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

Subjects

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

Notes

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

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

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Chemical Engineering Documents

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chemical engineering education

VOLUME 37 NUMBER 4 FALL 2003

Award Lectures
BSL Lecture ConocoPhilips Lecture
The Equations (of Change) Don't Change: Future Directions in ChE Education:
But the Profession of Engineering Does A New Path to Glory
to (p. 242) Ip. 284)
W. R. Schowahter Arvind airma

and...
Random Thoughts: Learning by Doing (p. 282)
Felder, Brent
.Exceptions to the Le Chatelier Principle (P. 290)
Corti, Franses
Learning in Industr): Returning as a Professor (p. 310)
Blau. Wankat
A Fluid-Mixing Laboratory for ChE Undergraduates (p. 296)
Ascanzo, Legros, Tanguy
Mixing Writing with First-Year Engineering: An Unstable Solution? (p. 248)
Lebduska, DiBiasio
Factors Influencing the Selection of Chemical Engineering as a Career (p. 268)
Shallcross
Particle Technology Demonstrations for the Classroom and Laboratory I p. 274)
Iveson, Franks
', Development and Implementation of an Educational Simulator: GLUCOSIM (p. 300)
Erzen, Birol, (inar
Sensitivity Analysis in ChE Education: Part 2. Application to Implicit Models (p. 254)
Smith, Missen
A Batch Fermentation Experiment for L-lysine Production in the Senior Laboratory (p. 262)
Shonnard, Fisher, Caspary
Simulation and Experiment in an Introductory Process Control Laboratory Experience (306)
MAuske
Using Spreadsheets and Visual Basic Applications as Teaching Aids for a Unit Operations Course (p. 316)

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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

EDITOR
Tim Anderson

ASSOCIATE EDITOR
Phillip C. Wankat

MANAGING EDITOR
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PROBLEM EDITOR
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LEARNING IN INDUSTRY EDITOR
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PUBLICATIONS BOARD -

CHAIRMAN *
E. Dendy Sloan, Jr.

MEMBERS *
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Princeton University
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North Carolina State University
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University of Washington
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University of Michigan
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North Carolina State University
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University of Delaware
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Iowa State University
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Rowan University
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Chemical Engineering Education

Volume 37

Number 4

Fall 2003

> LECTURES
242 The Equations (of Change) Don't Change: But the Profession of
Engineering Does,
W. R. Schowalter
284 Future Directions in ChE Education: A New Path to Glory,
Arvind Varma

> CURRICULUM
248 Mixing Writing with First-Year Engineering: An Unstable Solution?
Lisa Lebduska, David DiBiasio

> CLASSROOM
254 Sensitivity Analysis in ChE Education: Part 2. Application to Implicit
Models,
William R. Smith, Ronald W Missen
274 Particle Technology Demonstrations for the Classroom and Laboratory,
Simon M. Iveson, George V Franks
290 Exceptions to the Le Chatelier Principle,
David S. Corti, Elias I. Franses
300 Development and Implementation of an Educational Simulator:
GLUCOSIM,
Fetanet Ceylan Erzen, Gillnur Birol, Ali tinar
316 Using Spreadsheets and Visual Basic Applications as Teaching Aids for a
Unit Operations Course,

> LABORATORY
262 A Batch Fermentation Experiment for L-lysine Production in the Senior
Laboratory,
David R. Shonnard, Edward R. Fisher David W Caspary
296 A Fluid-Mixing Laboratory for ChE Undergraduates,
Gabriel Ascanio, Robert Legros, Philippe A. Tanguy
306 Simulation and Experiment in an Introductory Process Control Labora-
tory Experience,
Kenneth R. Muske

> SURVEY
268 Factors Influencing the Selection of Chemical Engineering as a Career,
David C. Shallcross

> RANDOM THOUGHTS
282 Learning by Doing,
Richard M. Felder, Rebecca Brent

> LEARNING IN INDUSTRY
310 Returning as a Professor,
Gary Blau, Phillip Wankat

CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engineering
Division, American Society for Engineering Education, and is edited at the University of Florida. Correspondence
regarding editorial matter, circulation, and changes of address should be sent to CEE, Chemical Engineering Department,
University of Florida, Gainesville, FL 32611-6005. Copyright 2003 by the Chemical Engineering Division, American
Society for Engineering Education. The statements and opinions expressed in this periodical are those of the writers and not
necessarily those of the ChE Division, ASEE, which body assumes no responsibility for them. Defective copies replaced if
notified within 120 days of publication. Write for information on subscription costs and for back copy costs and availability.
POSTMASTER: Send address changes to Chemical Engineering Education, Chemical Engineering Department., University
of Florida, Gainesville, FL 32611-6005. Periodicals Postage Paid at Gainesville, Florida and additional post offices.

Fall 2003

R1 lecture

The following is the first BSL Lecture, given at the
University of Wisconsin on October 2, 2001.

THE EQUATIONS (OF CHANGE)

DON'T CHANGE

But the Profession of Engineering Does

W. R. SCHOWALTER
University of Illinois at Urbana-Champaign Urbana, IL 61801

At the outset, I wish to express my thanks for the honor
to be associated with this celebration marking the
appearance of the 2nd edition of Transport Phenom-
ena. The enormous influence of the first edition on chemical
engineering education is so obvious and well known that it
would be gratuitous for me to spend time talking about how
the book transformed chemical engineering education
throughout the world. That is not to say its adoption was im-
mediate or uniform across the country. Similar to Feynman's
Lectures on Physics, the instructors often learned more than
the students. With apologies for the terribly mixed meta-
phors, one could describe BSL as a stew that didn't al-
ways fly well with lightweights.
This talk is meant to be forward-looking rather than back-
ward-reminiscing, but it is clear that included in my qualifi-
cations for delivering this lecture are (a) my pedigree as an
alumnus of this department and (b) a date of birth that puts
me in an ever-contracting pool of candidates who were edu-
cated in pre-BSL history. I therefore choose a few prelimi-
nary stories, which (beyond being amusing) have, I hope,
some value as reminders of the reach and the lasting influ-
ence, often unintended, those of us who teach have on a
large body of students.
Until late in my undergraduate experience, the most in-
students. Names such as Ednie, Garver, Woods, and Kirk come
to mind. Bob Kirk was an assistant professor. The others were
instructors and World War II veterans, several of them mar-
ried with young families. They were no-nonsense people who
took their teaching duties seriously and, for the most part,

explained the material well. There is a lesson in this bit of
history. In spite of our recoil when we are told that students
are forced to learn from graduate students rather than senior
faculty, instruction from graduate students isn't necessarily a
by someone more apt to appreciate student difficulties, often
similar to those endured just a few years earlier by the in-
structor, than is the case when a full professor is in charge.
The "big names" in the department in those days were
whatsoever with either one. In later years, however, I came
to know both gentlemen well-Bob Marshall through AIChE
committees and Olaf Hougen when he joined a Madison re-
tirement center to which my parents had moved. He was a
truly remarkable person.
ing. In my sophomore year I became frustrated because it
seemed all I was doing was rushing from one assignment and
exam to another, without time to reflect on what I was learn-
ing. I went to my adviser, Professor C.C. Watson, and told

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

William R. Schowalter, professor and dean
emeritus of the College of Engineering at the
University of Illinois at Urbana-Champaign, is
currently senior advisor to the president of the
National University of Singapore. He received
his BS from the University of Wisconsin, and
his MS and PhD from the University of Illinois,
all in chemical engineering. He is an authority
in the field of fluid mechanics, especially as it
applies to the processing of polymer melts,
polymer solutions, and colloidal dispersions.

242

him I wanted to cut back on the number of
courses and stretch out my residence time to
five years. He looked at my grades, then
looked at me, and said there was no reason
for me to take longer than four years. His an-
swer was no-end of discussion, end of ap-
pointment with adviser. Years later I could say
with conviction that his decision was abso-
lutely correct. I can only guess why he re-
fused me, but I suspect he believed I would
use the extra time for anything but "reflect-
ing" on what I was learning, and I was prob-
ably too immature to know what to reflect
about. Beyond that, one needs a balance be-
tween thoroughness and efficiency. Part of
engineering education is learning how to
find that balance.

AN OVERVIEW

Engineering education is, by its very na- s
ture, in a continuous state of flux. Appearance
every decade of a definitive report on the fu-
ture of engineering education is as predictable as a sighting
of the first crocuses in Madison near the end of March. The
constant uncertainty over what we teach should not be sur-
prising. Engineers solve problems. If they are successful, those
problems disappear. Then we find new problems to solve.
Although the principles used to solve successive generations
of problems change very slowly, the problems themselves
have different emphases and different details that require
continual fine tuning, and, as with BSL, occasional step
changes in our approaches.
In my remarks, I shall first offer comments on the purpose
of undergraduate engineering education within the context
of a large, selective university such as UW Madison. From
there I wish to specialize the discussion to challenges and
opportunities relevant to chemical engineering departments
within such institutions, looking successively at undergradu-
ate, professional, and graduate (PhD) curricula. Finally, a few
generalizations are offered regarding challenges for compre-
hensive public research universities.

A popular current claim of engineering educators, and one
to which I subscribe, is that our subject is the liberating art of
the 21st century. That claim lays upon the departments making
it a set of curricular responsibilities which, I believe, includes
1) A program of study sufficient for entry-level positions
in engineering practice and engineering-related fields
2) Exposure to "shoulder areas" of engineering
3) Provision for an understanding of professional and
personal ethics
4) Mastery of fundamentals sufficient to pursue graduate

Engine
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its very n
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Then we
aewpvoN

Fall 2003

study in engineering or related fields
isng These features of an undergraduate engi-
is, by neering education are not without contro-
atue versy, so I should explain why I believe they
ous state are important and valid.

tant .First, we are not in the business of pro-
viding solely a "pre-professional" education,
ty over in spite of the efforts of generations of edu-
teach cators to do so. The educators have failed
ot be because the market has dictated otherwise.
ing. In good economic times, eager companies
solve line up at the nation's best engineering
If l ey schools to nab graduates of four-year accred-
0ssf9 cited programs. Sometimes those graduates
b4kms enter highly focused technical areas in the
ea electronics, chemical, or automotive indus-
fitd tries, and they will probably receive a gen-
fid erous dose of in-house training to sharpen
-0vs ~the generalities learned in their BS educa-
,* tion. Nevertheless, they are hired as engi-
neering graduates, not as products of a gen-
eralized pre-engineering curriculum now
ready for finishing school. Alternatively, other companies are
anxious to hire them for jobs in which the analytical and rea-
soning skills of the graduates will be applied to a broad rather
than narrow and highly disciplinary context. During the past
decade, the consulting firm Accenture has been one of the
largest employers of entry-level engineers graduating with a
four-year BS degree from Illinois.
Second, I refer above to the "shoulder areas" of engineer-
ing. This is an acknowledgment of the fact that engineering
is a profession that cannot be practiced in isolation-it re-
quires a context. Here is where the "liberating art" label can
be argued. As technology forms an ever-deepening influence
on the lives of everyone, it should be expected that an educa-
tion in engineering must provide a foundation for future spe-
cialization in business, law, or (as we are beginning to see)
even the arts. Those connections should not be left to chance.
On the contrary, opportunities to link strictly technical issues
with economic, social, and political factors should be sought
and exploited. Note that this implies more than a simple re-
quirement for students to take x credits of subject y during
The third ingredient referred to pertains to professional
and personal ethics. If an engineering education does not help
us to understand and promote a civilized society, it is not a
liberating art. Again, this emphasizes that engineering is prac-
ticed in a context. Precisely because engineering is so impor-
tant in today's world, a so-called "engineering decision" is
seldom without consequences far beyond the realm of engi-
neering itself. Those decisions have far-reaching economic,
social, and ethical implications, and the choices among alter-
natives are seldom clearly right or clearly wrong.

ovt

Fourth, I have required that an undergraduate curriculum
properly serve the person who wishes to compete at the high-
est level in graduate study in engineering or a related field.
This is the true proof of principle when we claim to be edu-
cating engineers. It separates the schools preparing engineers
from the schools preparing dilettantes. My opinions here have
been shaped by many years on the faculty at Princeton. At
that institution, the largest number of undergraduate majors
over a period of several decades were in either English or
history. Clearly, very few of those majors went on to make a
living in either of those fields. Some did, however, and they
became distinguished in their specialty. We should be able to
do the same. It is not necessary for a school of engineering to
choose between producing either specialists or persons so
well-rounded they have no peaks of excellence.
I have laid out a daunting assignment for an undergraduate
engineering program. How can one provide the technical
depth required to excel at subsequent graduate courses in fast-
moving fields, while at the same time give proper attention
to the shoulder areas and gen-
eral intellectual maturation im-
plied in the above remarks? 1. Chemical Change
Let me be the first to admit that Reactor design
it is not easy, and it is prob- Material and energy balance
ably not possible for any but 2. Separations
2. Separations
the most selective of institu- The concept of staging
tions. To accomplish the ends Unit operations
stated here, one needs entering
students with a rare combina- 3. Therocess
tion of mental ability, prepa- Optimization
ration, and maturity. Those Economics
young people surely exist in Figure 1. Distinctive
our society. It is up to the en- Figure ng Distinctri
gineering profession to con-
vince them that study of engi-
neering is worth their atten-
tion. It is when we do not attract a sufficient number of these
students that we say the curriculum is too difficult, too stuffed
with requirements for completion in four years, or too bor-
ing. I should add that this can become a vicious circle. It is
possible to design a curriculum with all of these undesirable
features-one that will dissuade from the outset attracting
the type of students we wish to see.

CHEMICAL ENGINEERING

Undergraduate Education Everything said so far per-
tains to all of engineering. What can one say that is unique to
chemical engineering? This is, in fact, becoming an increas-
ate level, as we shall see shortly. There are some distinguish-
ing, if not unique, features of chemical engineering practice
and education, however. For the moment, let us concentrate
on ramifications for undergraduate education. I believe we

es

e fea
ng e

distinguish ourselves through the following three character-
istics:
A focus on chemical change
Well-developed methodologies for describing separation of
mixtures into their components
A systems approach to the design and description of
processes
These three features can be expanded as shown in Figure 1.
Will these characteristics ensure a healthy chemical engineer-
ing profession into the next generation? In my opinion, they
will not, because we have forgotten a critically important in-
gredient: the student. More than anything, a preponderance
of high-quality students has sustained us ever since World
War II. We have operated more-or-less successfully under
the paradigm, "Build a sound curriculum, and they will come."
I don't believe that approach will work in the future. In order
to engage the cream of the student body, we need to educate
students who, upon graduation, will find jobs with satisfac-
tory financial compensation, intellectual challenge (something
that really is rocket science),
and a sense of excitement and
mission, i.e., conviction that
one's work will make the world
Transport phenomena a better place.
(rates of transfer of mass,
momentum, and energy) How do we measure up?
Relative to other engineering
disciplines, job opportunities
for chemical engineers have
been plentiful, if not as legend-
ary as they were for several
years in computer engineering
rtures of a chemical and science. On the criterion of
education. intellectual challenge, we mea-
sure up very well indeed. We
teach fundamental reasoning
rather than rote application of
facts, and students are stretched accordingly. It is with re-
spect to the last item on the list that we fall short. Faculty
members are excited about what they are doing, but the num-
ber of links in a chain of inference between that excitement
and the excitements of engineering practice is perilously large.
This is not true with engineering in general. It happened in
our field because the interests of faculty members and the
needs of practitioners have diverged. Such does not have
to be the case if one is to retain the intellectual challenge
of the second point.
As an example, I have compared in Table 1 the citations of
Engineering in the chemical engineering section (Section 3)
and the electronics engineering section (Section 7). I believe
one finds a much closer identification of the latter group with
the current interests and proclaimed needs of the industry they
represent. Nevertheless, they are presumably conducting re-

Chemical Engineering Education

On the criterion of intellectual challenge, [engineering education] measures] up
very well indeed. We teach fundamental reasoning rather than rote
application of facts, and students are stretched accordingly.

search considered by their peers to be at the highest level
among their cohorts. I don't mean to imply a value judgment
by the comparison, but our profession is at some risk when
there is lack of identification with the areas of commerce we
mercial needs is much stronger in the bio-related areas of
chemical engineering, and that is one reason for the current
vitality of that subject.
It is universally agreed that bioengineering, biotechnology,
and bioscience are important to the future of chemical engi-
neering. Exactly how that importance is to be acknowledged
in our curricula and research is still an open question, and
indeed, there is no single answer. Pluralism has been a pillar
of strength for the U.S. educational system, and we shall no
doubt see many successful models. Before leaving this sub-
ject, I do wish to provide an often-forgotten historical per-
spective. Fifty years ago, programs in biochemical engineer-
ing, or its equivalent, already existed at Wisconsin and Illi-
nois, and probably at other schools as well. I do not believe
any of them had a large following. Timing is everything!
Bioengineering is not the only cross-cutting subject on
which chemical engineering should have an important influ-
ence. An emphasis on chemical change implies a special in-

TABLE 1
Comparison of Citations for Members Recently Elected
to the National Academy of Engineering

Chemical Engineering Section
of the behavior of block copoly-
mers and other polymeric and
complex fluids
of electrokinetic and electro-
hydrodynamic processes ...
For pioneering contributions in
engineering ...
of the mechanisms and modeling
in and pollutant control of com-
bustors
For elucidating the flow proper-
ties of complex fluids at the
molecular and continuum
levels ...

Electronics Engineering Section
devices, detectors for fiber optics,
and efficient LEDs for displays

For contributions to the develop-
ment of CMOS technology .

For contributions to signal and
image processing .. .

ship in research on micro-
electromechanical systems

For introducing photonic band-
gap engineering and applying
semiconductor concepts to
electromagnetic waves in
artificial periodic structures

terest and competence in things at the molecular and near-
molecular length scale, a current area of great promise in tech-
nology. At the other end of the length scale are macro-projects
associated with a systems approach. Although chemical en-
gineering education has profited from its close-knit structure,
perhaps the time has come to consider multiple tracks to a
degree, an approach successfully followed for decades by
electrical engineers.
because here, for the most part, chemical engineering depart-
ments are involved at the margins. Put differently, if we ex-
celled in this arena, the profession would benefit but the im-
pact would not be overwhelming. Likewise, if we turn our
backs on professional education, the damage done is not life
threatening to our profession or to the universities. To a large
extent, one can say this because other stakeholders have a
firm grasp on professional education: the professional soci-
eties, private firms, and the internal education programs of
most large technology companies.
Having said that, I believe there are significant opportuni-
ties for universities to gain from professional education ini-
tiatives. Stanford is probably the most outstanding example.
Its electrical engineering and computer science departments
and the technology culture in the Palo Alto area have been
inseparable. From that example as well as others, distinct ad-
vantages for an academic department and its inhabitants include
Discretionary income for the providing unit (a for-profit
venture)
Opportunity for faculty members to be closer to the firing
line (see above criticism aimed at many chemical engineer-
ing departments)
A chance for students and practitioners to mingle
Chemical engineers may have to accomplish this virtually
rather than actually because of distance and time constraints.
Historically, we have declined to be heavily involved in pro-
fessional education, but there are several interesting examples
that have some features of professional education. They in-
clude
An often-called "Master of Engineering" program, such as
the one at Cornell. These involve some type of project work
in place of a Master's thesis. Typical features of the project
include design, teamwork, and liaison with an industrial
partner.
The joint MS degree in chemical engineering between the
University of Illinois at Urbana-Champaign (UIUC) and the
National University of Singapore (NUS). Here, students
from both institutions combine the features of study abroad
and industrial experience in both countries, leading in
approximately 18 months to a Master's degree.

Fall 2003

The MIT Practice School. This venerable program, also
leading to a Master's degree, has been in existence for
generations and is arguably the most influential and effective
These examples indicate that it is possible for profession-
ally oriented education to be both financially and intellectu-
ally rewarding for chemical engineering departments. Issues
of resource allocation, faculty interest and talent, and geogra-
phy, however, all indicate a local decision on the importance of
a professional education component to a department's welfare.
Graduate Education This is the arena that has the deep-

est effect on faculty careers at
a research-oriented university
such as Wisconsin. Research
vancement and rewards all
is also the arena where, I be-
lieve, the distinctiveness of
chemical engineering is rapidly
disappearing-as is the distinc-
tiveness of any brand of engi-
neering. We are witnessing a
secularization of the disciplines
of engineering. When I was a

TABL
Some Consequences of Ta

L

a
D
e

U
s
m
R
ir

Assets
Students (and faculty!) become
technically multilingual
Solutions to important research
problems are more likely to
be found
Silo mentality is neutralized

Attractive research topics for
students

auto industry held sway over mechanical engineers. The
atrium of the Mechanical Engineering Building was deco-
rated with a huge banner hanging from the ceiling and pro-
claiming the latest doings of the Society of Automotive En-
gineers. Electrical engineering graduates went to work for
Wisconsin Electric Power or one of the electronics compa-
nies that at that time had a high concentration in the Midwest
(if I remember correctly, names such as Zenith, Haseltine,
and Collins were prominent), and chemical engineers worked
for chemical or petroleum companies, with a local emphasis
on the paper industry. Contrast that with today: ME's design
disk drives, ChE's work on prosthetic devices, and EE's work
These examples are drawn primarily from the BS/MS lev-
els, but it is perhaps even more evident at the PhD level. By
probing more deeply into our sub-specialties, we have gone
our separate ways, a bit like swimming through fish traps of
ever-narrower pore size, and now we are finding ourselves
all in the same large trap. It has the name "bio/info/nano." As
a consequence, we are entering a period of great excitement
and opportunity at the frontiers of knowledge. It is a devel-
opment we should welcome rather than fear, but it does pose
challenges for our system of doctoral education. I make no
claim to having all the prescriptions for meeting those chal-
lenges, but I do have some suggestions.

colleague, Michael Heath, in our Department of Computer
Science. Mike is director of a large DOE-sponsored effort
housed in the Center for the Simulation of Advanced Rock-
ets (CSAR) and known as the Accelerated Strategic Comput-
ing Initiative (ASCI). The mission of CSAR is to simulate
the behavior of rockets from a systems point-of-view, mean-
ing the problem involves issues of mechanics, combustion,
materials, and aerodynamics. Specific thrust areas are the
province of faculty members from departments of physics
and most of the departments of engineering at Illinois.
Mike, whose own specialty is scientific computing, de-
scribes the work of the Cen-
ter as "nonlinear everything."
_E 2 I asked him how it was pos-
isk-Oriented Research sible to make rational progress
when everything depends on
abilities
everything. His response was
[ore difficult to do academic not surprising. He stressed the
-ministration importance of a tight network
disciplinary core can become an for efficient and multichannel
endangered species
communication. It is impera-
tive that people talk with, lis-
nclear lines of reporting and re-
)onsibility for junior faculty ten to, and understand each
[embers other. This requires effort on
evidence time to degree can all sides. The materials people
increase need to appreciate the prob-
lems of the propulsion people,
who in turn need to know the problems and constraints of the
guidance and control people, etc. There must also be an over-
all goal and periodic evaluations of how the group is reach-
ing that goal. As we talked, I gained a new appreciation for
the importance on our campuses of interdepartmental labo-
ratories, centers, and institutes. They have become more than
desirable-they are now essential.
I conclude from these experiences that research themes must
go beyond the "Professor X group" mentality and that inter-
penetration among groups must be real and substantial. This
means that PhD research will need to be "managed" more
effectively than before. Perhaps more of the funding for our
research should be structured along the lines of NIH and be
project- or goal-oriented, as are most of the individual insti-
tutes of NIH. There has been periodic discussion of a similar
structure for NSF, but to the best of my knowledge, serious
consideration has not taken place.
In Table 2 I have shown a balance sheet for task-oriented
research conducted with graduate students. The capability to
be technically multilingual and to work in cross-functional
groups is a skill deemed critical to survival in contemporary
professional life, and the sooner students become adept at it,
the more valuable their service will be to an employer. This,
by the way, is no less true in academe than in industry. The
reason for this added-value is, of course, because most im-
portant problems today cannot be solved in isolation. Mike

Chemical Engineering Education

Heath's "nonlinear everything" applies
far beyond CSAR. Working against the
assets of Table 2 are the potential liabili-
ties. Note, however, that with the pos-
sible exception of the second item, the
liabilities are driven by structure rather
than by substance. That is not to claim

that alteration of a structure is a simple
matter, or that the present structure does not serve a purpose.
Overcoming the challenges posed in the liabilities column is
major research universities.
There is an additional contemporary issue not identified in
Table 2. Few will deny that our nation's research capability
has been put at risk by the demise of most of our major in-
dustrial research laboratories. In the past, they often carried
out the important task-oriented but fundamental engineering
research essential to a technically advanced civilization's tech-
nology base. Much of that research has now been transplanted
to university campuses. But if corporate shareholders are
unwilling to pay for these admittedly necessary results, who
should? The federal government? A consortium of federal
governments? (The European Union represents one model
of the latter.) This is a question that deserves a better answer
than either industry or government has provided to date. A
step in the right direction would be clearer articulation by
government research-supporting agencies of the relative im-
portance to them of research results and the advanced educa-

THE COMPREHENSIVE
PUBLIC RESEARCH UNIVERSITY
Moving to the final item on my agenda, we must not forget
that chemical engineering education is often conducted within
the environment of a research university, which itself is a
dynamic institution. Much has been written about the shape
of research universities in the future, the increasing role of
corporate and philanthropic support, and the need to preserve
excellence in subjects not directly related to economic needs.
For a more global view than is appropriate here, I refer you
to a recent book[31 by James Duderstadt, an engineer and
former president of the University of Michigan.
I do wish to voice a somewhat parochial concern about
universities such as Wisconsin and Illinois, and that is the
ever-widening gap in resources between the top-tier private
and the top-tier public research universities in this country.
The former had extraordinary endowment growth during the
1990s. That growth will, of course, erode in down-markets,
but the miracle of compound interest is such that I fear the
public will never catch up.
A few years ago, Illinois made a comparison of faculty sala-
ries at different ranks among leading public and private uni-
versities. The most dramatic result of this comparison was a

... an undergraduate curriculum [should] properly serve the
person who wishes to compete at the highest level in
graduate study in engineering or a related field.
This ... principle .. separates the schools preparing
engineers from the schools preparing dilettantes.

shift that has occurred during the past twenty years. Twenty
years ago there was a healthy mix of publics and privates
among the top performers. Today, private institutions domi-
nate those providing the highest faculty salaries. Salaries, of
course, do not alone reflect the quality of a research univer-
sity, but they are, over time, an important indicator.
Midwestern universities, in particular, need to reaffirm their
desire to compete with the best and to convince their citizens
of the value these universities add to their states. We need a
new articulation of the land-grant idea, probably in a con-
certed way across several states. This is too large an issue to
be appropriate for more than a passing comment in a talk of
this type, but it will surely affect chemical engineering edu-
cation at universities such as ours.
So what does all of this mean for Transport Phenomena II
and the University of Wisconsin's place in the history of
chemical engineering education? The clear and illuminating
developments of momentum, energy, and mass transfer found
in Transport Phenomena I are intact in the second edition.
Those concepts and the tight coupling between them will
surely remain in what we consider the chemical engineering
canon. But people toting the successor to that familiar red (or
in later printings, green) classic must find applications we
haven't dreamed of. If they don't, chemical engineering will
deserve to be devoid of bright, ambitious, competitive, and
interesting students. My own bet will be on the side of a fu-
ture in which Transport Phenomena II will follow its own
laws of diffusion. The subject will penetrate into new areas
of application and enrich them, and it will be students edu-
cated through Transport Phenomena II who will be the agents
of change for diffusion of the subject into the broad sweep of
modern technology.

1. Bird, R. Byron, "Mass, Momentum, and Heat Transfer: The Impact on
Engineering Education," in Recent Advances in the Engineering Sci-
ences, McGraw-Hill, New York, NY (1958)
2. Colton, Clark K., ed., Advances in Chemical Engineering, Vol. 16,
"Perspectives in Chemical Engineering Research and Education,"
3. Duderstadt, James J., A University for the 21st Century, The Univer-
sity of Michigan Press, Ann Arbor, MI (2000)
4. Hougen, O.A., "Seven Decades of Chemical Engineering," Chem. Eng.
Prog., 73, 89 (January, 1977)
5. Servos, John W., "The Industrial Relations of Science: Chemical En-
gineering at MIT, 1900-1939," Isis, 71, 531 (1980)
6. Servos, John W., Physical Chemistry from Ostwald to Pauling,
Princeton University Press, Princeton, NJ (1990) 0

Fall 2003

rje -1curriculum

MIXING WRITING WITH

FIRST-YEAR ENGINEERING

An Unstable Solution?

LISA LEBDUSKA,* DAVID DIBIASIO
Worcester Polytechnic Institute Worcester, MA 01609

Most first-year students have little in-depth knowl-
edge of their chosen profession-particularly in
engineering, which has so few high school experi-
ences connected to it. Moreover, chemical engineering de-
partments rarely offer core courses until the sophomore year
and hence have little contact with first-year students inter-
ested in chemical engineering. Recently, more departments
have begun offering seminars or other career-oriented activi-
ties for first-year students,M' recognizing that early engage-
ment with the profession can increase motivation for learn-
ing and improve retention in the major.[2,31 Improving student
understanding of engineering should certainly allow students
and professional careers, but providing them with such an
understanding can be challenging and too often devolves into
passive activities such as seminars and introductory techni-
cal courses. By contrast, a process that engages students ac-
tively in learning about and identifying with engineering
would benefit both them and the profession.
Students' ability to identify with their chosen profession
improves both motivation for learning and retention in the
major and also seems to influence their ability to write effec-
tively. Science writing is often influenced by "a student's in-
adequate sense of self as scientist,"141 and a similar rhetorical
struggle would be expected for students in engineering disci-
plines. If engineering students do not view themselves as
engineers, they cannot become fully aware of the audience to
which they are writing and the specific needs of that audi-
ence. Consequently, they approach engineering writing with-
out adequate knowledge of the language practices that define
their discipline. Traditional writing assignments such as lab
write-ups, while helpful in shaping students' thinking and
identifying what is new knowledge to them, may not help

*Address: Wheaton College, Norton, MA 01766

them adopt professional roles. Lab reports typically are writ-
ten to document completion and understanding of the engi-
neering process. For the most part (and with good reason),
first-year labs do not ask students to write as professionals
but as novices demonstrating skills and knowledge.J15
Educators have addressed engineering students' writing
abilities for over a hundred years, with varying degrees of
success and satisfaction.6'1 Institutions have adopted a range
of approaches to improve students' writing skills, such as
writing-across-the-curriculum (WAC) courses that integrate
technical content with rhetorical analysis. Despite good in-
tentions, however, some of these WAC approaches have nev-
ertheless failed to adequately prepare engineering students
for the types of writing tasks that they will encounter aca-
demically and in their careers. As technologists and human-
ists often use different techniques to teach writing, it may be
difficult for students to incorporate lessons from the humani-
ties into their engineering coursework.[71 Engineers may also
lack the language and understanding of composition stud-
ies to effectively teach the writing process. Offering a
pedagogical balance between engineering and rhetoric is
thus a challenging problem.
At Rensselaer Polytechnic Institute, the chemistry depart-
ment employed writing consultants from the Department of

David DiBiasio is Associate Professor of Chemical Engineering at Worces-
ter Polytechnic Institute. He received his BS, MS, and PhD degrees in
chemical engineering from Purdue University. His educational work focuses
on active and cooperative learning and educational assessment. His other
research interests are in biochemical engineering, specifically biological
reactor analysis.
Lisa Lebduska is the Director of College Writing at Wheaton College in
Norton, MA, where here she is designing a writing-across-the curriculum pro-
gram and contributing to the development of Wheaton's new College Learn-
ing Center. With research interests in computer-mediated literacies and
peer tutoring, she has contributed work to Writing Center Journal and the
anthology Student-Assisted Teaching and Learning.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

Language, Literature, and Communication
to work with junior-level chemistry ma-
jors on their lab reports in two required
"writing intensive" courses. These con-
sultants met with chemistry faculty to dis-
cuss writing practices in that discipline
before they began offering feedback to stu-
dents, who produced multiple drafts of
their reports before submitting final ver-
sions for grading. The writing focus in this
WAC effort targeted upper-class students
and formal lab writing and resulted in bet-
ter quality lab reports.171 A WAC effort in
the Department of Animal Sciences at the
University of Kentucky similarly targeted
upper-class students through a senior-level
course, but by contrast it emphasized more
"real world" assignments that would help
students recognize the importance of writ-
ing in their discipline-an achievement
that is often sought by WAC endeavors in
engineering and technical programs. The
Kentucky course stressed the importance
of rhetorical context in writing assign-
ments to improve student interest and to
clarify assignment objectives.8'
approach to WAC has been undertaken by the Materials Sci-
ence and Engineering Department at Virginia Polytechnic
Institute, which integrates writing and speaking into eight core
courses that students take over a three-year period. The se-
quence used a combination of formal and informal ("inter-
personal") communication assignments, peer writing consult-
ants, and supplemental writing workshops. Their efforts seem
to have contributed to the establishment of a required zero-
credit class for majors that asks students to create a writing
portfolio containing their best work in a variety of modes
from their required classes.[91
Historically, attempts to understand these varying ap-
proaches to writing have resulted in two groups: in one, the
expressivist model, writing is used as a means of teaching
and learning, employing free writing and journals, and in the
other, the "social constructionist model," writing pedagogy
emphasizes disciplinary or workplace conventions. Such cat-
egorization oversimplifies the WAC process, with some re-
searchers turning to an "interactionalist" approach that com-
bines elements of both models. "An interactional approach...
emphasizes that learning is a social process that necessitates
active involvement on the part of both the learner and the
teacher while also emphasizing the contribution of disciplin-
ary knowledge in the transaction.""''"
At WPI, we attempted to adopt a scaled-down version of
this "interactionalist" approach, which had been developed

through a successful collaboration be-
tween humanities and engineering faculty
at Michigan Tech University.o01 Our
interactionalist approach involved using
some writing activities that taught students
to use writing as a means of understand-
ing what they wanted to say and were ex-
ploratory. Other activities, by contrast, in-
troduced them to conventions within the
discipline and encouraged them to learn
and reproduce those conventions. The bal-
ance, in part, is between teaching students
what they need to learn to become practi-
tioners of an inherited discourse while also
giving them the critical thinking skills they
need to question and challenge conven-
tions. Leadership in any field requires in-
dividuals who can go beyond the mere re-
production of knowledge by continually
reexamining the discipline and, when
needed, reshaping it.

COURSE OBJECTIVES
Students often think of writing and
speaking strictly in terms of evaluation,
e.g., the lab report or presentation that they
must produce to "prove" that they com-
pleted and understood the science. They have a fairly limited
understanding of what "communication" can be used for. At
the same time, their knowledge of what chemical engineers
actually do is equally limited. Because WPI does not offer
freshman chemical engineering courses or require writing
courses, we wanted to design a course that would actively
engage students in the profession while improving their ap-
proach to and understanding of communication as a prob-
lem-solving tool. Additionally, we needed to recognize that
although first-year chemical engineering majors do not take
any chemical engineering courses, they carry one of the
challenged us to design a one-credit class that would
achieve our pedagogical goals but still attract students.

THE APPROACH
Jointly taught by a chemical engineering professor and a
writing professor, the course stressed collaboration between
chemical engineering and communication in its design and
its execution. We reasoned that the best way to teach that
communication and chemical engineering should inform each
other was to demonstrate the integration, so we collaborated
on the design and delivery of every assignment. Both instruc-
tors attended every class, so the students would again see the
connection between the two disciplines and not think of
"communciation days" versus "chemical engineering days."

Fall 2003

Course development was funded through a WPI grant (itself
supported by NSF's Institute-Wide Reform Program) the first
year and a Davis Educational Foundation grant the second year.
We offered the course three times over two academic years,
revising it after each offering. About one-third of the declared
majors took the course each offering (7-10 students per se-
mester). We required portfolios each time we taught the
course, but in the second offering we required the students to
submit all of the assignments from the course. Ideally (in
keeping with writing portfolio pedagogy), we would have
allowed the students to select what they felt were their stron-

To assess writing gains and to assess the
reliability of our portfolio assessment, we
used an external writing specialist. A final
evaluation measure involved student
self-assessment as expressed in
their portfolio cover letters.

gest pieces, but because we met only once weekly and the
course was "low-stakes" (only a single credit), there weren't
enough assignments from which to choose. We nevertheless
were able to design assignments about chemical engineering
that would give the students an awareness of audience, intro-
duce them to group writing, peer response, and revision, and
give them practice writing reflective cover letters that would
initiate a metacognitive approach to writing-that is, get them
class discussion so that students would receive practice com-
municating ideas, responding to others' ideas, and learning
the language needed to participate in the discipline.

THE ACTIVITIES
The course had several activities that covered a variety of
engineering topics integrated with communication issues. For
the purposes of this paper, we summarize a few of the activi-
ties, then follow with a detailed discussion of two. Our em-
phasis in this paper is on portions of the course dealing with
ethics/professionalism and understanding audience.
We started the course with a scavenger hunt that sent stu-
dent teams to various faculty, the writing center, and some
research facilities such as the electron microscope facility.
Teams collected some technical information from each visit
and gave an informal presentation on their findings.
A visual-rhetoric activity had students describe an assigned
visual element that was related to chemical engineering (e.g.,
a pump) to a partner who had to draw it without looking at it.
This activity gave students experience with precise verbal
communication and active listening, while illustrating some
basic chemical engineering principles. We then debriefed the
class with their sometimes-humorous drawings, their guesses
about what the devices were and what led them to their con-

clusions, and then an explanation about the real function of
the visual element.
To connect visual and verbal skills, students went to the
Unit Operations lab for a demonstration of a pilot-scale dis-
tillation column. Prior to the lab visit, they were asked to
develop and sketch a process for production of fuel-grade
ethanol from a fermentation broth. This exercise introduced
basic separation principles, including staging. The lab dem-
onstration was combined with a quantitative problem assign-
ment and a writing task that integrated all the elements.
This was the first time any of the students had observed
the operation of a larger-than-bench scale piece of chemi-
cal processing equipment.
The follow-up activity to the laboratory visit involved vis-
its to actual industrial facilities. We wanted students to expe-
rience chemical engineering in the workplace and to have an
opportunity to talk with practicing engineers in a more active
way than a standard plant tour allowed. Each team visited a
different site and spent several hours with a WPI alumnus
during a major part of their workday. Companies visited in-
cluded an environmental consultant's site visit, membrane
separations (Sepracor), and stem cell production (Viacell). After
the trips, each group wrote a trip summary and gave a brief oral
presentation to the rest of the class about the experience.
Although the activities described above provided some in-
teresting exercises and opportunities for writing within a tech-
nical context, we really wanted to engage students at a deeper
level. Course logistics and student background prevented
going too far into the details of chemical engineering funda-
mentals, so we took a different route. Two activities, described
below, resulted in some interesting issues and posed some
particularly challenging problems for the instructors. Details
about the course syllabus, assignments, and portfolios can be
obtained directly from the authors at or
.

