaction Engineering
Svante Arrhenius Edward Teller
Cato Guldberg Paul Emmet
Peter Waage Irving Langmuir
Maud Menten Thomas Sherwood
Leonor Michaelis Alan Colburn
Hans Lineweaver Ernest Thiele
Dean Burk Gerhard Damkbhler

and awards earned (Figure 1 and Figure 2). The degree and in-
stitution data show students that people from many fields have
contributed knowledge important to chemical engineering. It
also exposes students to the importance of advanced degrees
in science and engineering but also that some historical figures
had no more than a bachelor's degree. Major accomplishments
other than the one of current interest are also listed. In this
way, the versatility of these historical figures is demonstrated
as well as the fact that people often succeed and contribute
to fields outside their area of study. The break is concluded
with a short discussion of why the accomplishment occurred
at that time, the historical context in which it occurred, what
other historical events influenced it, and other broad societal
influences (intended and unintended).

The historically focused activity breaks have been used
over the last five years in two separate courses (a junior-level
required course in Kinetics and Reaction Engineering and a
senior-level elective in Industrial Chemical Production). For
the Kinetics and Reaction Engineering class, 14 biographies
have been developed (Table 1). Six biographies have been
developed for the Industrial Chemical Production class.
From the instructor perspective, what appears to draw the
students into the presentations is when they include contro-
versy. For example, Thomas Midgley was responsible for
two of the most important inventions of the 20th century:
tetra-ethyl lead gasoline additive and chlorofluorocarbon
refrigerants. These inventions lead to the tremendous suc-
cess of the automobile and allowed large population growth
in the American south and southwest. As a result of these
inventions he won numerous awards. Before the century was
over, however, the side effects of these inventions were well
known and both substances were tightly regulated. Similarly,
Fritz Haber and Carl Bosch developed catalysts to produce
ammonia from nitrogen and hydrogen. This allowed Germany
to make explosives for its war efforts after it lost access to con-
ventional nitrogen sources. On the positive side, subsequent
ammonia production and use as a fertilizer has also allowed
a worldwide expansion of agriculture production. Examples
such as the two above help our students understand the impact

Figure 1. Thomas Midgley picture and biography
for classroom use.

Wilhelm Ostwald
� Tb. 1853, Riga, Latvia
d. 1932, Leipzig, Germany
. Univ. of Tartu 1875 (Estonia)
Univ. of Tartu 1878, Ph.D.
1877: Prof. of Physical Chemistry at
S. ' Leipzig University. Students included:
S . Arrhenius (Nobel Prize 1903)
Van't Hoff (Nobel Prize 1901)
Nernst (Nobel Prize 1920)

i " Received Nobel Prize in Chemistry in
1909 for "Work on catalysis, chemical
S \ equilibria, and reaction velocities."

Figure 2. Wilhelm Ostwald picture and biography
for classroom use.

of engineering in a global and societal context and contribute
directly to desired outcome (h) of Criterion 3 in ABET.
Students can also be educated about the practice of sci-
ence and engineering through these historical biographies.
For example, most faculties are aware of the mentor/mentee
relationships between professors and graduate students. If the
historical biography lists an individual's advisor and students,
the students can see how one generation of scientists educates/
trains the next generation. An ideal example of this is Ostwald,
who mentored three Nobel laureates (Figure 2).
Whenever possible, women and minorities should be fea-
tured as historical figures (e.g., Maud Menten of Michaelis-
Menten kinetics). There is an ongoing effort by the NSF and
other organizations to encourage the participation of women
and minorities in science and engineering. By highlighting the
contributions of these groups, our own students can be encour-
aged. It should also be noted that many historical women and
minorities succeeded in spite of the roadblocks placed by soci-
ety. This can be used to show students that anyone can succeed

Vol. 43, No. 2, Spring 2009

despite whatever roadblocks they face. Resources focused on
information specifically about women and minorities in science
may be used to prepare these biographies.[3 51
The use of historical biographies also allows the opportunity
to expose undergraduate students to the scientific literature.
Show the students a copy of the paper where Thiele investi-
gated the relationship between catalytic activity and particle
size[6] (which led to the Thiele modulus) or when Michaelis
and Menten published their understanding of enzyme kinet-
ics.J' By showing students the original papers, they can begin
to understand the process whereby a problem evolves into a
research project, becomes published in a research journal,
is accepted by the researchers in the field, and graduates to
textbook fundamentals.
Information and images for these biographies can come
from a wide variety of sources. For historical figures in
transport phenomena, Bird has presented an extensive list
of microbiographies.J81 Similarly, for historical figures in
catalysis, more in-depth information is available from Da-
vis.[9] Additional published sources include the Dictionary of
Scientific Biography,[1�] the Bibliographical Memoirs by the
National Academy of Sciences,11I and the Memorial Tributes
series by the National Academy of Engineering.[12] Finally,
the American Institute of Chemical Engineers is currently
celebrating its centennial; as part of this celebration, a number
of sessions at the fall 2008 meeting were devoted to the history
of chemical engineering. Thus, the meeting proceedings may
provide another resource.
Many online information sources are quite useful. The
International Center for Heat and Mass Transfer has a Web
page with biographies of historical figures with dimensionless
parameters named after them.J131 If the figures come from a
medicine/biology background, the Web
site provides biographical information.[141 Finally, Wikipedia
provides an ever expanding source of information.JI51 For im-
ages, useful Web sites include the ChemTeam Photo Gallery[161
and Pictures of Physicists.["1 Again, if all else fails, both Google
and Google-image searches can cast a very wide net.

Student response has been very positive and in fact they are
responsible for coining the term "Old Dead Guys." After a few
of these biographies were presented, the students started to
expect them, often asking before class if there will be any "Old
Dead Guys" today. Additionally, the students have pointed out
instances where I have missed opportunities to present more
of these biographies. In several cases where it was difficult
to locate an image of the historical figure, individual students
have instigated their own successful Web searches to find an
image. All of these responses indicate that the students are
taking ownership of the concept.

The most recent class went a step further. They spontane-
ously decided to determine which member of our department
most resembled the historical figure. Due to the preponderance
of beards on 19th-century scientists, the two members of our
department with beards were frequent winners. Subsequently,
this class incorporated this idea into their own classroom
presentation. Approximately 75 percent of the student presen-
tations included a biography of a historically relevant figure.
Several students also noted to me how hard they worked to
find biographical data and images of the historical figure.
Additionally, as part of these presentations, the students
competed informally to see who could incorporate the oldest
historical figure into their presentation.

Historically focused activity breaks provide an excellent
way to incorporate history into the classroom. By connecting
the historical figure with a solution to an important problem,
the students gain a better understanding of the subject mat-
ter. These history lessons also serve to put a human face on
chemical engineering while providing an opportunity to
educate students about the broader societal impact of science
and engineering.

1. Felder, R.M., and R. Brent, "Effective Teaching: AWorkshop,"inASEE
Chemical Engineering Summer School, Washington State University
2. Prince, M., "Does Active Learning Work?A Review of the Research,"
J. ofEng. Educ., 93(3), 223 (2004)
3. Siegel, EJ., and K. Thomas Finley, Women in the Scientific Search,
Scarecrow Press, Metuchen, N.J. (1985)
4. Spangenburg, R., and K. Moser, "African Americans in Science, Math,
and Invention," Facts on File (2003)
5. Bailey, M.J., "American Women in Science-A Biographical Diction-
ary," ABC Clio, Santa Barbara, CA (1994)
6. Thiele, E.W., "Relation Between Catalytic Activity and Size of Par-
ticle," Indust. and Eng. ( h...... , 31(7), 916 (1939)
7. Michaelis, L., and M. Menten, Biochemische Zeitschrift, 49, p. 333
8. Bird, R.B., "Who Was Who in Transport Phenomena," Chem. Eng.
Educ., 35(4), 256 (2001)
9. Davis, B.H., and W.P Hettinger, Jr., eds., "Heterogeneous Catalysis
Selected American Histories,"ACS Symposium Series, ed. M.J. Com-
stock, 222, American Chemical Society: Washington, D.C. (1983)
10. Holmes, EL., ed., Dictionary of Scientific Biography, Charles Scrib-
ner's Sons, New York (1970)
11. National Academy of Sciences, ed. Biographical Memoirs. 1877-,
National Academy of Sciences, Washington D.C.
12. NationalAcademy of Engineering, Memorial Tributes. 1979-, National
Academy of Engineering, Washington, D.C.
13. Grigull, U., H. Sandner, J. Straub, and H. Winkler, org/dimensionless/dimensionless.html>
14. Enersen, O.D.,
16. Park, J.L., Menu.html>
17. Reinhardt, J., J

Chemical Engineering Education

--- - ^ K.___________________________o<



For a Mass Transfer Course

Northwestern University * Evanston, IL 60208

In the traditional undergraduate chemical engineering
curriculum, the mathematical formulations of engineer-
ing problems are solved almost exclusively by analytical
methods. A prototypical example is the analytical solution of
differential equations in transport. Many interesting-and
not particularly exotic-problems cannot be solved analyti-
cally, however. In the past, limiting cases and approximations
might have been used to circumvent this problem. But with
the availability of fast computers and user-friendly software
for numerical computation, we risk becoming irrelevant if
we do not equip our students to use these new tools. Other
disciplines are also concerned about this problem. For ex-
ample, concerns about whether undergraduates are equipped
to tackle problems of increasing complexity recently led the
Mathematical Association of America to convene a working
group of chemists to examine the connections between the
undergraduate mathematics and chemistry curricula.[1]
The mass transfer course is an ideal one for including nu-
merical solution methods for chemical engineers, because the
students have already seen the same mathematical methods
in their fluid mechanics and heat transfer courses. At North-
western University, momentum, heat, and mass transport are
taught separately in successive quarters in the third (junior)
year. Fluid mechanics is taught first, along with the requisite
vector analysis, followed by heat transfer. By the time mass
transfer is encountered, the analogies to fluid and heat transfer
can be used to speed the coverage of the core material, leaving
more time for exploration of other topics, such as numerical
methods or short group projects.
At Northwestern University's McCormick School of
Engineering and Applied Science, the computer solution
of numerical problems is introduced to first-year students
through the Engineering First program using MATLAB.[21
While FORTRAN 77 was often taught to chemical engineer-
ing students in the past, MATLAB now seems to be a favored

introductory programming language in the United States. It
has the advantage of incorporating a graphical user interface
and good graphing capabilities. In addition, MATLAB boasts
a range of ODE and PDE solvers that are of particular use for
transport problems. With the widespread availability of such
tools built into the software and on the Internet, it is no lon-
ger necessary to make students write their own code to solve
these types of problems. Researchers in industry also typically
operate by using numerical codes written and published by
experts in the relevant area of numerical computation. The
researcher is thus able to devote more time to solving prob-
lems in his or her own field of expertise. Therefore the ability
to understand and use existing pieces of high-level code is of
great practical importance.
Discrete particle- or agent-based simulations are rarely
taught to undergraduates, but they are becoming increasingly
commonplace in fields as diverse as materials science, trans-
portation, and sociology.[3] One could argue that such skills are
of more use to a chemical engineering graduate entering the

Manohar Murthi earned his B.S. degree in chemical engineering from
the University of California, Berkeley, and his M.S. and Ph.D. degrees
from Northwestern University. He is currently employed as a quantitative
researcher by a proprietary trading firm.
Lonnie D. Shea is a professor in the Department of Chemical and
Biological Engineering at Northwestern University. He holds B.S. and
M.S. degrees in chemical engineering from Case Western Reserve
University and a Ph.D. in chemical engineering and scientific computing
from the University of Michigan. His research laboratory focuses on the
combination of biomaterials and gene/drug delivery for regenerative
Randall Q. Snurr is a professor in the Department of Chemical and
Biological Engineering at Northwestern University. He holds B.S.E.
and Ph.D. degrees in chemical engineering from the University of
Pennsylvania and the University of California, Berkeley, respectively.
His research interests include molecular simulation, development of
new materials, diffusion in nanoporous materials, adsorption, catalysis,
and energy storage.

� Copyright ChE Division ofASEE 2009

Vol. 43, No. 2, Spring 2009

workforce today than the knowledge of rigorous distillation
column design. Stochastic simulation has become an integral
part of the computational chemist's or biologist's toolbox,
with a number of practitioners calling for its inclusion in
the undergraduate curriculum.4 As chemical engineers have
also embraced molecular simulation in their research, some
chemical engineering departments have added undergraduate
courses in molecular simulation and theory, covering topics
such as the estimation of thermochemical and reaction rate
data and the prediction of phase equilibria and transport
properties by molecular simulation.Es5
Solving problems numerically forces students to think
about mathematics in a different light, in that it is no longer
possible to simply learn the analytical solution. Some element
of programming is invariably involved in solving equations
numerically, forcing students to break the solution down into
the simplest steps possible, which can in turn lead to a more
concrete understanding of the mathematical relationships.
For students to become comfortable with solving problems
numerically, such problems must be incorporated throughout
the curriculum. In this paper, we give examples of problems
we posed to expose students to numerical solutions and
simulations in the context of mass transfer. The following
sequence of problems was assigned to increase the students'
familiarity with the solution of ODEs using MATLAB. We

started off with a diffusion problem
that could be solved analytically and
had the students compare the analyti-
cal solution to the numerical solution
generated by a boundary value solver
intrinsic to MATLAB. We also encour-
aged them to experiment with different
values of the parameters fed to the
boundary-value solver to see whether
the quality of the numerical solution or
the time taken to reach it were affected.
We then posed a problem with reaction
and diffusion that had no analytical
solution. Students were asked to vary
the reaction rate constant until the con-
centration profiles in the system began
to resemble those for the limiting case
of reaction being much faster than
diffusion. Finally, we presented stu-
dents with a lattice simulation of cells
invading a polymer tissue engineering
scaffold and had them experiment with
the different parameters controlling
the rate of cellular invasion and the
concentration profile of the invading
cells in the polymer matrix.
All of the problems discussed in
this paper can be found at the Web
site 154

edu/Publications/SupportingInfo/Download.html>. Instructors
can obtain MATLAB solutions by sending e-mail to snurr@

To provide a fairly gentle reintroduction to MATLAB, we
first asked students to determine the concentration profile and
flux of a liquid, A, slowly evaporating into a gaseous mixture
of A and B from a reservoir of pure A located at the bottom
of a cylindrical tube. Since the evaporation of the liquid is
slow, one may assume that the surface of the liquid is station-
ary. This example is covered in many texts and an analytical
solution is straightforward. We used the text by Middleman,t61
where this problem is solved as Example 2.1.1. We asked the
students to generate a numerical solution using MATLAB and
compare this with the analytical solution. The steady-state
equations to be solved are

dx -(1-x)N
dx X)(1)
dz CD
-- 0
where x is the mole fraction of A in the gas phase, N is the

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
Position in film (m)

Figure 1. Binary diffusion and second-order reaction in a stagnant film. The
concentration profiles of each species are shown for four different values of the re-
action rate constant, with the diffusivity of each species held constant. If reaction
is much faster than diffusion, almost all the reaction takes place at the reaction
front, marked on the figure as L,
Chemical Engineering Education

..............................................................,Lc i .... ..

Location of reaction front, LZ

flux of A, C is the total concentration in the gas phase, and
D is the diffusivity of gaseous A in B. The boundary condi-
tions are that at z = 0, x = xo (determined from the vapor
pressure of A at the liquid/gas interface), and at z = L (end
of the tube), x = x , the mole fraction of x in the gas mixture
flowing past the tube.
MATLAB incorporates a two-point boundary value problem
solver called bvp4c, which is useful in solving this problem.
The bvp4c solver requires as input an initial guess to the solu-
tion in a data structure that consists of the initial mesh points in
the domain of the solution and the values of the initial guess for
each mesh point. This data structure can be formed by another
function intrinsic to MATLAB called bvpinit. The other inputs
to bvp4c are the functions describing the system of ODEs and
the boundary conditions. Our ODE function consisted of just
the first of the above equations, with N as a parameter to be
determined. Since most students had only encountered initial-
value ODE problems, we first discussed the differences between
initial value and boundary value problems in class, pointing
out that the latter can have no solutions or an infinite number
of solutions. A hands-on introduction to MATLAB covered the
use of file input and output, functions, function handles, data
structures, and graphing. This was followed by fairly explicit
guidance in the use of the boundary value solver functions.
Students were also encouraged to try different initial guesses
for the solution and the unknown parameter and to examine
the effects on the validity of the solution and the time taken
to reach it. Increasing the number of initial mesh points from
10 to 10,000 resulted in an increase in computation time from
a few seconds to over a minute but did not affect the quality
of the solution for this simple problem. Certain initial guesses
for the concentration profile, however, resulted in numerical
disasters-with the result that no solution could be found. The
solution was completely insensitive to the initial guess for
the unknown parameter, N. Finding that this parameter was
in exact agreement with the analytical solution strengthened
the students' confidence in their ability to obtain correct
numerical solutions.