0 Ethics, Racism, and Engineering Practice
Civic responsibility, the interaction of technology and so-
ciety, and professional and ethical responsibility are all part
of WPI's educational philosophy, so in the first offering of
the course we attempted to engage the class in issues of work-
place racism. Wanting our students to realize that ethics and
race issues have a place in chemical engineering and in their
education as engineers, we used a campus event featuring a
documentary about racism in Japan and a discussion with its
director, and a real case-study involving a chemical company
and allegations of racism. This exercise provided important
data that only a collaboration would have provided.
The racial homogeneity of WPI, this class, and its instruc-
tors contributed to the impression that racism is something
that occurs elsewhere and is perhaps not a real problem, and
our all-too-brief treatment of the issue did little to counter

Chemical Engineering Education

250

Our conclusion is that mixing writing and first-year engineering is certainly a stable solution
when the experiment is properly conducted....Ensuring stability takes energy, time,
and commitment from the faculty, however-it's a challenging and
difficult process, but it is rewarding and fun.

that impression. Because the film examined racism in Japan,
our students responded to the issue as if it were a symptom of
Japanese culture in particular. Focusing on the lives of Afri-
can-Americans in Japan and their isolation there, the film
was interpreted by students as an instance of something that
occurs outside the racial democracy of the United States. Our
shift of the discussion to the Texaco racial-discrimination law-
suit['3] did little to alter students' perception that racism was
something that occurred "out there." Although we pointed
out that the Texaco executives who had been accused of mak-
ing racist remarks might have been trained in chemistry or
engineering professions, our students nevertheless discussed
the issue as if it were something that couldn't happen here.
When we shifted the discussion to subtle forms of racism
that we have witnessed, such as unofficial segregation in the
cafeteria or in fraternities, several students offered anecdotes
about their best friends who were of color. We seemed to
have created an atmosphere in which students felt the need to
testify against racism and to represent themselves as among
the enlightened, but our goal had been more to get students
to consider the complexities of racism and to examine how
they operate in the workplace. The exercise suffered from a
larger cultural constraint in which "racism seems always to
be an appendage to the classroom curriculum, something
loosely attached to a course but not quite integral, even when
race is the issue."[141
We have not yet resolved the race issue to our satisfaction
and will continue to explore ways to address it. We might
consider, for example, having students explore how "white-
ness" is often understood as a "non-race" or universal in the
workplace. We might also consider examining race in the non-
managerial levels of the workplace. At the same time, we
consider the exercise successful because it provided us with
lab activities cannot provide. Additionally, because the exer-
cise was presented within the context of a chemical engi-
neering class, it sent the message that racism is something
that concerns chemical engineers.
Scheduling logistics and the issues described above caused
us to reconsider our approach to introducing the grayer areas
of professional decision-making. We assumed that a shift from
the larger but harder-to-concretize issue of racism to other
more clearly defined ethical dilemmas might be easier for
students to grasp as an entry point into the profession's com-
plexities. So, in subsequent course offerings, we decided to
focus on a very specific well-defined problem. Using an On-
line Ethics Center web site ,

we designed an assignment to introduce students to common
chemical engineering ethical dilemmas. We used a case study
on "Request to Falsify Data" to generate in-class discussion
about how the engineer in the case study might have responded
if her manager wanted her to falsify data about an environ-
mental oil spill. The writing assignment followed up on this
discussion by asking students to evaluate the problem from
the perspectives of a member of the state's environmental
protection agency, the CEO of the company, company attor-
neys, and members of the community.
Some students seemed surprised that engineering had an
ethical component. As one student noted, "I never expected
[a discussion about ethics] in a department other than Hu-
manities. We discussed a dilemma between one's future ca-
reer and morality as part of the human community. From this
discussion, I learned how ethical issues were involved with
chemical engineering ... I liked the idea that we had to give
opinions from different perspectives."
Another student found himself challenged by a situation
that did not offer any moral certitude. By the end of the course,
he described his dilemma: "It was hard to decide how other
people would react and what they would do ... Why would
they want to jeopardize their career or the company and what
qualities are needed to stand up for what is right?"
Because these exercises did not offer the students any an-
swers, they introduced them to a significant but seldom-dis-
cussed component of chemical engineering as well as a lan-
guage by which to begin considering the issues involved. The
exercises provided practice in understanding and articulat-
ing multiple perspectives of the same scenario as well as
the subjective context in which professional life across
disciplines is situated.

N Understanding Audience
A major group-writing piece involved describing a current
field of chemical engineering research to a general audience.
Student teams were assigned a research area and provided
with at least one technical article describing that research,
major benefits that might come from it, and problems associ-
an article written for the campus newspaper that described
the role of chemical engineers in the specific research area.
Some groups interviewed appropriate faculty with expertise
in the area. The writing process allowed us to introduce tech-
niques for collaborative writing, revision, and peer review.
The difficulties of understanding audience in an educational

Fall 2003

context emerged as the students struggled to write to an audi-
ence of peers while recognizing that their professors would
be reading and commenting on drafts. One group was as-
signed the research area of obesity drugs-a topic involving
an interesting combination of medicine, biology, engineer-
ing, and patient treatment. In an effort to engage their pro-
spective peer audience early in the piece and to be funny, the
first draft of their paper appeared with the title in large, bold
font: "What's Up FATTY?" and a lead sentence of "Are you
Fat? If so, read on." Other examples of their humor included
statements such as "The diseases related to obesity include
heart disease, stroke, diabetes, hypertension, and gall BLAD-
DER disease (ooooh!)....Scientists were exstatic [sic] when
they discovered that the drug accts [sic] on the brain like CO-
CAINE!!! Fortunately, it does not have the harmful side af-
fects [sic] (you dope fiend)....Some people who are slightly
overweight (not obese) are very emotionally disturbed be-
cause of society around them projecting the image that to be
thin is better. They could then abuse the drug to become overly
thin. Drugs for the MASSES. New drugs: Fad or PHAT."
To a certain extent, the students' article demonstrated a kind
of "institutional under life," which, in the writing classroom,
is a productive assertion of identity against the one being
taught. Robert Brooke, who adapted the sociological con-
cept to explain student behavior in writing classes, notes that
contrary to teacher responses that see such behavior as detri-
mental to instruction, such rebellion is actually productive
because it indicates that students are acquiring a necessary
critical distance from roles that are imposed on them. Ac-
cording to Brooke, such critical distance helps to form a more
self-aware professional identity: "If the student in a chemistry
class grew to think of herself as someone who thinks in certain
ways to solve certain problems rather than as someone who
must 'learn' equations to pass tests, then the student would be-
gin to see herself as a chemist, and to act accordingly."'I5s
The review process included in-class peer revision and in-
structor comments. Both of those audiences suggested the
writers consider the effect of their language on readers. The
student team needed to recognize that their article's message
could be undermined by inappropriate humor. While some
of the students' peers might have been attracted to an article
designed to entertain them, some of their peers would have
been offended rather than entertained. Additionally, many
newspaper readers seek information rather than amusement.
We tried to point out that the campus newspaper ultimately
serves the entire community and that student writing should
reflect an understanding of that community. Their final ver-
sion was titled "Obesity No More?" and led with "Have you
ever wondered why someone can pig out and stay thin, while
someone else can never seem to maintain a healthy weight?
If so, read on." The subsequent article replaced the earlier
joking tone with one that was more formal: "If the drugs are
approved, chemical engineers will be responsible for design-
ing the necessary processes to produce the drug for the masses.
252

Chemical engineers would also be working to produce the
drugs more efficiently....Obese people could abuse the drug to
become overly thin because of the influence of society. Society
projects an overwhelming image that being thin is better."
This group's end-of-course portfolios indicated that they
realized, in reflection, their initial drafts were offensive to
the life out of the paper. Their cover letters pointed out that
they were not interested in the topic from the beginning and
had tried to find a way to make it interesting to each other:
"Todd and I wanted to make it goofy enough for a college
student, yet we all knew that some of our jokes would go
over badly....We managed to put together a pretty crude pa-
per full of stupid remarks." Rather than reflecting a lack of
understanding of audience, these remarks suggest a kind of
rebellion against it. Hence, their first draft was written suitably
for their intended audience: their group. This draft also suited
their purpose, which was to entertain and be entertained.
The subsequent revisions indicate a kind of capitulation to
the educational system. As that same student noted in his
portfolio letter, "The group got together again and took out
all of the brazen humor to make what I thought was a dry
article." His comments reflect an understanding of the edu-
cational game in which the faculty audience is the final arbi-
ter as well as his refusal or perhaps inability to identify with
that audience. At this stage, he knows what his audience wants,
and given that a grade is at stake, he will give that audi-
ence what it wants, but he will not identify with it. Also,
he cannot fathom how someone would find the subject of
obesity drugs relevant or interesting, but he is willing to
play the language game.
This activity also made us question our experiences with
the racism discussion. Again, those activities reflect the stu-
dents' desire to play the language game, which they inter-
preted as testifying against racism but did not reflect an un-
derstanding of what they themselves did not experience di-
rectly. These students could not imagine racism's existence
any more than they could imagine how someone would want
it. Ultimately, both exercises attested to the need for educa-
tion that requires students to imagine conditions and groups
other than themselves as part of their intellectual maturation.

EVALUATION
We used several measures to assess student gains in knowl-
edge of the chemical engineering profession and writing ap-
proach. To assess student gains in knowledge of the profes-
sion, an external evaluator administered questionnaires and
conducted focus groups that categorized "knowledge" in three
dimensions: "activities of chemical engineers, industries
employing them, and issues faced by them." To assess writ-
ing gains and to assess the reliability of our portfolio assess-
ment, we used an external writing specialist. A final evalua-

Chemical Engineering Education

tion measure involved student self-assessment as expressed
in their portfolio cover letters.
After the first iteration of the course, the evaluator com-
pared first-year chemical engineering majors who had taken
the course to a control group of first-year chemical engineer-
ing students who had not. These pre- and post-comparisons
were not useful due to the relatively small sample sizes. As a
result, the evaluator turned to focus groups to provide a fuller
We did not conduct any longitudinal studies, but it has been
clear that students who took this course remained in the de-
partment. Many became active in the student AIChE society
and others were academically outstanding. We believe this
probably has more to do with the students' predisposition for
chemical engineering as a major than the effects of a one-
credit course.

0 Gains in Knowledge
of the Engineering Profession
The evaluator concluded that the project had succeeded in
producing gains in student knowledge of the activities in
which chemical engineers engage. One of the greatest
struggles for the students involved the group writing assign-
ments, which they found difficult to complete because of in-
compatible schedules. Some also felt the course required too
much writing for a single-credit course. In the second itera-
tion of the course we addressed the group logistics problem
by giving them more instruction in collaborative writing,
fewer collaborative writing assignment, and more in-class
time to write collaboratively. We did not decrease the fre-
quency of writing assignments as we felt they were crucial to
achieving our objectives.

10 Gains in Approach to Writing
To evaluate gains in student writing approaches, we de-
signed a portfolio evaluation rubric that we provided to stu-
dents at the beginning of the course. The rubric identified
nine key criteria, each of which was ranked "Superior,"
Good," "Acceptable," or "Unacceptable." A majority of "Su-
perior" rankings earned the portfolio an "A"; a majority of
"Good" earned a "B;" a majority of "Acceptable" earned a
"C," and a majority of "Unacceptable" earned an "NR" ("Not
Recorded," which is equivalent to a fail grade; WPI does not
have a "D" or "F" grade). The portfolio review criteria were
Demonstrates a robust understanding of the chemical
engineering profession
Shows sustained original, logical thinking
Has strong organization at the paragraph and global level
Demonstrates a strong sense of audience and voice; language
is creative and appropriate; uses active voice wherever
appropriate
Uses grammar and mechanics to enhance meaning; has an
interesting, credible voice
Supports points thoroughly

Takes risks that challenge the reader
Is professionally presented
Is complete and on time
DiBiasio and Lebduska then evaluated each portfolio in-
dependently. That is, we did not share our evaluations until
we had ranked all of the portfolios. Although there was some
disagreement over the ranking of specific criteria for certain
portfolios, our overall rankings of the portfolios corresponded
exactly, suggesting reliability. To further assess the reliabil-
ity of our measures, the external writing specialist evaluated
the portfolios using the same rubric and without knowledge
of our evaluations. With the exception of one portfolio, her
assessments correlated with ours, again suggesting a fair
amount of portfolio assessment reliability. In the case of the
exception, the evaluator assessed a grade of "NR," while
we had each assessed it as a "C." In reviewing the materi-
als, we concluded that our assessments had been influ-
enced by our knowledge of the student, his participation
in class, and the effort we assumed he had devoted to a
low-credit, voluntary course.
The external evaluator of the portfolios concluded that "this
course experience, as reflected in the student portfolios [was]
valuable in contributing to student learning,"['21 but noted that
although the students' portfolio cover letters did reflect on
their learning, they did not demonstrate an understanding of
how the course's various assignments were related. We at-
tempted to address this deficiency by giving clearer letter-
writing guidelines in the second iteration of the course.
Perhaps the greatest insights about the course came from
the students themselves. Most of them recognized the mar-
ketability of the skills the course provided. The following
quotes, which validate our interactionalist approach, are rep-
resentative of what students wrote in their portfolio cover
letters. One student, for example, wrote
Unless an engineer is involved in solitary research and development,
he or she cannot expect to survive in the job market without superior
communication skills. These skills are needed to get hired via an
interview, to coherently and precisely express problems to the brass of
the company, and to write technical reports that management can read
without first acquiring an engineering degree.
Another wrote
On the field trip day I was very excited....The plant tour was
unexpectedly amazing. It was nothing like those I saw in the movies.
Another interesting fact was that the whole building was designed to
be explosion proof even inside the elevator... Chemical Engineering
and Communications class was a very unique opportunity offered to
me. It was nothing like other classes in WPI where I took notes on the
lectures and discussed them in groups, I felt that I learned something
new every class meeting. It was like a combination of different subjects
that would help prepare a future Chemical Engineer for the real world
out there.
And finally
What did I learn from this course? Well, I was exposed to environmen-
tal conservation organizations and I saw equipment used at the
industrial level being implemented to be environmentally friendly....!
Continued on page 261.

Fall 2003

[ME, classroom

SENSITIVITY ANALYSIS IN

ChE EDUCATION*

Part 2. Application to Implicit Models

WILLIAM R. SMITH, RONALD W. MISSEN**
University of Ontario Institute of Technology Oshawa, Ontario, Canada LIH 7K4

In Part 1 of this series,t1" we emphasized the importance
of sensitivity analysis (SA) in chemical engineering peda-
gogy and described its application to the class of engi-
neering models expressible in explicit form, y = f(x;p). Here,
in Part 2, we consider applications of SA to the more com-
plex class of models expressed in the implicit form,
f(y, x;p) 0 (1)
where y is the vector of N outputs, x is the vector of J system
variables, and p is the vector of K constitutive parameters.
Implicit models can take many forms; their distinguishing
property is that Eq. (1) cannot be "solved analytically" for y
in terms of the inputs (although we typically assume that the
solution of the equations is unique).
In Part 1, we showed how to use SA to determine and em-
ploy the sensitivity coefficients of the output quantities with
respect to x and to p. In this paper, we similarly discuss SA in
relation to several types of implicit models, including sets of
nonlinear equations, systems of ordinary differential equa-
tions, and unconstrained optimization problems (including
regression analysis). For an explicit model, determining the
sensitivity coefficients is relatively straightforward; for an
implicit model, this is usually a more complex task.
We then demonstrate the use of SA for a particular implicit
model arising in thermodynamics concerning two-phase equi-
librium of a pure substance, for which the underlying model
is a set of nonlinear equations with one system variable and
several constitutive parameters. Since calculation of the sen-
sitivity coefficients for an implicit model is a more complex
task, we focus here on their calculation and use for the sys-

* Part 1 appeared in Chem. Eng. Ed., 37(3), 222, 2003
**University of Toronto, Toronto, Ontario, Canada M5S 3E5

tern variable and for the constitutive parameters. We use the
former to illustrate the use of SA as a unifying theme, in this
case involving thermodynamics; we use the latter to address
items la and lb of Part 1.111 Thus,
1. We show the application of SA to the set of nonlinear
equations for vapor-liquid equilibrium (pure sub-
stance) arising from equating the chemical potentials
and pressures of the coexisting phases. The resulting
implicit model determines the coexistence properties
(output quantities) {p,vg,v e } in conjunction with an
EOS involving the three constitutive parameters:
critical temperature, T., critical pressure, P., and
acentric factor, o. Here, p" is the vapor pressure, and
v9 and vt are the molar volumes of the vapor and
liquid phases, respectively. From this model, we
calculate the first- and second-order sensitivity
coefficients of the output quantities with respect to
the single system variable, T.
2. We show how SA can be used to calculate the
uncertainties of the outputs {pvg,v } in terms of the
uncertainties of the constitutive parameters {T, Pc,

William R. Smith is Professor and Dean of Science at the University of
Ontario Institute of Technology. He received his BASc (Eng. Sci.) and
MASc (Chem. Eng.) degrees from the University of Toronto, and his MSc
and PhD degrees in applied mathematics from the University of Waterloo.
His research is in classical and statistical thermodynamics. He is co-au-
thor of Chemical Reaction Equilibrium Analysis (1982, 1991).
Ronald W. Missen is Professor Emeritus (chemical engineering) at the
University of Toronto. He received his BSc and MSc degrees in chemical
engineering from Queen's University and his PhD in physical chemistry
from the University of Cambridge. He is co-author of Chemical Reaction
Equilibrium Analysis (1982, 1991) and Introduction to Chemical Reaction
Engineering and Kinetics (1999).

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

w } of an underlying three-parameter EOS employed
in the nonlinear equation model for pure-fluid vapor-
liquid equilibrium.

OVERVIEW OF IMPLEMENTATION OF SA
FOR IMPLICIT MODELS
As discussed in Part 1, the implementation of SA requires
calculation of sensitivity coefficients. For an explicit model,
their calculation is relatively straightforward; for an implicit
model, their calculation depends on the particular type of
model. We briefly sketch how sensitivity coefficients are cal-
culated for several implicit models arising in chemical engi-
neering: sets of nonlinear equations, systems of ordinary dif-
ferential equations, and unconstrained optimization. The re-
sulting expressions are scattered in the literature, and it is
useful to present them all here.
For an implicit model defined by a set of nonlinear alge-
braic or transcendental equations
fi(y,x;p)= 0 i=1,2,...,N (2)

the first-order sensitivity coefficients of y with respect
or p are obtained by partial differentiation using the cl
rule. Thus, for the system variables x

@Y~ (af, '
axji axj

k=1 Yk

i = 1,2,..., N; j = 1,2,...,

where denotes evaluation at the solution to Eqs. (2). E
tions (3) are a set of NJ linear algebraic equations in the
sitivity coefficients 3yk/8x.. The result for the sensitivity
efficient ayk/8pj is analogous to Eqs. (3). We illustrate
low the use of Eqs. (3) by means of a numerical example
An implicit model defined by a system of first-order o
nary differential equations (ODEs) is expressed as

dyi gi(y,t; x,p)
dt

i = l,2,..., N

to x
chain

SA can serve as a unifying theme
for various topics involving engineering
models since, among other things, it can
show the relative importance of changes in
input quantities as they affect output
quantities ("the solution").

The corresponding equations for ayax. are obtained by re-
placing pj with x,.
We can also consider the initial conditions of Eq. (5) as
additional constitutive parameters; the sensitivity coefficients
with respect to these are given by the analogs of Eqs. (6) and
(7),

d (ayj ) N _i 1( aYk,

(a i
SayJ J(O -

i, j = 1, ,2,..., N

i,j = 1,2,..., N

where 8 is the Kronecker delta.
Equations { (6)(7) } and { (8)(9) } are initial-value problems
J for sets of first-order nonlinear ODEs for the sensitivity co-
efficients, which may be solved numerically simultaneously
(3) with the model, Eqs. {(4)(5)}. They appear in the literature
in various places relating to differential equations; a relatively
qua- early treatment is given by Cukier, et al.121
sen-
co- For an implicit model defined by an unconstrained optimi-
be- zation problem

e.
>rdi-

min f(y; p)

the outputs are the values at the optimal solution, y*. The
first-order necessary conditions for optimization are

yi(0)= yoi i= 1,2,...,N (5)
The first-order sensitivity coefficients of Eq. (4) with respect
to the constitutive parameters p are obtained by differentia-
tion of Eq. (4) to give

d y (@iy+ N_ (__gi )(Yk
Sdt=pkj .Y..pj
i = 1,2,...,N; j = 1,2,..., K

~-(a () = 0

(y; p)= 0
ayi

i= 1,2,..., N

To calculate the sensitivity coefficients of the optimal solu-
tion to changes in the constitutive parameters p, we can treat
Eqs. (11) as a set of nonlinear equations and apply Eqs. (3) to
give

N ( 2f *(,y* ( a2f

j=1y,.yj P k a J 1y PkJ
i =1, 2,..., N; k = 1, 2,..., K (12)

Equations (12) are a set of linear algebraic equations for
(7) ay,*/8pk involving the second-order coefficients of f at the
optimum, (82f/yiayj)* and (82f/ayiPk)*'

Fall 2003

We can also consider changes involving functions of the
output variables y in an implicit model. For example, a typi-
cal parameter-estimation problem involving an engineering
model can be viewed as an implicit model in which the pa-
rameters are outputs y obtained by minimizing the sum of
squares of deviations of a model from a set of observed data.
The values of the objective function at parameter values near
the optimal solution are important in determining their joint
confidence regions03J (their uncertainties in a statistical sense).
Thus, the change in the residual-sum-of-squares objective
function, Af, from the optimal value is given approximately
by the Taylor expansion

Af 6

+N N( a~ *8iy
+ = i j= 1 y1a y jJ y y =

N N ( 2 Y
| |_-)l 8yi8YJ (13)
i=1 j=J ayiyj

where the first-order term vanishes because of Eqs. (11).
Equation (13), involving the second-order sensitivity coeffi-
cients, defines an ellipsoidal confidence region for the pa-
rameters for a specified value of Af. This region, defined by
the set of all parameter values such that the right side of Eq.
(13) is less than or equal to the left side, can be viewed as the
parameter region that yields an acceptable uncertainty in the
residual sum of squares.

-1-

SENSITIVITY COEFFICIENTS FOR
COEXISTENCE PROPERTIES
OF VAPOR-LIQUID EQUILIBRIUM

For a pure fluid, {pI,vg,v } are output quantities arising
from a model consisting of a set of three nonlinear equations
involving an EOS that is assumed to be applicable to both
liquid and gas/vapor phases. The model equations result from
equating the chemical potentials and the pressures of the co-
existing phases (at a given T). The former equality gives rise
to Maxwell's equal-area rule[4] (first enunciated independently
by Maxwell151 and by Clausiust61)

rv[T;p]
p [T;p](vg[T;p]- v'[T;p])= J P(v,T;p)dv (14)

where P(v,T;p) represents the EOS, and we explicitly denote
the dependence of the outputs on the system variable T and
the constitutive parameters of the EOS, p. (Equation 14 was
given, in effect, by Planck.M7t) The pressure equality results in
two additional equations involving the EOS

p[T;p] = P(vg[T;p], T)

p'[T;p] = P(v[T; p], T)

The numerical solution of Eqs. (14) to (16) is part of the cal-
culations described in the following example.
We now turn our attention to the sensitivity coefficients for
this implicit model. Equations (14) to (16) are three equa-
tions in the three outputs {pf,vg.v e }, with the system vari-
able T, for a given set of constitutive parameters, p (which
we consider to be fixed in this section, and for simplicity
suppress their appearance in the following equations). We
carry out a first-order sensitivity analysis of the model by
differentiating the equations with respect to T, to give a set of
three linear equations for the sensitivity coefficients

(dpa / dT), (dvs / dT) and (dv' / dT)

in the form of Eqs. (3). The notation signifies evaluation at
the solution of Eqs. (14) to (16). These are ordinary (as op-
posed to partial) derivatives, since there is a single system
variable, T.
Differentiation of Eq. (14) (involving differentiation of the
integral) gives
dTP g -vT)= (v,T)dv (17)

dT 'v
Differentiation of Eqs. (15) and (16) (involving application
of the chain rule) gives

dT aT v V ~vTL

dp0 (aP) + (aPY' dv~
dT a T v~ a v )TdT)0a

In these equations, with respect to the derivatives on the right
side, uT denotes "along the saturation curve," and superscripts
g and e refer to evaluation at (vg,T) and (v 1,T) respec-
tively; all quantities are evaluated at the saturation conditions
corresponding to {p",vg,v 1,T}.
The sensitivity coefficients are available analytically from
Eqs. (17) to (19) as

v( v,T)dv
dT (20)

(dv9~
SdT)

dp0 (rapg
dT (BT), ( v g dp+ ( v)
ap (-P )T dT aT p
,aV JT

Chemical Engineering Education

(ae dT YT )v av jdpa aj
e~T aP dT aT
dT T (a

where the cyclic derivative rule has been used to obtain the
final terms in each of Eqs. (21) and (22). (Equations of the
type of 21 and 22 were obtained by Planck.171)
Equations (20) through (22) can be differentiated again to
obtain the second-order sensitivity coefficients on the satu-
ration curve, which are given by

d2pa I ap ___'dvg) ap dv_
dT2 v 7 T) JdT (aT) AvdT

dpa (dv, (dv) ] vg (a2p, (
dT L -+ r(v, Tr)dv (23)
ddT JdT dT jv aT2, vT2

(d2vg

d2p (02p (2p (dv )2 (2P g(dvg
dT2 12 av2 dT avaT dT,

p )T
(av j
(24)

(d2Ve
LdT2_J

d 2p- (a2p)' (a2p~ ( dvf )2 ( 2p Wdcvt
d1 ~2 2TdT Ja LavaTr J LdT~

aV )T
(25

-2-

UNCERTAINTY ANALYSIS OF VAPOR
PRESSURE WITH RESPECT TO
THE CONSTITUTIVE PARAMETERS (Pc,TC, 1)
The sensitivity coefficients of y, with respect to the consti-
tutive parameters p, can be obtained by differentiating Eqs.
(14) through (16) at each T. The normalized sensitivity coef-

ficients {3p'/3pj, avg/pj, 3v I/ap } are given by the analogs
of Eqs. (20) through (22) as

( aP 1
aIn y_ a inp! PJvi tJJ(V'T)dv (26)
aInpj aInp pj ep va-vp

apa ( ap g
a1ny2 lnvg) f V pj Pj j (27)p
a1npj 1alnpj (vS apg
aV JT

'Dp0 apY
alny3 r(alnfl2 aPJ~ a
In pj I~n pj9ve r afl
( aV )T

The derivatives aP/a3p on the right side are evaluated from
the EOS holding fixed v and T, and all parameters other than
pJ. The derivatives (3P/av)T are evaluated at fixed values of
all constitutive parameters, as in Eqs. (20) through (22).
If we denote the relative uncertainties in the three constitu-
tive parameters by u(ln pJ), the relative uncertainties in the
three output quantities, u(ln yi), are given by the analog of
Eq. (9) of Part 1 '

u2 (lnyi)=J In p u(np) (29)

where we assume that the input uncertainties are uncorrelated.
The upper and lower (95%) uncertainty limits for y, are then
calculated from

yi (upper)= yi exp[2u(ln yi)]; yi (lower)= yi exp[-2u(ln yi)]

NUMERICAL EXAMPLE
As a numerical example of items la and Ic of Part 11 or 1
and 2 above, we consider the calculation of {pFvg,v I} for
5) toluene, their sensitivity coefficients with respect to {T,Pc,() }
as functions of T from the triple-point temperature, Tt, to TO,
and the use of the latter in uncertainty analysis in conjunc-
tion with the Peng-Robinson EOS181

RT a(T)
P=
v-b v(v+b)+b(v-b)
where
2 2
a(T) = 0.45724 c a(T)
Pc

Fall 2003

b = 0.07780 RT
Pc

oa(T) = (1+ K(W)[1-(T/Tc)+5l)2

K(Wo) = 0.37464 + 1.54226w 0.26992 X2

The derivatives required in Eqs. (26) through (28) are given
from Eqs. (31) through (35) by

aP RT ( 31nb ) ( alnb 2ba(T)(v-b)
--b + ____
3pj (v-b)2 1npjj l1npj [v(v+b)+b(v-b)]2

a(T) (alna(T) 36)
v(v+b)+b(v-b)l ainp J

a 1na(T)2+ a In a(T) 2+(T)]-5 (37)
SIn Tc 3InT c TcI

a In a(T)_ 1 (38)
n P, 1 (38)
a In Pc

alna(T) alna(T)_ (T '5I In Kc(o)
a 1n o 3ano ) Tc) jL 3lno J

2) _1- (1.54226-0.53984 o) (39)
[x(T)]o" Tc

a-ln =1 (40)

-=-1 (41)
a In Pc

a1nb
a = 0 (42)

CP) RT 2a(T)(v+b)
lav T (v-b)2 [v(v+ b)+ b(v-b)]2

We have used Maple[91 to calculate the coexistence proper-
ties {p,vg,v I } from Eqs. (14) through (16) and their sensi-
tivity coefficients from Eqs. (26) through (28), with pj =
T ,P,w in turn. A Maple script is available on the web site at
.
Figure 1 shows the normalized sensitivity coefficients with
respect to the constitutive parameters {P,To,w} as functions
of T, from the triple-point temperature, T, to T., using the
nominal parameter values for toluene of'01 {42.365 kPa,
593.95 K, 0.26141 } (wo was calculated from the vapor pres-
sure equation given by Goodwin"t01). The ordinate values can

Figure 1. Normalized sensitivity coefficients with respect
to {Pc, T,,w for toluene from PR EOS over entire liquid
range (Tt = 293.15 K to T = 593.95 K):
(a) for p"; (b) for v8; (c) for ve.

Chemical Engineering Education

10
alnp'/8inP,

-10
D1np'/81nT.
-20 /O

, -30

-40

-50
100 200 300 400 500 40 700
T, TT/K T

a ina va/ 1n u

-10

-20
nv'/81nT,
-30

40

-50 i
100 200 300 400 500 600 700
T/K T-

-C

258

be interpreted as the % change in the output for a 1% change
in the input.1'1
The most important parameter for all three output variables
is TC. For p, (Figure la), the sensitivity coefficient with re-
spect to Tc is negative, and increases in magnitude from about
7% near Tc to over 28.5% at the triple point (T, = 178.15
K1101). The corresponding coefficients of vs (Figure lb) and
v (Figure 1 c) both become infinite in magnitude at Tc. At
lower temperatures, the coefficient of v9 is much larger in
magnitude than that of v 1. The latter coefficient decreases
from 0.9 at Tt to become negative at T = 461 K, and increases
rapidly in magnitude as T approaches Tc. The former coeffi-

Figure 2a. Vapor pressure (p) for toluene (178.15 K(T,) to
593.95 K (T)); central curve (nominal value) obtained from
PR EOS; points are experimentalilol outer curves define 95%
uncertainty bands (see text).

10-3 10-2 101 100 101 102 103 104 105 106 107 10.
v/L mol"
Figure 2b. Liquid-vapor binodal curve for toluene (T-v co-
ordinates); central curve (nominal value) obtained from PR
EOS; points are experimental;(ooJ outer curves define 95%
uncertainty bands (see text); the inset shows the breakdown
of the first-order SA expansion for the uncertainty bands
near TC (see text).

Fall 2003

cient is always positive, starting at 28.5 at Tt, going through a
minimum at T = 486 K, and rapidly increasing in magnitude
as T approaches Tc. Voulgaris, et al.,1"1t have also reported on
the "extreme sensitivity of p to To" for various fluids, al-
though they did not use SA in their investigation.
The sensitivity coefficients with respect to Pc are much
smaller in magnitude than those with respect to T., and all
have constant numerical values (+1 for p" and -1 for v9 and
v K), results not anticipated prior to the numerical calcula-
tions. In retrospect, however, it was realized that this follows
from the fact that the Peng-Robinson EOS is, in effect, a two-
parameter EOS with the acentric factor w incorporated into
the parameter a, via a function of the reduced temperature,
T = T/T For all such EOS, including a strictly two-param-
eter EOS such as the van der Waals, the reduced vapor pres-
sure, p'/Pc, is a universal function 01 of T, and w

pa = P,0l(Tr,o) (44)

Differentiation of Eq. (44) then gives

lnp-1 (45)
SlnPc

as in Figure la.
Similarly, as in Eq. (44), the liquid and vapor saturation
volumes are also universal functions of T and w

vg = v42 (Tr,O));

v = Vc03(Tr,O)

Also, the Peng-Robinson or similar EOS each has a univer-
sal value of the compressibility factor at the critical point

zc-= P(47)
RTc

Taking logarithms and differentiating both members of Eq.
(46) and Eq. (47) with respect to In Pc, we obtain

aInv 1ainvy
-1 (48)
aIn P aInPc

as in Figures lb and Ic.
The sensitivity coefficients with respect to w are also much
smaller in magnitude than those with respect to T with that
of p" being the largest. This coefficient (Figure 1a) is nega-
tive and increases from -5.2% at T, to zero at T. The coeffi-
cient of v9 with respect to w (Figure lb) is positive and de-
creases from 5.2% at T, to zero at Tc; for v it is negative and
very small (of magnitude less than 0.06%).
Figure 2 shows the output quantities p" (Figure 2a), and vt
and vs (Figure 2b) in the form of the T-v binodal curve, to-
gether with uncertainty bands calculated from Eqs. (29) and
(30), assuming 2.5% uncertainties in each of the constitutive
parameters, {P,,T,wo}, i.e., with 2u(ln pj) = 0.05. The experi-
mental points in Figure 2a, for comparison with the calcu-

lated PR EOS results (nominal values), are given by
Goodwin."101 The relatively large uncertainty of 2.5% in the
parameters was chosen to illustrate relatively large uncertainty
bands for the outputs. For a species such as toluene, 2.5% is
a much greater uncertainty than arises from experimental
measurements.tl21 If the critical constants must be estimated,
however, the uncertainties may be of comparable or greater
magnitude.Ell,131
In Figure 2a, the uncertainty bands for p" arise primarily
from the uncertainty in T., as indicated by Figure la. The
spread of the uncertainty bands increases as T -) Tc. This is
because, although the relative sensitivity coefficient decreases
as T increases (Figure la), the value of pa increases more
rapidly. At low temperatures (below about 350 K), the rela-
tively large sensitivity coefficient applies to very small val-
ues of p", and the resulting spread is imperceptible on Figure
2a. For CO2, a substance with a much larger vapor pressure
at T,, the uncertainty bands are more prominent, even for 0.5 %
uncertainty (not shown here).
In Figure 2b (in which the abscissa is a logarithmic scale),
below T. (up to about 550 K), there is a considerable uncer-
tainty spread in the vg values, but this is barely perceptible in
the v e values. The reasons for this correspond to those for
the corresponding spreads in the p6 values. As T. is ap-
proached, the uncertainty bands approach infinite magnitude,
because of the similar behavior of the sensitivity coefficients
of v9 and v e with respect to Tc; these coefficients completely
dominate the determination of the uncertainty bands. In this
region, the first-order SA expansion corresponding to Eq. (30)
gives these as

vg= vg(593.95)exp[2u(ln T) (a In v9
(a~lnT

V =vI~ti.~~texpLuI n ve) I
v =V(59.95)xp12u~l~c) aIn T, Ij

(49a)

(49b)

The inset shows the breakdown of this expansion near the
critical point, using an even smaller uncertainty in To of 0.5%
(2u(ln T) = 0.01). The solid curves are the actual binodal
curves calculated using parameter values for TC of 1% above
and below the nominal value of T = 593.95 K. The dashed
and dotted curves are the results for vg and v t, respectively,
from Eq. (49a,b); a few degrees below (the nominal) T., they
agree with the solid curves, but near T they become increas-
ingly inaccurate.
This example shows that one must beware when sensitiv-
ity coefficients become infinite in magnitude. The first-order
SA expansion cannot be applied to situations when the out-
put variable is not analytic for some values of the input quan-
tities, i.e., does not have a Taylor series expansion. The phe-
nomenon we have discovered numerically here is related to

the non-analyticity of the quantity (vsat- vc) as a function of
(T- T-).J141

CONCLUSIONS (Parts 1 and 2)
1. Sensitivity analysis (SA) is an important pedagogical
topic that should be explicitly included in the chemi-
cal engineering curriculum in many courses.
2. SA can serve as a unifying theme for various topics
involving engineering models, since, among other
things, it can show the relative importance of changes
in input quantities as they affect output quantities
("the solution").
3. SA is applicable to both explicit engineering models
(Part 1) and implicit ones (Part 2), whether they
involve algebraic, transcendental, or differential
equations, or optimization problems.
4. The elementary aspects involving sensitivity coeffi-
cients can be introduced into the undergraduate
curriculum, since they only require a background in
multivariable calculus. This includes an introduction
to uncertainty analysis.
5. Additional aspects of SA may have to be deferred to
the graduate curriculum. These include overall effects
of changes in system variables on the solution, which
needs a background in linear algebra, which, in turn,
may not be required of all undergraduates.

ACKNOWLEDGMENTS
Financial assistance has been received from the Natural
Sciences and Engineering Research Council of Canada. C.
Stuart assisted with the graphics.

REFERENCES
1. Smith, W.R., and R.W. Missen, Chem. Eng. Ed., 37(3), 222 (2003)
2. Cukier, R.I., H.B. Levine, and K.E. Shuler, J. Comput. Phys., 26, 1
(1978)
3. Draper, R.N., and H. Smith, Applied Regression Analysis, 3rd ed., John
Wiley & Sons, New York, NY (1998)
4. Hanif, N.S.M., G.-S. Shyu, K.R. Hall, and P.T. Eubank, Ind. Eng. Chem.
Res., 35, 2431 (1996)
5. Maxwell, J.C., J. Chem. Soc., 28, 493 (1875)
6. Clausius, R., Phil. Mag., Ser. 5, 9, 393 (1880); 12, 381 (1881)
7. Planck, M., Ann. Physik u. Chem., Ser. 3, 15, 446 (1882)
8. Peng, D.-Y., and D.B. Robinson, Ind. Eng. Chem. Fundam., 15, 59
(1976)
9. MAPLE is a registered trademark of Waterloo Maple, Inc.
10. Goodwin, R.D., J. Phys. Chem. Ref Data, 18, 1565 (1989)
11. Voulgaris, M., S. Stamatakis, K. Magoulas, and D. Tassios, Fluid Phase
Equilib., 64, 73 (1991)
12. Tsonopoulos, C., and D. Ambrose, J. Chem. Eng. Data, 40, 547 (1995)
13. Poling, B.E., J.M. Prausnitz, and J.P. O'Connell, The Properties of
Liquids and Gases, 5th ed., pp. 2.2-2.26, McGraw-Hill, New York,
NY (2001)
14. Rowlinson, J.S., Liquids and Liquid Mixtures, 2nd ed., Chapter 3,
Butterworth, London, U.K. (1969) 0

Chemical Engineering Education

Mixing Writing with First-Year Engineering

Continued from page 253.
was subjected to morally stimulating situations which made me think,
which is novel and frightening. And finally I was presented with two
projects that would be assigned to everyday chemical engineers. In my
opinion I feel that I have learned something about the chem. eng.
profession and that I must remember to communicate my ideas to
others succinctly and clearly as I take the roller coaster ride of
education towards the tunnel of real life working environments.