We followed by posing a problem without an analytical so-
lution, in this case Middleman's Example 3.2.9. This example
consists of steady-state binary diffusion through a stagnant
liquid film in which a second-order reaction is taking place.
The equations to solve are

D 1 - kCC = 0 (2)
Dz2 1 2
D 2 - kC1C2 = 0

At z = 0, C1 is maintained at a constant value of CO10, and compo-
nent 2 is not allowed to cross the plane, i.e., dC2 /dz = 0. At z = L,
Vol. 43, No. 2, Spring 2009

C2 is maintained at a constant value of C2L, and all of compo-
nent 1 is required to react within the film so that C1 = 0.
The concentration profiles in the film for different rate
constants are plotted in Figure 1. While no analytical solu-
tion is possible, an approximation in the limit of fast reaction
is possible. If the reaction is sufficiently fast and there is no
excess of either species, the concentration of each species
becomes essentially zero upon crossing a small zone known
as the reaction front, in which almost all the reaction takes
place. This behavior can be seen in the concentration profiles
in Figure 1 corresponding to the highest values of the reaction
rate constant, k. The location of the reaction front, Lf, can
be found from the realization that, due to the stoichiometry
of the reaction, the fluxes of the two components must be
equal. Then

Lf 1+ C2L D1 (3)

Since the bvp4c solver can only be used to solve systems
of first-order equations, the above system of equations and
boundary conditions must be rewritten as such via the substi-
tution y = dC,/dz, which results in a system of four first-order
equations to go with the four boundary conditions. The stu-
dents were expected to arrive at this realization on their own.
They were asked to calculate the concentration profiles of the
components in the film and find the value of the rate constant
at which the reaction front approximation becomes valid.
This exercise was repeated with different diffusivity values
to emphasize that the behavior of the system is governed by
the ratio of reaction rate constant to diffusivity, essentially
the Thiele modulus.

The tools that students gained in the problems above could
be readily extended to explore multicomponent diffusion,
a topic that is often completely ignored even in graduate
transport courses. For example, consider binary diffusion of
species i and j through a zeolite membrane. The membrane
can be considered a third, nondiffusing component. The fluxes
of the two species with respect to the stationary membrane
frame of reference can be written as 71
J1 = -DVC1 - DVCj (4)
J = -D VC - D VC
J Ji J J j
where J is the flux of component i, D is its main-term diffusivity,
and DO is its cross-term diffusivity. In general D :-- D , and for
guest molecules in zeolites all of the diffusion coefficients may
depend on the concentrations of both species. Sanborn and
Snurr have reported the concentration-dependent diffusion
coefficients for mixtures of methane and CF4 in the zeolite
faujasite, calculated from equilibrium molecular dynamics
simulations and fitted to simple analytical functions of the
concentrations. 8] They used MATLAB to solve Eqs. (4) for

several interesting sets of boundary conditions. For "co-diffu-
sion" boundary conditions, both species have a higher concen-
tration on one side of the membrane. For "counter-diffusion"
boundary conditions, species i has a higher concentration on
one side but species j has a higher concentration on the other
side of the membrane. Normally, one would expect species
i and j then to diffuse in opposite directions (counter-diffu-
sion). Depending on the magnitudes of the main- vs. cross-
term diffusivities, however, it is possible that both species
will diffuse in the same direction.E81 This illustrates that for
molecules in tightly confined spaces, such as zeolite pores,
the seemingly esoteric cross terms may, in fact, be important.
As an interesting question, one may ask the students if this
violates the laws of thermodynamics. (It does not, as both
species still diffuse downhill in chemical potential, illustrat-
ing that chemical potential and not concentration is the real
driving force for diffusion.)
Multicomponent diffusion is often ignored in courses be-
cause of the lack of access to the needed diffusion coeffcients
and because numerical solutions of the differential equations
are usually required. This example shows that modem mo-
lecular simulations may provide access to difficult-to-measure
multicomponent diffusivities. It also shows that the numerical
solution of the differential equations is easily undertaken with
widely available software such as MATLAB.

Certain types of problems may be more easily modeled as
computer algorithms than as differential equations. While this
type of modeling is now commonplace, competing with and
sometimes replacing equation-based approaches, chemical
engineering students tend to be almost entirely unacquainted
with it by the end of their undergraduate careers.P31 An in-
triguing and intuitive example of this type of modeling is a
simulation of ants foraging for food,[9] which can be found at
the Web site of Northwestern University's Center for Con-
nected Learning and Computer-Based Modeling, northwestern.edu/netlogo/models/Ants>.
This simulation concerns the manner in which a colony
of ants finds food and transports it back to their anthill. It
could easily be used as an in-class demonstration of a dif-
ferent mechanism for mass transfer, albeit one that would be
extremely difficult to describe by differential equations.
In this simulation, each ant encountering a large piece of
food deposits a chemical trail as it transports some of that food
back to the nest. The chemical trail evaporates and diffuses
over time. Ants can sniff out the chemical trail and follow
its gradient uphill. A similar mechanism using a "nest scent"
is used to return to the nest once food has been found. The
chemical trails are reinforced by repeated traversal, which
induces more ants to chip away at the food source until it is
completely consumed. Once this occurs, the chemical trail
begins to dissipate and the colony consequently forages else-

where. The colony generally exploits food sources closest to
the nest before foraging further afield since the evaporation
and diffusion of the chemical retards the formation of stable
chemical trails to more distant food sources.
The ant simulation described above is an example of agent-
based modeling based on the cellular automaton paradigm.
Cellular automaton simulations are used to model complex
systems comprised of interacting autonomous agents. Agent
behaviors are modeled explicitly, using a range of behavioral
models and representation schemes at appropriate levels of
detail. The crux of agent-based modeling and simulation
is that agents only interact and exchange locally available
information with other agents in their immediate vicinity.
What constitutes an agent's "immediate vicinity" varies
depending on the type of system being simulated. For ex-
ample, neighbors may be spatially close for a simulation in
continuous space, occupying adjacent grid cells in a lattice
simulation, or connected nodes in a simulation of a network.
Generally, an agent's set of neighbors changes rapidly as a
simulation proceeds. The problem of identifying an agent's
neighbors can dominate the computational expense of such
a simulation, particularly as the number of agents increases.
Different algorithms for neighbor-searching vary dramatically
in performance depending on the topology of the neighbor
interaction, the language used to program the search, and
the platform on which the calculation is run.1101 For example,
Mathematica, with its high-level list-processing functions and
cellular automata package, can run these simulations extremely
efficiently. There is a substantially steeper learning curve to
programming in Mathematica, however, due to the variety of
programming paradigms it supports, and since our students
already had acquaintance with MATLAB, we decided to imple-
ment an agent-based simulation project in MATLAB.
We developed an agent-based simulation project relevant to
chemical engineering based on the cellular automaton simula-
tions of Shea and Pasquinil111 of cells invading a polymer tissue
engineering scaffold representative of those implanted in a wound
or regenerating tissue. The scaffold, which serves to maintain a
space conducive to tissue formation, contains an interconnected
open-pore structure that can either be seeded with progenitor
cells or be infiltrated by such cells from the surrounding tissue.
The progenitor cells within the scaffold migrate, proliferate, and
differentiate to form a functional tissue that must eventually be
integrated with the host. Although tissue engineering is currently
a very active area of academic and industrial research, this was
our students' first encounter with the field.
The scaffold consists of impermeable polymer walls that
define a pore structure. These walls are modeled as evenly
spaced planes in the x, y, and z directions, which form cubic
cavities called macropores. There are randomly placed holes
called micropores in the macropore walls. Cells move between
macropores through these micropores. (Note that the terms
"macropore" and "micropore" as used in tissue engineering
do not correspond to the standard IUPAC definitions.)
Chemical Engineering Education

A lattice model is used to simulate the motion of cells in this
scaffold, with the lattice spacing being equal to the cell size.
Thus each lattice site can only be occupied by a single cell.
The macropore walls are several tens of lattice spacings apart
and a single lattice spacing in thickness, and the micropores in
our simulations are a single lattice spacing in size. Cells can
occupy vacant sites in this model pore network and migrate
or reproduce if space is available. Each cell must, however,
remain in some physical contact with the solid support of the
walls, either directly or through adhesion to other cells that are
in contact with the walls. This model is used to examine how
cells penetrate from the external surface of the scaffold to its
interior, ultimately filling the void space as they reproduce.

We used a simulation cell consisting of three macropores
in the x and y directions and five macropores in the z direc-
tion. The cells are initially placed at the bottom x-y plane,
with periodic boundary conditions being used in the x and
y directions. The z direction points inward into the scaffold,
with the cells initially filling the z = 0 plane and migrating in
the positive z direction. Several two-dimensional slices of this
three-dimensional lattice are shown together in Figure 2.
The mean square displacement for cellular migration is
given by
(d2)= nS2Pt (5)

where (d2) is the mean square displacement, n is the number

0 0

Figure 2. 2-D slices of a 3-D polymeric tissue-engineering scaffold. The scaffold is placed within some healing tissue and
serves to maintain a space conducive to the growth of new tissue from progenitor cells. The polymeric walls form macro-
pores that are connected by randomly placed micropores. The scaffold is shown divided into lattice sites. Empty lattice
sites in the scaffold are white, sites occupied by polymer walls are black, and sites occupied by cells are purple (gray).
The micropores can be seen as holes in the black macropore walls. In this simulation the progenitor cells are initially
present at the bottom of the scaffold (z = 0 plane) and migrate vertically into it, in the positive z-direction. A selection of
horizontal and vertical slices through the scaffold is shown.

Vol. 43, No. 2, Spring 2009










. ^ 30

of dimensions, S is the root mean square speed, and t is the
time. P is the persistence time, i.e., the time for which the
direction of the moving cell remains constant. Variations in P
have been shown to have little impact on system behavior. 121 P
was chosen to be the same as the simulation time step. Setting
the displacement, d, equal to the lattice spacing, 1, allows the
calculation of the time step from the above equation:

t ep =/3S (6)

At each time step, each cell moves to one of the adjacent
empty lattice sites. The choice of site is determined by com-
paring the probability of migration to each neighboring site
to a random number drawn from the uniform distribution
between 0 and 1. The probability of migration to a particular
site is dependent on the number of cell-cell and cell-wall
interactions that the cell will experience in that site and the
relative importance of these interactions. This probability is
normalized by the sum of migration probabilities to all the
sites neighboring the starting site at that time step:

P= AJ/ Ak (7)

Ak = nc * cp + nw

where P is the probability of moving from site i to site j, nc
is the number of neighboring sites occupied by cells, nw is
the number of neighboring sites occupied by polymer wall,
cp is the ratio of cell-cell cohesivity to cell-polymer adhesiv-
ity, and Z Ak is the sum of Ak over all sites that are nearest
neighbors to site i.
In addition to migrating, the cells can proliferate. Each cell
is initially set to proliferate at a time randomly drawn from a
normal distribution. At each time step, a counter indicating
the cell's time to proliferation is decreased until it becomes
negative, indicating that the cell should now divide. If space
is available in one of the adjacent lattice sites, the cell will
divide and the resulting new cell will occupy that site. The
counters for both cells are again set randomly from the normal
distribution of proliferation times.
The cells infiltrating the scaffold must maintain some physi-
cal connection to solid support, so no cluster of cells can be
completely disconnected from the wall. Moves that isolate a
cluster of cells from the walls must be disallowed. Therefore,
before a move is accepted, one must check that every cell
neighboring the one about to be moved has some connection
to the walls and that the cell in its new location will have some
connection to the walls. This is done by a depth-first search
(DFS) algorithmn131 adapted from that of Kevin Murphy, found
at . The DFS is
the most computationally expensive part of the program.
It is instructive to compare the lattice model formulation of

this "diffusion and reaction" problem with an attempt to cast
it as a system of differential equations. The physical condition
that no cell or cluster of cells can float unconnected to the
solid support of the walls is particularly difficult to describe
in the language of differential equations.
Since such a project involves a fair amount of coding effort,
we provided the MATLAB code to the students. We asked
them to run it for various values of macropore spacing, micro-
pore fraction, and cp and to examine how these factors affect
the time taken for cells to reach the top of the lattice and how
the concentration profile of cells in the pore space varies. At
low cp, the cells tend to penetrate into the lattice by crawling
up the walls and leaving the centers of the macropores rela-
tively empty. At higher values of cp, however, the increased
preference for other cells over polymer walls results in a fairly
uniform front of cells penetrating through the lattice. In this
latter case, the cell proliferation rate determines the progress
of the front, rather than the rate of migration along the walls.
All of this is only possible if the micropore fraction is high
enough to permit percolation from one end of the lattice to
the other. Above this critical value, the micropore fraction has
minimal impact on the rate of cellular invasion.
For a reasonably large system of a few hundred lattice sites
in each direction, the naive neighbor-searching algorithm
we implemented (in which all cells are examined as possible
neighbors) runs into recursion limits during the depth-first
search. We wanted the students to run simulations for several
different sets of parameters in a relatively short time, so we
initially disabled the depth-first search, decreasing the run
times to a minute or less even for large systems. Of course,
this also meant that groups of cells could detach from the
walls, unlike the work of Shea and Pasquini. Since we wanted
the students to examine how the code actually worked, we
refrained from explaining the physical meaning of cp, instead
requiring the students to infer its meaning from the way in
which it is used in the code. We also had the students modify
the code to make the function call to the depth-first search
routine and run simulations within a single small macropore,
which took a few minutes per simulation. Students were ad-
ditionally questioned about ways in which to make the full
simulation more efficient by using a better neighbor-search-
ing algorithm. Given sufficient time, the implementation of
a grid-cell based neighbor-searching algorithm could be a
useful programming exercise.
Thus, although the students were saved much of the grunt
work involved in writing the code, they had to become fairly
familiar with its workings to receive full credit. The code is
fairly well commented except for the deliberate omissions
regarding cp and the routine in which the depth-first search is
called. Most students were able to do this assignment without
much assistance after being provided with the above details on
the physical system and the overview of the code contained
in the README file.

Chemical Engineering Education

Despite the grumbling that ensues when students are prod-
ded out of their comfort zones, most of them were able to
complete these assignments without a great deal of difficulty.
In general, we noticed that the qualitative and open-ended
questions proved more taxing than actually solving the
differential equations or running the agent-based simula-
tions. Most of the students were interested in biological
applications but had not encountered many at this stage of
their education. This, coupled with the novelty of agent-
based modeling, added to interest in the tissue engineering
example. Though the students would have learned more
through coding the entire lattice model themselves, we feel
reasonably satisfied that they have been exposed to using and
modifying a relatively large piece of code, an accomplish-
ment in itself, in the short span of a couple of weeks. If one
wished to use this example in a course with more program-
ming, the project could be extended by having students
implement a more efficient neighbor-searching algorithm
or modify the code further to reproduce some of Shea and
Pasquini's other results,11l1 such as those for multiple cell
types invading the scaffold or for cells initially being seeded
throughout the scaffold.

This work was partially supported by the National Science
Foundation (CTS-0302428).

1. Craig, N.C., "Chemistry Report. MAA-CUPM Curriculum Foundations
Workshop in Biology and Chemistry," Macalester College, November
2-5, 2000," J. Chem.. Educ., 78, 582 (2000)
2. Carr, S.H., "Engineering First at Northwestern University," in Pro-
ceedings of the International Conference on Curricular ( t .. in
Engineering Education, (2001)
3. Ottino, J.M., "New Tools, New Outlooks, New Opportunities, "AIChE
J., 51, 1840 (2005)
4. Francl, M.M., "Crossing the Line: Stochastic Models in the Chemistry
Classroom," Ann. Rep. Comp. Chem., 1, 215 (2005)
5. Baldwin, R.M., J.E Ely, J.D. Way, and S.R. Daniel, "Incorporating
Molecular Modeling Into the ChE Curriculum," Chem. Eng. Educ.,
34, 162 (2000)
6. Middleman, S., An Introduction to Mass and Heat Transfer, John Wiley
and Sons, New York (1998)
7. Theodorou, D.N., R.Q. Snurr, and A.T. Bell, "Molecular Dynamics
and Diffusion in Microporous Materials," in G. Alberti and T. Bein,
Eds., Solid-state Supramolecular ( - .... ,, Two- and Three-Dimen-
sional Networks, Vol.7 of Comprehensive Supramolecular ( ....
Chapter 18, 507, Pergamon, Oxford (1996)
8. Sanborn, M.J., and R.Q. Snurr, "Predicting Membrane Flux of CH4
and CF4 Mixtures in Faujasite From Molecular Simulations," AIChE
J., 47, 2032 (2001)
9. v .1 I. I.. U., NetLogo Ants Model, Center for Connected Learning
and Computer-Based Modeling, Northwestern University (1998)
10. Knuth, D., The Art of Computer Programming Volume 3: Sorting and
Searching, Addison Wesley, Reading, MA (1998)
11. Shea, L.D., and B. Pasquini, unpublished results
12. Lee, Y., S. Kouvroukoglou, L.V. McIntire, and K. Zygourakis, "A
Cellular-Automaton Model for the Proliferation of Migrating Contact-
inhibited Cells," Biophysical J., 69, 1284 (1995)
13. Cormen, T.H., C.E. Leiserson, R.L. Rivest, and C. Stein, Introduction
to Algorithms, 2nd Ed., MIT Press and McGraw-Hill, Cambridge, MA
(2001) 1