CONCLUSIONS
For both students and faculty, this course experiment
seemed to move in a promising direction. On a professional
development level, the activity lessened the widening "gulf
of mutual incomprehension" between scientists and human-
ists that C.P. Snow said threatened the quality of intellectual
life."'61 DiBiasio and Lebduska each gained insight into how
the other half lived, into the priorities informing engineering
and humanities education, and on how the two sides, too of-
ten thought of dichotomously, might speak to each other in
the classroom. Equally important was the opportunity to al-
low students to hear the conversation-that is, to experience
chemical engineering as a practice that is informed by hu-
manities values, including clear and ethical communication.
Our conclusion is that mixing writing and first-year engi-
neering is certainly a stable solution when the experiment is
properly conducted. In our opinion, the unstable solution,
represented by segregated technical writing courses and en-
gineering writing that emphasizes only lab reports, is not as
productive. Ensuring stability takes energy, time, and com-
mitment from the faculty, however-it's a challenging and
difficult process, but it is rewarding and fun. The students
will also be challenged, not just by trying to understand a
profession they think they want to pursue, but also by being
engaged in thinking through writing. Generally, that's a new
concept for most of them.
For the most part, the activities we designed accomplished
our original goals while providing us with greater insight into
first-year students. In her evaluation of the portfolios, the
external writing specialist noted

Such opportunities for students to reflect on their learning-what
they learned, what it means, why it is important, etc.-are critical
components of effective portfolios, and they distinguish portfolios
from other kinds of student learned assessment (tests, essays, and
so on)."'21

The course experience, in other words, not only provided stu-
dents with information about chemical engineering, but it
offered them an opportunity to gain knowledge about it-
that is, a means by which they could reflect about the infor-
mation and place it within the context of their overall lives.
Despite problems such as course logistics, students' time
constraints, and a kind of cultural resistance to writing, most
students demonstrated growth in their knowledge of the pro-

fession and their use of communication as a learning tool.
Additionally, we discovered that a collaboration between
seemingly unrelated disciplines aids in faculty development
(an opportunity to see how the other half thinks), but to be
truly effective this approach needs to be transported be-
yond the two involved faculty members to a more global-
ized WAC endeavor.

Recently, the chemical engineering department voted to
expand the course and now offers a full 3-credit introduction
to chemical engineering on a two-year trial basis. The course
counts toward graduation requirements and it is expected to
become a permanent part of the department's curriculum.

REFERENCES

1. Roberts, S.C., "A Successful Introduction to Chemical Engineering
First-Semester Course Focusing on Connection, Communication, and
Preparation," Proceedings of 2000 Annual Meeting of AIChE, Los
Angeles, Chemical Engineering in the New Millenium, 406 (2000)
2. Young, V.L., "Technical Communication and Awareness of Social Is-
sues for Sophomores," Proceedings of 2000 Annual Meeting of AIChE,
Los Angeles, Chemical Engineering in the New Millenium, 399 (2000)
3. Yokomoto, C.F., M. Rizkalla, C. O'Laughlin, M. El-Sharkawy, and N.
Lamm, "Developing a Motivational Freshman Course in Using the
Principle of Attached Learning," J. Eng. Ed., 88(2), 99
4. Balley, R., and C. Gelsler, "An Approach to Improving Communica-
tion Skills in a Laboratory Setting," J. Chem. Ed., 68(2), 150 (1991)
A Study of the Contexts for Writing in Two College Chemical Engi-
neering Courses," Landmark Essays on Writing Across the Curricu-
lum, Charles Bazerman and David Russell, eds., Hermagoras Press,
Davis, CA (1994)
6. Mair, D., and J. Radovich, "Developing Industrial Cases for Technical
Writing on Campus," JAC 6,
(1985)
7. Lablanca, D.A., "Writing Across the Curriculum: A Heretical Perspec-
tive," J. Chem. Ed., 62(5), 400 (1985)
8. Aaron, D.K., "Writing Across the Curriculum: Putting Theory into
Practice in Animal Science Courses," J. Animal Sci., 74(11), 2810
(1996)
9. Hendricks, R.W., and E.C. Pappas, "Advanced Engineering Educa-
tion: An Integrated Writing and Communication Program for Materi-
als Engineers," J. Eng. Ed., 85(4), 343 (1996)
10. Flynnm, E.A., K. Remlinger, and W. Bulleit, "Interaction Across the
Curriculum," JAC 17.3,
11. Gurland, S.T., "Bridge Project: Communications and Chemical Engi-
neering," unpublished external evaluation (2000)
12. Williams, Julia, "Final Evaluation: Chemical Engineering and Com-
munication Bridge Course," unpublished external evaluation (2000)
13. "Texaco Settles Bias Suit," Posted 15 November 1996; Accessed 13
October, 1999: texaco_settle/a/index.htm>
14. Villanueva, Victor, "On the Rhetoric and Precedents of Racism," Col-
lege Composition and Communication, 50(4), 645 (1999)
15. Brooke, Robert, "Underlife and Writing Instruction," College Com-
position and Communication, 38(2), 141 (1987)
16. Snow, C.P., The Two Cultures, Cambridge University Press, Cambridge,
England (1959) 0

Fall 2003

[,1=1 laboratory

A BATCH FERMENTATION EXPERIMENT

FOR L-LYSINE PRODUCTION

In the Senior Laboratory

DAVID R. SHONNARD, EDWARD R. FISHER, DAVID W. CASPARY
Michigan Technological University Houghton, MI 49931-1295

Biochemical processes are finding increasing applica-
tion in the chemical industry for the production of a
wide variety of products from renewable resources.
These products include pharmaceuticals, consumer and food
products, fuel additives, industrial enzymes, and many oth-
ers. They are typically created using batch processing, a
marked departure from the more traditional continuous pro-
cesses for commodity chemicals. Recent graduates from chemi-
cal engineering programs are finding more opportunities for
employment in industries that use biochemical processes and
perhaps fewer opportunities on a percentage basis in traditional
commodity chemical and petrochemical production.1[1
Biochemical processes are complex, involving multiple
steps in converting raw material into products. In addition,
preparation steps and downstream separations are not typical
of traditional chemical processing. Examples of chemical en-
gineering laboratory experiments using biochemical processes
have recently appeared.[2-41 In these experiments, ethanol is
typically produced in short-duration experiments that are, by
necessity, abbreviated and less complex than most industrial
fermentations. In order to prepare undergraduates for oppor-
tunities in biochemical processing and to provide a labora-
tory experience with a complexity similar to a commercial
process, we have developed a batch fermentation experiment
to produce L-lysine for the senior laboratory.

In this experiment, student groups produce L-lysine, an
essential amino acid, from a glucose minimal defined media
scribe the pedagogical approach, the objectives for a semes-
ter-long design of experiments, and key results from the fer-
mentation experiment.

Figure 1.
Batch
Medi fermentation
Sterilizer Air Filter experiment
for L-lysine
product from
a defined
minimal
media
containing
A- .. 5-L Batch glucose

David R. Shonnard is Associate Professor in the
Department of Chemical Engineering at Michigan
Technological University. His research and teach-
ing interests are in the areas of environmentally
conscious design of chemical and biochemical pro-
cesses, optimization, life-cycle assessment, and
cell-based in-vitro toxicology. He is coauthor of 2
books in environmentally-conscious design and
over 40 peer-reviewed publications.

Edward R. Fisher received his BSc from Berkeley
in 1961 and his PhD from Johns Hopkins Univer-
sity in 1965, both in chemical engineering. After
teaching for 35 years at Wayne State University and
Michigan Technological University, he recently re-
tired as Professor Emeritus in Chemical Engineer-
ing and Chemical Engineering Technology.

David W. Caspary is Manager of Laboratory Fa-
cilities in the Department of Chemical Engineer-
ing at Michigan Tech University He received his
BSc from Michigan Tech in 1982 and has held
several engineering positions with the ChE de-
partment over the past nineteen years. He is cur-
rently co-instructing the Chemical Plant Opera-
tions and Unit Operations Laboratory courses.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

N2 Air 02

OVERVIEW OF THE EXPERIMENT
The L-lysine batch fermentation experiment is shown sche-
matically in Figure 1. It is conducted using a 5-liter bioreac-
tor (New Brunswick Scientific BioFlow3000) and a data ac-
quisition and control system (New Brunswick Scientific
BioCommand). With this system, students study the kinetics
of microbial growth and L-lysine production under controlled
conditions of temperature, pH, dissolved oxygen (DO), and
agitation. Auxiliary equipment includes a mobile autoclave
sterilizer (New Brunswick Scientific) and a media
microfiltration unit (Fisher Scientific).
Approximately 60 to 100 senior-year chemical engineer-
ing students annually conduct the batch fermentation experi-
ment in the "Chemical Plant Operations Laboratory" course.
Due to the complexity of this experiment, students work in

L-aspartic aspartyl aspartyl @ L-homoserine L-threonine
acid 4 phosphate semialdehyde

dihydrodipicolinate a-ketobutyrate

diaminopimelate

----------- L-lysine L-methionine L-isoleucine

Figure 2. Feedback inhibition for regulation of L-lysine syn-
thesis within the cell. Dashed lines indicate feedback inhi-
bition of key enzymes in the metabolic pathway (solid lines).

TABLE 2
Experiment Plan for Cell Growth and L-lysine Production
(Amino acid base case values are L-threonine (150 mg/L),
L-methionine (40 mg/L), and L-leucine (100 mg/L)

Glucose Concentration (g/L)
Amino Acid Concentration 20 30
1. Low (50% lower) Team 2 Team 5
2. Base case Team 1 Team 4
3. High (50% higher) Team 3 Team 6

teams comprised of two 4-member groups. The fermentation
experiment requires two to three days of continuous opera-
tion to complete due to the slow kinetics of cell growth and
L-lysine production. Table 1 shows the sequence of events
for this experiment.

PEDAGOGICAL OBJECTIVES
The first pedagogical objective for the fermentation experi-
ment is to introduce the students to biochemical process equip-
ment and to explain the key steps for production of a bio-
chemical product. Because most of the graduating seniors have
little or no biochemistry or biochemical engineering experi-
ence, the experiment objectives are geared toward an intro-
ductory treatment. Prior to conducting the experiments, we
give a 2-hour orientation and provide background informa-
tion on L-lysine production using Corynebacterium
glutamicum (American Type Culture Collection, ATCC No.
21253), we conduct a tour of the laboratory, and hold a dis-
cussion of experiment objectives.
We give background information in an oral presentation to
the 8-member student team and describe cell growth in the
context of the major growth stages: lag, exponential, decel-
eration, stationary, and death. Specific metabolic character-
istics of C. glutamicum are described as shown in Figure 2. 51
We further explain that due to a mutation in the cellular DNA
by chemical treatment, this cell cannot convert aspartyl
semialdehyde to L-homoserine. In order to grow the cells on
a glucose minimal medium, L-methionine, L-isoleucine, and
L-threonine must be added in trace amounts. Once these
supplemented amino acids are consumed by growth, any re-
maining glucose is converted to L-lysine rather than cell mass.
We explain that concerted feedback inhibition of the enzy-
matic conversion of L-aspartic acid to a aspartyl phosphate is
relaxed as L-threonine is consumed, thus allowing overpro-
duction of L-lysine. When these concepts are understood, we
tell the students that cell growth and product formation are
expected to occur separately in the batch culture. One of
the objectives for the student teams is to test this hypoth-
esis and also to determine if the amount of supplemented
amino acids controls the maximum concentration of cells
in the fermentation.
The second part of the orientation is a tour of the labora-
tory facilities. We describe each piece of equipment and ex-
plain its purpose in the production of L-lysine. We empha-
size the importance of maintaining sterile conditions and show
the students the two methods of sterilization used; steam au-
toclaving for the bioreactor and microfiltration for the growth
media. We discuss scale-up and the need for coordinating
processes at smaller scales to support production at a larger
scale (e.g., flask-scale cultures for inoculating the fermenter
and the associated equipment). Finally, we explain that the
safety aspects of the laboratory are consistent with Biosafety
Level I requirements (Center for Disease Control, CDC). The

Fall 2003

TABLE 1
Schedule for L-lysine Experiment

Orientation Week 1
Proposal preparation Weeks 1 and 2
Pre-laboratory check-in Start of week 3
Laboratory experiment During week 3
Post-laboratory oral presentation During week 4
Final report preparation Weeks 4 and 5

last part of the orientation is a discussion of handout materi-
als (available upon request by e-mail from
) and a schedule for meeting the re-
quirements as outlined in Table 1.
Another pedagogical objective is to test the effects of ini-
tial glucose and amino acid concentrations on L-lysine pro-
duction and cell growth in a design of experiments. As shown
in Table 2, this design of experiments involves six teams dur-
ing the semester. The goal is to involve the student teams in a

Safety is integrated into all aspects
laboratory experience... In the design
phase ... a thorough safety review
of the bioprocessing equipment,
procedures, chemicals, and
biological organisms
was conducted.

continuous improvement exercise and to increase their un-
derstanding of how fermentation parameters affect cellular
growth and L-lysine production. Each team conducts an ex-
periment at different initial glucose and amino acid concen-
trations. During the semester, as experiments are completed
and results become available, sharing the data with the other
student teams is intended to increase the level of understand-
dent teams share their results by attaching reports and pre-
sentations to an e-mail to the instructor-the cumulative re-
sults (as shown later in Table 6) are then organized and dis-
seminated by the instructor to the student teams (by e-mail
attachment) during the final days of the semester.

EXPERIMENTAL METHODS
Following the orientation, each team prepares and submits
a proposal in which students demonstrate their familiarity
with the process equipment, the objectives, laboratory safety
(chemical, physical, and biological hazards), sample calcu-
lations, and the market aspects of their product. Because of
scheduling limitations, during the 52-hour experiment the
teams are split into two groups. One group from the team
initiates the fermentation over a 4-hour period. This involves
formulating the growth medium, assembling and autoclav-
ing the bioreactor, sterilizing the medium and transferring it
to the bioreactor using microfiltration, calibrating 02 and pH
probes, and finally inoculating with flask-grown cells. Dur-
ing the next 48 hours, all students in the team periodically
sample for cell growth, glucose consumption, and L-lysine
production (no sampling is done between midnight and 8 a.m.,
however).
Each run in the experiment plan is conducted under identi-
cal conditions of temperature (300C), pH (7.0), dissolved

oxygen (50% of saturation with air), and duration (52 hours).
The experiment objectives given to each team are shown in
Table 3. The maximum specific growth rate is obtained by
applying the Monod equation6]' to the definition of the spe-
cific growth rate, g, as
1 dX
=--- =(1)
X dt
where X is the concentration of cells in the medium (g/L).
The Monod equation is
S A
S= maxK SK A (2)

where tmax is the maximum specific growth rate constant
(hr'), S and A are the concentration of glucose and supple-
mented amino acids, respectively (g/L), and Ks and KA are
the half saturation constants (g/L). At the start of the fermen-
tation, S>>Ks, A>>KA, and therefore 9= imax in Eq. (1). The
solution to Eq. (1) for exponential growth is

n --X =maxt (3)
x0

For cell growth, samples from the bioreactor are taken at
2-hour intervals on the first day and at 4-hour intervals on
the second and third days. Mass concentrations are obtained
by first measuring the absorbance (at 500 nm wavelength,
A0, Milton Roy Spectronic 21D) and converting those val-
ues using the conversion factor, y (g dry cell wt./L) = 0.5x,
where x is A00. Every 8 hours, samples are taken for glucose

TABLE 3
Fermentation Experiment Objectives

1. Determine maximum specific growth rate, i.t (hr')
2. Measure glucose consumption (g/L)
3. Measure L-lysine production (g/L)
4. Determine cell growth yield, Yxs
5. Determine L-lysine production yield, Ypis

TABLE 4
Major Steps in the Experiment Procedure
for L-lysine Production in Batch Culture

1. Assembly of fermenter and microfilter for steam sterilization
2. Steam sterilization of fermenter and microfilter
3. Media preparation
4. Filter sterilization of culture media
5. Calibration of pH and dissolved oxygen probes
6. Initialize data acquisition
7. Fermentation
8. Sampling for cell, glucose, and L-lysine
9. Analysis of glucose and L-lysine samples
10. Shutdown and clean-up of fermenter

Chemical Engineering Education

and L-lysine analysis by filtering 5 ml of cell culture solution
through a 0.2 pim (polycarbonate, 25 mm dia. Millipore
GTTP02500) membrane and into a closed capped vial (20
ml) to remove cells. These samples are then stored in a re-
frigerator (4C) until the end of the experiment, when they
were analyzed together by the second group of the team. Glu-
cose concentration is analyzed using the hexoskinase/glucose-

TABLE 5
Composition of Defined Minimal Media for L-lysine
Production using C. glutamicum.
(All values are per liter of final solution)

20 grams D-glucose
5 g (NH4)2SO4
8 g KHPO,4
4 g KH2PO4
0.2 g MgSO4 7 H20
*1.0 g NaCI
0.5 g citric acid
20 mg FeSO4 7 H,O
50 mg CaCl2 2 H20
150 mg L-threonine
40 mg L-methionine
100 mg L-leucine
I mg biotin
1 mg thiamine HCI
10 ml 100x trace salts

100x Trace Salts Solution: per liter of distilled water
200 mg MnSO4
6 mg HBO3
4 mg (NH4)6Mo070 *4 H2O
100 mg FeC13 6 HO
1 mg ZnSO4 .7 HO0
30 mg CuSO4 5 H20
(pH of this solution adjusted to 2 to avoid precipitation)

25 I deceleration I stationary decline
1,E+01
.. I exponential -
20 2-
C 15 1,E+00 -

1,E-01 o
0 13
0 1,E-02
0 5 10 15 20 25 30 35 40 45 50
Time (hours)
-Glucose Lysine -- -Cells

Figure 3. Results for cell growth, glucose consumption, and
L-lysine production for initial concentrations of 20 g/L of
glucose and base case amounts of amino acid supplements.

Fall 2003

6-phosphate dehydrogenase method (INFINITY Glucose
Reagent, Sigma Scientific) and L-lysine concentration by
using the saccharopine dehydrogenase assay (Sigma Scien-
tific S-9383). The yield of cell growth on glucose consumed
(Yxis) is calculated as Yxis = AX/AS and the data are taken
over the exponential and deceleration growth stages. The yield
of L-lysine produced on glucose consumed (Ypls) is calcu-
lated as Yp/s = AP/AS and the data are taken over the entire
fermentation period, but especially during deceleration and
stationary stages of cell growth (when L-lysine produc-
tion occurs). Although different student groups conducted
the initiation and sample analyses portions of the experi-
ment, the group that was not "on duty" was encouraged
to drop into the laboratory to observe the activities of the
other group, and many students did so when their class
schedules permitted.
The major steps in the fermentation procedure are shown
in Table 4. Table 5 shows the composition of the defined
medium for the fermentation per liter of solution. Handout
materials for this experiment can be obtained in electronic
format (PDF file) by contacting the author at
. Materials available include an over-
view of the semester-long experiment plan, an introduction
to bioprocess safety issues, and detailed steps in the fermen-
tation preparation, start up, and sample analysis.

RESULTS AND DISCUSSION

Figure 3 shows a set of results for the cell growth, glucose
consumption, and product formation for these experiments
using Corynebacterium glutamicum. Cell data shows four
stages of batch growth: exponential, deceleration, stationary,
and declining. Glucose is consumed fastest during the expo-
nential and deceleration stages and more slowly during the
stationary and declining stages. L-lysine production is most
rapid during the deceleration stage and increases to the greatest
amount during the decline stage. This observation is consis-
tent with the metabolic pathway shown in Figure 2, with L-
lysine production in Corynebacterium glutamicum being
greatest after the added amino acids are largely consumed
and cell growth ceases, and during the period that concerted
feedback inhibition of the L-lysine metabolic pathway is re-
leased. The students are made aware of the difference be-
tween growth-associated versus non-growth-associated
product formation. Figure 3 provides an example of mixed
growth-associated product formation-that is, intermedi-
ate between the two types. Results from the remaining
experiments (for the most part) showed similar trends for
the batch culture data.
Table 6 shows the results for all six teams from the semes-
ter-long experiment plan. For the 20 g/L initial glucose con-
centration experiments, the maximum cell concentration de-
creased (from 9.5 to 4.0 g/L) when the initial amino acid con-
centration was decreased by 50%, but cell concentration did

not increase (it decreased slightly from 9.5 to 8.5 g/L) as ex-
pected from the metabolism shown in Figure 2, when the
initial amino acid concentration was increased by 50%. The
absence of this additional cell growth may be due to the in-
crease in L-lysine production. An increase in the initial amino
acid concentration of 50% did increase the ultimate L-lysine
concentration (from 2.09 to 7.5 g/L), whereas a decrease in
the initial amino acid concentration did not significantly
change the L-lysine concentration.
For the 30 g/L initial glucose experiments, again the maxi-
mum cell concentration decreased (from 8.0 to 3.9 g/L) when
the initial amino acid concentration was decreased by 50%,
but (contrary to the 20 g glucose/L results) the ultimate L-
lysine concentration increased (from 2.55 to 10.0 g/L). The
results for 30 g glucose/L and 150% amino acid concentra-
tion were compromised because the dissolved oxygen probe
failed during the run, causing the culture to become anaero-
bic and changing the cell growth and L-lysine production
characteristics. This team proceeded in the same manner as
the other teams. They measured cell concentration, plotted a
cell growth curve, measured glucose consumption and lysine
production, and calculated all growth and yield parameters.
The purpose for doing this in this case was to measure effects
of anaerobic growth conditions on fermentation performance.
The cell growth yield, YxIs, varied from 0.27 to 0.99 for
these experiments, with the exception of the last experiment,
which became anaerobic, as mentioned previously. These
values are in the range typically found for aerobic culture on
glucose and similar growth substrates.161 The highest value
violates a carbon mass balance, however, which predicts a
maximum biomass yield of

Yxis = g bio. 72gC -0.8gbio./gsugar
x/s 0.5 gC 180gsugar

for typical values for biomass dry weight fraction carbon of
49-51%. Most likely, this erroneous result came from mea-
surement error on glucose, as the cell mass measurement is
more accurately obtained. The L-lysine production yield var-
ied over the range of 0.14
to 0.60 for the various ex-
periments.

The results from this ex-
periment plan for cell
growth and L-lysine pro-
duction confirm the
student's prior understand-
ing regarding metabolism
for this culture, as shown in
Figure 2. Maximum cell
growth did decline ap-
proximately in proportion
to the decrease in the ini-
tial amino acid concentra-

tion, although it did not increase with increasing amino acid
concentration. Additional experiments are needed to reduce
uncertainty in measured results, which may help explain the
higher-than-possible biomass yield observed in one of the
experiments. Enhanced L-lysine production was observed
compared to the basecase conditions for two experiments, 20
g glucose/L, 150% amino acid concentration and 30 g glu-
cose/L, 50% amino acid concentration. From the results thus
far, however, the exact mechanism for this enhanced produc-
tion is not yet understood.
Table 6, along with a summary narrative of the results from
the entire set of experiments, was developed by the instruc-
tor and disseminated by e-mail attachment at the end of the
semester to the students who participated in the fermentation
experiments. The narrative contained a summary of key re-
sults for these fermentation experiments:
1. The supplemental amino acids limit the maximum cell
concentration that is achieved during fermentation.
2. Cell growth and L-lysine production appear to occur
in separate stages of the fermentation.
3. It is possible to increase L-lysine concentration by the
end of the fermentation by altering initial glucose and
amino acid concentrations.
This end-of-semester summary provided the cumulative
results needed to address the two most important experiment
objectives: testing the hypothesis that maximum cell concen-
tration in the fermentation is affected by the initial concen-
tration of supplemented amino acids and identifying whether
initial glucose and amino acid concentrations could be al-
tered to enhance L-lysine production.
The Department of Chemical Engineering at Michigan Tech
has an assessment program for the evaluation of student learn-
ing outcomes. As required by ABET 2000 Criteria, we use
these assessments to monitor student proficiency in master-
ing chemical engineering fundamentals and for improving
faculty teaching effectiveness.
In this assessment program there are eight major efforts,

TABLE 6

Summary of Student Team Results from the Fermentation Experiment Plan
(Base case concentrations of amino acids [L-threonine, L-methionine, and L-leucine) are given in Table 5)

Initial Glucose Concentration (g/L)
Initial Amino Acid Concentration
Maximum L-lysine Concentration (g/L)
Maximum Cell Concentration (g/L)
pm. (1/hr), Max. Specific Growth Rate
Td (hr) Doubling Time
Yxs (g cells/g glucose)
Ys (g L-lysine/g glucose)

Team 1
20
Basecase
2.09
9.5
0.38

Team 2
20
1/2 Basecase
2.21
4.0
0.50

Team 3
20
150% Basecase
7.51
8.5
0.33

1.82 1.39 2.09

Team 4
30
Basecase
2.55
8.0
0.43

Team 5
30
1/2 Basecase
10.0
3.9
0.42

1.6 1.64
0.27 0.99
0.23 0.60

Team 6
30
150% Basecase
0
2.1
0.30
2.31
0.02
0

Chemical Engineering Education

one of which is an assessment of student outcomes in the
Senior Laboratory. From a critical reading of student team
reports by members of the faculty, we evaluate how well stu-
dents communicate in writing, the thoroughness of data analy-
sis and discussion of results, how well they function in teams,
and how proficient they are in understanding the experimen-
tal system, in developing an experimental plan, and in con-
ducting that plan. We include this fermentation experiment
in the assessment plan for the Senior Laboratory.
It is apparent from reading these reports that the students
understand the basic concepts of microbial growth and growth
stages during batch fermentation, concerted feedback inhibi-
tion of enzymes for amino acid production, and growth-as-
sociated and nongrowth-associated product formation. Thus,
from the one-hour orientation and out-of-class readings from
the handout materials, the students appear to be assimilating
and retaining the biochemical concepts needed to interpret
the experimental results. Also, the majority of student teams
have demonstrated that they are up to the task of carefully
executing the detailed experimental procedures provided to
them, although admittedly a good deal of faculty and teach-
ing assistant supervision is required to achieve good results.

SAFETY CONSIDERATIONS

Safety is integrated into all aspects of the undergraduate
chemical engineering laboratory experience at MTU. In the
design phase, before any equipment was purchased, a thor-
ough safety review of the bioprocessing equipment, proce-
dures, chemicals, and biological organisms was conducted.
The physical and chemical hazards in this laboratory are com-
mon to other chemistry or chemical engineering laborato-
ries: contact or ingestion of concentrated HCl and NaOH;
flammability hazards; hazards of high-pressure bottled air,
02, and N2; and hazards of poor housekeeping.
In addition to the chemistry laboratory safety concerns,
Corynebacteria glutamicum is classified as a Level 1 bio-
hazard (the lowest biohazard classification). To mitigate the
additional hazards of biological agents, the Center for Dis-
ease Control (-search for biosafety) recom-
mends specific standard practices including
Washing hands with antimicrobial soap prior to
leaving the laboratory
Disinfecting all work surfaces with 75% ethanol after
any spill
Decontamination (by autoclaving or use of 3% bleach)
of all cultures, growth media, equipment, and
disposables after use

Proper preparation of growth media, sterilization of equip-
ment before use, sterile transfer of growth media into the re-
actor, and proper inoculation techniques are critical to the
success of fermentation, and all these aspects expand the stu-

dents' awareness beyond the traditional chemical engineer-
ing experience. Couple this with the biosafety program, and
students are well prepared to enter this exciting area of the
chemical engineering profession.

CONCLUSIONS
A batch fermentation experiment to produce L-lysine was
developed for the Chemical Engineering Senior Laboratory
at MTU. The experiment objectives and procedures are ap-
propriate for an introductory treatment of batch fermentation
processes, microbial growth, and metabolism. A semester-
long experiment plan has been implemented to test for the
effects of initial amino acid and glucose concentrations
on cell growth and L-lysine production in long-term ex-
periments (52 hours).
The distribution of tasks between the two student groups
in each team appears to result in a reasonable level of student
effort in this long-term experiment. Judging from the oral
and written reports, the students appear to understand the fun-
damental biochemical principles (provided during a pre-labo-
ratory one-hour orientation and from handout materials) at a
level sufficient to interpret experimental results. Consider-
ing that most students had little or no prior biochemistry edu-
cation, this outcome is viewed as positive.

ACKNOWLEDGMENTS
Funding to develop this experiment was provided by a
National Science Foundation Instrumentation and Laboratory
Improvement grant (Proposal No. 97-50570), by the James
and Loma Mack Endowment Fund, and by the Davis W.
Hubbard Memorial Fund at Michigan Technological Univer-
volved in the development of these experiments, including
Dale Clark, Amber Kemppainen, Renu Chandrasekaran,
anonymous reviewers were greatly appreciated.

REFERENCES
1. Cussler, E.L., "Do Changes in the Chemical Industry Imply Changes
in Curriculum?" Chem. Eng. Ed., 33(1), 12 (1999)
2. Shuler, M.L., N. Mufti, M. Donaldson, and R. Taticek, "A Bioreactor
Experiment for the Senior Laboratory," Chem. Eng. Ed., 28(1) 24
(1994)
3. Badino Jr., A.C., and C.O. Hokka, "Laboratory Experiment in Bio-
chemical Engineering: Ethanol Fermentation," Chem. Eng. Ed., 33(1),
54(1999)
4. Brown, W.A., "Developing the Best Correlation for Estimating the
Transfer of Oxygen from Air to Water," Chem. Eng. Ed., 35(2), 134
(2001)
5. Araki, K., Amino acids (survey), Kirk-Othmer Encyclopedia of Chemi-
cal Technology, 4th ed., Vol. 2, p. 504, John Wiley & Sons, New York,
NY (1992)
6. Shuler, M.L., and F. Kargi, Bioprocess Engineering: Basic Concepts,
2nd ed., Prentice Hall, Upper Saddle River, NJ (2002)
7. AIChE, Chemical Engineering Graduates-What's Happened to the
Class of 2000?, American Institute of Chemical Engineers, New York,
NY (2000) 1

Fall 2003

267

rdMe survey

FACTORS INFLUENCING

THE SELECTION OF

CHEMICAL ENGINEERING AS A CAREER

DAVID C. SHALLCROSS
University of Melbourne Melbourne, Victoria 3010, Australia

round the world a range of strategies has been pro-
posed and adopted in an effort to attract more stu-
dents into chemical engineering. These strategies
range from distributing brochures, videos, and interactive CD-
ROMs to secondary school careers teachers, to running ac-
tivities for either the school students or their mathematics
and science teachers.
In Australia in the early 1990s, the Joint Victorian Chemi-
cal Engineering Committee commissioned a short video,
"This is Chemical Engineering," that was later distributed to
all secondary school careers teachers,'11 and in 1997, to cel-
ebrate the 75th anniversary of the Institution of Chemical
Engineering, that UK-based body prepared and distributed a
CD-ROM aimed at secondary school students."t2 More re-
cently the Institution of Chemical Engineers has established
an innovative website aimed at attracting secondary school
students into the profession (found at chemeng.com>).13' The American Institute of Chemical En-
gineers has a similar, but less interactive, site at org/careers/>.'41 Some universities, such as North Carolina
State University, run summer engineering camps for school
students and their teachers.'5'
Rather than targeting the students, another strategy involves
working with secondary school math and science teachers to
raise the profile of the profession in the secondary school
community. The Faculty of Engineering at the University of
Melbourne has followed this strategy since 1994. In that year,
the faculty began running one-day seminars for secondary
school math and science teachers to introduce them to engi-
neering.i6'7' More recently, a book (jointly written by a chemi-
cal engineering academic and four practicing secondary
school math teachers) has been published that introduces
teachers and students of years 9 to 11 (ages 15 to 17) to real
engineering applications of mathematics.181 The problems
presented to the readers relate to the design of a bulk liquid

chemical storage facility, i.e., a tank farm. As another strat-
egy, the Tufts University Center for Engineering Educational
Outreach has been involved in a project pairing graduate-
level engineering and computer science students with sec-
ondary school classroom teachers.191
But, which of these strategies is most effective? While en-
gineering graduates have been surveyed to identify the fac-
tors that led them to study engineering at the undergraduate
level1101 or at the postgraduate level,"11 and to identify the main
work activities in their professional careers,'121 no studies have
been reported in the literature that investigate the career
choices of currently enrolled chemical engineering under-
This paper reports on the results of a survey aimed in part
at identifying the most effective strategies. Between October
2000 and October 2001, over 2,500 undergraduate chemical
engineering students studying at 15 universities in seven coun-
tries were surveyed. The survey sample was drawn from all
year levels and included students who had left their home
country to study. The aims of the two-page survey were three-
fold:
To investigate student perceptions of the chemical
engineering profession
To investigate the key factors that influenced the
student's decision to become a chemical engineer

David Shallcross is Associate Professor in the
Department of Chemical and Biomolecular En-
gineering at the University of Melbourne and is
s Associate Dean (International) of the Faculty of
Engineering. The author of three books, he is
active in the secondary school community de-
veloping teaching material aimed at raising the
profile of the engineering profession for school
students.

@ Copyright ChE Division of ASEE 2003

Chemical Engineering Education

TABLE 1
Survey Questions

Indicate the extent to which you agree
or disagree with these statements:
* Chemical engineering is a well-paid
profession.
* Chemical engineering offers scope to
express my creativity.
I am happy with my choice of chemical
engineering as a career.
* Chemical engineers are concerned with
sustaining/enhancing the quality of our
environment.
* Chemical engineering is important to
the well-being of society.
* Chemical engineering will allow me to
work and travel internationally.
* Chemical engineering is different to
what I thought it was when I applied to
enter the course.
* Chemical engineering is a well-
respected profession.
* Chemical engineering is of more value
to society than other forms of
engineering.
* Chemical engineers need communica-
tion skills of a high standard.
* I would recommend others to study
chemical engineering.
* I expect that within ten years of
graduating, I will have moved out of
engineering into a management role.

I chose chemical engineering because
* I was inspired by a member of my
family to study chemical engineering.
* I was inspired by a "role model"
chemical engineer (not a family
* I really liked chemistry at school.
* Chemical engineering is involved in a
range of diverse industries.
* I wanted to do engineering, but didn't
like/take physics at school.
* I wanted to do engineering, but the
other engineering disciplines didn't
appeal to me.
* A chemistry teacher at my school
triggered my interest in chemical
engineering.
* A careers teacher at my school
suggested that I consider chemical
engineering.
* I was inspired by visiting a tertiary
information session/event.
* I attended an engineering camp/summer
school type event.
* Chemical engineering is a "clean" form
of engineering.
* I was told to study chemical
engineering by a family member.
* I will be able to make a positive
difference in caring for the environ-
ment.

To determine which of a list offifteen industrial sectors the students most and least
want to work in upon completion of their degree

This paper examines the key factors that influenced the students to choose chemical engi-
neering as their profession. The results from the other sections of the survey are published
elsewhere.[13,14]

SURVEY METHODOLOGY

The survey consisted of a single-sheet, two-page form prepared in English, German,
Russian, and Vietnamese. It was only given to students currently enrolled in an under-
graduate chemical engineering course. The students were asked to identify their gender,
their grade level, and whether or not they were studying in their own country. The ques-
tions asked of students are shown in Table 1.

Some thirty universities in a range of countries that included Australia, Canada, Ger-
many, New Zealand, Russia, Thailand, the United Kingdom, the United States, and Viet-
nam were contacted and asked to participate in the survey. A number of universities de-
clined for a variety of reasons, including university policies against conducting external
surveys and concerns over the privacy rights of their students. Fifteen of the sixteen uni-
versities that agreed to participate are listed in Table 2 (the University of Hanoi also par-
ticipated in the survey, completing about 500 forms, but they were lost by the Vietnamese
postal service and were not received for processing.) Table 3 summarizes the number of
respondents by gender and national origin. In all countries except Vietnam, the
English-language version of the survey was used.
There is a total of eleven university chemical engineering departments in Australia and
New Zealand, so the four participating in the survey provided a statistically significant
sample of the student population from this region. The same is true for the United King-

TABLE 2
Summary of Survey Respondents

Gender Student Origin
Not Not
Country Total Male Female Stated Local Foreign Stated
Total 2584 1538 1037 9 1940 459 185

University of Melbourne Australia 300 150 150 0 230 69 1

McMaster University Canada 82 44 38 0 72 7 3

University of Canterbury New Zealand 65 39 25 1 57 2 6

Imperial College London UK 337 247 90 0 195 138 4

University of Loughborough UK 53 34 19 0 45 6 2

University of Surrey UK 65 43 21 1 32 31 2

Iowa State University USA 235 140 94 1 213 12 10
...

Fall 2003

dom, in which five of the twenty undergraduate chemical
engineering programs were sampled, and for both Thailand
and Vietnam, which each have only three major programs.
Within the United States there are approximately 160 under-
graduate programs, of which only two were sampled by the
survey, and only two of Canada's twenty programs were sur-
veyed. As a consequence, while the data for Australia, New
Zealand, Thailand, the United Kingdom, and Vietnam can be
considered representative of the countries, the same is not
true for the North American data.
To preserve the anonymity of most of the universities, the
survey responses are grouped together by country or region.
Thus, the University of Canterbury is grouped with the three
Australian universities, the five United Kingdom universi-
ties are grouped together, and the two Canadian universities
are grouped together, as are the two United States universi-
ties. Because of the large number of responses from Ho Chi
Minh City University of Technology, that university is con-
sidered separately. As there is no logical grouping into which
to place the Prince of Songkla University responses, and since
the number of responses is so few as to have little statistical
value, those responses play no further part in this analysis.
In most of the countries surveyed, the decision to study
chemical engineering is usually made while the student is
still enrolled in secondary school. In countries such as Aus-
tralia and Vietnam, students apply for specific courses at their
desired universities while they are in their last year of sec-
ondary school. Because this present study seeks to identify
the different local factors that influence students to take chemi-
cal engineering, this study only considers the responses from
students who are native to the country of their institution.
The responses from students who traveled internationally to
study chemical engineering are not considered. Thus, for ex-
ample, the response of students originally from outside the
United Kingdom who have traveled to study at one of the
UK institutions participating in the survey will not be con-
sidered. Table 3 summarizes the number of respondents for
each of the five university groupings for local (i.e., non-in-
ternational) students. It is the responses from these 1858 stu-
dents upon which the present analysis is based.
In the survey, students were given
statements on why they chose to
study chemical engineering (such
as "I really liked chemistry at Summary of Respon
school") and were asked to indicate
the level to which this influenced
their decision. The survey re- Country 1
sponses were scored "strongly in- Australia/New Zealand
fluenced" 3, "some influence" 2, Canada
"no influence at all" 1, no response
0, and more than one response 0.
To illustrate how the survey results United States
might be analyzed, consider the Vietnam

following example. Of the 220 local Canadian students sur-
veyed, 216 non-zero responses were recorded to the state-
ment above. Of these, 76.4% indicated no influence, 19.9%
indicated some influence, and just 3.7% indicated a strong
influence. The average score for this statement is 1.27 and is
based only on the non-zero responses.
The questions and statements used in the survey were care-
fully selected after consultation with students enrolled at Aus-
tralian universities. The thirteen statements relating to the
choice of chemical engineering as a career are not exhaus-
tive, and other statements such as "My prospects for even-
tual employment will be enhanced by have a degree in chemi-
cal engineering" could have been included. The number of
statements was limited by the desire to keep the survey as
short as possible.

SURVEY RESPONSES
The average scores for each of the thirteen statements pre-
sented in the survey are presented diagrammatically in Fig-
ure 1 for each of the five university groupings. These state-
ments relate to the selection of chemical engineering as a
career and Table 4 presents the equivalent information nu-
merically, but also classified by gender.
Several important points arise from the results:
0- A third of students admitted to being inspired by a mem-
ber of their family. Responses to the statement "I was in-
spired by a member of my family" are shown in Figure 2.
Overall, no more than 11% in each country admitted to being
strongly influenced to take chemical engineering by a family
member. In the U.S., however, significantly more female stu-
dents were influenced by this factor (15.4%) than were male
students (7.4%). Over half the female students admitted to
some form of influence, while two-thirds of the male stu-
dents were not influenced at all by family members.
I- Very few students were influenced by non-family role mod-
els. In Australia and New Zealand, nearly 90% of respon-
dents said they were not influenced at all by this factor, while
in Vietnam, nearly 40% were influenced to some degree.
10 One of the two most important factors identified by the

TABLE 3
dent Classes Grouped by Country for Students of Local Origin
Gender Engineering Year Level
Not Not
totall Male Female Stated Year 1 Year 2 Year 3 Year 4 Year 5 Stated
458 288 168 2 56 139 137 123 0 3
220 127 93 0 0 72 59 59 29 1
448 345 103 0 159 111 106 68 2 2
254 149 104 1 55 42 41 83 31 2
478 239 234 4 1 82 168 159 64 4

Chemical Engineering Education

Inspired by family member

Inspired by role model

Liked chemistry at school

Diverse range of industries .