Vol. 43, No. 2, Spring 2009

MR! t classroom
---- --- s_____________________________________



To Teach a Graduate Course on

Chemical Process Simulation

University of Calgary * Calgary, Alberta, Canada T2N IN4

or chemical engineering graduates, being able to use
a chemical process simulator is considered as a sine
qua non of the discipline, yet relatively few students
have a direct appreciation of what is involved in constructing
a chemical process simulator. The complex chemical process
simulators, such as ASPEN and HYSYS, that are almost
universally known to chemical engineers, have significantly
streamlined the task of chemical process design. Efficient
these simulators are, however, they also mask myriad complex
calculations. Thus one of the end results is that users of these
software packages may not have a full appreciation of how
elegantly and succinctly process simulators intertwine almost
all aspects of chemical engineering from thermodynamics to
equipment design to cost estimation.
An ancient Chinese proverb says, "Tell me and I'll forget;
show me and I may remember; involve me and I'll under-
stand," and it was with this mind-set that Professor P.R.
Bishnoi (one of the founders of Hyprotech) developed, in the
mid-1980s, a post-graduate course in process simulation in
which students would enhance their understanding of process
simulation by constructing all, or part, of a chemical process
simulator. In the initial years of its existence, individual
students constructed relatively simple simulators, using FOR-
TRAN 77, to solve a specific problem rather than to serve as
a general process simulator. In the 1990s, there was a shift
from FORTRAN 77, a procedure-oriented language, to C and
then finally to C++, which is an object-oriented language. The
use of an object-oriented language allowed for the creation

of re-usable blocks of code that could be connected in a near
infinite number of configurations, thereby greatly extend-
ing the generality of the students' simulator. As the scope
of the term project became more complex over the years, it
necessitated a migration from individual term projects to a
format in which all of the class member would contribute to
a single final project. To the best of the author's knowledge,
this course is unique and is not offered, in this format, at any
other institution.
Following Professor Bishnoi's retirement, this course
took an extended hiatus from the list of courses available to
graduate students in Chemical and Petroleum Engineering at

Matthew Clarke is an assistant professor
of Chemical and Petroleum Engineering at
the University of Calgary. He has a Ph.D.
in chemical engineering from the University
of Calgary. His research interests are in
hydrates and biofuels.

Carlos Giraldo i
is pursuing his
Ph.D. in chemi-
cal engineering
at the University
of Calgary. He graduated from the Na-
tional University of Colombia in 2001 with
a degree in chemical engineering. Subse-
quently, he worked as a process engineer
in Bogota, Colombia.

� Copyright ChE Division of ASEE 2009
Chemical Engineering Education

the University of Calgary. At the time of its resurrection, in
2007, much had changed in the world of chemical engineer-
ing education and computing, particularly with respect to
students' familiarity with structured programming languages.
Thus, the decision was made to do the project with a more
familiar platform: that of MS Excel with VBA. While it is not
possible to construct a stand-alone simulator using Microsoft
Excel, it was an attractive choice because it provides a conve-
nient platform for entering and displaying data and because
it is almost universally known to post-graduate students in
chemical engineering. The use of spreadsheets for various
chemical engineering calculations is not new and has been
documented in many sources.1-5] What makes this course
unique is that Excel is being used to create an "all-purpose"
simulator, with a built-in graphical user interface (GUI), for
solving simultaneous heat and energy balances.
Additionally, unlike traditional graduate courses in chemi-
cal engineering, this course is distinctive in that it is a group
effort, rather than a solo pursuit. Because of the sheer size of
the project, it is not feasible to expect each student to construct
his or her own simulator in a one-semester course. Thus, each
student is given a task and, toward the end of the semester, the
pieces are fit together to produce a working simulator.
Because of the unique nature of this course, this paper is
being written to evaluate the delivery format of the course
and the effectiveness of teaching chemical process simulation
in a "hands-on" format.

The idea of learning by doing is not a new one; the great
Italian renaissance polymath Leonardo Da Vinci once said
"Knowing is not enough; we must apply. Being willing is
not enough. We must do." The objective of this course is to
give to the students hands-on experience at developing a gen-
eral-purpose, steady-state, chemical process simulator and to
understand the various types of computations involved in such
a simulator. In this respect, it's as much a course in software
design as it is a course in chemical engineering.
In the university's calendar, the course was allocated three
hours per week for lectures, of which half was used for lectur-
ing and presenting new material and the other half was used
for a weekly seminar in which students would individually
discuss their previous week's progress and their goals for the
following week. This seminar was particularly important since
two of the students were employed full time. The material
covered in the lectures was, for the most part, not entirely
new to the students and consisted of a review of basic heat
and energy balances and unit operations, selected topics from
numerical methods and computational thermodynamics, and
sequencing. Sequencing, which will be discussed in more de-
tail later, was the only section that was completely new to the
students. At several points throughout the semester, an invited
speaker who worked in the chemical process simulation field
Vol. 43, No. 2, Spring 2009

gave lectures on object-oriented programming fundamentals
and on how to put all of the components together to form the
final product.
Because the course was primarily a group effort, evaluation
of the students' progress was not a trivial task. As alluded to
earlier, each student was given a specific task to work on and
then at the end of the semester, the pieces were assembled into
their final magnum opus. Thus, for roughly the first two-thirds
of the semester, each student worked independent of the others
and it was felt that the appropriate method for midterm evalua-
tion was a combination of a written report and an oral exam for
each student. These components were each worth 15% of the
final grade. In the latter portion of the semester, the students
were collaborating much more closely than in the early part
of the semester and thus the term-end evaluation consisted
of a final oral presentation and exam for each student, worth
25% of their grade, plus a single final report submitted by all
group members, worth 45% of the final grade.

The aforementioned course was first offered to graduate stu-
dents more than 20 years ago. Due to the original instructor's
retirement, however, the course had not been offered in almost
five years. Thus, students were not able to learn about the
course by word of mouth and the only information available
to the students regarding the course came from the university's
catalog description, which, at the time read
"Chemical Process Simulation: Synthesis. Analysis and
screening of process alternatives. Steady state simulation.
Material and energy balances for systems of process units.
Modular approach. Heat exchanger network and separation
When this course description was first conceived, two
decades ago, it quite adequately conveyed what the course
was about. Most of the 12 students that arrived to class on
the first day of the semester were expecting something com-
pletely different, however. When I asked the students what
they were hoping to achieve in taking this course, responses
ranged from "HYSYS training" to "I need an easy course for
my professional registration." When I handed out the course
outline to the students, a great silence fell across the room
and faces paled at the revelation that this was not a software
training course, that this would not be an easy course, and
that they would have to do the programming themselves. The
end result was that the class size dropped from 12 to four by
the second lecture. (It should be noted that, because of the
necessary division of labor, four students is the minimum
number necessary to run the course.)
After re-examining the calendar description quoted
above, I felt it could be written to better elucidate the
course content. For the upcoming year, the calendar entry
has been changed to make it explicitly clear that it is an

object-oriented programming course. It now reads:
"Chemical Process Simulation: Object-oriented program-
ming applied to the design of a steady state chemical pro-
cess simulator via the sequential modular approach and by
the equation-based approach. Material and energy balances
for systems of process units."

It was felt the above wording would not only inform stu-
dents that it is not a software training course, but it would also
inform other students that it is a programming course.