Didn't like/take physics

Didn't like other disciplines

Chemistry teacher J

Careers teacher

Tertiary information event
0 Australia & New Zealand
0 United Kingdom
Chemical engineering is clean l0 United States

Told to do chemical engineering

Positive difference for environment

1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00
Average Response Score
Figure 1. Average scores for each university groupings regarding the level of influence
in selecting chemical engineering. A response of "No influence at all" corresponds to
a score of 1 and "Strongly influences" to a score of 3.

TABLE 4
Summary of Average Scores Regarding the Level of Influence
of Factors in Selecting Chemical Engineering

Australia
and New
Gender Zealand

Inspired by a family member

Really like chemistry at school

Didn't like/take physics at school

Chemistry teacher triggered interest

Inspired by visiting tertiary information session/,

Chemical engineering is a "clean" form of engin

Able to make a positive difference to environme

Male
Female
Male
Female
Male
Female
Male
Female
Male
Female

Female
Male
Female

_. P. m -faal,
event Male
Female
S Fe l .

eering Male
Female

nt Male
Female

1.32
1.37
1-15
1.12
2.35
2.35
226
2.33
1.38
1.59
- 20t0

1.46
1.43

--1.3-T
1.41
1.48

1.32
1.36
1..14-

1.68
1.83

United United

1.40
1.57
1.24
1.32
2.35
2.27
-2.33-
'2.42
1.52
1.53
- 1.82
:4-12
1.63
1.54

1.13
1.29
1.34

1.38
1.38
- ..25
41.33
1.70
1.97

1.39
1.38

1.20
2.26
2.17

2.49
1.31
1.57

2-9&
1.55
1.54
M6
1.406
1.41
1.60

1.29
1.34

1 19
1.51
1.70

1.40
1.66
1.29
1.29
2.67
2.59
234
2.57-
1.29
1.48
.L82
2.02
1.83
1.71
19-

1.21
1.38
_- .17 .
1.47
1.30
1.48
t.6.
1,33
1.71
1.99

1.51
1.57
1.52
1.41
2.32
2.31
2.4
2.37
1.53
1.61

1.74I-o
2.12
2.21

1.31
1.72
1.77
.- _.32

1.55
1.44
42
116
2.30
2.21

survey was, not surprisingly, that
the students liked chemistry at
school. Nearly 70% of the U.S. re-
spondents said they were strongly
influenced by their school chem-
istry experiences, with just 5.1%
admitting that they were not in-
fluenced at all. The percentages of
Australian and New Zealand, Ca-
dents who were not influenced at
all by this factor were 12.3%,
18.0%, 12.7%, and 17.4%, respec-
tively (see Figure 3). There was
little difference in responses be-
tween genders.

- The second major factor iden-
tified by the survey was that stu-
dents perceived that chemical en-
gineering is involved in a diverse
range of industries. Care must be
taken, however, in interpreting the
responses to this particular state-
ment. Of the thirteen statements
in this section of the survey, all
but two (including this one) were
framed directly in response to the
opening statement, "I chose
chemical engineering because..."
Thus, it is possible that students
responded to this statement not in
terms of whether or not they were
influenced by it to study chemi-
cal engineering, but whether they
believed the statement to be true.
Nonetheless, the fact that chemi-
cal engineering has application
across such a diverse range of in-
dustries should be emphasized
when recruiting students into the
profession's courses. Across the
five university groupings, the per-
centage of students not influenced
at all by this perception ranged
from 5.7% in Vietnam to 11.5%
in the U.S. Outside Vietnam, more
females were strongly influenced
by this perception than were
males.

I- Across the five groupings, the
percentage of students who iden-
tified that the statement "I wanted
to do engineering but didn't like/

Fall 2003

take physics at school" played no part in the selection of
chemical engineering as a career ranged from 58.0% in Viet-
nam to 74.3% in the UK. In Australia, New Zealand, Canada,
and Vietnam, around 15% of students were strongly influ-
enced by this factor (see Figure 4). There were differences
between the genders in all countries, but particularly in the
UK, where just 8.1% of males were strongly influenced by
this factor, while for females it was 23.0%
1 More female students than males were strongly influenced
by the fact that they wanted to study engineering but the other
disciplines didn't appeal to them. In Canada, 17.6% of males
and 34.1% of females were strongly influenced by this fac-
tor, while the corresponding figures for the UK were 19.8%
and 31.0% for males and females, respectively. Of the 70
students from Australia and New Zealand who were strongly
influenced in this respect, only five indicated they were not
influenced at all. When coupled with the responses to the
preceding statement regarding physics, it is apparent that
chemical engineering owes a significant proportion of its
appeal to the fact that of all the major engineering disciplines,
it is the one in which a sound foundation in physics is the
least important. Kumagai conducted focus group meetings

with over 500 female undergraduate students at eight differ-
ent universities1"31 and found that women who had chosen
chemical or environmental engineering did so because of
negative experiences in physics at secondary schools. Fig-
ure 5 presents the distribution of responses for the five
regional groupings.
- In Australia, New Zealand, and the United Kingdom, the
influence of a chemistry teacher was relatively low compared
to a much greater influence in Vietnam (see Figure 6). Just
one-third of all Australian and New Zealand students re-
sponded that they were influenced to some extent by their
chemistry teachers. This is all the more surprising because
nearly 90% of these students said that they really liked chem-
istry at school. These statistics suggest that in all countries
other than Vietnam, significant opportunities exist to work
with chemistry teachers to raise the profile of chemical engi-
neering as a profession. This could be achieved by running
professional development sessions for chemistry teachers
where chemical engineering is showcased, or by developing
material for the secondary school chemistry classroom that
illustrates how chemical engineers use basic concepts taught
in chemistry in real-life applications.

Distribution of Responses to Statements

Figure 2. "I was inspired by a
member of my family."

80
70
60
50
40
30
20
10

D Strong influence M Some influence D No influence
Figure 5. "I wanted to do engineer-
ing, but the other disciplines
didn't appeal to me."

Figure 4. I wanted to do engineering,
but didn't like/take physics."

O Strong influence Z Some influence ONo influence
Figure 6. A chemistry teacher at my
school triggered my interest."

E Strong influence Some influence ONo influence
Figure 7. "A careers teacher
suggested I consider
chemical engineering."

Chemical Engineering Education

Perhaps the most important conclusion that can be drawn from this survey relates
to the different extent that an enjoyment of chemistry at school and the
role of chemistry teachers influences students to
study chemical engineering.

0 School careers teachers play a relatively insignificant role
in steering students toward chemical engineering (see Figure
7). In North America, 87% of all respondents were not influ-
enced at all by them, while in the UK they were more effec-
tive, having had some level of influence over 36% of the stu-
dents. It is possible that many of the North American respon-
dents misunderstood the term "careers teachers" as this is
not a term in common use there. In other parts of the world,
the term is well understood. One conclusion that can be drawn
from these results is that the institutions and professional
bodies in all countries should work more closely with ca-
reers teachers.
> Many educational institutions put a lot of effort into events
such as university open days. The results presented in Figure
1 and Table 4 show that in Vietnam, in particular, these events
are effective, with 19.8% of Vietnamese respondents being
strongly influenced and 34.6% influenced to some degree.
At the other extreme, only 5.1% of U.S. students were strongly
influenced by such events, compared to 76.4% who were not
influenced at all. It should be noted, however, that the term
used in the survey, "tertiary information session/event," may
have been misinterpreted so that respondents did not con-
sider it to encompass university open days and the like.
- One of the biggest differences in responses between gen-
ders was observed for the role of the engineering camp/sum-
mer school-type event. Just 20% of male UK students indi-
cated they were influenced to some extent by such events,
while nearly 45% of the female UK students were influenced.
A similar difference in responses between genders was ob-
served for U.S. students. In Australia, Canada, and New
Zealand, such events had very little influence.
D "Chemical engineering is a clean form of engineering" is
the second of the two statements not directly framed in re-
sponse to the opening statement. The responses indicate that
this perception has relatively little influence on the selection
of chemical engineering as a career, with less than 7% of
students in each of the groupings being strongly influenced
by this factor. Of those few who were strongly influenced by
this perception, however, some two-thirds were also strongly
influenced by the perception that as chemical engineers they
will be able to make a positive difference in the environment.
- Very few respondents chose to study chemical engineer-
ing because they were told to by a family member. The great-
est degree of influence occurred among Vietnamese respon-
dents. Across all countries, females admitted to being more
strongly influenced than males.

- The perception that the respondents will be able to make a
positive difference in caring for the environment had rela-
tively high average scores across all five groupings. In Viet-
nam, nearly 40% of the respondents indicated that they were
strongly influenced by the perception. Across most country
groupings, females were influenced significantly more than
male students by this perception.
In Australia, high proportions of students are enrolled in
combined degree programs in which they can pursue two
degrees simultaneously. These programs have been described
more fully elsewhere."4' No statistically significant differences
in the factors leading to the selection of chemical engineer-
ing were observed between students currently enrolled in
single and combined degrees.
No statistically significant differences were observed be-
tween students enrolled in different year levels. This is as
expected since the factors leading to a student's selection of
a particular course should not vary significantly in the space
of five years.

CONCLUDING REMARKS
The results of this international survey clearly show the
factors that influence a student to study chemical engineer-
ing differ between countries. Some of these differences may
arise due to cultural factors and historical influences. Viet-
namese students are more strongly influenced in their choice
of chemical engineering than students in other countries by
their chemistry teachers, by tertiary information events, and
by the perception that they will be able to make a positive
difference to the environment. In the UK, the role of careers
teachers is much more important than in Australia, New
Gender issues are also important, with the responses from
male and female students differing considerably in several in-
stances. A number of workers in the past have studied the gen-
der issues related to course selection at school. Lewis'17' stated
It is at the crucial adolescent age when females seek interrelat-
edness and males seek independence that we ask students to
make their subject choices. Girls who choose the physical
sciences or engineering not only have to show a strong sense of
independence by choosing a nontraditional subject, they are
also asked to choose a set of math and science subjects which
are characterized as abstract laws disconnected from their
social and physical worlds. Boys, on the other hand, can make a
decision in tune with their peer group, and overlapping their
need for emotional separation through disconnected abstract
laws.
Continued on page 281.

Fall 2003

273

S classroom

PARTICLE TECHNOLOGY

DEMONSTRATIONS

For The Classroom and Laboratory

SIMON M. IVESON, GEORGE V. FRANKS
University of Newcastle Callaghan, NSW 2308, Australia

ne of the joys of teaching a course on powder tech-
nology is the abundance of quick and simple experi-
ments that can be used in lectures to demonstrate
the fundamental phenomena being discussed. These can be
used as breaks part way through a lecture or as an interest-
arousing introduction to a new topic. Demonstrations can be
used to highlight the often counter-intuitive behavior of pow-
ders by asking the students to break into groups and try to
predict a priori how they expect a given system to behave. The
often quite different behavior that they subsequently observe
will then challenge them to understand the causes of their mis-
conceptions and arouse their interest in the lecture material."'21
There are more than enough such demonstrations to fill a
spot in every lecture of a one-semester introductory course
on powder technology. Most, however, are referred to only in
passing in references scattered throughout the literature1eig,3-6J
or are passed on by word-of-mouth from one practitioner to
another. Klinzingt7' has provided a partial list of such demon-
strations, and a recent CD by Rhodes and Zakharil81 contains
video clips of many others.
This paper seeks to provide a comprehensive compilation
of demonstrations to act as a reference for new instructors in
particle technology. Demonstrations related to wet-powder
systems are presented first, followed by dry-powder systems.
Wet-powder system behavior covered includes single-particle
settling, hindered and lamella settling, sedimentation, the ef-
fect of surface chemistry on slurry rheology, powder wet-
ting, and wet-granule coalescence. Dry-powder system be-
havior covered includes flow from hoppers, percolation and
elutriation segregation, the "Brazil-nut" effect, surface fric-
tion, and powder compaction. Where possible, the source of
the ideas presented is acknowledged, either by reference to a
publication or mention of the person who first told the au-
thors. Many of these ideas have been around so long, how-
ever, that it is difficult to identify their origin, and we apolo-
gize in these cases for not acknowledging their original source.

WET-POWDER SYSTEMS
Single-Particle Settling (in-class demonstration)
Most courses on fluid-particle interactions begin by exam-
ining the settling of a single spherical particle. The effect of
fluid viscosity can be demonstrated by using glass marbles
in two identical perspex tubes about 40 cm long, one filled
with water and the other with glycerol (or any other transpar-
ent viscous fluid).[91 Start by asking the students in groups to
estimate the settling time of each marble. Most will correctly
guess that the marble will settle more slowly in the glycerol.
When asked why, they will probably refer to either glycerol's
greater density or its greater viscosity compared to water.
If students think that density difference is the cause, then a
simple buoyant force balance can be used to calculate how
long it would take the marble to fall under the influence of
gravity alone. For water = 1 g/cm3, pglycerol = 1.25 g/cm3 and
Pglass = 2.5 g/cm3, the increase in fall time in the glycerol due
to its greater density would be only 10%. The calculated set-

Simon Iveson completed his Bachelor of
Chemical Engineering in 1992 and his PhD in
1997, both at the University of Queensland.
Since then he has been a research fellow and
lecturer in the Department of Chemical Engi-
neering at the University of Newcastle. His re-
search interests are in the field of particle tech-
nology, with his focus being on the agglomera-
tion of fine particles by the addition of liquid bind-
ers.

George Franks completed his BS in Materials
Science and Engineering at MIT in 1985 and his
PhD in Materials at the University of California
at Santa Barbara in 1997. He has been a senior
lecturer in the Chemical Engineering Department
at the University of Newcastle since 1999. His
research interests include colloidal processing
of ceramics, mechanical behavior of wet pow-
der bodies, and mineral processing processes
such as flocculation.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

tling times for a 40-cm long tube are of the order 0.4 s, which
is less than the approximate 1 sec and 10 sec observed in
practice. Clearly, buoyancy effects alone do not explain the
speed at which the marbles fall.
At this stage (if they have not already done so), some stu-
dents may recall the concept of viscosity and fluid drag from
their previous fluids courses. This can lead to a brief review
of drag coefficients, terminal velocities, etc. For the marble
in glycerol, the Reynolds number is low and Stokes' law (CD
= 24/Re) applies, Hence, the terminal settling velocity VT of
the marble is given by

VT (pp -L)d2g (1)
18
where pp and pL are the density of the particle and liquid, d is
the marble diameter, g is gravitational acceleration, and [L is
the fluid viscosity.
For the marble in water, the Reynolds number is of order
105, giving a drag coefficient of approximately CD = 0.44.
The terminal settling velocity is given by

VT- =4(pp-pL)dg (2)
3pLCD
Thus, the difference in viscosity between glycerol (R 1
Pa-s) and water (R. = 0.001 Pa-s) can be shown to be the
major cause of the difference in their settling velocities.
Some students may also think of another cause for the
slower than expected fall of the marbles, namely hindering
caused by the back flow of displaced liquid up the tube walls
as the marble moves past. This is illustrated in the next dem-
onstration.
Hindered and Lamella Settling (in-class demonstration)
Hindered settling can be illustrated using a pair of perspex
tubes filled with the water, the first containing only a single

(a) (b) (c)

g ;'

Figure 1. (a) Hindered settling and ways to speed up
settling by (b) tilting the tube or (c) shaking it in a
circular motion.

The settling rates of the two systems can then be compared,
to illustrate how the presence of many particles reduces the
settling speed. Explain how settling is hindered by the need
for the displaced water to flow back up through the bed of
particles (see Figure la); then ask the class to think of ways
to increase the rate of particle settling.
One way to accelerate settling is to tilt the tube slightly so
that particles have only a short distance to fall to reach the
tube wall, where they can then slide down quickly as the dis-
placed water flows unhindered above (Fibure lb).101 This il-
lustrates how lamella settlers operate. Another method is to
shake the tube in a horizontal circular motion while keeping
it vertical. The centrifugal force moves particles to the wall,
leaving the center of the tube free for displaced water to flow
upward, thus allowing the particles to settle more quickly
down the sides (Figure Ic). This is similar to what happens
inside a hydro-cyclone.
Sedimentation and Flocculation (in-class demonstration)
The different types of sedimentation behavior can be eas-
ily demonstrated by filling three tall jars with Type I, Type II,
and colloidal (non-settling) particle suspensions. Shake the
jars at the start of the lecture and point out the different be-
haviors. Type I suspensions are those that form three zones
during settling-a clear liquor above the settling particles
(zone A), a suspension of particles of the same concentration
as the initial suspension (zone B), and a settled bed at the
base (zone S). During settling, the interface between zones A
and B falls and the interface between zones B and S rises,
until the two meet and zone B disappears.
Type II suspensions form four zones during settling. In
addition to zones A, B, and S, there is a zone of variable
concentration (zone E) that forms between zones B and S.
Colloidal particles do not settle out at all. Toward the end of
the lecture, once students are convinced that the colloidal
particles are not going to settle, a flocculant can be mixed
into the suspension to demonstrate the resultant dramatic im-
provement in settling behavior.
Sedimentation and Flocculation (laboratory module)
A laboratory module based on particle settling is also pos-
sible. Give the students three or four samples of silica of dif-
ferent average particle size ranging from about 1 micron to
about 250 microns. The size distributions should be mono-
modal and less than one decade in breadth. Prepare 250 ml of
a suspension of 3 wt% solids for each powder in distilled
with NaOH so that the silica is well dispersed. Shake the
cylinders and observe the sedimentation. Measure the time
required for the first noticeable formation of the sediment
bed. Measure the height of the interface between the clear
supernatant and the suspension as a function of time.
Students will notice that the micron-sized silica does not
settle appreciably in the time available. Mention that for par-

Fall 2003

tiles smaller than about 0.1 microns,
Brownian motion dominates gravita-
tional settling so that a stable suspen-
sion results. Use a suitable cationic poly-
mer to flocculate the suspension so a
clear supernatant results.
The students should calculate the size of
the largest particles in the sample assum-
ing that the time for the first noticeable
sediment bed to form corresponds to the
time that the largest particles settle the dis-
tance from the top of the tube to the bot-
tom. Using that velocity and Stokes' law
or Newton's law, the size of the largest
particles can be calculated. They should
also calculate the size of the smallest par-
ticles based on the velocity of the suspen-
sion/clear supernatant interface. Then pro-
vide them with the measured particle size
distributions of the silica samples and ask
them to compare their calculated largest
and smallest particle sizes with the size
distribution data provided. The compari-
son is surprisingly good.
Interparticle Force Effects on Colloidal
Suspension Rheology
(laboratory module)
Many chemical engineers are not trained
to consider how the chemical nature of the
fluid medium can influence the rheologi-
cal behavior of a suspension. pH is one of
the easiest properties of a slurry to mea-
sure on-line and it can also dramatically
affect suspension properties. A simple
laboratory project that illustrates this ef-
fect by comparing the slumping behavior
of zircon suspensions as pH is varied is
shown in Table 1.
Wetting Behavior of Dry Powders
(in-class activity or laboratory module)
The wetting behavior of liquids on dry
powders is important in applications such
as mixing pigments into paints and the for-
mation of agglomerates in agitated granu-
lators. If the paint pigments do not wet
well, then they will not disperse and in-
stead form clumps of dry powder with
trapped air inside. This detrimentally af-
fects the paint quality. In granulation, the
initial wetting behavior can have a large
effect on the final product size produced
in a granulator. Drops that penetrate the

TABLE 1
Laboratory Module: Interparticle Force Effects on Colloidal Suspension Rheology

Few chemical engineers are trained to consider how the chemical nature of the fluid medium can
influence the rheological behavior of a suspension. pH is one of the easiest properties of a slurry to
measure on-line and it can also have a dramatic effect. The students measure the yield stress of a
0.40 volume fraction of solids zircon suspension over a range of pH values. The average size of
the zircon is about 6 microns, so the interparticle surface forces are important in determining the
rheological behavior. The density of zircon is 4400 kg/m3. The yield stress can be measured by the
slump method."" In this method, the paste-like suspension is filled into a cylinder on a flat surface
and the cylinder is lifted off the suspension. The resulting slump height is measured (see Figure
Al). The yield stress is related to the slump height by

y = pg9 1 (A1)

where Ty is the yield stress, p is the suspension density, g is the gravitational acceleration (9.8 m/
s2), and H and s are indicated in Figure A1.
The students should measure the yield stress of the suspension at pH values of approximately
pH 7, pH 6, pH 5, pH 4, and pH 3. Use HCI and NaOH to adjust the pH, being careful not to
overshoot the pH and come back since this will add salt to the suspension and thus affect the
interparticle forces and thus the yield stress. Make sure the suspension is well mixed. The zeta
potentials of the powder as a function of pH can be provided to the students as shown in Figure
A2. Ask them to compare the measured yield stress values with the zeta potentials. They should
comment on the behavior in their report.

Abbreviated Laboratory Report:
Figure A3 is a photo of the slump test being performed by one of the authors. The density of the
suspension can be calculated as
Psus = OPzircon + EPH20
Psus = 0.4(4400 kg / m3) + 0.6 (1000 kg / m3) = 2360 kg / m3

The initial cylinder height (H) was 0.103 m. The slump (s) was measured with a ruler over a range
of pH values from 3 to 7. The measured slump was used to calculate the yield stress (using Eq.
Al). The yield stress is plotted against pH in Figure A4. The maximum yield stress correlates with
the isoelectric point (where the zeta potential is zero). At this pH, only van der Waals attraction is
operating between the particles creating a strong attraction and thus a high yield stress. The yield
stress decreases as the pH is moved away from the isoelectric point. This is because as the charge
on the surface of the particles increases, the electrical double layer repulsion also increases-thus
reducing the magnitude of the attraction and thus the yield stress. See Shaw,"121 Hunter,"3' or
Johnson, et al.,"4] for more details.

Figure Al. Dimensions used in
calculation of yield stress from
slump test.

Figure A2. Zeta potentials of
zircon.

Figure A3. Slump test in progress.

6 300

200oo

3 4 5 6 7
pHFigure A4. Yield stresses of zircon.
Figure A4. Yield stresses of zircon.

Chemical Engineering Education

276

bed surface quickly are more likely to form individual nu-
clei-hence controlling the drop size controls the granule size.
Slow penetration can lead to pooling of liquid on the powder
surface, resulting in widely sized initial nuclei and widely
sized final product."011
The rate of penetration of a liquid into the pores of a pow-
der bed can be estimated by equating the capillary pressure
driving force from the Young-Laplace equation

A 2y LV COS (3)
cap r
with the viscous resistance to laminar flow predicted from
the Hagen-Poiseuille equation
APvis = 8 ull
AP (4)

to give a form of the Washburn equation

dl ryLvCose (5)
dt 41j
where u is the liquid velocity, r is the effective pore radius,
LV is the liquid-vapor surface tension, 0 is the solid-liquid
contact angle, 1 is the length of pore filled, and [t is the liq-
uid viscosity.
The effects of the parameters in Eq. (5) can be demonstrated
by asking students to measure the penetration times of drops
of water, honey, and alcohol onto a number of different pow-
der beds, e.g., coarse and fine sugar, ground pepper, and
parmesan cheese (see Figure 2).[I61 The coarse and fine sugar
demonstrate the effect of pore size r. The rate of liquid pen-
etration is approximately proportional to the particle size.
Hence, the water penetrates the fine sugar more slowly than
the coarse sugar. (Note: if an alternative powder that is in-
soluble in water is available in two different particle sizes,

Figure 2. The non-wetting behavior of drops of water (front
row) and sugar solution (middle row) compared with the
rapid wetting of alcohol (back row) on a bed of grated
parmesan cheese. Dye added to liquids to enhance visibility.

this may be preferable to using sugar.) The water and honey
demonstrate how increasing viscosity pi slows down the rate
of penetration. The water and alcohol on the cheese and pep-
per demonstrate the important effect of contact angle 0. Wa-
ter does not wet or penetrate into either of these two pow-
ders, but alcohol wets both powders because it has a lower
contact angle due to its lower surface tension, as seen by a
force balance at the contact line between the three phases
(the Young-Dupre equation)

COS VS -YLs (6)
YLV
where the subscripts V, S, and L refer to the vapor, solid, and
liquid phases, respectively.
A more comprehensive predictive model for the penetra-
tion time of a liquid drop onto a powder surface is presented
by Hapgood, et al."51 This could form the basis of a labora-
tory module for students in more advanced powder technol-
ogy subjects where they would be required to measure the
powder size and bed porosity.
Granulation Coalescence Behavior (in-class demonstration)
Wet granulation is performed by spraying a liquid binder
onto an agitated powder mass. There is great interest in being
able to predict the rate at which these granules grow as they
are agitated. This depends on how likely it is for granules to
coalesce during collisions of varying velocity.
In more advanced powder technology subjects, students
may be introduced to two of the models available for predict-
ing wet-granule coalescence. The Ennis model considers the
collision of two equi-sized elastic spheres of radius r collid-
ing head-on at a relative speed of 2u.'171 Each sphere is sur-
rounded by a layer of fluid of viscosity R. and thickness h.
The surface of each sphere has a roughness of ha, which lim-
its how close they can approach together. The spheres have a
coefficient of restitution, e, and a density, p. Solving Newton's
second law of motion, it is predicted that coalescence will
occur when the viscous Stokes number, Stv, is less than some
critical viscous Stokes number, St,*, where

St = 8p and St* =, I+ln) 4+ (7)

This model predicts that reducing the impact speed acts to
increase the likelihood of coalescence. This behavior can be
demonstrated by dropping a rubber ball from different heights
onto a flat surface coated with a layer of honey. Below a thresh-
old impact velocity (release height), the ball will not rebound.
Liu, et al.,[181 model colliding granules as elastic-plastic
spheres that are initially surface dry, but then have liquid
squeezed to the surface during collisions. This model pre-
dicts that low-velocity collisions are less likely to result in
coalescence. This is because very little permanent plastic de-
formation occurs, and hence the area of contact formed be-

Fall 2003

277

tween the two granules is very small and weak. This behav-
ior can be demonstrated by dropping round balls of plasticine
from different heights onto a flat surface (it helps if the
plasticine is first warmed up by vigorously hand rubbing to
make it softer). When the surface is inverted, the plasticine
dropped from a low height will drop off because it did not
deform, whereas plasticine dropped from a large height will
remain stuck on for some time due to the greater amount of
deformation forming a strong bond.
These two demonstrations serve to illustrate how coales-
cence behavior varies as consolidation changes granules from
being low-density and deformable to high-density and non-
deformable during the granulation process.

DRY-POWDER SYSTEMS
Hopper Flow (in-class activity)
A good hands-on introduction to a set of lectures on hop-
per flow is to split the class into groups of 2-4 students each
and supply each group with some thin cardboard, paper, over-
and a pan (to prevent spilling sand all over the classroom
floor). Give them 10 to 15 minutes to build a funnel (hopper)
that must discharge a set mass of sand in a set time (starting
full). Make up a hopper beforehand to check that the time
limit is reasonable-try to set a required time that is long
enough so that in trying to slow down the flow, the students
will encounter problems such as arching or rat-holing. Offer-
ing an incentive such as a large chocolate bar as a prize for
the group that gets closest to the set time adds some competi-
tive spirit and fun to the exercise.
Wander between the groups as they try different designs
and ask them what the design parameters are (hopper angle,
opening size, and possibly the wall material), how the mate-
rial is flowing (mass or funnel flow), and what problems they
are encountering (e.g., arching and rat-holing). Some groups
may resort to things such as tapping or stirring the hopper in
order to promote flow-discuss the practicalities and costs
associated with this in an industrial setting.
Funnel Flow and Mass Flow (in-class demonstration)
The two main types of flow from hoppers are mass and
funnel flow. In mass flow, the entire powder bed is in motion
as the bin discharges. The first material put into the bin is
also the first to come out. In funnel flow, material slips from
the top surface down through a rat-hole in the center of the
bin. The material at the bin walls is static-hence the first
material put into the bin is often the last out of it. Jenike and
Johanson[119 demonstrate the difference between mass and
funnel flow by using an hourglass arrangement with a differ-
ent hopper angle in each half (photograph can be found in
reference 7). If the hopper angles and material are chosen
correctly, the material will flow through the steep-angled hop-
per in mass flow and through the shallow-angled hopper in

funnel flow. Fan151 extends this idea by connecting the two
hoppers by a long straight pipe. This column then acts as a
standpipe, exhibiting regions of both moving bed transport
and suspension transport of the solids.
Consolidation Effects of Powder Flow
(in-class demonstration)
One important aspect of powder technology that should be
stressed to students is that, unlike most fluids, the behavior
of powder systems is history-dependent. The effect of con-
solidation on flow behavior can be demonstrated by using
some dish-washing powder and a funnel (the end of a plastic
drink bottle works fine). Pour the powder into the funnel and
when the exit is opened, then it will flow out easily. But if the
powder is poured into the funnel and tapped before the exit is
opened, it will have consolidated and no flow will occur when
the exit is opened.1201 Mention should be made that other factors
besides consolidation can also cause powder properties to change
with time, such as capillary condensation, re-crystallization, and
solid-state diffusion causing bonding at interparticle contacts.
Particle Dilation (in-class demonstration)
Osborne Reynolds[21] demonstrated shear-induced particle
dilation using a manometer attached to a rubber bag filled
with saturated sand. This experiment can be repeated using a
clear plastic drink bottle (the type with the straw built into
the cap so that it is easy to use while running or bike riding).
Tightly pack the main bottle cavity with saturated sand and
then top off with water until the water level reaches part-way
up the tube. Ask students what will happen when the bottle is
squeezed lightly. Counter to intuition, the water level actu-
ally drops. This is because the sand must dilate in order for
particles to slide over one another. Water flows back into the
powder bed as it dilates. This dilation behavior explains why
sand "dries up" around your foot as you walk along the beach
near the water's edge. Water is sucked away from the sur-
roundings into the dilated sand matrix. When you lift your
foot, this excess water then causes the sand to temporarily
liquefy as the load is relaxed.[eg .,22]
Wall Friction (in-class demonstration)
Powder bed behavior is different from that of a Newtonian
fluid. In a fluid, some flow is always initiated when a shear
force is applied, but powder beds offer a finite resistance to
shear forces. This ability of a powder bed to support large
a plunger up a tube that is gradually filled with more and
more particles. Eventually, a stage of filling is reached be-
yond which they can no longer move the plunger-the force
they are exerting is totally transferred by the particles to the
wall of the tube. The force being exerted can be made visu-
ally evident by either including a spring balance on the pull
cable"71 or by attaching a large spring on the shaft used to
push the plunger up the column.'81 The implications of this
behavior for the distribution of stresses on hopper walls and

Chemical Engineering Education

278

the difficulty of achieving uniform compaction in presses and
dies can then be discussed.
A variation of this demonstration is to tape a thin sheet of
tissue paper over one end of the tube, fill the tube with the
powder, and then ask for a volunteer who thinks he or she is
strong enough to push the powder bed through the tissue paper.
Segregation During Hopper Flow (in-class demonstration)
Another counter-intuitive behavior of powders is that flow
and agitation often cause segregation, rather than mixing.
Segregation during discharge of material onto a stockpile or
into a hopper is a well-known phenomena. Many workers
have used transparent 2D hoppers to demonstrate the "her-
ring-bone" pattern formed due to a combination of percola-
tion of fine particles and the lower angle of repose of the
coarse particles (see Figure 3).ie.g.'7-8.19.23] The small particles
percolate between the larger ones and this causes the fine ones
to become concentrated in the center of the bed. During the
periodic avalanches, large particles tend to roll further down
the sloped surface of the bed because of their higher inertia and
lower angle of repose. During these avalanches, the fine par-
ticles tend to settle out along the way. This causes the large
particles to become concentrated at the base of the pile and also
gives rise to the alternate bands of fine and coarse material.
A third, and less-often demonstrated mechanism of segre-
gation is the elutriation or fluidization of ultra-fine particles
in the upflowing air displaced by the downflowing solids.
This can result in the ultra-fine particles settling out after the
other particles and forming a layer on top of the heap. With
an airtight 2-D hourglass arrangement and correct choice of
particles, elutriation and percolation segregation phenomena
can both be demonstrated simultaneously in the same appa-
ratus. Figure 3 shows the demonstration midway through the

-

Figure 3. Elutriation segregation of-20 micron hollow glass
spheres (fluidized bed in the upper chamber) and forma-
tion in the lower chamber of a segregated "herring-bone"
pattern of 200-400 micron beach sand (light color) and 50-
100 micron hematite/iron-ore particles (darker color) dur-
ing discharge from a sealed hopper.

Fall 2003

discharge process. The back flow of air has elutriated the ul-
tra-fines from the material flowing through the opening. The
ultra-fines have instead formed a fluidized bed in the upper
hopper. As a result, they are the last particles to flow from the
hopper and hence they deposit on the top surface of the heap
and flow down to the base at each edge.
Before performing this demonstration, the students should
be asked to predict where in the heap they think the different
size fractions of material will be preferentially deposited. Then
they can compare their predictions with the final result. Dis-
cuss the difficulties this behavior causes in obtaining repre-
sentative samples from a poured heap of granular material.
Representative samples can only be obtained by sampling at
random intervals of time the full cross-section of a powder
stream when it is in motion.
Vibrational Segregation (in-class demonstration)
The well-known "Brazil nut" effect can be easily demon-
strated by covering a steel ball bearing with sand and then
vertically tapping the container. The steel ball will rise to the
surface, in spite of its greater density. The cause of this phe-
nomena is not fully understood, but is believed to be linked
to the inertia of the object, causing it to "punch through" the
expanded bed during the upstrokes, whereas the packing of
the powder prevents it from descending during the
downstroke. [824-25]
Shinbrot and Muzzio1251 suggest a variation to this demon-
stration. If a low-density object is also added to the container,
then the behavior of the two objects varies depending on
whether the container is shaken horizontally or vertically.
Under vertical vibrations, the steel ball rises and the low-
density object sinks. Under vigorous horizontal vibrations,
the steel ball sinks and the light object rises! The cause of
this reversal is unclear, but is probably due to the bed dilating
and becoming fluidized during horizontal vibration. The class
can be asked to predict beforehand which of the two objects
will rise or sink when the jar is "shaken" (without specifying
how). Then the instructor can deliberately shake the jar in a
direction that gives a result counter to the majority class opin-
ion, in order to arouse their interest.
Fluidization (in-class demonstration)
Fluidization can be demonstrated in the classroom using a
small bed connected to a portable compressor, or if the bed is
small enough, a willing volunteer's lungs.[]l Behavior that
can be displayed includes the way the fluidized bed remains
level as the bed is tilted and the floating and sinking of ob-
jects of different density when the bed is fluidized. This can be
contrasted with the behavior of these objects in the bed when it
is vertically vibrated (see Vibrational segregation above).
Bubbling behavior can be demonstrated by filling a long
tube most of its length with a Geldart Group A powder. In-
verting the tube will result in a slug slowly rising up the length
of the column.161 Again, students could be asked beforehand

to predict what will happen when the tube of fine powder is
inverted. Many may expect the powder to move as a solid
plug from one end to the other.
Flow Improvement Due to Powder Agglomeration
(in-class demonstration)
The dramatic improvement in the flow properties of granu-
lated versus ungranulated materials can be demonstrated by
setting two hoppers side-by-side, one with the raw fine pow-
der and the other with the same powder after it has been granu-
lated. When inverted, the raw powder arches and does not
flow without tapping, whereas the granulated product flows
freely (see Figure 4). Small batches of granules for use in
this demonstration can easily be prepared at home in a do-
mestic food processor.

OTHER RESOURCES FOR
POWDER TECHNOLOGY EDUCATION
If you do not have the resources or time to build and per-
form these demonstrations, many of them are shown as video
clips on a CD produced by Rhodes and Zakhari.181 An ex-
panded version of this CD is due out soon that will include
interactive problems.
The Particle Technology Forum of the American Institute
of Chemical Engineers has established a website with many
good educational resources for particle technology.1261 For
ideas on how to construct and structure an introductory course
on powder technology, we suggest reading the papers by
Chase and Jacob'31 and Donnelly and Rajagopalan,[4' and also
the textbook by Rhodes1231 that was written specifically with
the purpose of being an introductory undergraduate textbook.

CONCLUSIONS
Instructors of powder technology courses have no excuse
for not using visual, hands-on demonstrations to introduce a
little more variety and interest to their teaching. Most of the
demonstrations mentioned in this paper can be built at little
cost using materials readily available in most engineering de-
partments. No expensive or hazardous chemicals are needed,
and most of the powders can be found at your local beach or
supermarket. Asking students to guess the powder behavior
before the demonstration is performed is an effective tool for
engaging their interest.

REFERENCES
1. Felder, R., "How About a Quick One?" Chem. Eng. Ed., 26(1), 18
(1992)
2. McKeachie, W. J., Teaching Tips, 8th ed., D.C. Heath & Co., Lexing-
ton, MA (1986)
3. Chase, G.C., and K. Jacob, "Undergraduate Teaching in Solids Pro-
cessing and Particle Technology: An Academic/Industrial Approach,"
Chem. Eng. Ed., 32, 118 (1998)
4. Donnelly, A.E., and R. Rajagopalan, "Particle Science and Technol-
ogy: Educational Initiatives at the University of Florida," Chem. Eng.
Ed., 32 122 (1998)
5. Fan, L.-S., "Particle Dynamics in Fluidization and Fluid-Particle Sys-

Figure 4. Granulated powder (left-hand side) flows easily
into lower hopper, whereas raw powder arches and does
not flow (right-hand side).

teams: Part 1. Educational Issues," Chem. Eng. Ed., 34, 40 (2000)
6. Fan, L.-S., "Particle Dynamics in Fluidization and Fluid-Particle Sys-
tems: Part 2. Teaching Examples," Chem. Eng. Ed., 34, 128 (2000)
7. Klinzing, G., "Experiments, Demonstrations, Software Packages and
Videos for Pneumatic Transport and Solid Processing Studies," Chem.
Eng. Ed., 32, 114 (1998)
8. Rhodes, M., and A. Zakhari, "Laboratory Demonstrations in Particle
Technology," CD, Monash University, Melbourne, Australia (1999)
9. Idea introduced to the authors by Professor Nafis Ahmed, formerly of
the University of Newcastle, Australia (1998)
10. Idea introduced to the authors by Professor Kevin Galvin, University
of Newcastle, Australia (1998)
11. Pashias, N., and D.V. Boger, "AFifty-Cent Rheometer for Yield Stress
Measurement," J. Rheol., 40, 1179 (1996)
12. Shaw, D.J., Introduction to Colloid and Surface Chemistry, 4th ed.,
Butterworth Heinemann (1992)
13. Hunter, R.J., Introduction to Modern Colloid Science, Oxford Science
Publications (1992)
14. Johnson, S.B., G.V. Franks, P.J. Scales, D.V. Bogher, and T.W. Healy,
"Surface-Chemistry-Rheology Relationships in Concentrated Mineral
Suspensions," Int. J. Miner. Process., 58, 267 (2000)
15. Hapgood, K.P., J.D. Litster, S.T. Biggs, and T. Howes, "Drop Penetra-
tion into Porous Powder Beds," J. Colloid & Interface Sci., 253, 353
(2002)
16. Idea introduced to the authors by Dr. Bryan Ennis and Professor Jim
Litster during one of their industrial short courses on granulation (1999)
17. Ennis, B.J., G.I. Tardos, and R. Pfeffer, "A Micro-Level Based Charac-
terization of Granulation Phenomena," Powder Technol., 65,257 (1991)
18. Liu, L.X., S.M. Iveson, J.D. Litster, and B.J. Ennis, "Coalescence of
Deformable Granules in Wet Granulation Processes," AIChE J., 46,
529 (2000)
19. Jenike & Johansen, Westford, Massachusetts
20. Idea mentioned to the authors by Professor Martin Rhodes, Monash
University, Australia (2000)
21. Reynolds, 0., "Experiments Showing Dilatancy, a Property of Granu-
lar Materials, Possibly Connected with Gravitation," Proc. Roy. Inst.,
11, 354 (1886)
22. Nagel, S., "Shifting Sands," New Scientist, 53, July (2000)
23. Rhodes, M., Introduction to Particle Technology," Wiley (2000)
24. Liffman, K., D. Gutteridge, M.J. Rhodes, and G. Metcalfe, "The Bra-
zil Nut Effect," CHEMECA '98, Paper #122
25. Shinbrot, T., and F.J. Muzzio, "Non-Equilibrium Patterns in Granular
Mixing and Segregation," Physics Today, 53, 25, March (2000)
26. 0

Chemical Engineering Education

Chemical Engineering as a Career
Continued from page 273.