The students enrolled in the course had a diverse academic
background and each brought certain strengths to the project.
As previously mentioned the lecture content included topics
from basic chemical engineering, numerical methods, thermo-
dynamics, and sequencing. Thankfully, all students were well
versed in the basics of chemical engineering and numerical
methods and thus it was not necessary to devote significant
lecture time to these topics.
Computational thermodynamics, on the other hand, was a
subject with which the students had little direct experience.
Thus, this section included a review of vapor/liquid equilib-
rium, equations of state, activity coefficient models, bubble
point and dew point calculations for nonideal systems, iso-
thermal/isobaric flash calculations, isoenthalpic/isobaric flash
calculations, isentropic/isobaric flash calculations, and Gibbs
free energy minimisation for reacting systems.
Sequencing, as mentioned previously, was the lone topic
that was completely new to the students and the lectures were
devoted to presenting various algorithms for determining in
which order the unit operations should be solved.
The biggest deficiency in the students' knowledge base,
however, was not in any of the chemical engineering topics; it
was in object-oriented programming. Maixner[61 observed that
after taking basic engineering computing, students "usually
allow their programming skills to stagnate." While some of the
students were out of practice with respect to programming, it
was found that for 100% of the students, their knowledge was
limited to procedure-oriented programming. The advantage
of an object-oriented approach is the ability to solve and test
individual modules together and the ease with which modules
can be combined, solved, analyzed, and swapped.�71
After the semester, the three remaining students were asked,
among other things, what skills they had to learn and their
responses are listed below:
* "Thermodynamics, unit operations, programming, logi-
cal .,,,i ,,11,. teamwork."
* "During the course, we learned some concepts of OOP,
thermodynamics, simulation solver other than extensive
use of computer programming."
* "Teamwork."

The construction of a steady state, sequential, modular
simulator is a daunting task when first approached by students
and it's not feasible for individual students to construct their
own simulator in a one-semester course. Thus, the project was
done as a group project in which each student was assigned
a part of the object-oriented simulator to construct. Initially,
one student was assigned to create a GUI and component da-
tabase, one student was assigned to create the thermodynamic
routines, one person was responsible for the unit operations,
and the remaining member was responsible for sequencing.
Midway through the semester, the student in charge of the
thermodynamics routines withdrew from the class and these
duties were subsequently divided among the remaining group
members. Fortunately, one of the remaining students had
previous exposure to computational thermodynamics.
The program is composed of a GUI, information sheets,
thermodynamic routines, unit operations routines, and the
sorting/tearing algorithm-all of which interact with each
other, as shown in Figure 1. In the ensuing subsections, a brief
description of each section of the program is provided.
Information Sheets
The information sheets, which are merely Excel worksheets,
provide a platform for entering and displaying data and for
storing thermodynamic component data. Data is read from
and written to the appropriate worksheet using the built-in
cells() function.
GUI and Component Database
The graphical user interface was constructed in Excel using
the built-in VBA editor. Once the equation of state and the
components for the new project have been selected, the pro-
gram closes all dialogs and takes the user to the main interface
window, where the Process How Diagram is built.
On this page, the program shows the core of the graphical
user interface: the "Unit Operations" tool bar. This tool bar
is divided in five main sections: adding new unit operations,





Figure 1. Block diagram for the simulator.

Chemical Engineering Education

i: 811 i. & ire Fgw Ia oo I Wna Wse

S. -9.

B C 0D I FI G | H
rF ... . �, r ,


li De gEt 1ew . insertt Forllt loos D ,ndow tj - . l x
D El 9 a a[ a * - -N -DL V >> -A G kko aD a 9 I off
-na -E9 10 A / I z $ C % , z*of (E iE _tw i f �P r" P, 0 1 t' All A ?i.



- .- i . i .

19 CH4

28 |liquid phase

Jl -

055 068049 0 103538
004 0040441 003849
04 .*

0685985 068049 0

0 102117 0 0 103538

S Anter / proct / unop \ streams /
aw- 4 Autos9ew- \ \DOB140flE &.-^A.- �!UW.

0 55 0 68049
004 0040441

0 0 68049

M N 0 P Q R

Vol. 43, No. 2, Spring 2009

Chat Nea

valve 1

N 4 I N ~chease~.xcpJ Sfrens Jprkiter LPvor I ReaAcx/~aI

Figure 2.
capture of a
typical flow

Figure 3.
Screen cap-
ture of the

Wit op,.,ti,., , X
7-d. ". P�.. C_�_... C�P.A, V�I, P�, �� S*" R�Sj

V1iisf xe rcinAp 3fn D C' x

I,,,,,,,,,, : i ..... i ,,,,,,,,,

adding a material stream, editing a material stream, deleting
a unit operation, and running the simulation.
Thermodynamic calculations represent the basis of the sim-
ulator, since all the unit operations are assumed to reach the
equilibrium. To develop the current simulator, two equations
of state have been selected: the Soave-Redlich-Kwong (SRK)
equation of stateE81 and the Peng Robinson (PR) equation of
state.[9] As part of the process simulator, we are generating the
value of thermodynamic properties (enthalpy and entropy),
thus, the designation of a reference state becomes essential.
For this simulator, the reference state that was chosen was an
ideal gas at 273.15 K and 1 Pa.
The thermodynamic routines provide a necessary support
for the unit operations in that they calculate necessary outlet
conditions such as temperature, pressure, and/or composition.
Depending upon the specific unit operation, these values are
calculated with the aid of a constant-temperature/constant-pres-
sure flash routine, a constant-enthalpy/constant-pressure flash
or a constant-entropy/ constant-pressure flash. The values of
the thermodynamics quantities, such as entropy and enthalpy,
are calculated by using the appropriate departure functioni101
in conjunction with an equation of state. In addition, a Gibbs
free energy minimisation routine was implemented to support
the reactor unit operation. The algorithms for each of these
routines are available in the open literature.110 121
Unit Operations
To code the unit operations, an object-oriented programming
philosophy was adopted. For this section it is important to
introduce some related terminology, mainly the object, class,
properties, and method. An object is defined as a program-
mable entity with specific characteristics and feautures,131 a
class is what defines the object and serves as the template or
blueprint for all the objects created from that class; any of
the object's particular features, including properties, methods,
and events, are handled by the class module.J131 Properties
are all the characteristics and features of the object without
executing any action, and method is an entity that provides
the actions supported by the objects created from the class.I131
Methods are defined as the abilities, or actions, that the object
can carry out.[131
Basically, a module class was created for every single unit
operation; this class contains the most important properties
and methods. In addition, modules were included to collect
the inputs from the interface, which become the properties of
the class and present the results again on the interface. Unit
operations that were included in the project were separators,
valves, pumps, compressors, expanders, heaters, coolers,
heat exchangers, mixers, splitters, recycle loops, and a
Gibbs free energy minimization reactor. The details of the
individual unit operations are available in any standard
chemical engineering textbook.[141

Sequencing is a term that essentially refers to the process
of figuring out the order in which each of the unit operations
should be solved. The sequential modular approach is the
most popular approach and there are a number of commercial
simulators that use this solution methodology. "Sequential
modular" simply means that calculations start with known
feeds, and continue on a unit-by-unit basis until all unit op-
erations in the flowsheet are calculated.["51
In sequential modular approach, the material balances for
an entire process are solved one module (process block) at a
time. For sequential modular material balance calculations,
the output streams can be calculated if the input streams and
the module parameters are known.

A case study was initiated to study how the new Process
Simulator compares with the popular commercial simulator,
Aspen HYSYS. The simple case illustrated the capability of
the new Process Simulator for performing reliable chemical
process calculations for the Linde Process. Methane is usually
liquefied in a Linde process. Initially, the vapor is compressed
to 6MPa and cooled at 300K. Subsenquently the vapor passes
through a heat exchanger before reducing its pressure (to
0.1MPa) through a valve. The unliquefied fraction leaves
the separator at the saturation point and passes through the
heat exchanger exiting at the end at 295K. A screen capture
of the flow diagram and the constructed worksheet for the
process used in the case study is presented in Figures 2 and
3 (previous page).
The components that were present in the case study were
methane, ethane, propane, n-butane, and carbon dioxide. T he
fluid properties were calculated with the PR equation of state.
It was found that all of the stream compositions, temperatures,
and pressures as calculated by the new simulator were within
1.5% of the values calculated by the commercial simulator.