Perhaps the most important conclusion that can be drawn
from this survey relates to the different extent that an enjoy-
ment of chemistry at school and the role of chemistry teach-
ers influences students to study chemical engineering. It is
worth restating that across all country groupings, 90% of the
respondents admitted to being influenced to some degree be-
cause they liked chemistry at school, whereas 60% of the
respondents outside of Vietnam were not influenced at all by
their chemistry teachers. This suggests that educational and
professional institutions should work together with chemis-
try teachers to raise the profile of the chemical engineering
profession in the secondary school chemistry classroom. At
the same time, careers teachers have little influence on stu-
dents selecting chemical engineering. Further work, possi-
bly including the use of focus groups, needs to be done to
identify the reasons for this. It may be that there exists con-
siderable scope for working with careers teachers to promote
the profession.
By its very nature, this limited survey cannot gauge the
effects that localized programs and activities such as those
run by North Carolina State and Tufts have had on increas-
ing interest in the profession. Nonetheless, this survey pro-
vides the basis of an international benchmark for com-
paring factors that influence students to select our pro-
fession for their future.
This survey has identified and to some extent quantified
the important influences that acted on students currently en-
rolled in undergraduate chemical engineering degree pro-
grams. This work could be extended by surveying not only
students before they have finally selected their courses, but
also students currently enrolled in other engineering disci-
plines. The survey could also be extended to more non-En-
glish speaking countries.
The author welcomes contact from academics who might
be interested in participating in another, more comprehen-
sive survey.

ACKNOWLEDGMENTS
The author gratefully acknowledges the cooperation of the
students who participated in the survey. Special thanks are
owed to those people who administered the surveys at the
participating institutions: Dr. Adisa Azapagic (University of
Surrey), Dr. Charun Buyakan (Prince of Songkla University),
Dr. Caroline Crosthwaite (University of Queensland), Pro-
fessor Fraser Forbes (University of Alberta), Professor Phan
Van Ha (University of Hanoi), Dr. Graham Harrison (Clemson
University), Professor Andrew Hrymak (McMaster Univer-
sity), Professor Lester Kershenbaum (Imperial College of
Science, Technology and Medicine), Professor Peter Reilly
(Iowa State University), Professor Martin Rhodes (Monash

University), Professor Jonathan Seville (University of Bir-
mingham), Professor Phan Minh Tan (Ho Chi Minh City Uni-
versity of Technology), Dr. J. Keith Walters (University of
Nottingham), Professor Laurence Weatherley (University of
Canterbury), Dr. Robin Wilcockson (University of
Loughborough). In addition, the assistance of Mr. Vo Son
Binh of the University of Melbourne is gratefully acknowl-
edged for his assistance in conducting the surveys in Hanoi
and Ho Chi Minh City, and to Mr. Duong Minh Hai of the
University of Melbourne for his translation of the survey into
Vietnamese.

REFERENCES

1. "This is Chemical Engineering," Institution of Chemical Engineers in
Australia, Melbourne, Australia (1993)
2. "Chemical Engineering: One Profession, Many Careers," Institute of
Chemical Engineers, Rugby, UK (1997)
accessed April of 2003
4. "Career Choices for Chemical Engineers," at careers/> accessed April of 2003
5. Bottomley, L.J., and E.A. Parry, "Engineering Alive: A Summer Engi-
neering Camp for Middle School Students and Teachers," Proc. ASEE
6. Shallcross, C.D., D. Novak, C. West, C.F. Duffield, and R.L. Hughes,
"Engineering! For Secondary School Science and Maths Teachers,"
Proc. Australian Assn. for Eng. Ed. 7th Conv., Melbourne, Australia,
December, 394 (1995)
7. Shallcross, D.C., J. Anderson, and D. Schaffner, "Introducing Engi-
neering into Secondary Schools: A Collaboration Between University
Academics and School Teachers," Proc. 3rd UICEE Ann. Conf. Eng.
Ed., 214 (2000)
8. Shallcross, D.C., D. Dell'Oro, D. Lamson, M. Schaffner, and J. Vincent,
Investigative Projects in Engineering: Designing a Bulk Liquid Chemi-
cal Storage Facility, Mathematical Association of Victoria, Melbourne,
Australia (1999)
9. Rushton, E., M. Cyr, B. Gravel, and L. Prouty, "Infusing Engineering
into Public Schools," Proc ASEEAnn. Conf., Montreal, Canada (2002)
10. Isaacs, B., "Mystery of the Missing Women Engineers: A Solution,"
ASCE J. Prof. Issues in Eng. Ed Pract., 127(2), 85 (2001)
ence and Engineering Majors: A Survey of GRE Test Takers," GRE
Board Professional Report No. 85-01 P, ETS Research Report 92-51,
Educational Testing Service, Princeton, NJ (1992)
12. Burton, L., L. Parker, and W.K. LeBold, "U.S. Engineering Career
Trends," ASEE Prism, 5/98, 18 (1998)
13. Shallcross, D.C., "Perceptions of the Chemical Engineering Profes-
sion: Results of an International Survey," Internat. Conf. Eng. Ed.,
Manchester, UK (2002)
14. Shallcross, D.C., and G.H. Covey, "Undergraduate Chemical Engi-
neering Student Perceptions of the Pulp and Paper Industries," 6th
World Congress of Chem. Eng., Melbourne, Australia (2001)
15. Kumagai, J., "Physics Anxiety in Engineering," Physics Today (1999)
16. Shallcross, D.C., and D.G. Wood, "Combined Degree: A New Para-
digm in Engineering Education," Proc. ASEE Ann. Conf., Montreal,
17. Lewis, S., "Intervention Programs in Science and Engineering Educa-
tion: From Secondary Schools to University," in Equity in the Class-
room Towards Effective Pedagogy for Girls and Boys, P.E Murphy
and C.F. Gipps, eds., The Falmer Press, London, 192 (1996) J

Fall 2003

Random Thoughts...

LEARNING BY

DOING

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

Thanks to some excellent research in recent decades,
we know a great deal about how learning happens
and how little of it happens in lectures.01 As fasci-
nated as professors think students should be with an hour of
material like
dA = PdV SdT -> dA = (dA/dV)TdV + (dA/dT)vdV &
dG = VdP SdT -- dG = (dG/dP)7P + (oG/dT)p dV
& dH = (dH/dS)pdS + (OH/9P)sdP -- V = (dH/dP)s = (dG/
dP)r _> S = (dA/dT)V = (dG/dT), & (dP/dT)v = (dS/dV)r

there's no mistaking the dazed stupor that falls over class-
rooms after even just a few minutes of it. Numbed minds
can't learn. The students who decide that their interests lie in
cutting that 8 a.m. class and getting more sleep may be right
on target.
You have roughly 40 contact hours in a typical course. If
all you do in them is lecture, you might as well just hand out
your notes and let the students find something more produc-
tive to do with all that time. The only way a skill is devel-
oped-skiing, cooking, writing, critical thinking, or solving
thermodynamics problems-is practice: trying something,
seeing how well or poorly it works, reflecting on how to do it
differently, then trying it again and seeing if it works better.
Why not help students develop some skills during those con-
tact hours by giving them some practice in the tasks they'll
later be asked to perform on assignments and tests?
Which is to say, why not use active learning? At several
points during the class,
1. Give the students something to do (answer a ques-
tion, sketch a flow chart or diagram or plot, out-
line a problem solution, solve all or part of a prob-
lem, carry out all or part of a formula derivation,
predict a system response, interpret an observa-
tion or an experimental result, critique a design,

troubleshoot, brainstorm, come up with a ques-
tion,...).
2. Tell them to work individually, in pairs, or in groups
of three or four; tell them how long they'll have
(anywhere from 10 seconds to two minutes); and
turn them loose.
3. Stop them after the allotted time, call on a few in-
teered responses, provide your own response if
necessary, and continue teaching.
You may also occasionally do a think-pair-share, in which
the students work on something individually and then pair
up to compare and improve their responses before you call
on them.
As little as five minutes of that sort of thing in a 50-minute
class session can produce a major boost in learning. For start-
ers, it wakes students up: we have seen some of them elbow-
ing their sleeping neighbors when an active learning task was
assigned. Academically weak students get the benefit of be-
ing tutored by stronger classmates, and stronger students get
the deep understanding that comes from teaching something
to someone else. Students who successfully complete a task
own the knowledge in a way they never would from just
watching a lecturer do it. Students who are not successful are

Richard M. Felder is Hoechst Celanese Professor Emeritus of Chemical
Engineering at North Carolina State University. He received his BChE
from City College of CUNY and his PhD from Princeton. He is coauthor of
the text Elementary Principles of Chemical Processes (Wiley, 2000) and
codirector of the ASEE National Effective Teaching Institute
Rebecca Brent is an education consultant specializing in faculty devel-
opment for effective university teaching, classroom and computer-based
simulations in teacher education, and K- 12 staff development in language
arts and classroom management. She co-directs the SUCCEED Coali-
tion faculty development program and has published articles on a variety
of topics including writing in undergraduate courses, cooperative learn-
ing, public school reform, and effective university teaching.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

put on notice that they don't know something they may need
to know, so when the answer is provided shortly afterwards
they are likely to pay attention in a way they never do in
The number of possible active learning tasks is limitless.121
At a minimum, you can ask the same questions you would
class trying to answer them and not just the same two stu-
dents who always answer them. You can also use any of the
activities suggested in Item 1 of the list several paragraphs
back, and you might occasionally run a TAPPS ("thinking-
aloud pair problem solving") exercise, arguably the most
powerful classroom instructional technique for promoting
understanding.E3] Have the students work in pairs through a
complex derivation or worked-out problem solution in the
text or on a handout, with one of them explaining the solu-
tion step-by-step and the other questioning anything unclear
and giving hints when necessary. Periodically stop them, call
on several of them for explanations, provide your own when
necessary, and have the students reverse roles in their pairs
and proceed from a common starting point. It may take most
or all of a class period to work through the entire solution,
but the students will end with a depth of understanding they
would be unlikely to get any other way.
Here are several techniques to make active learning as ef-
fective as possible.
At the beginning of the course, announce that
you'll be assigning short exercises during class and
explain why you're doing it (research shows
students learn by doing, and the exercises will give
them a head start on the homework and tests). The
explanation can help defuse the resistance some
students feel toward any teaching approach other
than the instructor telling them just what they need
to know for the exam.
After an active learning exercise, call on a few
individuals for responses before opening the floor to
volunteers. The knowledge that you might call on
them gets active participation from students who
would normally just sit passively and let others do
the work.
Go for variety. Vary the type of activity (answer-
ing questions, solving problems, brainstorming,
etc.), the activity duration (10 seconds-2 minutes),
the interval between activities (1-15 minutes), and
the size of the groups (1-4 students). Mixing things
up keeps active learning from becoming as stale as
straight lecturing.
As many as half of the participants in our recent teaching

workshops report using active learning in their classes, but
nonusers often have concerns about the approach. (1) If I use
active learning, will I still be able to cover my syllabus? (2)
Can I do it in a really large class? (3) What should I do if
some of my students refuse to participate?
We have offered detailed answers to the first two questions
in another column14 and so will just give the short versions
here. (1) Yes. (See Reference 4 for details on how.) (2) Yes,
and in fact, the larger the class, the more important it is to use
active learning. Try finding another way to get students ac-
tively engaged when there are 150 of them in the room.
What about students who refuse to participate? There may
indeed be several who just sit staring straight ahead when
groupwork is assigned, even after the awkwardness of the
first few times has passed. We never see more than two or
three of them in our classes, but for the sake of discussion
let's say it's as many as 10% in yours. That means that while
you're doing an active learning exercise, 90% of the students
are actively engaged with the material and getting practice in
the skills you're trying to teach them, and 10% are out to
lunch. On the other hand, at any given moment in a tradi-
tional lecture, if as many as 10% of your students are ac-
tively involved with the lecture material you're doing very
well. No instructional technique works for all students at all
times: the best you can do is reach as many as possible, and
90% is more than 10%. If some students opt out, don't let it
bother you-it's their loss, not yours.
In short, if you start using active learning in your classes,
you can expect to see some initial hesitation among the stu-
dents followed by a rapidly increasing comfort level, much
higher levels of energy and participation, and above all, greater
learning. Check it out.

References
1. (a) McKeachie, W.J., P.R. Pintrich, Y-G Lin, D.A. Smith, and R.
Sharma, Teaching and Learning in the College Classroom: A Review
of the Research Literature, 2nd ed., University of Michigan, Ann Ar-
bor, MI (1990); (b) Bransford,J.D., A.L. Brown, and R.R. Cocking,
Eds. How People Learn: Brain, Mind, Experience, and School, Na-
tional Academy Press, Washington, DC (2000)
2. (a) Johnson, D.W., R.T. Johnson, and K.A. Smith, Active Learning:
Cooperation in the College Classroom, 2nd edn., Interaction Book Com-
pany, Edina, MN, (1998); (b) Felder, R.M., and R. Brent, "Coopera-
tive Learning in Technical Courses: Procedures, Pitfalls, and Payoffs,"
ERIC Document Reproduction Service, ED 377038 (1994),

3. Lochhead, J., and A. Whimbey, "Teaching Analytical Reasoning
through Thinking Aloud Pair Problem Solving," in J.E. Stice (Ed.),
Developing Critical Thinking and Problem-Solving Abilities, New
Directions for Teaching and Learning, No. 30, Jossey-Bass, San Fran-
cisco, CA (1987)
4. Felder, R.M., and R. Brent, FAQs-II. Chem. Engr Ed., 33(4), 276-277
(1999) D

Fall 2003

All of the Random Thoughts columns are now available on the World Wide Web at
http://www.ncsu.edu/effective_teaching and at http://che.ufl.edu/-cee/

BBlecture

FUTURE DIRECTIONS IN

CHE EDUCATION

A New Path to Glory

This is the 2003 ConocoPhillips Lecture, presented at Oklahoma
State University, Stillwater, Oklahoma, on April 25, 2003.

ARVIND VARMA
University of Notre Dame Notre Dame, IN 46556
he chemical engineering profession is in the midst of
great change. Chemical engineers used to focus on
making large quantities of small, relatively simple
molecules (commodity products). With increasing frequency,
in the future they will have to make smaller quantities of more
complex, possibly biologically active, molecules and
nanostructured materials (specialty products). Further, we
used to only scale things up; now we must also scale down,
as in lab-on-a-chip devices and portable fuel cells. In addi-
tion, developments in science and other engineering disci-
plines-such as nanoscale synthesis and characterization tech-
niques, molecular biology and information technology-in-
fluence progress in our field. There is also a continuing need
to consider what will be the energy sources for the future-
conventional fuels such as oil, gas, and coal, or others such
as nuclear, biomass, and solar? Finally, growing environmen-
tal considerations in society make us aware of the long-term
and global implications of our manufacturing practices.
I would like to discuss how all these factors, currently at
play, will impact the education of chemical engineers pri-
marily at the undergraduate level, although some remarks
opportunities.

THE DEVELOPMENT
OF CHEMICAL ENGINEERING
Before turning toward the future, it is instructive to first
examine how the discipline of chemical engineering evolved.
Fascinating detailed accounts of early developments in the
curriculum and the profession have been presented in many
sources,1-61 so I will keep this discussion brief.
It is generally agreed that chemical engineering as a dis-
tinct discipline began in January of 1888 when George E.
Davis gave a series of twelve lectures on the subject at the

Manchester Technical School in England. He had previously
coined the term "chemical engineer" in 1880 and promoted
it (unsuccessfully) to found a society of chemical engineers.
The first four-year undergraduate chemical engineering de-
gree program was established at MIT by the chemistry pro-
fessor Lewis Mills Norton in 1888. It was soon followed by
those at the University of Pennsylvania (1892), Tulane (1894),
Michigan (1898), and others, including our own at Notre
Dame (1909). Most early curricula had their origin in chem-
istry departments, although there are examples of some evolv-
ing from mechanical (e.g., Colorado, 1904) and electrical (e.g.,
Wisconsin, 1905) engineering departments as well.
The early chemical engineering curricula included an amal-
gam of courses taken by chemists and mechanical engineers,
with those in industrial and applied chemistry in the third
and fourth years being unique to the field. The discipline re-
ceived its first unifying theme with development of the con-
cept of "unit operations," which is often called the first para-
digm of chemical engineering. It grew out of the realization
that purely physical operations of chemical processing,
whether to produce smaller quantities of fine or larger amounts
of heavy chemicals, all depended on certain common prin-
ciples of physics and chemistry. As first noted by Arthur D.
Little (1915) in the Chemical Engineering Visiting Commit-

Arvind Varma is the Arthur J. Schmitt Profes-
sor of Chemical and Biomolecular Engineer-
ing, and Director of the Center for Molecularly
Engineered Materials at the University of Notre
Dame. Author or coauthor of more than 230
archival journal research articles and three
books, he has received a variety of recogni-
tion for his teaching and research, including
the Wilhelm Award of AlChE (1993) and the
Chemical Engineering Lectureship Award of
ASEE (2000).

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

tee report to the President and Corporation of MIT
Any chemical process, on whatever scale conducted, may
be resolved into a coordinated series of what may be termed
'unit actions,' as pulverizing, mixing, heating, roasting, ab-
sorbing, condensing.... The number of these basic unit op-
erations is not very large and relatively few of them are in-
volved in any particular process.
The first significant textbook for the discipline, Principles of
Chemical Engineering by Walker, Lewis, and McAdams of
MIT, appeared in 1923.'71 It showed that by combining a few

The discipline received its first unifying
theme with development of the concept
of "unit operations," which is often
chemical engineering...

chemical industries followed, and in turn catalyzed, devel-
opments in chemical engineering.
The 1950s also saw a greater emphasis on the use of analy-
sis and applied mathematics in solving chemical engineering
problems that can be traced to three separate events.t1"I First,
it was recognized that the individual unit operations involve
a combination of the same basic principles in microscopic
momentum, heat, and mass transport, each with similar math-
ematical descriptions. Thus, a study of the individual trans-
port processes as a unified subject "Transport Phenomena"
can lead to a greater understanding of chemical processes;
this concept was greatly aided by the appearance of a fa-
mous book in 1960 with that same title, written by Bird,
Stewart, and Lightfoot.""I
Second, applications of sophisticated mathematical tech-
niques were yielding strong results for the design and opera-

principles of momentum, mass, and heat transfer, it is pos-
sible to understand the unit operations. It was an extremely
influential textbook that charted the education, development,
and practice of chemical engineering for decades.
Soon after the introduction of unit operations, attention
turned to developing procedures for overall material and en-
ergy balances in processes, including single or multiple reac-
tions, recycle, and bypass, and curricula in the 1930s included
courses in industrial chemical calculations. In the 1940s,
courses in thermodynamics were introduced that included
properties of gases and liquids and applications of both the
first and second laws. This decade also saw the development
of courses in equipment and process design.
Although there were important efforts in German, notably
by Damkohler,1sI the systematic development of chemical and
catalytic reaction engineering principles in the English lan-
guage, using information on reaction rates and catalysis,
waited until the appearance in 1947 of Chemical Process
Principles: Part III. Kinetics and Catalysis by Hougen and
Watson.[9' By the end of the 1950s, most chemical engineer-
ing undergraduates took formal courses in reaction engineer-
ing and courses in process control were initiated.
All through this period, since the early days of the profes-
sion, a synergistic relationship existed between academia and
industry. Much of university research was supported by in-
ing petroleum refining, petrochemical, and chemical indus-
tries. The oil companies refined petroleum crude to produce
gasoline and other fuels for automobiles and airplanes, the
petrochemical complexes produced bulk chemicals, while the
chemical companies produced these as well as polymers, fer-
tilizers, paints, and other specialty chemicals. All these prod-
ucts satisfied a rising demand from a society that had an in-
creasing standard of living. The growth of the petroleum and

. the 1950s and 60s saw the emergence of
the so-called engineering science approach
in chemical engineering.

tion of separation processes and chemical reactors, as exem-
plified in the works ofAmundson.1 21 Finally, the general avail-
ability of computers, whereby it became possible to conduct
numerical simulations of process models to identify optimal
design and operating conditions, also accelerated the appli-
cation of analytical and numerical techniques.
Thus, the 1950s and 60s saw the emergence of the so-called
engineering science approach in the discipline-the second
paradigm in chemical engineering. This approach led to a
is a unique blend of chemistry, physics, and mathematics.
The chemical engineers educated in this manner could effec-
tively develop, design, and operate complex chemical pro-
cesses that typically produced commodity products.

CURRENT STATUS AND CHALLENGES
I will now examine the current status of the discipline as it
relates to the education and employment of chemical engi-
neers. I will be brief since the topic has been addressed well
in a lecture by Ed Cussler last yearE3' and elsewhere.[141 Fur-
ther, there is much discussion of these issues in the context of
undergraduate curriculum revitalization as a result of the
"New Frontiers in ChE Education" workshops organized
through the Council for Chemical Research (CCR) and spon-
sored by the National Science Foundation (NSF).1"1
Education

A typical undergraduate chemical engineering curriculum
consists of foundation courses in mathematics, physics, chem-

Fall 2003

istry, and engineering in the early years, as well as courses in
humanities and social sciences that serve to provide a broad
education. The chemical engineering courses typically include
offerings in mass and energy balances, thermodynamics,
transport processes, separations, reaction engineering, pro-
cess design, process control, and laboratories where principles
learned in the lecture courses are reinforced and include ele-
ments of both written and oral communication of experimen-
tal results and analysis. Finally, there are generally several
electives to choose from, in chemical engineering as well as
in other science and engineering disciplines.
A striking fact is that while the discipline of chemical engi-
neering has evolved significantly over the last forty or so years
(as I shall detail next), the undergraduate curriculum has re-
mained essentially unchanged. The engineering science para-
digm continues to dominate the core curriculum as well as
the textbooks that are used. The examples used in courses
continue to come primarily from the petroleum refining and
bulk chemicals production industries.

Employment

Between 50% and 60% of the BS degree chemical engi-
neering graduates in the U.S. seek industrial employment im-
mediately upon graduation-Figure 1 shows their distribu-
tion during the 2000-01 year by nature of the industry. It is
remarkable that the skills learned from understanding engi-
neering principles and processes, based largely on physical
and chemical transformations, are considered to be valuable
by a large number of industries. If we consider chemical and
energy companies as the traditional employers, however, then
only about 40% of chemical engineers find their initial em-
ployment there. About an equal number go to the electronic,
food/consumer products, biotechnology, and materials-related

Figure 1.
Busine
Initial industrial Engrg. Svcs.- Environmental 2.4
employment of Engrg. Svcs.- Research
BS chemical & Testing 1.8%
engineers, Engrg. Svcs. Design
y& Cnstrctn. 5.6%
2000-01 year.
(AIChE,
(ArChE, Pulp & Paper 2.1%
Department
of Career
Services) Biotech./Related
Services) -Inh.+i- Dharmn \ l /

industries, which were not significant employers some years
ago. Overall, as noted elsewhere,1141 only about 25% of the
graduates are hired by companies that manufacture com-
modity chemicals emphasized in the curriculum, while
about 50% go to those with a product orientation-in
contrast with approximately 80% and 15%, respectively,
twenty-five years ago.
In addition to the increasingly wider spectrum of indus-
tries where chemical engineers now find employment, sev-
eral other factors currently at play, even with the traditional
energy and chemical companies, are

The companies are becoming more global, with a
greater fraction of their manufacturing and research
conducted overseas
*Many companies are merging into larger ones, with
significant reductions in the workforce
Chemical companies are increasingly incorporating
life sciences into their manufacturing and products
Chemical engineers cannot expect to work with a
single company or industry type and must now accept
several job changes over their professional careers

Other Driving forces

There are also other driving forces currently operative, and
I would like to enumerate some of them, without claiming
completeness. First, biology is rapidly developing as a mo-
lecular-based science so that its connections can now be made
more readily to chemical engineering. There are numerous
opportunities for coupling molecular-level understanding of
biological reactions and interactions with chemical engineer-
ing concepts and processes, that can result in products of tre-

Chemical Engineering Education

mendous value. Some examples are bioprocessing for pro-
duction of pharmaceuticals and even commodity chemicals,
metabolic engineering, controlled drug delivery, biomaterials,
tissue engineering, functional genomics, gene therapy, drug
design and discovery, nano and micro biotechnology for lab-
on-a-chip devices, etc.
Second, there is a current trend toward establishment of
bioengineering and biomedical engineering departments,
driven by the Whitaker Foundation grants (see, for example,
Ref. 16). Owing to the closest fit, these new programs com-
pete for students and resources that in many instances would
otherwise come to chemical engineering.
Third, there is growing awareness of the pressures that cur-
rent manufacturing practices place on the environment in
terms of pollutants that require remediation and waste gen-
eration that demands disposal and diminishes resource uti-
lization. Thus, environmentally benign processing and sus-
tainable development is receiving increased attention, both
to satisfy environmental regulations and to increase prof-
itability.
Fourth, new educational tools and methods are being de-
veloped that can be used to enhance the quality of chemical
engineering education. Examples include use of web-based
educational materials that can be shared across institutions,
web interfaces to run actual laboratory experiments, and
simulations to explore influence of parameters or to learn
about cases too dangerous to conduct in the laboratory,
such as explosions.

THE FUTURE DIRECTIONS
Based on the current status of the discipline, some sugges-
tions can now be made for future directions of chemical en-
gineering education, especially at the undergraduate level.
The intent is to provide a framework that takes advantage of
both the unique aspects of the present curriculum and the
changing scene related to employment and developments in
other science and engineering disciplines. My basic premise
is that the defining characteristics of chemical engineers, i.e.,
the ability to apply molecular level understanding to convert
raw materials into more valuable products by physical, chemi-
cal and biological transformation using economic and safe
processes, should remain unaltered. Thus, the core subjects
in the curriculum involving mass and energy balances, ther-
modynamics, transport processes, reaction engineering, sepa-
rations, laboratories, and design should continue in the fu-
ture, but with structural modifications as discussed below.

Expanded Examples of Applications

As noted earlier, chemical engineers now find employment
in a wide variety of industries. It is apparent that their skill
set, which includes chemistry in addition to physics and math-

.. molecular engineering of products
and processes is emerging as
the discipline.

ematics also available to other engineering disciplines, makes
them uniquely qualified to impact a diverse set of technolo-
gies. The curriculum, however, continues to include examples
primarily from the petroleum refining, petrochemical, and
bulk chemicals industries. It is important to broaden the scope
by including examples from areas such as materials process-
ing, biotechnology, pharmaceuticals, food processing, and en-
vironment. Similarly, when discussing design, considerations
of product and not merely process should be included. These
movements will require new textbooks and teaching mod-
ules. Some steps in this direction are already being taken.

Modern Biology as an
Underlying Fundamental Science

Recent developments in molecular and cellular biology, the
similarity of using biological and chemical reactions at the
molecular level for design of new products and processes,
and the growth of biotechnology industries where chemical
engineers are currently employed (and from all indications
will be in greater numbers in the future) all suggest that biol-
ogy will soon reach an almost equal status with chemistry as
a basic science in defining chemical engineering. Thus, it is
now timely to include one or two formal courses in biology
and biochemistry in the early years of the undergraduate cur-
riculum. This requires two types of actions: one, working to-
gether with the relevant disciplines to arrive at suitable
courses, and two, incorporating elements of biology within
all the chemical engineering courses just as chemistry is to-
day. Thus, for example, in the reaction engineering course,
building upon knowledge of biochemistry and biology gained
earlier, connections between molecular mechanisms and mac-
roscopic kinetics could be made and related to modeling of
cells and bioreactors, similar to what is done today with chemi-
cal catalysis and diffusion-reaction in catalyst pellets leading
to fixed-bed reactor design. Similarly, based on biological
understanding, separations courses can readily include liv-
ing systems and processing of biomolecules.
Numerous opportunities also exist in other core courses,
such as mass and energy balances, thermodynamics, trans-
port processes, and design. These developments are likely to
take some time to materialize, but movement in this direc-
tion is critical for chemical engineers to contribute effectively
and exercise leadership in the biotechnology areas that offer
tremendous potential for growth.

Fall 2003

Recruitment of Talented and Motivated Students

People are our greatest asset, so for the vitality and future
of the discipline we must attract the best and the brightest to
chemical engineering. This will occur naturally if we offer
imaginative courses and programs involving new technolo-
gies, use newer methods and tools in our teaching, and pro-
vide intellectual challenges for our stu-
dents, so that they have promise of a
bright future while solving important
problems facing society.
A specific method I have found to
be effective in challenging students
intellectually is to involve them in un-
to do an independent project with only
general overall guidelines provided,
often using equipment assembled on
their own, is stimulating for most stu-
dents. Over the last ten years, when I
began to keep a record of this activity,
search in my laboratory, many starting
in their junior year, and some 15 have
gone on to attend graduate school else-
where, most for PhD degrees. (In a
lighthearted vein, I sometimes say that
I have saved a large number of bril-
liant chemical engineers from leaving
our profession for careers such as in
medicine or law-of course, I do not
say this in front of my daughters, one a
lawyer and the other studying to be-
come one!) Many work closely with a
graduate student or a postdoctoral as-
sociate, to mutual benefit, and I have a
number of journal papers with undergraduates as coauthors.
Undergraduate research exposes students to the frontiers of
the field and provides the intellectual challenges that are dif-
ficult to match in typical lecture or laboratory courses.

Name Change of Departments

As noted earlier, the chemical engineering profession is
changing rapidly and faces many new challenges. The most
impressive movement appears to be the emergence of mod-
em biology as a fundamental science, on an almost equal
footing with chemistry, in defining the field. Further, all indi-
cations are that its role will continue to grow in the future.
For this and other pragmatic reasons, including the facts that
students are attracted to biological departments and degree
names and that we face new competition for students and
resources from new bioengineering and biomedical engineer-
ing departments (some 90 such departments already existed

at the end of 2001Ei5]), many chemical engineering depart-
ments are changing their names to include some biological
term. Among several that are possible, chemical and
biomolecular engineering seems to be gaining acceptance,
as adopted recently by departments at Cornell, Illinois, and
ours at Notre Dame. It connects with the scientific base of
the discipline, is more inclusive of modern biotechnology as
compared with alternatives, and owing
to its molecular focus, it offers more
potential for collaborations with bio-
chemists and biologists. Thus, while
"What's in a name? That which we call
a rose, by any other name would smell
as sweet," for the reasons cited, I fa-
vor departmental name changes.

and Research
Although I have limited my remarks
so far to undergraduate education, I
would like to say a few words about
Graduate education also started in the
early 1900s, at both the MS and PhD
has essentially mirrored the curriculum
at the undergraduate level, with the
former always being more fundamen-
tal and mathematical in content. Thus,
courses in thermodynamics, kinetics
and reaction engineering, transport pro-
cesses, and mathematical analysis,
based on the engineering science ap-
proach, are currently required in most
graduate programs. They are augmented by other courses in
chemical engineering, various sciences, and other engineer-
ing disciplines, to suit the student's research needs and inter-
courses also need to include examples in newer application
areas and incorporation of biology, particularly as it is intro-
duced in the earlier years.
In research, chemical engineering graduate programs have
moved forward rapidly to embrace all areas of new technolo-
gies, including biological, materials, environmental, infor-
mation, and energy. This movement was promoted by the
National Research Council's "Frontiers in Chemical Engi-
neering" report published in 1988,E1'1 whose recommenda-
tions were recently reinforced and updated.[sJ Further, there
is a growing trend toward interdisciplinary research involv-
ing faculty members and students from different fields work-
ing together to solve research problems. This trend has its
origin in at least two related facts: one, the cutting-edge prob-

Chemical Engineering Education

By offering imaginative courses that use new teaching methods and tools, and by providing
intellectual challenges, we will be able to attract the best and brightest to chemical engi-
neering and educate them to become leaders in industry, academia, and society.

lems are often at the interface between disciplines, and two,
funding agencies (now primarily federal and state, as com-
pared to mainly industrial prior to the 1950s) seem to favor
this approach. In turn, universities have responded by estab-
lishing research centers, typically involving colleges of sci-
ence and engineering but sometimes also business or public
policy, that facilitate interdisciplinary interactions. While the
to tension, I believe that organization along these lines is re-
quired and that this structure is here to stay for some time.
Finally, there is another movement currently occurring in
the chemical engineering discipline, particularly at the gradu-
ate education and research levels. On one hand, in addition
to a molecular-level description of chemical and biological
transformations and processes, there is growing feasibility
now to also conduct molecular-scale simulations to compute
thermodynamic, transport, and other properties of fluids and
materials. On the other hand, owing to the strengths of analy-
sis inherent in the engineering science approach, along with
a systems view, it is possible to analyze complex systems
and their interactions. These directions are changing the na-
ture of chemical engineering such that it could be claimed
that molecular engineering of products and processes is
emerging as a new paradigm for the discipline. This move-
ment will take some time to significantly influence the edu-
cation of chemical engineers at the undergraduate level, and
there is current discussion ongoing in this regard."5'

CONCLUDING REMARKS
Chemical engineering as a distinct discipline started with
applications primarily in petroleum refining and bulk chemi-
cals production industries, but skills developed as a result of
a solid foundation in the fundamental sciences (chemistry,
physics, mathematics, and now increasingly, biology), along
with a quantitative engineering science approach, have per-
mitted chemical engineers to move rapidly into many of the
emerging technologies. Their impact in the newer areas will
be enhanced by continuing the core curriculum and augment-
ing it by expanding examples of applications, incorporating
biology in all core courses, and including orientation toward
both product and process design. By offering imaginative
courses that use new teaching methods and tools, and by pro-
viding intellectual challenges, we need to attract the best and
brightest to chemical engineering and educate them to be-
I hope that these remarks, along with the current discus-
sion ongoing in the NSF/CCR workshops,1I51 will lead to in-

Fall 2003

novative chemical engineering programs that involve new
technologies and provide a bright future for our students while
solving important problems facing society.

ACKNOWLEDGMENTS
I have benefited much from discussions with my colleague
Mark McCready. Bob Armstrong and Barry Johnston of MIT
helped immensely by providing information about the NSF/
CCR workshops. The Edison Lectures of Bob Brown, also
of MIT, provided a valuable perspective in the evolution of
chemical engineering. Finally, by collecting data from sources
and designing slides, Chris Norfolk and Alexander Mukasyan
helped prepare this lecture.

REFERENCES
1. Aris, R., "Academic Chemical Engineering in an Historical Perspec-
tive," I&EC Funds., 16,1 (1977)
2. Hougen, O.A., "Seven Decades of Chemical Engineering," Chem. Eng.
Prog., 73(1), 89 (1977)
3. Pigford, R.L., "Chemical Technology: The Past 100 Years," C&ENews,
54(15), 190 (1976)
4. Furter, W.F., Editor, "History of Chemical Engineering," Adv. in Chem.
Series, 190 (1980)
5. Furter, W.F., Editor, A Century of Chemical Engineering, Plenum Press,
New York, NY (1982)
6. Scriven, L.E., "On the Emergence and Evolutiion of Chemical Engi-
neering," Adv. in Chem. Eng., 16, 3 (1991)
7. Walker, W.H., W.K. Lewis, and W.H. McAdams, Principles of Chemi-
cal Engineering, McGraw-Hill, New York, NY (1923)
8. Damk6hler, G., "Einfluss von Diffusion, Str6mung und Warmetransport
auf die Ausbeute bei chemisch-technischen Reaktionen," Der Chemie-
ingenieur, A. Euken and M. Jakob, eds., 3, 359 (1937)
9. Hougen, O.A., and K.M. Watson, Chemical Process Principles: Part
III. Kinetics and Catalysis, John Wiley, New York, NY (1947)
10. Varma, A., "Some Historical Notes on the Use of Mathematics in Chemi-
cal Engineering," pages 353-387 in A Century of Chemical Engineer-
ing, W.F. Furter, ed., Plenum Press, New York, NY (1982)
11. Bird, R.B., W.E. Stewart, and E.N. Lightfoot, Transport Phenomena,
John Wiley & Sons, New York, NY (1960)
12. Amundson, N.R., The Mathematical Understanding ofChemical Engi-
neering Systems: Selected Papers ofNeal R. Amundson, R. Aris and A.
Varma, eds, Pergamon Press, Oxford (1980)
13. Cussler, E.L., "What Happens to Chemical Engineering Education?"
Phillips Lecture, Oklahoma State University (2002)
14. Cussler, E.L., D.W. Savage, A.P.J. Middelberg, and M. Kind, "Refocus-
ing Chemical Engineering," Chem. Eng. Prog., 98(1), 26S (2002)
15. New Frontiers in Chemical Engineering Education, a series of work-
shops on the Chemical Engineering Undergraduate Curriculum; docu-
ments available following the link at
16. Katona, P.G., "The Whitaker Foundation: The End Will be Just the Be-
ginning," IEEE Trans. Med. Imaging, 21, 845 (2002)
17. Frontiers in Chemical Engineering: Research Needs and Opportuni-
ties, National Academy Press, Washington, DC (1988)
18. Beyond the Molecular Frontier: Challenges for Chemistry and Chemi-
cal Engineering, The National Academies Press, Washington, DC (2003)
0

289

Classroom

EXCEPTIONS TO THE

LE CHATELIER PRINCIPLE

DAVID S. CORTI, ELIAS I. FRANSES
Purdue University West Lafayette, IN 47907-2100

When studying chemical reactions within a single
phase, chemical engineers require knowledge of
the equilibrium constants. For a given tempera-
ture and pressure, equilibrium compositions may then be cal-
culated for all relevant reactions. If the temperature, pres-
sure, or composition of one of the components changes, how-
ever, the equilibrium position usually shifts. The direction of
such shifts can be calculated by direct computation of the
new equilibrium state.
Observations of the direction of shifts in the equilibrium
position led to the formulation of a general statement referred
to as the "Principle of Le Chatelier,"E'1 or sometimes as the
"Principle of Le Chatelier and Braun."'21 Le Chatelier's prin-
ciple can be stated as follows:'1i
In a system at equilibrium, a change in one of the
variables that determines the equilibrium will shift the
equilibrium in the direction counteracting the change
in that variable.
The above statement is useful in inferring, without direct
calculation, the effects of changes in a system initially at equi-
librium. Yet, still not widely known, particularly in the chemi-
cal engineering literature, is that Le Chatelier's principle is
not universally valid, and exceptions are known to occur. (See,
however, Sandler[2] and Tester and Modell131 as examples of
current chemical engineering textbooks that highlight the limi-
tations of the above statements. Exceptions to Le Chatelier's
principle appear to be more widely known in the physical
chemistry literature and have been discussed for some time.
See, for example, de Heer141 and Liu, et al.,E15 for an historical
account of Le Chatelier's principle.)
Consider, for example, the ammonia synthesis reaction
N2 +3H2 <.- 2NH3
in which equilibrium has been established at a given tem-

perature, T, and pressure, P. Le Chatelier's principle predicts
that the reaction will shift to the right (i.e., more ammonia
will be produced) upon the addition of more nitrogen to the
reaction vessel. If the initial mole fraction of nitrogen ex-
ceeds 0.5 and the given T and P are held fixed, however, the
reaction instead proceeds to the left, producing more nitro-
gen, as predicted from rigorous equilibrium constant calcu-
lations (the value of 0.5, as shown later, is calculated assum-
ing ideal gas behavior). This shift to the left is a clear excep-
tion to the principle of Le Chatelier, which has not been rig-
orously proven[41
Proofs of this unexpected shift have been given before.14-61
Most chemical engineering texts do not provide a proof, ex-
cept, for example, Tester and Modell,i31 which does provide a
detailed proof. The most widely referenced and reproduced
proof is by Katz[16 (the procedure followed in Liu, et al.,15t is
nearly the same as the approach by Katz, although the au-

David S. Cortl is Assistant Professor of Chemi-
cal Engineering at Purdue University. His re-
search interests include molecular thermody-
namics of liquids (both stable and metastable),
glasses, and complex fluids, droplet conden-
sation and bubble nucleation, and the devel-
opment of molecular simulation algorithms. He
teaches courses on Thermodynamics and Sta-
tistical Mechanics.

Elias I. Franses is Professor of Chemical Engi-
neering at Purdue University. His research in-
terests include adsorption equilibria and dynam-
ics of surfactants and proteins at air/water inter-
faces, with applications to lung surfactants, and
at liquid/solid interfaces, for bioseparations. He
teaches courses on Colloidal and Interfacial
Phenomena, Thermodynamics, and Chemical
Reaction Engineering.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

To address the technical and educational issues of Le Chatelier's principle,
we therefore present in this paper a new and conceptually more straightforward
analysis of the direction of the equilibrium shift for the
ammonia synthesis reaction as an example.

thors were apparently unaware of Katz). This proof makes
use of a "reaction quotient" that has the same functional form
as the ratio of mole fractions at equilibrium and is applicable
whether or not equilibrium has been established. The value
of this reaction quotient, defined in Eq. (3), varies if a change
occurs, but must equal the equilibrium constant when the sys-
tem returns to an equilibrium state. The direction that the re-
action quotient takes to restore itself to the equilibrium value
determines the direction of reaction for the given change.
The use of a reaction quotient can be confusing to students,
particularly to students exposed to reaction equilibria for the
first time. To address the technical and educational issues of
Le Chatelier's principle, we therefore present in this paper a
new and conceptually more straightforward analysis of the
direction of the equilibrium shift for the ammonia synthesis
reaction as an example. Our approach is, however, more gen-
eral. In contrast to the other methods, changes at constant T
and P are now considered in which the value of the reaction
quotient is strictly held fixed and equal to the equilibrium
constant. Hence, the analysis makes no use of a separately
defined reaction quotient (that is applicable whether equilib-
rium is or is not established) and should be easier for stu-
dents to understand. The analysis also involves finite, as
well as infinitesimal, changes, which can be the basis of
future experimental tests that may demonstrate more viv-
idly the key thermodynamic laws (see del Pino, et al.,171
for an example of a simple experiment concerning shifts
of chemical equilibrium).
Le Chatelier's principle can be reformulated in a more gen-
eral way that becomes universally valid,14,51 although it bears
little resemblance to the statement given earlier. For peda-
gogical reasons, we briefly discuss this new general state-
ment in the last section of this paper. An excellent overview,
and proof, of this new general statement is given by de Heer.141
It is, however, only valid for infinitesimal changes from the
initial equilibrium state.151 In this paper, we also consider the
ammonia synthesis reaction for the case of adding nitrogen
in finite amounts (Liu, et al.,s15 considered finite additions as
well, but the present analysis provides a more straightfor-
ward and quantitative discussion). The value of 0.5 for the
mole fraction of nitrogen, above which the reaction proceeds
to the left while below the reaction proceeds to the right, is
shown to be true for infinitesimal additions of nitrogen.
For finite changes, no universally valid statement on the
direction in which the reaction shifts can be formulated, and
thus each case must be considered individually. In such cases,

instructors should advise ignoring the reformulated Le
Chatelier's principle and instead should calculate, in general,
the shift in the equilibrium state directly from the relations of
chemical equilibrium.

AMMONIA SYNTHESIS REACTION
Exception to the Principle of Le Chatelier
Let us consider the ammonia synthesis reaction and assume
for simplicity that the components comprise an ideal-gas mix-
ture. Analyses for nonideal mixtures, although possible, have
not been reported. Let species 1 represent nitrogen, species 2
hydrogen, and species 3 ammonia. The chemical potential of
each species i, i, in the ideal-gas mixture is given by181

i = Fi(T)+RTfinyP (1)
where F,(T) is the chemical potential of pure component i, as
an ideal gas, at the temperature T (and a fixed reference pres-
sure P.), R is the ideal gas constant, P is the system pressure,
and y, is the mole fraction of species i. At equilibrium, the
chemical potentials of the components participating in the
chemical reaction must satisfy"31

4Vii = 0 (2)

where vi is the stoichiometrically balanced coefficient of
species i in the reaction (vy = -1, v2 = -3, v3 = 2). Upon sub-
stituting Eq. (1) into Eq. (2), rearrangement yields

2
y3- P2K(T)= Kp(T,P) (3)
yly3
where K(T) is the equilibrium constant and Kp(T,P) is a func-
tion ofT and P. The ratio of mole fractions on the far left side
of Eq. (3) is the "reaction quotient."
Now, let the system be at equilibrium at a given T and P At
the initial equilibrium state, there are no, no, and no moles
of each species with mole fractions y?, y', and y' satisfy-
ing Eq. (3). Next, we consider the addition of A moles of
nitrogen (1), while keeping T and P constant. As the system
re-equilibrates, the reaction proceeds so that the final mole
numbers of each species will be given byE81

n = n + A -

n2 = no 3

n3= no + 2

Fall 2003

where i is the extent of reaction starting from the above
initial equilibrium state; i is defined to be positive if the
reaction proceeds to the right, i.e., nitrogen and hydro-
gen are consumed while ammonia is produced, and nega-
tive if the reaction proceeds to the left. The above rela-
tions imply that the final mole fractions are given by

= n++A yo +A'- '
n+A-24 1+A'-24'

yo-3'
Y2= = 2
1 1+A'-2 '

Y3 = y +23 (5)
1+A'- 2'

where n =no +no +n', A'-A/n, and 4'--4/n; A'
and i' are dimensionless quantities. Since T and P are
held constant, Eq. (3) implies that

33 = Kp(T,P)= (y) (6)
(y? +A',- y 3')3 y(y4 )

Equation 6 is valid for all values of A' and can be used to
determine the value of 4' for a given choice of A'. The
sign of i', however, determines the direction in which
the reaction shifts, and its value determines the extent of
the reaction triggered by the addition of nitrogen.
First, we focus on how the extent of the reaction varies
when an infinitesimal amount of nitrogen, i.e., A' -+ 0,
is added. One can solve Eq. (6) for various values of A'
and then determine the sign of 4' as A' -) 0. But since
-' -> 0 as A' -> 0, we instead determine d4' / dA' ana-
lytically for A' -> 0. To proceed, and for ease of further
manipulations, we first rewrite Eq. (6) as

We now differentiate both sides of Eq. (7) with respect to
A' for constant y?, y', and yo, letting
n = d' / dA' = d' / dA. We then take the limit for A' -4
0, with -> 0 as well, and finally solve for nT. After a
few lines of algebra, we obtain

d yoy(1-2y1)
d- 0 (8)
dA 4yy (1-y )+yjy +9yly3

Since the denominator in Eq. (8) is always positive, the
sign of il is given by the sign of (1 2y'). Therefore, for
infinitesimal additions of nitrogen, we conclude that

when y0 <2-, >0:
reaction proceeds to the right,
consistently with the Le Chatelier Principle (9a)

when y0 >-, 1<0:
2
reaction proceeds to the left,
against the Le Chatelier Principle (9b)
0 1
when y? = -,= O:
2
no reaction takes place,
against the Le Chatelier Principle (9c)
Hence, the exception to Le Chatelier's principle occurs when the
initial equilibrium mole fraction of nitrogen is equal to or ex-
ceeds 0.5 and is independent of the mole fractions of the other
species or of the values of the temperature and pressure.
Why the reaction reverses direction can be understood qualita-
tively1m by considering the form of the reaction quotient in Eq.
(3). The addition of nitrogen increases the mole fraction of nitro-
gen, y', but also causes a decrease in y2 (hydrogen) and Y3 (am-
monia). Since y2 is cubed in the denominator of the reaction quo-
tient, the decrease in y2 may have a more significant effect on the
reaction quotient than the increase in y, or decrease in Y3" When
the mole fraction of nitrogen is small, the change in y, upon addi-
tion of some nitrogen yields a proportionally larger change in y,
as compared to the decreases in y2 and Y3 To compensate, and so
ensuring that the reaction quotient must remain equal to K,(T,P),
the reaction proceeds to the right, reducing some of the added
nitrogen and producing more ammonia. When the mole fraction
of nitrogen is large, so that the mole fraction of hydrogen is small,
the proportional decrease in y2 is greater than the increase in y,.
The decrease in y2 is magnified by the appearance of y23, and so
the reaction proceeds to the left, generating more nitrogen and

Figure 1. Extent of reaction versus the amount of
nitrogen added for yo = 0.5.

Chemical Engineering Education

0.000-

0.6 0.7 0.8 0.9 1.0

A.

yo)2 (Yo )3
A'- ')(y 34

0.0 0.1 0.2

hydrogen (thereby offsetting, to some degree, the decrease in y2)
Why the reaction shifts direction when y, exceeds 0.5 is, however,
not readily apparent from the above analysis. The composition at
which the reaction changes direction is, in general, dependent on
the form of the reaction quotient. 61
The above exceptions, relations (9b) and (9c), do not occur when
hydrogen or ammonia are added to the system or when the tem-
perature and volume are held constant. 1161 The addition of an inert
species does not alter these conclusions. Many other reactions can
exhibit such exceptions to Le Chatelier's principle, including liq-
uid-phase reactions. Katz161 considers in general the conditions un-
der which a reaction with several reactants and products shifts to
the left. The results depend on the stoichiometric coefficients of
the given species and can be analyzed similarly as above. Such
examples can provide useful teaching assignments, and use of

Figure 2. Extent of reaction versus the amount of
nitrogen added for yo = 0.7.

Figure 3. Extent of reaction versus the amount of
nitrogen added for yo = 0.25.

nonideal gas models may provide further enrichment.
Equation (8) and the conclusions of (9) are valid only
for infinitesimal additions of nitrogen at constant T and
P. Equation (6) or (7), however, is valid for finite addi-
tions of nitrogen at fixed T and P. To determine how the
reaction shifts upon addition of a finite amount of nitro-
gen, one must use Eq. (6) or (7) to determine the value
(and sign) of !' for a given value of A'. Given that y3
= 1 y,O y2o, Eq. (7) can be rewritten as

(1- y y + 2 ')2(1+ A'- 2 ')2y(y)3

= 1- y- y2)2 (y + A'- '(y- 3!') (10)

This equation is fourth-order in 4' with roots that de-
pend on A', y1o, and y,. The physically relevant value
of i' must be such that each of the terms in parentheses
in Eq. (10) and the final mole fractions of Eq. (5) lie
between 0 and 1. For small to moderate values of A',
the physically relevant solution of Eq. (10) is therefore
small. Equation (10) was solved by the standard New-
ton-Raphson's method with an initial guess of = 0.
Convergence to the one physical root was readily
achieved. Values of were generated for a range of A'
at a given yo and y,. One may vary y2 independently
from y o, with the constraint that 0 < y20 < 1 y, Equa-
tion (10), like Eqs. (6) and (7), also does not require that
one specify the pressure and temperature explicitly. The
value of y2 for a given yo must be consistent with the
choice of T and P in Eq. (3), but the specific value of T
and P is not required for the determination of W'.
Figure 1 displays a plot of 4' versus A' for yo0 = 0.5
and different values of y20. In all cases, !' -4 0 as A'
-* 0, and the slope of approaches zero as A' -> 0,
consistent with relation (9c). Nonetheless, for any finite
addition of nitrogen, the reaction proceeds to the left,
i.e., 4' < 0. The value of is quite small, remaining so
as A' -* 1. The reaction proceeds to the left, but only
by a relatively small extent, even if nitrogen is added in
an amount equal to the total number of moles of all the
species initially present (e.g., = 0.006 for A' = 1.0
and y20 = 0.30). The extent of reaction, though always
negative, also depends on y2.
Figures 2 and 3 display plots of 4' versus A' for y, =
0.7 and y,0 = 0.25, respectively, at different values of
y2. When y = 0.7, the limiting slopes are all negative,
consistent with relation (9b), and a finite addition of ni-
trogen, at least up to A' = 1, causes the reaction to pro-
ceed to the left (t' < 0). When y,0 = 0.25, the limiting
slopes are all positive, again as required by relation (9a),
and a finite addition of nitrogen up to A' = 1 causes the
reaction to proceed to the right (! > 0). Yet, the curves
in Figure 3 display maxima, suggesting that for suffi-

Fall 2003

0.000

0.0 0.1 0.2 0.3 0.4 0.5
A'

0.6 0.7 0.8 0.9 1.0

ciently large A', the curves will eventually yield nega-
tive values of 4'.
To illustrate this effect further, we consider Figure 4
in which y, = 0.45. As required by relation (9a), all the
curves initially have a positive slope, so that the reac-
tion proceeds to the right for small values of A'. At
some critical value of A' (which depends slightly on
y20), 4' becomes negative. Therefore, at y, = 0.45, the
reaction proceeds to the right for small additions of ni-
trogen, but shifts to the left when a sufficient quantity
of nitrogen is added. The figures suggest that for all
values of y,, the reaction will eventually proceed to the
left if a large enough amount of nitrogen is added to the
reaction vessel. These calculations also suggest ways
for experimentally testing the predictions and demon-
strating the thermodynamic laws.

GENERALIZATION OF
LE CHATELIER'S PRINCIPLE

The Principle of Moderation

We close this paper by briefly discussing the general-
ized statement of Le Chatelier as stated and proved by
de Heer,141 which is more appropriately called a Prin-
ciple of Moderation (the proof given by de Heer is be-
yond the scope of an undergraduate course). Since gen-
erality often causes one to sacrifice simplicity, the more
general principle of moderation may be given as'14
The change of an intensive variable caused by
changing the corresponding (conjugate) extensive
variable is smaller if chemical equilibrium is
maintained than if no reaction could take place in the
system.
The change of an extensive variable caused by
changing the corresponding (conjugate) intensive
variable is larger if chemical equilibrium is
maintained than if no reaction could take place in the
system.

The above statement has been shown to be valid only
for infinitesimal changes from the initial equilibrium
state.14,51 It does not necessarily hold for finite changes.511
The principle of moderation applies, for example, to
the change of the chemical potential of nitrogen (inten-
sive variable) upon the addition of nitrogen (conjugate
extensive variable). With the ammonia synthesis reac-
tion prevented from occurring, the addition of nitrogen
at constant T and P yields an increase in the value of the
chemical potential of nitrogen. If nitrogen were instead
added while maintaining chemical equilibrium, i.e., the
reaction was allowed to proceed, the resultant increase
in the chemical potential of nitrogen would be smaller

than the increase obtained when the reaction was prohibited. In
other words, the change in the chemical potential of nitrogen is
moderated, or lessened in this example, by the reaction.
Since at constant T and P the chemical potential of a component
in an ideal-gas mixture increases with increasing mole fraction, we
instead analyze the change in the mole fraction of nitrogen upon
the addition of nitrogen to illustrate in more detail the principle of
moderation (this is one aspect of the ammonia synthesis reaction
that was not directly discussed by de Heer). We consider the addi-
tion of nitrogen with the ammonia synthesis reaction taking place
and with the reaction prevented from occurring. From Eq. (5), we
see that in the limit of A' -> 0

dyl- y +n(2y ) (11)

If no reaction is allowed to take place, then the final mole fraction
of y, is equal to

Sy+A' (12)
I+A'
Taking the derivative of y, with respect to A', we find in the limit
of A' -> 0 that

dy1 n
-dA')norxn

=l- yo > 0

Equations (11) and (13) imply that
dy ( dy (2y 1)
dA IdA'-)no rxn + 1

Since Eq. (8) indicates that il(2y1 1) < 0, then

dyl <(dyl )
dA' -dA'no rxn

0.0 0.1 0.2 0.3

0.4 0.5 0.6 0.7 0.8 0.9 1.0
A'

Figure 4. Extent of reaction versus the amount of
nitrogen added for y1, = 0.45.

Chemical Engineering Education

or the change in the mole fraction of nitrogen is always less
(or equal) when the reaction proceeds than when no reaction
takes place. The reaction is said to "moderate" the mole frac-
tion of nitrogen, i.e., the reaction decreases the final mole
fraction of nitrogen as compared to the case when no reac-
tion occurs. This result is counter-intui-
tive, since Eq. (15) is also valid when
the reaction shifts to the left, thereby pro-
ducing more nitrogen. In this instance,
the additional hydrogen that is pro-
duced by the reaction shifting to the _wof y I
left offsets the increase in the mole
fraction of nitrogen. .
Similar arguments, as discussed by de -
Heer, show that the partial pressure and .
chemical potential of nitrogen are also '
moderated by the reaction: the change
in these intensive quantities is always -
less when the reaction occurs than when J
no reaction takes place. Equation (15)
also supports these conclusions since, at
constant T and P, the partial pressure and i
chemical potential of a component in an
ideal gas mixture increase with increas- s
ing mole fraction. .
For finite additions of nitrogen, and
for most conditions, calculations show Igct z
that Eq. (15) is still satisfied. There are
ranges of finite A', however, in which prob
the reaction does not moderate the
change in mole fraction of nitrogen (a
value of yo0 = 0.45 provides an example
for A' between approximately 0.12 and
0.22). In this case, the final mole fraction of nitrogen after
reaction is in fact greater than the final mole fraction of nitro-
gen without reaction. The ratio of the final mole fraction of
nitrogen with reaction to the mole fraction without reaction
is, however, only slightly greater than unity. Thus, in this case,
the violation of the principle is minor for finite values of A'.

CONCLUSIONS

When a gas-phase system is at chemical reaction equilib-
rium at constant temperature and pressure, and some extra
reactant or product is added, the system, upon reestablishing
equilibrium does not always respond in a way qualitatively
consistent with the traditional Le Chatelier principle. If there
is a change in the number of moles, as in the ammonia syn-
thesis reaction, then adding one reactant (N,) may cause the
reaction to proceed in a direction that produces more of the
added ingredient (N2). These results are perfectly consistent
with the laws of thermodynamics. The direction of the reac-
tion depends on whether the added amount is infinitesimal or
finite. For infinitesimal additions, a new principle of mod-

eration, first suggested formally by de Heer,14 does apply.
Even this principle does not apply for finite additions of re-
actant (N,). These results indicate that the principle of Le
Chatelier should be taught in its more general form. In addi-
tion, instructors should emphasize that even the more gen-
eral formulation is valid for infinitesimal
changes only. (Nonetheless, the principle
does appear to be valid for finite changes
t- in temperature and pressure.) The present
analysis provides for a deeper understand-
- VPi-- S ing of chemical reaction equilibria and can
form the basis of several stimulating lec-
tures and problem-solving sessions.
-t .. As a final note, a general statement con-
cerning the direction of shift for changes
S...-- in temperature of arbitrary amounts at
constant pressure can be formulated. As-
- suming that the heat of reaction is always
_ positive or negative, then an increase in
temperature of any amount will cause the
m- equilibrium to be displaced in the direc-
tion of the heat of reaction. A similar state-
ment appears to be possible for pressure
_C changes at constant temperature and de-
pends on which direction the volume
changes upon reaction. The addition of
uzn1 reactants and/or products, however, re-
quires care, and in these cases it is not
S possible to formulate a general statement
that is universally valid for any addition
of products or reactants.

ACKNOWLEDGMENTS
The work described in this paper was partially supported
by an Academic Reinvestment Proposal, Purdue Research
Foundation.

REFERENCES
1. Levine, I.N., Physical Chemistry, 3rd ed., McGraw-Hill Book Co.,
New York, NY (1988)
2. Sander, S.I., Chemical and Engineering Thermodynamics, 3rd ed.,
John Wiley & Sons, Inc., New York, NY (1999)
3. Tester, J.W., and M. Modell, Thermodynamics and Its Applications,
3rd ed., Prentice Hall PTR, Upper Saddle River, NJ (1997)
4. de Heer, J., "The Principle of Le Chatelier and Braun," J. Chem. Ed.,
34(8), 375 (1957)
5. Liu, Z.-K., J. Agren, and M. Hillert, "Application of the Le Chatelier
Principle on Gas Reactions," Fl. Phase Equil., 121(1-2), 167 (1996)
6. Katz, L., "A Systematic Way to Avoid Chatelier's Principle in Chemi-
cal Reactions," J. Chem. Ed., 38(7), 375 (1961)
7. Plaza del Pino, I.M., and J.M. Sanchez-Ruiz, "A Simple, Experimen-
tal Illustration of the Le Chatelier Principle," J. Chem. Ed., 68(11),
944(1991)
8. Smith, J.M., H.C. Van Ness, and M.M. Abbott, Introduction to Chemi-
cal Engineering Thermodynamics, 6th ed., McGraw-Hill Book Co.,
New York, NY (2001) 0

Fall 2003

re

'U

S

OSi

9-8

doi

re M. laboratory

A FLUID-MIXING LABORATORY

FOR ChE

GABRIEL ASCANIO, ROBERT LEGROS, PHILIPPE A. TANGUY
Ecole Polytechnique Montreal, Quebec, Canada H3C 3A7

Mixing is a common operation in the process indus-
tries and is generally performed by a rotating im-
peller in a vessel. Products obtained from food,
petroleum, mining, pharmaceutical, pulp and paper, and
chemical industries would not be available without fluid mix-
ing equipment and technology. Mixing also plays a vital role
in industrial waste treatment and in environmental cleaning,
such as in sulfur dioxide absorption for treatment of acid
rain.1,21
A wide range of mixing situations can be found in practice,
which may involve high- or low-viscosity fluids, suspending
solids in liquids, dispersing gas or solids in liquids, etc. Mix-
ing operations at the industrial level are increasingly carried
out at low to moderate Reynolds numbers, leading to segre-
gated or dead regions and resulting in long mixing times.
The simplest way used to improve mixing efficiency con-
sists of increasing the rotational speed, which unfortunately
leads to higher energy consumption. Mixing times in small-
scale stirred tanks are commonly measured by non-intrusive
techniques such as colorimetry. This technique also allows
observation of the aforementioned segregated regions and
how they tend to disappear as the impeller speed increases.
The objective of the mixing laboratory is to give students
practical experience in the fluid mechanics of mixing by ana-
lyzing power consumption and mixing times associated with
radial and axial flow impellers with Newtonian and non-
Newtonian fluids.
The mixing laboratory is part of an undergraduate unit op-
erations course offered by the Department of Chemical En-
gineering at Ecole Polytechnique of Montreal for senior-year
students. Groups composed of a maximum of three students
perform the required laboratory work in a period of four hours.
The group prepares a preliminary report after finishing the
experiments, and the students either hand over a full report

or give an oral presentation the following week. Both the full
reports and the oral presentations consist of a description of
the experiment's objectives, its theoretical basis, the engi-
neering method used, the experimental setup, and the operat-
ing conditions. Then they present the experimental data, dis-
cuss the results, and make recommendations to improve the
laboratory.

EXPERIMENTAL SETUP
The mixing system used in all the experiments is a modi-
fied Turbotest (VMI Rayneri) laboratory mixer, shown in
Figure 1. It consists of a transparent polycarbonate vessel of
165-mm inner diameter and 230-mm height, with an open
top fixed to a rigid table for safe operation. Two classical
turbine) and an axial-flow impeller (marine propeller). The
impellers are mounted on a rigid shaft driven by a DC motor,
with the speed carefully regulated in a range from 10 to 2500
rpm by means of a DC controller. The motor is mounted on a
rigid structure that can be moved to adjust the vertical posi-

Gabriel Ascanio received his BS and MS from the National University of
Mexico in 1988 and 1995, respectively, and his PhD from Ecole
Polytechnique of Montreal in 2003. He is currently a postdoctoral fellow at
URPEI in the Department of Chemical Engineering. Some of his research
interests are in coating processes and mixing of rheology complex fluids.
Robert Legros is Professor of Chemical Engineering at Ecole
Polytechnique of Montreal. He received his BS from Ecole Polytechnique
in 1983 and his PhD from the University of Surrey in 1987. His academic
research involves solids thermal treatments in fluid beds, modeling of com-
bustion reactors, heat and mass transfer, and hydrodynamics of spouted
beds. Some of his current research interests are related to pharmaceutical
engineering, namely in powder technology and downstream processes.
Philippe A. Tanguy is Professor of Chemical Engineering at Ecole
Polytechnique of Montreal. He received his BSc in 1976 and his Doctorat
de spdcialitd in 1979, both from Universit6 de Paris, and his PhD from
Laval University in 1982. His research interests are in non-Newtonian fluid
mechanics, CFD and process engineering involving complex fluids, in par-
ticular coating processes, and in agitation and mixing operations.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

The purpose of this experiment consists of determining the mixing time with two impellers
providing different flow patterns. The mixing time, defined as the time needed to reach
a specified degree of homogeneity, can be determined by various techniques ...

tion of the impeller. As can be seen in Figure 1, a standard
mixing configuration is used as a starting point, with the im-
peller placed on the vessel centerline at 1/3 of the liquid height.
The agitation torque is measured by a non-contact type
torquemeter (range between 0.1 and 1.42 N.m) fitted between
the motor and the agitation shaft.
Newtonian fluids consist of aqueous solutions of corn syrup
having a viscosity of 1.5 Pa.s, while aqueous solutions of
carboxy methyl cellulose (CMC) are employed as non-New-
tonian fluids. The mixing times are measured with a colored
tracer consisting of Methylene Blue diluted in both solutions.
The two solutions, together with the tracer, are prepared prior
to the experiments and allowed to settle at least 24 hours in
order to eliminate air bubbles. The rheological properties of
the fluids are determined
by a Bohlin Visco 88V
viscometer using a con- MOTOR_-
centric cylinder configu- MOTOR
ration. Rheological mea-
surements and the ex- TORQUEMETER
periments are performed
at room temperature
(around 24oC). LIQUID LEVEL

The cost of the labora-
tory mixer and the solu-
tions used for the experi-
ments is about $5,000 and$20, respectively.

EXPERIMENTS

Figure 1. Experir

Power Consumption
This experiment consists of determining the power con-
sumption for both radial- and axial-flow impellers with New-
tonian fluids. For that purpose, the fluid under study must be
added to the H level of the tank (see Figure 1) and then the
mixer speed is set to zero rpm and the torquemeter to zero
N.m. The impeller speed is gradually changed from 15 to
700 rpm, and the torque reading for each speed is used to
calculate the power consumption by means of

P = 2 TirNT (1)

where r is the impeller radius in m, N is the rotational speed
in rps, and T is the torque in N.m.
The power consumption is correlated to the impeller speed
by means of the dimensionless power number (Np) and the
Reynolds number (Re), defined by

P
Np= pND
pN3D5

pND2
and Re = -pND
9

where P is the power in Watts, p is the fluid density in kg/m3,
D is the impeller diameter in m, and [L is the dynamic viscos-
ity in Pa.s.
The laminar and transition regimes must be identified after
plotting Np as a function of Re on a log-log scale;13'41 the
constant K for each impeller can be calculated by

Kp = Np Re (3)
Mixing Times
The purpose of this experiment consists of determining the
mixing time with two im-
pellers providing differ-
ent flow patterns. The
mixing time, defined as
the time needed to reach
a specified degree of ho-
RUSHTON TURBINE mogeneity, can be deter-
mined by various tech-
niques based on the mea-
surements of concentra-
HT = 1 PROPELLER tion, density, electrical
S= 1/3 conductivity, tempera-
C=D
ture, or by colorimetry,
optical methods, thermal
method, etc. The colorim-
etry technique is a quali-
zental setup, tative method to deter-
mine the mixing time by
adding a small amount of a color tracer to the fluid that is
being mixed. The overall fluid color will change, and mixing
time corresponds to the time when the tracer is judged to
have completely dispersed within the fluid. The detailed pro-
cedure for measuring the mixing time is

1. Use the configuration shown in Figure 1 with the Rushton
turbine.
2. Add fluid (aqueous corn syrup or aqueous CMC) up to the H
level.
3. Prepare the color tracer solution by dissolving 10 mL of
Methylene Blue in 100 mL of fluid to be studied.
4. With the mixer at rest, add 15 mL of the color tracer solution
to the tank containing the fluid.
5. Set impeller speed at 100 rpm and switch the mixer on.
6. Measure the mixing time at this speed.
7. Repeat Steps 3 to 5, using different speeds. The speed range

Fall 2003

TRANSPARENT,
VESSEL

for this experiment is from 100 rpm to 600 rpm, with
increments of 100 rpm.
8. Repeat the experiment for the marine propeller.
As proposed by Moo-Young, et al.,E 1 mixing time can be
correlated with the impeller speed by means of a dimension-
less mixing time defined as

Ntm = a(Re)' (4)
where tm is the mixing time in s, N is the impeller speed in
rps, Re is the Reynolds number, and oa and P3 are adjustable
parameters.
Shear Rate of non-Newtonian Fluids
The purpose of this experiment is to find out the effective
shear rate for non-Newtonian fluids in the vicinity of the im-
peller by the Metzner-Otto correlation.[61 They developed a
general relationship to correlate the impeller speed and the
shear rate of a non-Newtonian fluid in the laminar regime.
Based on the single knowledge of the power curve for
Newtonian fluids, this relationship can be used to interpret
and correlate power draw data for non-Newtonian fluids. This
method assumes that there exists an average mixer shear rate
developed in the vicinity of the impeller, which corresponds
to the power consumption. This shear rate is directly propor-
tional to the impeller speed through

7A = ksN (5)
where k is the mixer shear rate constant.
The average shear rate, Y'A, defines an apparent viscosity,
which is used in the definition of the Reynolds number for
power consumption prediction for non-Newtonian fluids. The
apparent viscosity is determined from viscometric measure-
ments at the appropriate shear rate and used directly for plot-
ting the power curve. The determination of the average shear
rate, YA involves the following steps (see Figure 2):

Np'=

1. For a given impeller speed, a power number (Np') is
calculated from the P vs. N for non-Newtonian fluids.
2. Using this power number, Np', a Reynolds number (Re')
is obtained from the power number-Reynolds number corre-
lation for Newtonian fluids.
3. Finally, the average shear rate can be determined from
the viscometric data and, using the impeller speed, the mixer
shear rate constant, k,, can be calculated from Eq. (5).
The procedure for this experiment consists of the following
manipulations:
1. Mount the Rushton turbine at the end of the shaft and
locate it in the center of the vessel, as in the first
experiment.
2. Add the aqueous CMC to the H level.
3. Gradually change the speed, record the torque for
each speed, and calculate the impeller power con-
sumption from Eq. (1).
4. Plot the power consumption (P) vs. impeller speed
(N).
5. By using the viscometer with the same fluid, record
the apparent viscosity for each shear rate and plot the
PIA vs. YA curve.
6. Following the steps mentioned above, determine the
average shear and calculate the mixer shear rate
constant ks from the Metzner-Otto correlation (Eq. 5).
7. Repeat the experiment using the propeller.

FULL REPORT AND ORAL PRESENTATION
As mentioned before, students are asked to prepare a pre-
liminary report after finishing the experimental work. A week
later they must deliver a full report or give an oral presenta-
tion. The full reports must contain

N' N ie log Re YA

2nN'P' D2 N'p ks
D (NY p A Re* N
(a) (b) (c)

Figure 2. Determination of the shear rate constant ks: a) non-Newtonian power consump-
tion, b) Newtonian power consumption, c) non-Newtonian viscometry.

Chemical Engineering Education

A

10An abstract, including the objectives, the methodology
used to achieve the objectives, and results and conclu-
sions in relation to the proposed objectives.
0 The objectives must be clearly stated.
1,A theoretical perspective different from the one presented
in the laboratory manual.
0-Main results for discussion and analysis, including
graphs and tables. An example of a set of experimental
data obtained by students is shown in Figures 3 and 4.
The power curves in terms of the dimensionless power
number (Np) as a function of the Reynolds number (Re)
are shown in Figure 3. After performing linear regres-
sion with the experimental data, a good correlation can
be observed between Np and Re. It must be noted that a
slope of -1 should be obtained between Np and Re cor-
responding to the laminar region. An error of 5.47% and
0.53% in the slope is obtained for the Rushton turbine

10 --- -- --- i' -
S32.705Re5" -*- Rushton turbine
= 0.9948 --0-- Propeller

a.

Np = 12.649ReW'"7
R2 = 0.9997

Figure 3. Experimental power curves for the Rushton
turbine and the propeller.

3000
S-0-- Rushton turbine ;
2500 N Nt =3x106Re'13 --0- Propeller
R'= 0.9939
2000

1500
E
1000

500 Ntm = 6xl 0a Re. '
R2= 0.997
0 -

4 6

10 12 14

and the propeller, respectively. Figure 4 shows the di-
mensionless mixing time as a function of the Reynolds
number for both impellers with a Newtonian fluid. From
the linear regression results, it can be observed that the
larger coefficients o and 3 correspond to the Rushton
turbine, which is in good agreement with the results re-
ported in the literature.121
Interpretation, analysis, and discussion. These elements
should be presented in great detail in a quantitative way,
including the experimental error encountered. In the case
of the experiments of power consumption and shear rate
of non-Newtonian fluids, the torque should be measured
at least three times in order to determine the experimen-
tal error.
I Recommendations. This feature is used as feedback chan-
nel, so the students should suggest another experiment
to perform or modifications to the experimental setup in
order to improve the experiments.
1'Appendix. All the raw data must be presented so the re-
viewer can verify if the data were well processed.
On the other hand, the oral presentation is evaluated in terms
of the form and the content. The introduction and objectives,
presentation structure, illustrations, conclusions, and ques-
tions are all considered in the form. The subject knowledge,
theoretical basis, and references and analysis capability are
considered as parts of the presentation.

CONCLUSION
Because mixing is a unit operation involved in many in-
dustrial applications, a good understanding of this operation
is central for a successful process. The proposed experiments
give the students a general introduction to the fluid mechan-
ics of mixing with Newtonian and non-Newtonian fluids,
using impellers that provide different types of flow. In fluid
mixing technology, as in other process design areas, dimen-
sionless groups are used to correlate scale-up parameters. For
that reason, experimental results must be presented in terms
of these dimensionless numbers to be useful to the process
designers. The proposed mixing experiments enable engi-
neering students to gain excellent insight into the use of
dimensionless groups.

REFERENCES
1. Coulson, J.M., J.F. Richardson, J.R. Backhurst, and J.H. Harker, Chemi-
cal Engineering, Vol. 1, Pergamon Press, p. 225 (1990)
2. Harnby, N., M.F. Edwards, and A.W. Nienow, Mixing in the Process
Industries, 2nd ed., Butterworth Heinemann (1992)
3. Rushton, J.H., "The Use of Pilot Plant Mixing data," Chem. Eng. Prog.,
47, No. 9, p. 485 (1951)
4. Rushton, J.H., E.W. Costich, and H.J. Everett, "Power Characteristics
of Mixing Impellers, Part 1." Chem. Eng. Prog., 46, No 8. p. 395 (1950)
5. Moo-Young, M., K. Tichar, and FA.L. Dullien, "The Blending Effi-
ciencies of Some Impellers in Batch Mixing,"AIChE J., 54,139 (1976)
6. Metzner, A.B., and R.E. Otto, "Agitation of Non-Newtonian Fluids,"
AIChE J., 3(1), 3 (1957) 17

Fall 2003

Figure 4. Dimensionless mixing time as a function of
the Reynolds number for Newtonian fluids.

BI, -classroom

DEVELOPMENT AND IMPLEMENTATION

OF AN EDUCATIONAL SIMULATOR:

GLUCOSIM

FETANET CEYLAN ERZEN,* GULNUR BIROL,** ALI (INAR
Illinois Institute of Technology Chicago, IL 60616

he quality of student learning can be enhanced sig-
nificantly by simulation of complex systems with user-
friendly software. Complex real-world problems and
solutions can be introduced to students by using simulation
systems to conduct virtual experiments. These virtual experi-
ments are especially useful when their real-world analogs are
expensive and/or dangerous.
Simulation involves the use of the model of a system to
observe the system's response to changes in properties and
inputs to the system. Simulations can introduce realistic prob-
lem situations and support a particularly active form of learn-
ing by letting students manipulate the conditions of the sys-
tem and observe the consequences of those variations. The
availability of a reliable and realistic mathematical model
is essential to conduct simulations and understand the be-
havior of the system.
We have developed a dynamic simulator for glucose-insu-
lin interactions in a healthy person and a Type- 1 diabetic pa-
tient. The aims of this public domain simulator are to provide
assistance to bioengineering students in learning glucose-in-
sulin interactions in the human body, to offer a tool for engi-
neering students in learning system dynamics, and to pro-
vide an illustrative tool to diabetic patients. The simulator
cannot be used for adjusting a patient's insulin dosage regu-
lation in real life, but may be helpful for patient education.
Both MATLAB-based-stand-alone and web-based graphi-
cal user interfaces (GUI) are software designs that yield in-
teractive systems. Despite many similarities between the two
designs, there are also many differences. Simulators with web-
based GUIs are more accessible over the internet, but stand-
alone software can also be distributed widely while giving

* Pharm Tech, Inc., 14048 Petronella Dr., Libertyville, IL 60048
** Northwestern Uiversity, Biomedical Engg., Evanston, IL 60208

the developer/designer an opportunity to keep track of the
users. Furthermore, since the stand-alone GUIs are in a de-
fined frame, the designer controls where the user goes when
browsing among the links, while in web-based GUIs, the user
has all the control and in many typical situations there is a
high possibility that he or she may branch out to an arbitrary
website while browsing.
Modeling glucose-insulin interactions requires an under-
standing of the physiological and metabolic processes that
determine observable behavior.111 Mathematical models de-
scribing carbohydrate metabolism are available in the litera-
ture.12-41 We have used and extended two mathematical mod-
els based on pharmacokinetic diagrams of glucose and insu-
lin in the human body. Mass balances for both glucose and
insulin resulted in a set of ordinary differential equations,
and the models are implemented in a computer program writ-
ten in MATLAB 5.3. The mathematical details of these mod-
els are available elsewhere. 1l51 ODE23 (low-order Runge-
Kutta routine) is used for solving differential equations. The
models are then integrated with a GUI that is responsible for
presenting information to the user in a clear and friendly way.