As previously mentioned, at the conclusion of the course,
the students were asked for their feedback. In addition, one
student (who is the second author on this paper) provided a
detailed evaluation of the course. The following paragraphs
are his evaluation of the course:
"The construction of a steady state, sequential modular
simulator represented an immense challenge for all the
members of the group since none of us had done ,a i,,,, ,
similar in previous courses. The experience acquired until
that moment with programming languages was limited to
very "simple" oi,. ., i i... dedicated for particular cases.
Thus, when the distribution of the work was assigned by the
professor, a sensation of confusion came up in the group
because nobody was really sure about how to tackle the

Chemical Engineering Education

problem. Since the beginning of the semester, this course
was different from the ones a regular graduate student usu-
ally takes, where the professors impart lots of information
in the lectures. In this case, the classes were divided in two
sessions per week; one of them was a lecture reviewing the
basic tools that we required to complete this course suc-
cessfully and the second one was a group m.-it,,, to show
everyone's progress, difficulties, and critical points, etc.
During the first few weeks, the work was done independent-
ly; each of the members of the group wrote his or her own
code without considering anybody else's problems or dif-
ficulties. In,, ,., .i. *. of the code was not the main concern
in that particular moment. But, fortunately, the professor
invited as guest lecturer a former student who had taken
the course a few years ago; he basically commented about
his experience in ,. 1,11, a process simulator. His main
contributions to us were definitely the concept of working as
a group and the fact that it is necessary to completely define
the structure of the simulator on a piece of paper before
any coding is done; in addition, he highlighted that the
final product should be written with the mind-set that it is
going to be used by an external user. From that moment on,
teamwork began and it was established how the simulator
was going to work and what kind of special characteristics
should be included. For instance, definition of the variables
that would be supplied by the user, the variables that would
be public (available for all the program) or private and
the possible inconsistencies due to errors when wrong data
were supplied by the users, final outputs, etc.
Once the designing stage was finally done, all of the mem-
bers of the group had to recode a big part of our programs
to make them suitable for the final .,, , , iiI. - After hav-
ing succeeded on this, the skeleton of the whole simulator
was ready. The following phase was to complete the rest of
the thermodynamic oi,. -, i .... and unit operations, which
was a lot easier due to main parts being already done.
The first simulator was really big and it was really difficult
to handle, thus, some parts of the program were recorded
once again to make them better. In this part of the work
a very helpful support was provided from one student at
U of C whose knowledge in Visual Basic for Applications
was far beyond any of the other members of the group.
His main contributions were the implementation of useful
techniques and hints to reduce the number of lines in the
program and increase the speed of processing. One of the
most challenging parts was the debugging of the code;
from our point of view the best way to debug any long
program is by ensuring that every piece of code is working
properly rather than to verify the whole program. It is also
important to keep in mind that a minimum knowledge is
required of programming, creation of oi,., -*d- . numeri-
cal methods focused on the solution of single and simulta-
neous systems of non-linear algebraic equations, .* t,,.
matrixes, etc. But the most important .hi-*, is to always
be motivated and be open to learning new concepts. At
the end of the term, the group was really satisfied with the
final product; since we were able to reproduce the results
of commercial simulators by using simple programs."

Additional comments by the other students are given
Which parts were the most challenging?
* .i /.. ,,,, the best way to represent the unit operations and
connect the graphical part to the database in Excel. "
* "The most challenging part was debugging. The oi,.., i i....
initially written was not the best one. The program went
very big and was just too big to handle."

Problems to comment on for future students?
* "Teamwork is a key component in this course.

Which skills you got to the end of the course?
* "Computer programming skills, basic structure of simula-
tor, simulation solver knowledge. Above all we learned
how to put .. .,, i, , a simulator."

The structure and content of the course make it unique
among graduate courses in chemical engineering at the Uni-
versity of Calgary and thus it presented many challenges to
the instructor. As previously mentioned, this was the first time
in almost five years that the course had been offered, and in
spite of that fact, the overall sentiment of the instructor was
that the course achieved its desired outcomes.
Over the course of the semester, there were only two nega-
tive events to dampen evaluation of the course. The first was
that, as previously stated, a large number of students enrolled
believing the course would be a software-training course. It is
also hypothesized that some students-who may have been
keen programmers-avoided the class for the same reason.
Secondly, the number of students was below the optimal
number for the course. When one of the students withdrew
from the course, a tremendous burden was placed upon the
remaining students.
Conversely, many aspects of the course were extremely
positive. The total project was divided into manageable parts
and, at the end of the semester, each student was able to say
that they had not only learned how to program a part of the
simulator, but they also benefitted from having to work in a
team environment. The regular weekly debriefings not only
allowed the students to receive weekly feedback from the
instructor, but they also served to educate each group member
as to what challenges the other members were facing with their
programming. Additionally, the use of Excel as the program-
ming platform was advantageous. While Excel may not have
all of the capabilities of high-level programming language,
such as the ability to create a stand-alone executable file, the
fact that students had previous exposure to it and the fact that
student access to Excel is practically universal made it the
best choice for the course.

Vol. 43, No. 2, Spring 2009

For any instructor that is contemplating offering a graduate
course in simulation, I would make the following recom-
1. Ensure that the calendar description clearly conveys
that it is a course in software design and not merely a
software-training course.
2. Advertise a detailed synopsis of the course well in ad-
vance of the beginning of the term.
3. Stipulate a minimum of six students. This ensures that if
one or two students withdraw partway .1,,. .,,, the term,
the remaining students are not overly burdened.
4. To attract and retain a larger number of students, include
minimal hands-on work with a commercial simulator,
perhaps as a means of. /Ih / .u111, lecture topics.
5. Spend the majority of lecture time covering object-orient-
ed programming fundamentals, computational thermody-
namics, and sequencing.

A post-graduate course on chemical process simulation
was offered in the Department of Chemical and Petroleum
Engineering at the University of Calgary in which students
were given the opportunity to construct a chemical process
simulator as a group project. Microsoft Excel, along with its
built-in Visual Basic for Applications (VBA) programming
environment, was used to create a fully functioning modular
chemical process simulator. An object-oriented approach
was used to create and combine the necessary sections of the
simulator; mainly the graphical user interface and component
database, the thermodynamic routines, the unit operations, and
the sequencing algorithms. The result is a fully functioning,
steady state, chemical process simulator that is capable of
matching the results of the far more expensive commercial
simulator, as was seen with the validation study. Student feed-
back on the course indicated that the students learned a great
deal with respect to both software design and to working in
a team environment. From the instructor's point of view, the

course was successful in achieving its goals and recommenda-
tions for future offerings of the course were made.

The authors would like to acknowledge Dr. Ryan Krenz
from the Virtual Materials Group in Calgary, Alberta, for
sharing his experiences in creating object oriented process
simulation tools.

1. Clarke, M.A., and ER. Bishnoi, "Development of an Implicit Least
Squares Optimization Scheme for the Determination of Kihara Poten-
tial Parameters Using Gas Hydrate Equilibrium Data," Fluid Phase
Equilibria, 211, 51 (2003)
2. Lwin, Y., "Chemical Equilibrium by Gibbs Energy Minimization on
Spreadsheets," International J. ofEng. Educ., 16, 335 (2000)
3. Savage, PE., "Spreadsheets for Thermodynamics Instruction," Chem.
Eng. Educ., 29(4), 262 (1995)
4. Ravella, A., "Use a Spreadsheet for Preliminary Reactor Design,"
Chem. Eng. Progress, 89, 68 (1993)
5. Bornt, B., "Spreadsheets for Heat Loss Rates and Temperatures," Chem.
Eng., 102, 107 (1995)
6. Maixner, M.R., "Design of a Waterjet-Propelled Barge: A First
Computer Modeling Project," International J. of Eng. Educ., 21, 745
7. Chen, J., and R.A. Adomaitis, "An Object-Oriented Framework for
Modular Chemical Process Simulation With Semiconductor Processing
Applications," Comp. Chem. Eng., 30, 1354 (2006)
8. Soave, G., "Equilibrium Constants from a Modified Redlich-Kwong
Equation of State," Chem. Eng. Sci., 27, 1197 (1972)
9. Peng, D., and D. Robinson, "A New Two-Constant Equation of State,"
Ind. Eng. Chem. Fund., 15, 59 (1976)
10. Elliot, R., and C. Lira, Introductory Chemical Engineering Thermo-
dynamics, Prentice Hall, Upper Saddle River, NJ (1999)
11. Walas, S., Phase Equilibria in Chemical Engineering, Butterworth-
Heinemann, Newton, MA (1985)
12. Tester, J.W., and M. Modell, Thermodynamics and its Applications,
3rd Ed., Prentice Hall, Upper Saddle River, NJ (1997)
13. Harrison, B.K., "Computational Inefficiencies in Sequential Modular
Flowsheeting," Comp. Chem. Eng., 7, 637 (1992)
14. Biegler, L.T., I.E. Grossman, andA.W. Westerberg, Systematic Methods of
Chemical Process Design, Prentice Hall, Upper Saddle River, NJ (1997)
15. Norman, R.L., "A Matrix Method for Location of Cycles of a Directed
Graph," AIChE J., 8, 450 (1965) 1