Fetanet Ceylan Erzen received a BS degree in chemical engineering
from the Middle East Technical University (1999) and an MS degree from
Illinois Institute of Technology (2000). Her thesis studies included model-
ing and simulation of glucose-insulin interaction in the human body and
graphical user interface development.
GOInur Birol received BSc, MSc, and PhD degrees in chemical engi-
neering from Bogazici University in 1990, 1992, and 1997, respectively.
Her current research interests include glucose biosensors, investigation
of retinal vascular occlusion, and the relationships between oxidative and
glycolytic metabolism in the retina on animal models.
All Cinar received a BS degree in chemical engineering from Robert Col-
lege, Turkey (1970), and MEng (1973) and PhD (1976) degrees from Texas
A&M University. His teaching and research interests are process model-
ing and control, statistical process monitoring and fault diagnosis, and
use of knowledge-based systems for real-time process supervision and
control.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

SIMULATOR
EL System Availability
GLUCOSIM was originally developed in MATLAB 5.3.1 on
a PC platform. It requires three MB of hard disk space. A
demonstration of the package is available on the web at /www.chee.iit.edu/~control/software>. The simulator can be
obtained by writing to Ali Cinar (e-mail at cinar@iit.edu).
Ea User Interface Design
A computer is limited not by its power to compute, but rather
by its power to communicate with its human users.16] The
main requirement for wide acceptance and use by the stu-

START

Tutorial & Information Files

Demo I <> Simulator

I .

User Inputs

Simulation Models
Normal Man
--* Diabetes Patient
OGTT

Output

dents is an easy-to-learn, easy-to-use efficient interface.7' A
simple and natural dialogue for modem computer systems
with GUIs can be achieved by a good graphic designt'8 and
consistent screen layouts. Several guidelines are followed for
this purpose while designing the GUI in this work:
Consistency of the user interface. Similar objects and colors
are used to perform similar functions throughout the
simulator to facilitate recognition. If users know that the
same command or the same action will always have the
same effect, they will feel more confident in using the
system.'91 Also, the design is limited to a small number of
consistently applied colors.
Ease of navigation. The user is able to navigate without
getting lost or worrying about causing harm.
Importance of help and documentation is kept in mind. If
students need to refer to documentation for help or for
background information, there is sufficient and comprehen-
sive, but brief, documentation throughout the simulator.
Navigation is also available between the documentation; for
file.
Dialog boxes have a quit and/or back button. This gives
users a feeling of being in control since the user rather than
the computer decides where to go, what to see, and when to
leave.
The structure of the simulator is illustrated in Figure 1 and
its capabilities are outlined in Table 1. There are three cat-
egories of windows in the simulator: information windows,
transition windows, and input/output windows. A detailed de-
scription of these windows is presented later in this paper.

El Model Equations
The pharmacokinetic models for glucose and insulin are
based on mass balance equations on various physiological
compartments such as heart, lungs, and arteries (H), nervous
system (NS) (for glucose), or subcutaneous tissue (SC) (for
insulin), liver (L), pancreas (PN), gastrointestinal tract (GT),
kidney (K), and periphery (PR) (skeletal muscle and adipose
tissue). For example, the circulating blood insulin concentra-
tion, I is described by

VB = QSC(ISC B) +QK(K -IB)+
QPR(IPR -IB)+QLIL -(QHA +QPN +QGT)IB (1)
where Q denotes the blood-flow rate (dl/min), V denotes the
volume (dl), t denotes time (min), and I denotes the insulin
concentration (mg/dl). Subscripts B and HA denote blood and
hepatic artery, respectively. The mass balance in subcutane-
ous tissue is

VsC =Qsc(IB Isc) + rIA (2)

where r denotes a metabolic source or sink rate, and the sub-
script IA denotes insulin absorption. The detailed model con-
sists of a system of ordinary differential equations represent-

V

Figure 1. Structure of the simulator.

TABLE 1
Program Features

Large Database Related internet sites
Diabetes dictionary
Carbohydrate values
Over 100 references
Operational Modes Demo
Simulator
Experimental Modes Oral glucose tolerance test
Healthy person
Type-1 diabetic patient
Inputs Carbohydrate content
Time of meal and injection
Insulin type and dose
Body weight
Duration of exercise and simulation
Save Options and Outputs Continuous graphical display
Saving in ASCII and graphic modes
Recall/display profiles from previous runs

Fall 2003

ing mass balance equations in all compartments. The overall
model is derived by assuming that the mass balances in
each tissue are in quasi-steady state (i.e., dl/dt = dG/dt =
0). The resulting algebraic equations for glucose and in-
sulin concentrations are combined into the glucose and
insulin balances in the blood, yielding an overall model
with two differential equations.
Two models of insulin release were taken from the literature,
modified, and used in the current simulator for healthy hu-
mans. The first one is based on islet insulin secretion model
developed by Nomura, et al., E10 for rat islets, and the second
one is based on the pancreatic insulin release model devel-
oped by Carson and Cramp.E""
EL Features
A MATLAB-based, user-friendly GUI was designed and
integrated with the MATLAB code written for the mathemati-
cal model. The interaction of the user with the software has
been kept as simple as possible. Menus, buttons, and sliders
are widely used as controlling elements. Values are displayed
graphically with a "save" option. "Help" windows through-
out the program are available and the user can quit the pro-
gram at any time. Furthermore, the simulation can be stopped
at any time by using the "stop" button on the simulation
progress bar. The main window (see Figure 2) is designed to
familiarize the user with the environment.
There are three buttons-"About," "Tutorial," and "Back-
ground Information." The "About" button gives a brief in-
troduction to the program; "Tutorial" provides information
about the model used, along with a short literature review;
and the "Background Information" button is linked to an-
other window where it is possible to search for the definition
of a word related to diabetes from the database created (Fig-
ure 3) to view the relevant web links (Figure 4) or to get
information about the references used on the development of
both the mathematical model and the simulator.

Figure 2. Main window.

By using the "NEXT" button placed in the bottom left-
hand side of the main window (see Figure 2), the user can
choose between "DEMO" and "SIMULATOR" modes. The
purpose of the DEMO, which consists of snapshots, is to give
the user a general idea of the simulator's capabilities and a
preview of how the simulator functions. By selecting the
SIMULATOR mode, the user goes from the "information"
mode to an "experiment" mode. Here, there are three options
for the virtual experiments. The first option performs the "Oral
Glucose Tolerance Test" (OGTT), the second and third op-

Figure 3. Dictionary

M,110 (hH 8 1 4 10H 3i- *Ofjf Ad~

7, Tb.-h.I.d-fl

flq ~ I ib..4 I ..bi

h.. -1-4 Al..dlc. M ib.. pK".,.~

sm61 "01k4- .6

P W. .ahm. I ,....hAul. I,. PIk., %ibb D~"

100%b %t~ -. .41.1 A"4 i,.tr~~~ .i-.

Chemical Engineering Education

tions simulate a "Healthy Person" and a "Diabetic Patient,"
respectively. The user has the flexibility to choose between
the two different models for the healthy mode (Model I and
Model II) and between the two different models for the Type-
1 diabetes mode (detailed model and overall model).
For OGTT, the only input is the weight of the person. There
is also an option where the user can load his or her own pre-
viously saved data. Inputs for the other two modes (Figures 5
and 6) are
1. Carbohydrate content of the meal. There is also a
nutritional database where the user can find the
carbohydrate content of a specific meal.
2. Time of meal and injection. The user can enter a
value between 0-24 hours for time of meal and
insulin injection.
3. Insulin type and dose. Two types of insulin are
available, i.e., regular and ultralente.
4. Body weight
5. Duration of exercise. The exercise option, which is

Figure 5. Main window for Type-1 diabetes mode.

Figure 6. Main window for healthy person mode.

Fall 2003

specifically designed for moderate exercise,1121 is
available for only Type-1 diabetes mellitus mode.
6. Duration of simulation. It is possible to simulate the
dynamics of the diabetic patient and a normal person
for a maximum of 24 hours with up to four injec-
tions in diabetes mode.
The outputs of the simulation are displayed by continu-
ously updating the figures displayed on the screen (Figure
7). Once the simulation is finished, data can be saved in ASCII
and/or graphic form to make the recall and display of the
profiles possible for further analysis.

IMPLEMENTATION
EN Overview of the Course
The course focuses on application of engineering principles
to biochemical and biomedical systems. Biochemical engi-
neering topics include biological systems, enzymes and mi-
crobial kinetics, and design and analysis of biological reac-
tors. Biomedical engineering topics include flow properties
of blood, transport in human cardiovascular systems, and
analysis and design of artificial organs. Half of the semester
is spent on biomedical engineering, while the other half is
used for biochemical engineering. Details of the course are
documented elsewhere.[131 The average number of students
registering for this class is around twelve every semester.
The primary learning goals of the course are to provide
students with basic principles in cellular biology of micro-
bial cells, bioreactor operations and transport phenomena in
living systems, and enzyme and microbial kinetics and phar-
macokinetics-in short, to provide them with a working
knowledge of bioengineering applications.
The course was designed to achieve these learning objec-
tives that were assessed using fairly traditional methods (i.e.,
homework assignments, examinations, and term projects)

Figure 7. Output window.

throughout the semester. The class has been
taught by the same instructor for three semes-
ters at IIT and has been updated from semes-
ter to semester to better meet the learning ob-
jectives and the needs of the students in an
effective learning environment. During this
time, it has become a popular course. The
overall rating of the instructor and the course
increased 18% and 31%, respectively, since
its inception. It was rated 15% and 12%
higher when compared to the average instruc-
tor and average course ratings of the depart-
ment (Chemical and Environmental Engi-
neering Department), respectively.

aE Implementation of the Simulator

Previously, the beta version of the simula-
tor had been tested in the course in the Fall
'99 semester.1131 Based on the feedback pro-
vided by the students, MATLAB codes were
updated and the gamma version was inte-
grated into course material in the Fall '00
semester.

This was one of the term projects in which
students were expected to use the simulator
for a period of two weeks, and it formed 7.5 %
of the class grade. The simulation package,
which was distributed to students on a CD,
was introduced immediately after the phar-
macokinetics topic had been covered in a se-
ries of lectures. Distributing the software on
CDs helped students work from home as well
as from different PCs as long as they had
MATLAB software installed.

The students were asked to run a series of
simulations at different conditions, and the
choice of models was left up to the students
so they could have the opportunity to inves-
tigate the parts) they wanted and were most
interested in. Their interests varied signifi-
cantly. Some tried all the combinations (de-
scribed in the Features section), while others
focused on investigating a single issue (e.g.,
the effect of body weight on glucose levels).

At the end of the two-week exposure to the
simulation package, a class discussion was
organized where students could share their
experiences with the simulator, talk about
their findings, and make conclusions in an
informal discussion setting. During the two-
week period, the instructor and a graduate
student were available outside of class to as-

TABLE 2
Survey Questions for the Project

1. How could the simulator and GUI be improved?
2. How computer literate do people need to be in order to use the simulator:?
3. How much do people need to know about human physiology in order to benefit from the simulator?
4. In your opinion, does the product have any educational (or other) value?
5. What did you learn from the project? What else would have been interesting to learn?

TABLE 3
Survey Questions and Responses for the Simulator

Average
iStd. Dev,

Question

Design of Screens
1. The design of the Home Page (main page) of the simulator is: poor(l)...good(5) 4.22
2. Page colors are chosen to help concentrate: poor(l)...well(5) 3.66 +
4. During the navigation from one page to the next, you get: lost(l)...well oriented(5) 4.11
5. During the navigation from simulator to links, you get: lost(l)...well oriented(5) 4.00
6. Learning how to navigate is: easy(l)...difficult(5) 1.44
7. Reading the text is: easy(l)...difficult(5) 1.88 +
8. Text facilitates hypertext and branching: poor(l)...well(5) 3.55 +
9. Simulation outputs are: poor(l)...good(5) 4.11 +
10. Using the output for further analysis is: easy(l)...difficult(5) 2.77 +
11. To read the characters on the computer screen: hard(l)...easy(5) 4.22
12. Screen layouts were helpful: never(l)...always(5) 4.11
13. Sequence of screens: confusing(l)...clear(5) 4.00
System Experience
1. Terrible(l)...Wonderful(5) 3.55
2. Frustrating(l)...Satisfying(5) 4.00
3. Dull(l)...Stimulating(5) 3.88
4. Difficult(l)...Easy(5) 4.11
6. Rigid(l)...Flexible(5) 4.22
Terminology and System Information
1. Use of terminology throughout system: confusing(l)...clear(5) 4.11
2. Terminology relates well to the work you are doing: never(l)...always(5) 4.00
3. Learning the simulator: difficult(1)...easy(5) 4.00 +
4. Tasks can be performed in a straightforward manner: never(l)...always(5) 3.88
System Capabilities
1. System speed: too slow(l)...fast enough(5) 3.11
2. The system is reliable: never(l)...always(5) 3.44
3. Correcting your mistakes is: difficult(l)...easy(5) 3.66
4. Ease of operation depends on your level of experience: never(l)...always(5) 3.00
Background and Technical Info
1. Have you looked at background info? Yes/No Yes 100%
2. Have you looked at demo? Yes/No Yes 100 %
3. Have you looked at technical info? Yes/No Yes 100%
4. Technical info provided as a guidance in INFO sections are confusing(l)...clear(5) 3.66 +
5. Information from INFO is easily understood: never(l)...always(5) 4.00 +
6. Information from INFO is easily applied: never(l)...always(5) 3.88
7. Information from BACKGROUND is: poor(l)...satisfactory(5) 4.44 +
Simulator
1. This simulator is a helpful learning tool: disagree(l)...strongly agree(5) 4.55

0.67
0.71
0.78
0.93
1.00
0.72
1.05
0.72
0.60
0.83
1.09
0.60
0.70

0.72
1.00
1.05
1.05
1.23
0.83

0.78
0.70
1.11
0.78

1.53
0.72
0.50
1.41

0.86
0.86
0.92
0.72

0.52

Chemical Engineering Education

ware, so extra meetings were arranged to overcome and mini-
mize any technical difficulties. The instructor also encour-
aged students to visit her outside of class and to discuss the
progress of their projects. Most students showed a high inter-
est in the course during this period because they were able to
integrate textbook topics with real-life situations.
In order to assess the educational benefits that the simula-
tor provided, a discussion session that took one lecture hour
was conducted by the instructor, students handed in individu-
ally prepared written reports at the end of two weeks, and a
survey was prepared and administered to assess the use-
fulness of the project as a means for achieving the learn-
ing goals (see Table 2).

Furthermore, to assess the simulator's design capabilities, a
questionnaire based on earlier works on software and
courseware design and evaluation'14] was developed and ad-
ministered at the end of the project. Table 3 lists the ques-
tions that were targeted to serve as a tool for refinement
of the simulator and summarizes students' responses to
the survey questions.

Students commented favorably on the project and the simu-
lator. Most of them thought they better appreciated the appli-
cation of theories that they learned in the biomedical section
of the course, that they learned the difference between a
healthy person and a diabetic person, that the project was
stimulating because it allowed them to do something other
than calculations or a report, and that it gave them an oppor-
tunity to experience a practical application of pharmacoki-
netics in a real-life problem. They felt that even though it
took them some time to start working with the simulator,
its clarity made the project interesting. Some of the stu-
dents provided feedback on typographical errors and im-
provement of the GUI.
Furthermore, students identified the simulator as a great
learning tool for open-ended real-life problems. They found
it interesting to input their own daily diet and see how their
glucose rates changed throughout the day. They also found
the exercise option interesting. Some of them were even
amazed at how MATLAB software could be turned into such a
user-friendly form and could be used in such a practical way.

CONCLUSIONS

based on glucose insulin interactions in the human body. A
simulation package was integrated into an Introduction to
Bioengineering course and was assessed for its efficacy
through assigning a term project that allowed students to ex-
plore glucose insulin interactions in the human body with the
aid of a simulator. Further assessment of the simulator has
been carried out via surveys for additional improvement and
refinement. These data are in the form of questionnaires com-

pleted at the end of the term project. The course is being re-
fined based on student and expert feedback, and examination
problems that address the learning objectives of the simula-
tor are being developed to better assess the simulator's effec-
tiveness as a learning tool. A web version of the software has
also been developed that will provide an opportunity to serve
and obtain feedback from other student communities.

ACKNOWLEDGMENTS
The authors are grateful to Drs. J. Abbasian, I. Birol, V.
Perez-Luna, and C. Undey of IIT and Peter J. Reilly of Iowa
State University for their valuable suggestions. Financial sup-
port provided by NSF (EEC-0080527) is gratefully ac-
knowledged. Special thanks to the Fall 1999 and 2000
students for their feedback.

REFERENCES
1. Erzen, F.C., G. Birol, and A. Cinar, "Simulation Studies on the Dy-
namics of Diabetes Mellitus," in proc. EEE Internat. BIBE Simp., p.
231 (2000)
2. Guyton, J.R., R.O. Foster, J.S. Soeldner, M.H. Tan, C.B. Kahn, L.
Konez, and R.E. Gleason, "A Model of Glucose-Insulin Homeostasis
in Man that Incorporates the Heterogeneous Fast Pool Theory of Pan-
creatic Insulin Release," Diabetes, 27, 1027 (1978)
3. Puckett, W.R., "Dynamic Modeling of Diabetes Mellitus," PhD the-
sis, Chemical Engineering Department, University of Wisconsin-Madi-
son, (1992)
4. Sorensen, J.T., "A Physiologic Model of Glucose Metabolism in Man
and Its Use to Design and Assess Improved Insulin Therapies for Dia-
betes," PhD thesis, Department of Chemical Engineering, Massachu-
setts Institute of Technology (1985)
5. Erzen, F.C., "Studies on Modeling Glucose Insulin Interaction in Hu-
man Body and Development of a Simulation Package," Master's the-
sis, Department of Chemical Engineering, Illinois Institute of Tech-
nology (2000)
6. Hartson, H.R., and D. Hix, "Human-Computer Interface Development:
Concepts and Systems for its Management," ACM Computing Sur-
veys, p. 5 (1989)
7. Neilsen, J., Useability Engineering, American Press Limited, London,
UK (1993)
8. Marcus, A., Graphic Design for Electronic Documents and User In-
9. Lewis, C., D. Hair, and V. Schoenberg, "Generalization, Consistency,
and Control," in Proc. ACM CHI'89, Seattle, WA, p. 1 (1989)
10. Nomura, M., M. Shichiri, R. Kawamori, Y. Yamasaki, N. Iwama, and
H. Abe, "A Mathematical Insulin-Secretion Model and Its Validation
in Isolated Rat Pancreatic Islets Perifusion," Comput. Biomed. Res.,
17,570(1984)
11. Carson, E.R., and D.G. Cramp, "A Systems Model of Blood Glucose
Control," Inter J. Bio-Med. Comput., 7, 21 (1976)
12. Berger, M., P. Berchtold, H.J. Cuppers, H. Drost, H.K. Kley, W.A.
Muller, W. Wiegelmann, H. Zimmermann-Telschow, F.A. Gries, H.L.
Kruskemper, and H. Zimmermann, "Metabolic and Hormonal Effects
of Muscular Exercise in Juvenile Type Diabetics," Diabetologia, 13,
355 (1977)
13. Birol, G., I Birol, and A. Cinar, "Student Performance Enhancement
by Cross-Course Project Assignments: A Case Study in Bioengineer-
ing and Process Modeling," Chem. Eng. Ed., 35(2), 128 (2001)
14. Gallagher, T., "A Proposed Software Evaluation Form or Toll and Its
Use in the Evaluation of First Verbs from Laureate," Software and
Courseware Design and Evaluation, (1999) found at www.hyde2000.fsnet.co.uk/documents/eval.htm> I

Fall 2003

M &^ laboratory

Simulation and Experiment in

AN INTRODUCTORY

PROCESS CONTROL LABORATORY

EXPERIENCE

KENNETH R. MUSKE
Villanova University Villanova, PA 19085-1681

here are several advantages to integrating classroom
and laboratory exposure. For many students, under-
standing concepts taught in the classroom improves
significantly when they have the opportunity to gain hands-
on experience in a laboratory. A laboratory exercise also pro-
vides an opportunity to apply the theory they have learned in
the classroom to an actual engineering problem. Finally, com-
paring experimental data and dynamic simulation results is
an effective way to reinforce process dynamics education
in a laboratory exercise. The wider incorporation of pro-
cess dynamics into the curriculum is considered to be a
key component in process control education of chemical
engineering students.t1M
There are a number of simulation-based chemical process
dynamics experiments presented in the engineering educa-
tion literature. They range from modules incorporated into a
commercial process control computer system,t2] case studies
illustrating various process control concepts programmed
using MATLAB/SIMULINK,'351 and workshops based on
real-time simulation of industrial unit operations.161 Although
there are benefits of simulation-based experiments, a major
disadvantage is the lack of an actual physical process that the
students can watch, hear, and touch while it is operating.
Understanding the dynamic behavior of a process is greatly
enhanced by observing the physical process operation. Visu-
alization provides a significant benefit to many students as
they attempt to apply the theoretical concepts taught in the
classroom.17,81 This aspect was one of the main motivations
for developing the experience documented in this work.
A review of the equipment-based chemical process dynam-
ics experiments presented in the engineering education lit-

erature reveals a wide range of complexity in the processes
considered. They range from relatively simple liquid-levelt91
and stirred-tankt10l systems, multiple tank systems,[1" quite
complex reaction[121 and distillationt"31 systems, and combi-
nations of simple, more complex, and simulated systems.1141
Because this experience is intended to be an introductory
exposure to process dynamics, simulation, and control, us-
ing an easily modeled, simple, physical process that incorpo-
rates the introductory concepts from the process control and
simulation course is appropriate. For this reason, a single-
tank liquid-level system was chosen.
Feedback control is performed using a proportional-only
controller. Proportional control provides two benefits for this
introductory experience. The first is that a proportional con-
troller is easily simulated. The additional complexity required
in the simulation of integral action in the controller provides
little, if any, benefit to the understanding of process dynam-
ics and dynamic simulation in an introductory experience.
The second benefit is that proportional control results in
steady-state offset of the tank level. This concept is often dif-
ficult for some students to initially grasp in the classroom.
The ability to observe this phenomenon on a real physical
system can be very helpful for these students.

Kenneth Muske is Associate Professor of Chemical Engineering at
Villanova University, where he has taught since 1997. He received his
BSChE and MS from Northwestern (1980) and his PhD from The Univer-
sity of Texas (1990), all in chemical engineering. Prior to teaching at
Villanova, he was a technical staff member at Los Alamos National Labo-
ratory and worked as a process control consultant for Setpoint, Inc. His
research and teaching interests are in the areas of process modeling,
control, and optimization.

Copyright ChE Division of ASEE 2003

Chemical Engineering Education

For many students, understanding concepts taught in the classroom improves significantly
when they have the opportunity to gain hands-on experience in a laboratory.
A laboratory exercise also provides an opportunity to apply the
theory they have learned in the classroom to an
actual engineering problem.

LABORATORY
EQUIPMENT Manual Inlet
Valve
The experiment is carried
out using a 50-gallon gravity-
drained tank equipped with F
liquid level and outlet flow in
sensors. Liquid level is con-
trolled by a valve on the inlet
water pipe. There is an addi- h
tional inlet water pipe with a
manual valve. The outlet flow
rate can be adjusted by a
manual valve on the outlet pipe (
of the tank. A steam heater is
connected to the tank but not
used in this experiment. The Figure 1. Expe
tank is 2.5 feet in height and
1.8 feet in diameter. The tank
system is shown in Figure 1.
Liquid level control is provided by a single-loop electronic
controller. There is also a distributed computer control sys-
tem connected to the tank. Because we believe there is value
in exposing the students to both the single-loop electronic
and computer control systems, we have the ability to switch
between the two systems on this tank. The single-loop con-
troller is used for this introductory experiment, while the com-
puter control system is used for temperature-control experi-
ments and a model predictive control experiment in the se-
nior laboratory course.1151

LABORATORY EXERCISE
The exercise comprises two three-hour laboratory sessions.
During the first session, the student groups become familiar
with the tank system and perform the experimental work. In
the second session, they develop their dynamic simulation
model, compare their simulated results with those obtained
experimentally, and document their findings in a short memo
report to the instructor.
The laboratory exercise begins with the tank operating at
steady state under proportional-only feedback control with a
water level setpoint of 50%. The instructor reviews the physi-
cal operation of the tank, goes over each component com-
prising the feedback control loop, and leads a short discus-
sion concerning the options to remove steady-state offset with
the student group. The students are then instructed to adjust

imen

the controller bias to remove
Control Valve tank level. They may either put
the controller in manual and
tion or adjust the bias directly
@P to eliminate the offset. The
S value of this exercise is gain-
A ing an appreciation for the re-
sponse time of a real physical
LT system. The students are
prompted to estimate both the
Manual Outlet time constant of the system,
Valve which is on the order of five
Fout minutes, and the open-loop re-
sponse time of the tank in or-
tal tank system. der to determine how long it
should take for the tank level
to reach steady state after a
change to the inlet water valve position is made. Although
process simulators provide valuable training experience for
the students, a major drawback is that those experiences are
in "simulation" time. The first part of this laboratory exer-
cise demonstrates that real process dynamics are not on this
same simulation time scale.
After the students have adjusted the bias to eliminate the
steady-state offset in the tank level, the system is returned to
closed-loop control and they are allowed to choose one dis-
turbance from a list in the laboratory instructions. This list
contains the following disturbances:
Simultaneously dump two small buckets of water into
the tank
Dump one large bucket of water into the tank
Change the inlet flow rate by opening the manual
disturbance flow valve
Change the outlet flow rate by opening or closing the
manual outlet valve
Change the level setpoint
Change one of the level controller tuning parameters
where the two small buckets are each two gallons, resulting
in an impulse disturbance that is approximately 20% of the
liquid volume; the large bucket is 25 gallons, resulting in an
impulse disturbance when full that is about the same as the
liquid volume; and the disturbance flow results in a step

Fall 2003

state inlet flow rate.
From the instructor's perspective, it is desirable to have
as much variation in the selected disturbances between
groups as possible to make the students' semester-end oral
reports on this experiment more interesting. In practice,
other than discouraging the one large bucket, prompting by
the instructor in order to provide this variation has seldom
been necessary.
Prior to implementing their chosen disturbance, the tasks
of time keeper, data logger, and disturbance initiator are
distributed by the group members among themselves. Their
selected disturbance is then implemented on the tank sys-
tem under closed-loop level control. The initial data point
is collected after the disturbance has been completed. In
the case of the buckets, this point is the time when all of the
water has been emptied into the tank. Because two students
(and sometimes the instructor) are required to empty the
bucket contents into the tank, the time-keeping and data-
logging tasks are performed by one student at the begin-
ning of the experiment. For the other disturbances, the ini-
tial data point is taken immediately after the valve position
or controller tuning parameter has been changed. Data is
collected at intervals of ten to twenty seconds until the tank
level reaches steady state. The experimental phase of this
exercise is typically completed well within the three-hour
laboratory period.

PROCESS SIMULATION
The second phase of this exercise involves the dynamic
simulation of the closed-loop tank system with the distur-
bance chosen by the group. This phase is carried out during
the laboratory period immediately following the experimen-
tal session. Process simulation begins with an unsteady-
state material balance over the tank. Assuming a constant
cross-sectional area of the tank, Ac, and the same constant
density for all water streams, a macroscopic mass balance
results in
dh
Ac = Fin Fout (
dt
where h is the height of water in the tank, Fin is the inlet
volumetric flow rate, and Fo.t is the outlet volumetric flow
rate.
The inlet volumetric flow rate of water is determined by
the position of the control valve. Although this control valve
is linear, the inlet flow rate is not a linear function of valve
position over the entire valve position range due to varia-
tion in the water supply pressure as the valve position
changes. The students are given a calibration curve, shown
in Figure 2, that is used to relate the inlet flow rate to the
control valve position. Over the linear operating range of
the valve, the following correlation can be used to deter-

mine the inlet flow rate

Fin =0.171 (Vp)-1.03

10

where Fn is the flow rate in units of gpm and V is the control
valve position in units of % open. If the disturbance flow was
selected, there is a second constant inlet flow rate that must be
The outlet volumetric flow rate is assumed to be propor-
tional to the square root of the pressure drop across the manual
outlet valve due to the static head of fluid in the tank

Fout=Kvh+1 (3)

where Fout is the flow rate in units of gpm, Kv is the proportion-
ality constant, h is the height of the water in the tank in units of
feet, and the bottom of the tank is 19 inches above the outlet
valve. The proportionality constant Kv is determined from the
measured outlet flow rate and water height when the tank level
The control valve position is determined by the level con-
troller on the tank. For the proportional-only controller, the
valve position is determined from the controller equation

Vp =B+Kc(Sp L) (4)

where V is the valve position in units of % open, B is the
controller bias in units of % open, Kc is the proportional gain
in units of % open/% level, S is the water level setpoint in
units of % level, and L is the level of the water in the tank in
units of % level. In practice, the controller gain is kept at a
value around 1 %/% to prevent the control valve position from
moving out of its linear operating range during the transient
response due to the disturbance.
Simulation of the process is carried out by numerical solu-
tion of Eqs. (1) through (4). Before they can be solved, how-
ever, the units must be made consistent throughout all of the

Figure 2. Inlet water control valve calibration curve.

Chemical Engineering Education

relationships. The controlled variable for the controller is con-
figured to be in units of % while the tank dimensions are given
to the students in units of feet and the flow rate calibrations are
given in units of gpm. This variation in the units given to the
students is intentional. Numerical solution is typically carried
out by the student groups using MathCad, which is used by the
department in the introductory material balance and the nu-
merical methods prerequisite courses, although they are free
to use any of the other mathematical software packages such
as MATLAB, EXCEL, and Maple that are available on the
engineering college server.

EXAMPLES AND DISCUSSION OF RESULTS
Example experimental and simulation results are shown in
Figures 3 and 4. Figure 3 presents the results for the large bucket
impulse disturbance. In this example, the large bucket was only
about half full. Figure 4 presents the results for a reduction in
the outlet flow rate from closing the manual outlet valve. In

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Time (minutes)

Figure 3. Experimental and simulated closed-loop tank
level for the large bucket impulse disturbance.

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Time (minutes)

Figure 4. Experimental and simulated closed-loop tank
level for a change in the outlet valve position.

both cases, the experimental and simulated responses
are very similar. These results are typical for most of
the student lab groups.
In addition to presenting their experimental and simula-
tion results, the student groups are asked to discuss the
sources of error in this experiment in their group memo
report. Examination of the experimental and simulated dy-
namic responses reveals that the simulation leads the ex-
perimental response. Because there are dynamics associ-
ated with the level sensor and control valve that are not
included in the simulation model, this result would not be
unexpected. The effects of valve friction, sensor noise, and
the precision of the liquid level value displayed by the con-
troller can also contribute to error as well as the assump-
tion of a perfect square root relationship and a constant Kv
value for the outlet flow rate that may not be valid over the
liquid level ranges encountered in the experiments. Experi-
mental error in the timing of the collected level data samples
is also present. Almost every student group mentions the
valve, sensor noise, and sampling error as sources of error
in their report. Some groups also mention the outlet flow
relationship used in the simulation model. Few groups dis-
cuss the dynamic effect of the valve and sensor.

STUDENT RESPONSE
As part of the student evaluation of the process simula-
tion and control course, a number of supplemental ques-
tions concerning the value of the text and controller simu-
lation software used in the course, the laboratory experi-
ence documented here, and the preparation received in the
required prerequisite courses are included. The evaluation
scores ranged from 5=Very Effective to l=Very Ineffec-
tive. The average scores from the last four years are: pre-
sentation and explanation of concepts in the textbook,
3.04; use of CStation for class examples, 3.25; use of
CStation for homework problems, 2.96; process control
experiment in Lab II, 4.02.
CStation1161 is the process control simulation software
package used in the course, Essentials of Process ControltI7'
was the course text at the time of these evaluations, and the
process control experiment in Lab II is the experience docu-
mented in this work.
The average score given by the students for this labora-
tory experience is considerably higher than for the text and
process control simulation package and is essentially the
same as the average score of 4.10 for the value of the pro-
cess control and simulation course over the same period. It
should be noted that a number of students have provided
somewhat negative comments concerning the length of the
loop tuning homework assignments requiring the use of
CStation. These feelings may have had some influence on
the CStation scores. It should also be noted that only one
Continued on page 315.

Fall 2003

learning in industry

This column provides examples of cases in which students have gained knowledge, insight, and experience in the
practice of chemical engineering while in an industrial setting. Summer internships and co-op assignments typify such
experiences; however, reports of more unusual cases are also welcome. Description of the analytical tools used and the
skills developed during the project should be emphasized. These examples should stimulate innovative approaches to
bring real world tools and experiences back to campus for integration into the curriculum. Please submit manuscripts to
Professor W. J. Koros, Chemical Engineering Department, Georgia Institute of Technology, Atlanta, GA 30332-0100.

RETURNING AS A PROFESSOR

GARY BLAU, PHILLIP WANKAT
Purdue University West Lafayette, IN 47907-1283

Chemical engineering departments should stay in con-
tact with industry so their students can be taught
material that is useful after graduation and so research
will be relevant to the needs of industry. Unfortunately, very
few of the professors being hired from graduate schools or
after post-doctoral experiences have significant industrial ex-
this contact-by bringing back experienced engineers from
industry as post-early retirement Industrial Professors or En-
gineers in Residence. These individuals should be integrated
into all aspects of teaching and research within the depart-
authors (GB) who joined the School of Chemical Engineer-
ing at Purdue University during the spring semester of 1998
and who has served in the Industrial Professor role since that
time. The results are generalized for other "wannabe profes-
sors" from industry who are contemplating a career shift, as
well as other chemical engineering departments considering
initiating such an infusion of industrial talent.

THE INDUSTRIAL GUY
Dr. Gary Blau had a successful industrial career with the
Dow Chemical Company, primarily on the technical ladder.
Waterloo with a BASc in chemical engineering and went on
to get his PhD at Stanford University in 1968. He then went
to work with Dow Chemical. In 1991, he accepted an offer to
work with DowElanco (now DowAgrociences), a joint ven-
ture between the agrochemical business interests of Dow
Chemical and Eli Lilly.
At DowElanco, his final assignment was leading a group

of six engineers in the development and application of math-
ematical modeling tools to optimize work processes within
the company. He remained professionally active by writing
over fifty journal articles, coauthoring a book on mathemati-
cal modeling, editing another on Environmental Exposure to
Chemicals, organizing meetings, and serving in various lead-
ership roles in the Computing and Systems Technology
(CAST) division of AIChE. In 1998 he won the Computing
Practice Award from AIChE.
Why, then, did a highly successful, mid-career engineer
decide to take early retirement for a lower-paying, temporary
position? The answer embraces timing, location, opportunity
to develop a business, fulfillment of a dream, and idealism.
agement support made fighting for proper recognition for his
group increasingly stressful. In other words, the job was
not much fun any more. After thirty years of experience,
he was eligible for early retirement-so he began to look
for new challenges.
Gary, like many PhD engineers in industry, was a "closet
dream that all Stanford graduate students harbor. A model for
this ambition was Dr. Park M. Reilly, who had worked in

Gary Blau received his BASc from the University of Waterloo and his MS
and PhD from Stanford University, all in chemical engineering. Following a
successful career with Dow and DowAgrociences, he joined the faculty at
Purdue University as a Visiting Industrial Professor. His research is in risk
analysis and decision-making.
Phillip Wankat received his BSChE from Purdue, his PhD from Princeton,
and a MSED from Purdue. He is the Clifton L. Lovell Distinguished Profes-
sor of Chemical Engineering and the Head of Interdisciplinary Engineering
at Purdue University. His research is in separation processes.
Copyright ChE Division of ASEE 2003

Chemical Engineering Education

His primary motivation, however, was his desire to be the faculty "industrial guy" and to
share his real-world experiences with future engineers. He felt he could prepare
the chemical engineering students for what industry is really like.

industry for 25 years before pursuing a successful academic
career at Waterloo. Gary also had a desire to do independent
consulting in the modeling area, but his networks and paper
trail were too thin to support this activity.
His primary motivation, however, was his desire to be the
faculty "industrial guy" and to share his real-world experi-
ences with future engineers. He felt he could prepare the
chemical engineering students for what industry is really like.
He planned to develop "ill-defined, open-ended" problems
and to teach the students how to use their engineering skills
to solve them. He would train them in the proper use of sta-
tistical modeling, quality control, and risk management tech-
niques so they could have an immediate impact in industry.
He would show by examples and "war stories" that "soft
skills" are really important in industry. Since Gary had de-
veloped and taught process optimization short courses to lit-
erally hundreds of Dow engineers and chemists around the
globe, he felt his teaching skills were sufficiently honed to
motivate students.

BECOMING AN INDUSTRIAL PROFESSOR
While at Dow Agrociences, Gary became involved in sup-
ply-chain optimization issues, resulting in joint research col-
laboration with Professor Joe Pekny at Purdue. Gary helped
support some of Joe's research, worked with him on organiz-
ing the Foundations in Computer-Aided Process Operations
conference, and presented some lectures. He also knew Pro-
fessors Rex Reklaitis and Nick Delgass (Head and Associate
Head of Chemical Engineering, respectively) from their days
as graduate students at Stanford. Since Purdue was a short
50-minute commute on the interstate, Gary decided to accept
Rex's offer to be a Visiting Industrial Professor.
The courses Gary would teach and his time commitment to
Purdue were finalized during initial discussion with Rex. Gary
felt that 2/3 time during the academic year, with summers
off, would provide time for him to pursue both consulting
and leisure activities. He identified a required core course he
was well-qualified to teach and a new elective course he would
like to develop. He would also become involved in the sys-
tems research program and help jointly direct the research
program of some of Joe Pekny's graduate students.
Once a mutually agreeable salary was determined, Gary
became a Purdue professor. Since tenure was not an impor-
tant consideration, the position was not on the tenure track-
making it easier for the university to develop the position.
The process by which the new industrial professor and the
institution found each other is probably transferable, so a list

of the steps that took place is appropriate. First, the potential
professor should generate a record of accomplishment in in-
dustry that is respected by the academic community. If re-
search is to be part of the academic position, this industrial
record must include an adequate publication record. There
should be personal contact (networking) with some of the
professors in the department. The applicant should become
involved with the research program-sponsoring research is
particularly helpful. He/she needs to give some lectures to
search seminar.
After determining core undergraduate courses and one or
more electives that he/she is qualified for and wants to teach,
the applicant can make a proposal to the department head
concerning time commitment, course assignments, research
involvement, salary, etc. Since the question of tenure can be
a major stumbling block, formal ties are easier to forge if a
yearly contract is acceptable.
Of course, "making it happen" is not the sole responsibil-
ity of the industrial practitioner. The academic institution can
also be proactive by identifying individuals who might be
good candidates for the industrial professor program. A de-
partmental representative can talk with the prospect about
the program and determine if there is any interest.