Chemical Engineering Education

BN editorial
----- --- s___________________________________________


Imperial College London * London, SW7 2AZ, U.K.
A re the steam tables dead?
I have recently had two strong hints that appeared
to indicate that what we know as the "steam tables"
(tabulations of volumetric and energetic properties of satu-
rated and superheated water) have slowly but surely died. In
the first place I managed to buy, through a used book dealer,
a very nice copy of the Keenan steam tables. This is a 1930
edition that included in an inside flap a beautiful Mollier
diagram as large as my own desk. The book is in pristine
condition, properly printed and beautifully hardbound, and
all-for the staggering price of 50 cents. This is not only a
collector's item, but also a very useful tool still. Extensive
tables with a very fine grid of temperatures and pressures
allow precise calculation of the thermodynamic properties
of water. Looking up, for example, at 520 �F and 39 psi, this
table reports a specific volume of 14.838 ft3/lb. Considering
that the density of water has not changed with time, the result
is still of acceptable accuracy for most purposes (a reliableMll
value today would be 14.845 ft3/lb-a difference of less than
0.05%). The other parallel event that sparked my imagina-
tion was that I managed to download to my PDA a steam
table program 21 (which also gave me the expected 14.84424
ft3/lb answer for the state point in question). So, why have
my steam tables not gone the same way as logarithm tables,
which disappeared sometime after I left high school?T31 For
some reason thermodynamic tables have endured the passage
of time, and most major modem thermodynamic textbooks
have abridged versions as appendices. You can buy many
versions of these "smaller" classroom tables[41 (so they must
be used extensively by someone). Furthermore, you can buy
a "new" edition5s] of my recently acquired Keenan tables. In
fact, they are obviously not things of the past, if one notices
that this year a new version of the International Steam Tables
was published.A61
A rapid (non-exhaustive) searchW71 showed me that steam
tables are also available as spreadsheet plug-ins,[81 as commer-
cial[9] and academico101 stand-alone programs for PCs, and as
phone[11] applications, just to mention a few. Special mention
has to be made to the NIST Webbook.J11 This is an outstanding
resource that allows the precise and efficient determination of

thermophysical properties of a rather significant amount of
fluids with all the usual features one would typically require:
choice of units, choice of conditions, display of an array of
volumetric, energetic, and derivative properties, generation
of tables and graphs that can be "cut and pasted" to other
places, etc. Three things make it stand out among all other
options, however
a) It is accessible .1- ..., /, the Internet via a Web page, so
it is not device-specific. All calculations are done on the
remote machine, so it is also fast.
b) It is free, with no needless j ., , .r. -procedure or
cost to the user. A very generous and highly appreciated
c) It is state-of-the art and in constant update in terms of
the equations of state used to generate the data. All
this means that any computer connected to the Web
can automatically be converted into a "steam e-table,"
therefore the utility of the site cannot be underestimated.
So, is there any point in continuing the discussion? A com-
mon argument in favor of insisting on the use of "paper"
tables is that learning to use them will teach students about the
different regions of the phase diagram (since the boundaries
where the tables end usually coincide with the boundaries of
the change of behavior: saturation, ideal gas, etc.). It is hard
to think that this is not a biased opinion, for the programs
have limits also. I started to look at other data points using
my palm-held program, for example raising the pressure at
the given temperature. For 2500 psi (@520 F) it refused to
give me an answer. Granted, the table did not have an answer
either. It would take some basic knowledge on thermophysical
properties to recognize that by increasing the pressure above
the saturation line the system would be in the liquid state, and

About the Author: Erich A. Matter is a Reader in Thermodynamics at the
Department of Chemical Engineering at Imperial College London with 20
years of experience teaching university-level thermodynamics. His re-
search interests lie in the application of molecular simulation to determine
thermophysical properties of complex fluids. He is the author of more than
50 papers and an undergraduate textbook on thermodynamics.

C Copyright ChE Division of ASEE 2009

Vol. 43, No. 2, Spring 2009

if no other information were available, the low compressibility
of the liquid phase would allow one to use the specific volume
at saturation (0.37693 ft3/lb) as a likely estimate.[12] Another
repeated argument is that given a computational tool -be it a
process simulator or simply a spreadsheet add-in-a lecturer
can focus on more elaborate problems which may involve,
for example, taking the thermodynamics into its context for
typical engineering applications.
Does this then back the hypothesis that we should shelve
our tables forever? Please think again. A problem with using
computer programs (or Web pages, or phones), apart from the
fact that they are useless when no electricity is present, is that
one can easily fall prey of the "black box syndrome," a condi-
tion in which the brain ceases to perform its usual analytical
functions while the user simply inputs numbers and accepts
the response from his or her electronic instrument without
questioning. Prausnitz[131 warned us of this many years ago
when he stated, in the onset of the computer age, N .l% i be
impressed by calculated results merely because they come
out of a computer. The virtue of a computer is speed, not
intelligence." I think, however, that the student who recently
reported reading from a table the density of liquid water at
STP to be "roughly 1, umm, kg/m3" wasn't actually thinking
much anyway.
Although it is not the subject matter of these lines, com-
puters offer (at least in theory) the ability to visualize 3-D
thermodynamic surfaces (for example the P-v-T surface)
interactively. This is particularly useful when studying phase
equilibria of mixtures, where the usual graphs are slices of
a more elaborate and complex surface. Prof. K. Jolls (Iowa
State) has made a lifetime effort of providing thermodynamics
students with such interactive and pictorial representations.[141
In spite of the fact that there is no doubt about the enormous
pedagogical value of these and similar representations, it is
clear that they are still emerging technologies, and e-tables
still dominate the field.
An important argument is that while for water the thermo-
physical properties are well known and documented, they
are not so for many other simple fluids, let alone the more
complex or exotic ones. Therefore, even today, the chemical
engineer will have to deal with sometimes just a few sparse
data or an odd table, from which he or she must interpolate,

correlate, and sometimes even estimate data. This is a daily
task for any practicing engineer, and it is up to the thermo-
dynamics lecturer to train students for this awful reality.
Perhaps the best course of action is to do both: teach the use
of the programs and resources while simultaneously showing
students the "facts of engineering life"-one of them being
that you will never have as much information as one would
desire for a given system. Probably we still have to teach them
some "old school" methods. So with this in mind, I sent my
dutiful students out to buy their abridged steam tables sold
in the bookstore, wondering if next year the answer to the
question will be different.

1. Taken from the NIST Webbook, fluid/>
2. I downloaded version 2.2.0 of "Steam Properties" from Process Ace
Software, (). There is a free
15-day demo and a full version is retailed at US$14.99.
3. Quite some time ago, I fear.
4. For example: Engineering Steam Tables, by A. Malhotra, Lulu.com
(2006); Physical Property Data Book for Engineers and Scientists, D.
C. Shallcross, IChemE (2004); Thermodynamic and Transport Proper-
ties of Fluids, 5th Ed., by G. E C. Rogers and Y.R. Mayhew, Blackwell
(1994); Thermodynamic Tables in SI (Metric) Units, 3rd Ed., R.W.
Haywood, Cambridge University Press (1990)
5. It is actually a 1992 reprint of the 1978 edition of Steam Tables by J.H.
Keenan, EG. Keyes, PG. Hill, and J.G. Moore, Kreiger Publishing
Company (1978)
6. Wagner, W, U. Overhoff, and H.-J. Kretzschmar, International Steam
Tables for Industrial Use, 2nd Ed., Springer (2006)
7. I would like to stress the point that my search is very incomplete,
and that I am just placing some examples to make a point. There is
an incredible amount of steam table resources available varying from
small-scale amateur ideas to some very commercial ones, with all
degrees of professionalism in between.
8. See for example SteamTab v3.0 from Chemicalogic ( chemicalogic.com/steamtab/>)
9. Wagner, W., U. Overhoff, and H.-J. Kretzschmar, Extended Iapws-If97
Steam Tables (v2.0), Springer (2006)
10. For example the CATT program bundled with Fundamentals of Ther-
modynamics, 6th Ed., by R.E. Sonntag, C. Borgnakke, and G.J. Van
Wylen, Wiley (2006)
11. Steam Table for Smariphone 2003 vl.0 by TA Cybernetic Solutions
12. It compares well with the reported (NIST) volume of 0.36927 ft3/lb
13. In Reid, R.C., J.M. Prausnitz, and T.K. Sherwood, The Properties of
Gases and Liquids, 3rd Ed., McGraw Hill (1977)
14. See an example at [

Chemical Engineering Education

on the

University of Florida Home Page
© 2004 - 2011 University of Florida George A. Smathers Libraries.
All rights reserved.

Acceptable Use, Copyright, and Disclaimer Statement
Powered by SobekCM