EXPECTATIONS VERSUS REALITY

Like many other senior engineers, Gary frequently taught
short courses, and since there had never been complaints, he
believed he was prepared for teaching in a university. Al-
that the grading scheme would be unchanged from what he
had observed as a student or that he would be given clear
instructions on how to grade. He expected the students would
be courteous and neatly groomed. After all, he reasoned, they
were in school because they wanted to learn and thus should
be highly motivated to learn from someone who could show
them the value of their education.
Gary assumed that the students would have the same strong
technical background in mathematics and science as he and
his classmates had thirty-five years ago. He expected to share
his knowledge and thus prepare the students for careers in
industry. He looked forward to building personal relation-
ships with some of the students, and he viewed teaching as
the most important role he would fill, with research being a
secondary consideration. Since he was experienced, teach-
ing just one class (even if it was a large class) three times a
week would be a "piece of cake," allowing him plenty of

Fall 2003

time for other pursuits. Finally, it never occurred to him that
the students might challenge him.
Those were the expectations. The reality had a different
face. A book by Peter Sacks[" gives an accurate portrayal of
the trials of returning from the working world to become a
that engineering students would be different. That did not
turn out to be true. Unfortunately, many students believe that
if they do poorly, it's the professor's fault, not theirs. As a
new professor, Gary unwittingly played into this rationaliza-
tion for poor performance by giving tests that were difficult
and too long. With test averages in the 30s and 40s, the stu-
dents blamed Gary for their lack of preparation.
Gary also learned that many students seemed to be more
interested in the final course grade than they were in learning
the material. Since grading procedures were never well de-
fined for him, he tried to enforce what he thought were rea-
sonable grading standards, but some students argued con-
stantly with him in an effort to raise their grades.
Teaching evaluations were a new concept for Gary since
they had not been in use when he was a student, and he found
that some students used them to "dump" on a professor. He
worried that firm grading would be penalized when students
filled out the mandatory teaching evaluations. Also, being
connected on-line to the class allowed students to provide
immediate, often unflattering, feedback on Gary's classroom
performance. Because of his position in industry, Gary had
always been insulated from direct criticism from subordinates,
and he found the harsh criticism from 19- and 20-year-olds
hard to accept.
Gary found that today's students are different from those
of thirty-five years ago in other ways. For one thing, they
wanted to be entertained. Fortunately, he found that his ex-
perience was useful in this regard since the students enjoyed
listening to his industrial stories. He also found that the stu-
dents' work ethic was low and that they were less comfort-
able with ambiguity. When he introduced his industrially in-
spired "open-ended, ill-defined" problems, many students
were frustrated with them, wanting instead problems that were
crystal clear and did not require assumptions.
Talking during class was also rampant and required special
control techniques that had been unnecessary in his small classes
in industry. To his surprise, some students were actually rude
and disrespectful. Some staff members also let Gary know that
as a visiting professor, he was at the bottom of the heap.
Gary found that teaching was much more difficult in aca-
deme than in industry and that it was difficult to learn
everyone's name, let alone build a personal relationship with
them. Students in industry were more polite, more motivated,
and better prepared-they wanted to be in the educational
session, and any errors in presentation were quietly corrected.
But at the university the students were vocal about errors and

were unwilling to think their way through a derivation and
develop all the details by themselves.
While students in industry never complained about too
much material (apparently they sorted out for themselves what
was useful and what wasn't), university students were over-
whelmed by the amount of material, and trying to introduce
new methods such as new software only made matters worse.
The resistance to change was much greater at the university
than it was in industry.
Testing was a challenge that had never arisen in industry.
Some students would become angry if they were unable to
finish a test, so creating one that was not too long became an
enormous challenge. Gary found that students often seemed
incapable of doing very simple problems, particularly if there
were multiple steps. Grading the exams took much more time
than he had anticipated, and Gary soon came to see the beauty
of short-answer problems. Student cheating led to Gary's
general distrust of students, and he learned to place students
in alternate seats and to roam the classroom during exams.
Gary also found that teaching was more time consuming
than he expected. For the initial course offering, each 50-
minute lecture took over four hours to prepare, and the sec-
ond offering took almost as long because of the many revi-
self-starters in industry for ten students who were just
"doing a job" for the money.
Since it was essential to be present for every class, teach-
ing meant a much less flexible schedule than Gary had had in
industry. It came as a surprise that in some ways, time pres-
Finally, Gary found that at a research university, teaching
was not the top priority. It had to be adequate, but research
(specifically, research funding) was most important. Most pro-
fessors wanted to talk about research, not teaching.

LEARNING TO SURVIVE
The most important step to surviving is adaptation: reflect-
ing on what happens, sorting through the criticism, talking to
students and professors alike, revising, and doing it again.
Talking to students revealed that their pressures are much
different than they used to be-they are busier and many of
them work part-time. Fewer have strong backgrounds in
mathematics, chemistry, physics, or other areas of engineer-
ing, and fewer still are dedicated to becoming chemical engi-
neers. In talking to the students and professors, Gary also
found that he had not been singled out as a new professor for
criticism-it was more of an equal-opportunity endeavor, and
more important, there were methods to prevent it. There were
also approaches that would improve the course while at the
same time reduce the time required to conduct it.

Chemical Engineering Education

Initially, Gary's self-confidence was so badly shaken that
he asked the associate head to team him with one of the more
successful teachers in the department. Although this presented
a scheduling nightmare, Gary was allowed to share his teach-
ing responsibilities with Joe Pekny, a younger but more ex-
perienced professor. Gary was a good student and absorbed
the lessons rapidly.
Discussions with students and experienced professors con-
vinced Gary that a course outline with firm
dates for exams and major assignments was .-
absolutely necessary since students could not
adjust their complicated schedules to accom- -
modate last-minute changes. He was also
advised to reduce the amount of material cov-
ered, which was easy initially but proved to
be more difficult as additional cuts were
needed. The process is ongoing.
Gary tried several presentation styles. Stu-
dents complained that his handwriting was
unreadable, so he tried class notes-but in
addition to the construction being time con-
suming, they were boring and students either
did not attend or went to sleep. He then tried
notes with spaces for one-word answers, but
the students viewed those as childish. He -
found that notes with large spaces for ex- --
amples or derivations worked best, and they
plete notes for lectures and created student
notes by simply removing parts from them.
This procedure allowed for more time for questions and
stories, kept the students interested, and reduced the num-
ber of board errors.
As he became more experienced, Gary was able to write
exams and projects that would challenge, but not overwhelm,
the students. He scheduled exams at times that gave the stu-
dents extra time, and he learned to recognize those problems
that would be difficult to grade and used them only when it
was educationally necessary. With more time available to him,
Gary was able to get to know the TAs and the students better
and found they were more like the students he remembered
than he initially thought.
By taking a section of the computer laboratory in the sta-
tistics class, Gary learned what was giving the students trouble
and was able to improve descriptions for the laboratory exer-
cises. He also got to know the students in this small section
very well and was able to recruit competent undergraduate
TAs for the next offering of the course.
Today, Gary is teaching a large sophomore-junior class by
changed, his teaching evaluations have risen significantly and

U

Fall 2003

he has been able to put to rest his worry that firm grading
would by punished by low evaluations. Both he and the stu-
dents now agree that it is fun to go to class.
Gary has learned to be an "edutainer," and the students are
fascinated by the "war stories" he has built into his projects
and exams. Since he better understands the pressures facing
students, he is now better able to counsel them and give ad-
vice. Many of them realize that a letter of recommendation
from someone with thirty years of industrial
experience is an advantage and they make the
7 effort to establish the one--one relationship
Gary was looking for in the beginning. Al-
though the large undergraduate course was
Gary's major challenge, he built such enthu-
siasm for his Risk Management elective course
that enrollment had to be capped.

THE RESEARCH COMPONENT
Gary's transition to the research environ-
ment was smoother than it was to the teaching
component of his new career, although expec-
tations and reality were, again, frequently in
conflict. Professors were always willing to talk
about their research interests provided Gary
could track them down, but they were not ac-
tively looking for an "industrial perspective."
Gary soon learned that researchers were driven
Sby the primeval need for survival-they
needed funding for everything: graduate stu-
dents, laboratory facilities, computers, release time, tele-
phones, and even copying services. They needed to write pro-
posals, give presentations, serve on committees, teach courses,
supervise graduate students, etc. If they were successful, up-
per-level management in the university often rewarded them
Gary had no desire to compete in this environment. He sim-
ply wanted to work with some of the graduate students to
pursue some ideas he felt compelled to develop. Professor
Joe Pekny helped by involving Gary with his research group.
In addition, he managed to bring in sufficient annual funding
for a graduate student or two. This was ideal. He could con-
duct research, which resulted in publications and presenta-
tions while providing the necessary new material for his up-
per-level course in risk management. He also accepted a po-
sition as director for an industrial consortium that would chan-
nel funding into the department's systems research efforts.
Gary developed an increasing appreciation for the stimu-
lating nature of the academic environment. Working with pro-
fessors from other universities and engineers from industry
was stimulating, and he was able to develop lasting relation-
ships with some of the students (easier with graduate stu-

Gary had success in bringing an industrial perspective to
the department and found it extremely rewarding to see former
students who said they used his "stuff' in their jobs and found
it valuable. Also, having the summer off for consulting and/
or "down time" at the lake has been a bonus no industry is
willing or able to match.
The challenges of academe are such that Gary, who was
slightly bored in industry, now looks forward to every day.
He has found that doing research and working with graduate
students is exciting and has led to even more ideas for re-
search. Since there is no textbook for the graduate-level course
on risk analysis, Gary would like to write one...and there is
always the challenge of getting everything right in teaching

IMPROVING THE PROCESS
There are a number of advantages for both the department
and the students in having industrial professors on staff. For
one thing, it is useful to maintain contact with industry to
ensure that curriculum content is relevant. Other professional
schools, such as medical and law schools, regularly have prac-
titioners teach, and engineering colleges could benefit by
following that lead and developing positions for professors
with industrial experience. Industrial professors can help with
the teaching load, particularly in design classes (although this
was not the case with Gary). They tend to be more commit-
ted to teaching'21 and are more likely to assign open-ended
problems and projects that include teamwork and writing.
Their presence can also help the department prepare students
for industrial careers and thus satisfy ABET criterion 4. Pro-
fessors who had active industrial research programs and con-
tacts can help the department bring in more research con-
tracts and ensure that the research is relevant.
The process can be improved, however. First, a critical mass
of professors with extensive industrial experience is needed.
One on staff is not enough-it is more appropriate if 20-30%
of the faculty has extensive industrial experience.
Although tenure is probably not an issue for most return-
ees, planning for the next year is. A rolling contract that would
allow the visiting professor to know at least a semester in
advance whether or not he/she would still have a job would
be helpful. (Although Gary's position was originally viewed
as a visiting position, the "visit" is now in its fifth year.) A
title that implies a longer-term commitment (but without ten-
ure) would be appropriate. In addition, a formal program
would ease the red tape involved when the next engineer-in-
residence is hired.
The department should ease the teaching transition of in-
dustrial professors and realize that they need to be taught how
to teach-that they want to be taught how to teach. If there
are no local workshops on teaching, the returnee should be
encouraged to go to a national workshop such as the ASEE
NETI (National Effective Teaching Workshop) at the annual

meeting of ASEE. The department should provide a teaching
mentor to discuss teaching with the returnee on a regular ba-
sis where both general pedagogical principles and the
university's specific rules can be explored. This mentor should
invite the returnee to visit his/her classes and volunteer to
visit the new professor's classes. The mentor can be particu-
a guide to teaching at that particular university. The returnee
should be made aware of pedagogical journals such as Chemi-
cal Engineering Education, ASEE PRISM, the Journal of En-
gineering Education and appropriate books such as Teaching
Engineering (available free at https://Engineering.Purdue. edu/
ChE/Newsand_Events/publications/teaching _engineering).
These suggestions are also true for new assistant profes-
sors, most of whom want or are at least willing to be taught
how to teach. Such teaching resources should also be made
available to the experienced professors in the department who
may want to "tune up" their teaching or learn some new tricks.
If the industrial professor is to be involved in research, the
department should ease that transition. The returnee will usu-
ally be experienced in research, but the differences between
academic and industrial approaches to research are likely to
be surprising. Providing a research mentor who is in the same
research area, but who is not the same person as the teaching
mentor, is advisable. The mentor should carefully explain the
need, and the mechanisms, for funding.
The returnee should collaborate with experienced profes-
sors on research and on proposals and should be encouraged
to write proposals on his/her own-but the research mentor
should review the proposal before it is sent out. The mentor
ates in research. The returnee should be told of the resources
available at the university and of the formal and informal
procedures for sharing those resources.
The department should prepare its faculty and staff for the
arrival of the new professor, and the faculty should agree be-
forehand that hiring an industrial professor is a good idea. If
the professors treat the individual with respect, the staff will
also. The returnee's office should be ready from the start and
should be equivalent to the offices of other professors-
"ready" means the office is clean, has furniture, the com-
puter is hooked up to the network, the telephone is working,
the nametag is on the door, secretarial assignments have been
made, etc. Every new professor, whether industrial or not,
should be introduced to everyone else in the department and
should be invited to faculty meetings and other gatherings.
All new faculty, not just those from industry, can benefit
from formal courses or workshops on pedagogy and from
informal discussions with experienced teachers. They need
mentoring in both research and teaching. Also, some indus-
trial perspectives could be useful for universities-resource
planning, for one, is a major push in industry but does not

Chemical Engineering Education

valuable in industry and could be useful in academe (e.g.,
which centers should the university compete for?). Asking
questions is valuable-how long do professors need for dif-
ferent tasks, what can be done to improve the process, if stu-
dents aren't the customers, who is, etc. Industrial faculty
members can help ask the questions and help search for an-
swers.

SUMMARY
Many chemical engineering departments have been criti-
cized for a lack of industrial experience in their faculty. One

Process Control Laboratory Experience
Continued from page 309.

experience over the four-year period. Because there are no
formal course evaluations for laboratory courses, student re-
sponse data from the second-semester junior laboratory course
concerning the laboratory course and this experiment is not
available. Qualitative assessment of this experience based on
experiment indicate that this experience has been generally

CONCLUSIONS
An introductory laboratory experience in process dynam-
ics and control that is conducted concurrently with the pro-
cess simulation and control course at Villanova University
has been presented here. The experience is intended to rein-
force the introductory concepts of dynamic simulation and
feedback control presented in the classroom by using a simple
liquid-level process. Based on quantitative and qualitative
student responses in the laboratory and process simula-
tion and control courses, the students found the experi-
ence a valuable addition to their process simulation and
control education.

ACKNOWLEDGMENTS
A curriculum revision grant to the Villanova University
Chemical Engineering Department from Air Products and
Chemical Co. that supported development of this laboratory
experience, and the contributions of Professor Robert
Sweeney in the design and construction of the experimental
system are gratefully acknowledged. I would also like to thank
the Villanova University chemical engineering students over
the past four years for their active participation in the con-
tinuing development and improvement of this experience, and
Ami Badami and Jenny Papatolis of the class of 2003 for
supplying their respective group's experimental and simula-
tion results that are presented in this paper.

approach to partially solving this problem is to hire early re-
tirees from industry. As shown by the experiences related in
this paper, these returning professors will probably experi-
ence some degree of cultural shock. Their transition to be-
coming productive contributors can be eased by providing
both formal training in teaching and informal mentoring.

REFERENCES
1. Sacks, P., Generation X Goes to College, Open Court, Chicago, IL
(1996)
2. Fairweather, J., and K. Paulson, "Industrial Experience: Its Role in
Faculty Commitment to Teaching," J. Eng. Ed., 85, 209 (1996) O

REFERENCES
1. Luyben, W., "The Integration of Research and Undergraduate Process
Control Education," AIChE Annual Meeting, paper 204d (1999)
2. Rivera, D., K. Jun, V. Sater, and M. Shetty, "Teaching Process Dy-
namics and Control Using an Industrial-Scale Real-Time Computing
Environment," Comput. Appl. Eng. Ed., 4(3), 191 (1996)
3. Bequette, B.W., "Computer Applications in Process Dynamics and
Control Courses," Comput. Appl. Eng. Ed., 6(3), 193 (1998)
4. Bequette, B.W., K. Schott, V. Prasad, V. Natarajan, and R. Rao, "Case
Study Projects in an Undergraduate Process Control Course, Chem.
Eg. Ed., 32(3), 214 (1998)
5. Doyle, F., E. Gatzke, and R. Parker, "Practical Case Studies for Un-
dergraduate Process Dynamics and Control Using Process Control
Modules," Comput. Appl. Eng. Ed., 6(3), 181 (1998)
6. Young, B., D. Mahoney, and W. Svrcek, "Real-Time Computer Simu-
lation Workshops for the Process Control Education of Undergraduate
Chemical Engineering," Comput. Appl. Eng. Ed., 9(1), 57 (2001)
7. Felder, R., D. Woods, J. Stice, and A. Rugarcia, "The Future of Engi-
neering Education: Part 2. Teaching Methods that Work," Chem. Eng.
Ed., 34(1), 26 (2000)
8. Vivaldo-Lima, E., "Student Motivation, Attitude, and Approach to
Learning," Chem. Eng. Ed., 35(4), 62 (2001)
9. Palanki, S., and V. Sampath, "A Simple Process Dynamics Experi-
ment," Chem. Eng. Ed., 31(1), 64 (1997)
10. Romagnoli, J., A. Palazoglu, and S. Whitaker, "Dynamics of a Stirred-
Tank Heater," Chem. Eng. Ed., 35(1), 46 (2001)
11. Johansson, K.H., and J.L. Rocha Nunes, "A Multivariable Laboratory
Process With an Adjustable Zero," in Proceedings of the 1998Ameri-
can Control Conference, 2045 (1998)
12. Luyben, W., "A Feed-Effluent Heat Exchanger/Reactor Dynamic Con-
trol Laboratory Experiment," Chem. Eng. Ed., 34(1), 56 (2000)
13. Pintar, A., D. Caspary, T. Co, E. Fisher, and N. Kim, "Process Simula-
tion and Control Center: An Automated Pilot Plant Laboratory,"
Comput. Appl. Eng. Ed., 6(3), 145 (1998)
14. Joseph, B., C.-M. Ying, and D. Srinivasagupta, "A Laboratory to
Supplement Courses in Process Control," Chem. Eng. Ed., 36(1), 20
(2002)
15. Muske, K., "A Model-Based Control Laboratory Experiment," in Pro-
ceedings of the 2003 American Control Conference, 700 (2003)
16. Cooper, D., and D. Dougherty, "Enhancing Process Control Educa-
tion with the Control Station Training Simulator, Comput. Appl. Eng.
Ed., 7(4), 203 (1999)
17. Luyben, W., and M. Luyben, Essentials of Process Control, McGraw-
Hill, New York, NY (1996) 0

Fall 2003

re classroom

AND VISUAL BASIC APPLICATIONS

As Teaching Aids for a Unit Operations Course

Tulane University New Orleans, LA 70118

he design of separation processes frequently uses in-
tensive trial-and-error procedures as well as graphi-
cal methods such as McCabe-Thiele, Ponchon-
Savarit, and Triangular diagrams. Using process simulation
design packages such as ChemCAD, HYSYS, or AspenPLUS
facilitates the design of complex processes, but students of-
ten treat simulators as black-boxes and tend to accept the re-
sults they obtain without further analysis.1' Additionally simu-
lators may not provide the user with knowledge of all calcu-
lations that are performed or the respective algorithms. On
the other hand, manual step-by-step calculations and graphi-
cal methods, while allowing students to understand the fun-
damentals of the design process, do not equip them with the
ability to adapt software tools to the solution of chemical
engineering problems or to critically use existing simulation
packages. Tools such as MS Excel Macros and small Visual
Basic Applications (VBA) bridge the gap between the previ-
ous alternatives.
At Tulane University, spreadsheets have been intensively
used as teaching aids in undergraduate courses.12'31 Using
spreadsheets and VBA to solve chemical engineering prob-
lems requires a deep understanding of the concepts behind
the calculations, while the extensive and time-consuming trial-
and-error procedures are left to the computer. The interactive
nature of the spreadsheets and VBA programs allows "what
if" analyses in which the parameter values are changed and
the results are immediately displayed.121 One advantage of
using spreadsheets as teaching tools is that the instructor can
spend significantly more time discussing the fundamentals
of mass transfer and the conceptual and quantitative descrip-
tion of processes, as well as the engineering insight that is
needed in designing distillation, absorption, and other sepa-
rations, by spending less class time on the details of solving
problems graphically and by trial-and-error."41
* Currently an Assistant Professor at North Carolina State University.

During this course, we initially lectured on the fundamen-
tals of the calculation methods and presented illustrative ex-
amples. These first examples were solved using the trial-and-
error and graphical procedures. Then we presented a solu-
tion to the same problem using spreadsheets and VBA. We
discussed the details on how to program the spreadsheets and
elaborate the macros. Once the students had learned how to
use these tools, we asked them to develop their own Excel
Macros and VBA programs to solve problems for homework.
We used a process simulator (ChemCAD) during some of
the lectures and compared results obtained from both ap-
proaches. As a final project, we asked the students to create a
more complex algorithm for the design of an absorber. We
creative, user-friendly computer programs. By the end of the
course, 76% of the students used some kind of Excel spread-
sheets and Macros to solve their homework, compared to
11.5% at the beginning of the semester.

Juan P. Hinestroza is Assistant Professorat North
Carolina State University, Department of Textile
Engineering, Chemistry and Science. He received
his PhD from Tulane University in 2002. His re-
search interests are in the development, testing,
and modeling of novel protective clothing and bar-
rier materials.

Kyrlakos D. Papadopoulos is Professor of
Chemical Engineering at Tulane Universil hav-
ing joined its faculty in 1981 and served as De-
partment Chair from 1998 to 2001. He obtained
his DEngSc from Columbia University in 1982.
His research focuses on some of the phenom-
ena that are important in the separation, trans-
port, and reaction processes of particulate sys-
tems, with emphasis on drug delivery, lubricant-
technology, and environmental applications.
Copyright ChE Division of ASEE 2003

Chemical Engineering Education

It should be noted that although we have chosen Excel,
Version 2000, for all examples in this paper, other spread-
sheet programs such as Quattro Pro and Lotus will perform
equally well.

DESIGN OF ABSORPTION COLUMNS

The design of absorption using the McCabe-Thiele diagram
can be considered as a graphical solution to a series of se-
quential nonlinear equations.41] Spreadsheets have been used
in solving simultaneous nonlinear equations due to their in-
corporation of a variety of mathematical functions and the
ease of interactive programming, modification, and rapid
graph generation."1'

Example 10.3 from Geankopolis[6] is used here to illustrate
the use of spreadsheets in the design of absorption units. The
problem requires removal of acetone from an acetone-air gas
stream using water in a countercurrent stage tower. The pro-
cess schematic and spreadsheet used for solving this prob-

2
3
4
5
6
7
8
9
10
11

12
14
15
16
17
18
19
20
21
22
23
24
25
26
27

28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44

lem are shown in Figure 1. The initial data provided in the
problem, such as the percentage of recovery and the flows
and composition of the entering gas and liquid streams, are
shown in the upper portion of the spreadsheet under design
parameters. Assumptions include a constant molar overflow
in the tower, negligible solubility of air in the water, and a
phase equilibrium relationship that could be represented by
Henry's Law. The compositions of acetone in the liquid and
vapor outlets, xN and yN+, can be obtained from a mass
balance as shown in cells D8 and D9 of the spreadsheet;
the equations have been added to the respective comment
bubbles on the graph.

The equilibrium and operating lines are plotted using
Henry's Law and Equation 10.3-13 from Geankoplis, as
shown in the D15-E25 cell range of the spreadsheet and the
respective comment bubbles. Using Excel's "chart wizard,"
an X-Y plot can be readily constructed showing the equilib-
rium and operating lines.

Absorption of Acetone in a Countercurrent Stage Tower

DESIGN PARAMETERS
% Recovery 80 0.0300
L [kg-mol/h], V[kg mol-h] 90 30 pe
x0, yN+1 0 0.01 0.0250 -
xN,yl 0.00267 0.00200
Henry's Constant 0"0 2.53 0 0200 -

[-(D6*D7+E6*E7- 5 1 1

CALCULATION OF THE OPERATING AND EQUILIBRIUM L

0.00000
0.00133
0.00267
0.00400
0.00533
0.00667
0.00800
0.00933
0.01067
0.01200
0.01333

Y Operating
0.0020
00060
0.0100
0.0140
0.0180
0.0220
0 0260
0.0300
0.0340
0.0380
S0.0420

~DS5

L=25(6/$E$6).$E$B

INE
Equilibrium 0.0100 Equilibrium
0.0000 Line
0.0034 00050
0.0067
0.0101
0.0135 00000
00169 a 0000 0.0020 0.0040 0.0060 0.0080 0.0100
00202
0.0236 X
0.0270
0 0304
37 Calculating the # stages using Function
0.0337 FORECAST
=FORECAST(E7,G30:G42,F30:F42) of Stages
--3.6103|

D32($D$6/SES6)~$ES8 Figure 1. Spreadsheet used for ilustrating absorption of acetone in a countercurrent stage tower. Fall 2003 IB [ C D E F G H J K L M I N CALCULATING THE CONCENTRATION OF ACETONE PLATE BY PLATE Concentration in Concentration in the Number x the Liquid Phase Y Vapor Phase of Stages 0.000000 0.000000 x0 0.000000 0.000000 0.000000 yl 0.002000 1 X1 0.000791 0.002000 0.000791 y2 0 004372 2 x2 0.001728 0.004372 0.001728 y3 0007184 3 X3 0.002839 0.007184 0 002839 y4 0.010518 4 X4 0004157 0010518 0004157 y5 0.014472 5 X5 0.005720 0.014472 0.005720 y6 0.019161 6 x6 0 007573 .==.:-0.019161 Q-FS0S6J 'C~F2 w The next step involves the plate-by-plate calculation of the concentration of acetone in the liquid and vapor phases. In hand calculations, this step is made graphically,[4] but in this case advantage is taken of the fact that both the operating and equilibrium lines are expressed as mathematical functions, so the concentration in the liquid and vapor phases can be easily determined numerically, as shown in the D29-F42 cell range of the spreadsheet. The (x,y) data series is added to the existing graph, thus completing a numerical McCabe-Thiele diagram, also shown in Figure 1. Finally, the number of ideal stages required for the desired percentage of recovery is determined using the built-in "FORECAST' function, which operates as a linear interpola- tor. The series in the interpolation represents the number of stages and the concentration of the vapor phase (columns start- ing at F29 and G29), while the value to be interpolated is the calculated concentration at the exit of the tower (E7). Once the spreadsheet is built, several "what-if' scenarios can be analyzed. For instance, in this example an increase in the recovery requirement as well as a moderate increase in the gas flow will readily show that the number of stages re- quired will increase significantly. Also, a large decrease in the liquid flow rate or an increase in the gas flow rate will demonstrate that the separation is impossible to achieve as the operating line and the equilibrium line cross each other. INTERFACIAL COMPOSITIONS IN MASS TRANSPORT BETWEEN TWO PHASES Trial-and-error iterative procedures for determining the composition of the interface between immiscible phases are frequently required in mass-transfer-based separation pro- cesses. To demonstrate the versatility of spreadsheets in ac- complishing this task, we use Example 10.4-1 from Geankoplis,61] as shown in Figure 2. The objective of this prob- lem is to determine the interfacial concentrations of the va- por and liquid phases YA, and xAP, respectively, in a wetted- I I c I D I E [ F G H I J K 2 Iterative calculation of interface compositions in interphase mass transfer 4 Gas phase film mass transfer coefficient ky= 0.001465 Kg mol A/ m^2 5 Liquid phase mass transfer coefficient kx= 0.001967 Kg mol A/s a m^3 a XAL 0.1 Ne 7 YAG 0.38 1re ___9 ITERATIVE CALCULATION / 10 Formula First Iteration Secon, 11 xi Initial Guess 0.4 V 12 yi Initial Guess 0.9 13 (1-xasi) =((1-$DS6)-(1-E11))/LN((1-$D$6)/(1-E11)) 0739891
14 (1-yal) =((1-E12)-(1-$D$7))/LN((1-E12)/(1-$D$7)) 0.285002
Calculated Slope from
is Equation 10-4-8 =-(F$5/E13)/(SF$4/E14) -0.517186
16 x equiliblum 0.302346
y equi (From slope 5. 0
17 calculations) =+E15*(E16-$D$6)+$D$7 0. 50
y equi (from Equilibrium =8.1414*E16^3-1.4766*E16^2+O.6184*E16-
ie correlation) 0.0022 0.27480
19 Error =+(E17-E18)^2 0 000

w guess from the
vious iteration J
7/'- ---

ration Third Iteration Fourth Iteration
0302346 0.258376 0.257171
0.275350 0200427 0.197928
0.794537 0.818259 0.818902
0.670966 0.705984 0.707134
1 133842 -1 158433 -1 159408
0.258376 0.257171 0.257145
0200427 0197928 0197805
0.199593 0 197805 0 197767
.000001 0 000000 0.00000C

Value obtained from
solving numerically the
Equilibrium equation and
Equation 10-4-8

0.090 0.140 0.190 0.240 0.290 0.340

Final Value

Equilibrium Data
xa ya
0.000 0.000
0.050 0.022
0.100 0.052
0.150 0.087
0.200 0.131
0.250 0.187
0.300 0.265
0.360 0.385

SOLVE PERFORM THE
ITERATION
CALCULATION

Error between the value of y
from Equation 10-4-8 and the
value predicted by the
equilibrium correlation
This is the target cell for the
SOLVER routine and the
objective is to minimize it.
'-<___

Figure 2. Spreadsheet and Macro used for interactive calculation of interface compositions in interphase mass transfer.

Chemical Engineering Education

231

Sub INTERPHASECOMPOSITION 0
' INTERPHASE COMPOSITION Macro
' Macro recorded 9/22/2002 by JPH

Range("G2T7) Select
SolverOk SetCell:="$E$19", MaxMinVal:=3, ValueOf:="0", ByChange:="$E$16"
SolverSolve
SolverOk SetCell.="$F$19". MaxMinVal:=3. ValueOf:="0". ByChange:="$F$16"
SolverSolve
SolverOk SetCell:="$G$19", MaxMinVal:=3, ValueOf:="0", ByChange'="$G$16"
SolverSolve
SolverOk SetCell:="$H$19", MaxMinVal -3, ValueOf:="0", ByChange:="$H$16"
SolverSolve
End Sub

wall tower. Experimental equilibrium data are provided as
well as the gas and liquid phase film mass-transfer coeffi-
cients. In this problem, the solute A diffuses through stag-
nant B in the gas phase and then through a liquid film.

The first step in solving this problem involves initial guesses
for xAi and YAi- In solving the problem by hand, these guesses
are crucial to the rapid convergence of the iterative process.
Spreadsheets are less sensitive to the initial guesses as a large
number of iterations can be processed and visualized in frac-
tions of seconds.

In Figure 2, cells D13-D19 display the equations and col-
umns E H display results from four iterations. Once the
initial guesses are selected (cells E 11 and E12), the slope for
the line connecting the bulk concentration and the assumed
interfacial concentrations is calculated, as shown in cell E15.
With the slope from El 15 and point P (the bulk concentration
in cells D6 and D7) on the x-y plot in the lower-right comer
of Figure 2, an equation for a straight line is deduced as shown
in cell D 17. A third-order polynomial was used to fit the equi-
librium data (cell D18).

The Excel function "SOLVER' is used to solve simulta-

neously the equations in cells D17 and D18 by minimizing
the error between the values of cells E16 and E17. SOLVER
can use a Newton or a conjugate numerical procedure to find
the answer; the default Newton procedure was chosen for
this example. When comparison between the values for x,
and yA. from this procedure (cells E15 and E16) and the
initial guesses (cells El2 and E13) shows a discrepancy,
an additional iteration is required. The latest calculated
values for xAi and yAi (cells E15 and E16) are used as the
new initial guesses.

Due to the ease of modification of spreadsheets, the cells
containing the equations can be copied and pasted into the
next columns as many times as necessary. In this example,
four iterations provide a reliable answer (less than 0.1% be-
tween the latest and penultimate calculated values).

What-if" scenarios in this example include how an increase
in the liquid-film mass-transfer coefficient will readily show
that the value for the interfacial concentrations xAi and YAi
increase and how a large decrease in the bulk concentration
will produce a significant decrease in xAi and YAi- In order to
automate the iteration process, a MACRO was created using

OVERALL MASS BALANCE AND
THE INTERCEPT BETWEEN THE Q
AND ENRICHING LINE
-j

D _^ _Calculatin the DItillhat and Bo9tsm FFowrai
D 70. 401 Overall M Bala 560098E-05 =D5-C15-C16
1241173Component Mass Balance 2 3696E-05 =D5D6-C15"D7-C16'D8
i E Mrr 369859EA. =E15'2-E16^2
Un.e
0 1141 =(D10+D11"(D13-D12))/D010
Slope q Line 6 163 =9/(C1-1)
Intercept -2 065 +D6-C20'D6

1 300431=IOO E2411(D8-E23) Num8b880W Plare8
41033"0433 -E24-C31.E23

=FORECAST(D7,M35 M43
7.373345262 ,135143)

32 1 V 400deposes hfl E2r~n '1e 8505 Un L;SC2
-10 "

019
0.254
039
0 578
0 22

-0 033040433
0073391913
029956085
0 612205667
1 017978988

-2 065273689
-1 572218952

1.0

0.9

0.8

0.7 Ennching
Line
0.6

0.5

0.4

0.3 Snppin

0.2

0.1

0.0
0.0 0.2 0.4 0.6 0.8 1.0

78052414711.

98I ag 1 29 139 39 04400979109 i* IMacr0osfillabof Mact

40 X Y Equilibdum X StrippIng X Enriching Sta8 e
=IF(K35>L35.K35.L35) =4 3392'130*5-12 539130*4 -(J30-$CS33)/SC$32 =(C30-$J$309)/$C29 *14.226'130&3 - 8 4962'130'2 3 4699'130 41 42 0 1 0 275043492 0 231571649 0 106304365 1 43 0231571649 0491409759 0394203612 0 37676219 2 44 0394203612 0657535069 0519071890 0584418837 3 48 0 54418837 0 798732794 0.625203337 0 760915993 4 48 0760915993 0.891914543 0695243509 0877393178 5 47 0877393178 0 93799581 0729880549 0934994783 6 4 0 934994763 0 962684833 0 748438082 0 965856041 7 49 0965856041 0978595855 0760397621 0 985744819 8 0 0 9085744819 0 9900439752 0 7693001 1 00054969 9 SMacro recorded 9292002 by JPH SOLVING THE MASS AND COMPONENT BALANCES TO OBATIN D AND W SolverOk SetCelL="SF$18", MaxMinVa.=2, ValueOf ="0, ByChange.="SC$16 SCS17" SolverSolve SOLVING THE INTERCEPT BETWEEN THE q LINE AND THE ENRICHING UNE Solve0Ok SetCell ="$F$27, MaxMinVal =2, ValueOf ="". ByChange ="$F24"
SolverSolve
End Sub

Figure 3. Spreadsheet and Macro used for distillation of a benzene-toluene mixture.

Fall 2003

Rectification of a Benzene-Toluene Mixture
DESIGN PARAMETERS -
F 200 molnh
xF 04
"D 0.90
.W 0.1
R 4
Latent Hea 32090 KJKg
C,. 1859 /Kg-ol1
T, 327.6 K
T. 366.700 K

NiT EtelogpLi

29 Slope
30 lid1e-p

IY firnll, enh~el On9e 0 264816 IC8E3
Emor 930E-M (.9393A

I I

VBA; its text is also shown in Figure 2.
To create a user-friendly interface, a button is inserted into
Excel and assigning the Macro to it. The button allows the
user to run several "what-if' scenarios by changing the de-
sign parameters.

DISTILLATION
While interfacial composition calculations used a VBA
program and the absorption example was based on cell and
formula manipulation of the spreadsheet, in this example a
combination of both approaches is used for the design of a
distillation unit. Such design is made using the McCabe-Thiele
diagram with special considerations for the location of the
feed and the types of condenser and reboiler.161
Example 11.4-2 from Geankoplis' book is chosen to illus-
trate use of spreadsheets in the design of distillation towers.
The problem requires the rectification of a benzene-toluene
mixture. Initial data of the problem include the flow and con-
dition of the feed stream as well as its composition. The re-
flux ratio and the compositions of the distillate and bottoms
are also specified. These design parameters are located in the
upper portion of Figure 3 under design parameters. It is as-
sumed that a constant molar overflow is present in the tower.
Solving the overall mass balance (cell F15) and a benzene
mass balance (cell F16) simultaneously with SOLVER pro-
vides the values for the distillate and bottom-stream flow-
rates (cells C15 and C16). In this example, we take advan-
tage of the capabilities of SOLVER for multivariable calcu-
lations. The error cell (cell F17) is set as the target cell, and
the SOLVER should change the values of cells C15 and C16
until the value of F16 becomes negligible. The multivariable
optimization capabilities of SOLVER are implicit, which is
very useful since no additional programming is required.
After calculating all flowrates, the next step is to build the
equilibrium and operating lines. The equilibrium line is con-
structed using experimental equilibrium data and fitted to a
fifth-degree polynomial using the TRENDLINE option of
Excel. The "q line" is calculated by using a boiling point dia-
gram and the physical properties of the feed stream. Cells
B 18 to D21 show the calculations performed to obtain the
value of q and hence the slope and intercept of the "q line."
The enriching line is constructed using Eq. 11.4-8 from
Geankoplis,[6] as shown in cell range B26 to D27. Once the
slope and intercept of the q and enriching lines are deter-
mined, a numerical method is used to calculate the intercept
between these two lines. SOLVER is again used as shown in
cell range E21 to G25. Since this problem requires the use of
SOLVER twice, a VBA program is built and assigned to a
button so these calculations are automated with a single click
by the user. The stripping line is constructed using the initial
conditions of the problem and the intercept between the q
and the enriching lines as shown in cell range B28 to D 30.

The table containing the data as well as the formulas used
to determine the equilibrium, enriching, stripping, and q lines
is shown on cell range B32 to G38. To calculate the number
of plates required for the rectification, the following proce-
dure is followed, as shown in cell range B40 to F50. The
initial point (cell B42) corresponds to the bottoms concentra-
tion, xw,, y is calculated using the equilibrium equation (cell
C42), and the equations for the enriching and stripping lines
are used for cells D42 to E50. For every iteration an IF state-
ment is used to select the larger value for x. This IF statement
initially selects the stripping line as the operating line, but
once the "q line" is reached, the enriching line becomes the
operating line. The number of plates is calculated using the
FORECAST function as shown in cells E29 to G29. Based
on the spreadsheet, "what-if' scenarios can be considered and
the student is able to visualize the effect of changes in the
design parameters such as concentrations, flowrates, reflux
ratios, etc., on the number of plates required for a desired
separation. Concepts such as the pinch point and the mini-
mum reflux ratio can also be analyzed.

CONCLUSIONS
MS Excel Macros and Visual Basic for Applications en-
hanced the educational experience of students in a junior-
level separation processes course, teaching them to develop
simple software and providing them with an intermediate step
between doing hand calculations and using commercially
available packages. Distillation, absorption, and interfacial
mass-transfer problems were solved using spreadsheets and
were incorporated into a web-based learning platform.
In addition to analyzing several "what-if" scenarios, these
teaching tools can also be slightly modified to solve the in-
verse problems. For example, in the absorption case, the num-
ber of stages as well as the inlet flowrates and concentrations
can be given as design parameters, and then the students can
be asked to determine the concentration of the outlet streams.
Also, in the distillation case, the number of plates in the en-
riching and stripping sections can be fixed, and the students
can be asked to determine the appropriate reflux ratio and
inlet flowrates to achieve a certain degree of purity in the top
or bottom streams.

REFERENCES
1. Wankat, P., "Teaching Separations: Why, What, When, and How?,
Chem. Eng. Ed., 35, 168 (2001)
2. Rives, C., and D. Lacks, "Teaching Process Control with a Numerical
Approach Based on Spreadsheets, Chem. Eng. Ed., 36, 242 (2002)
3. Mitchell, B.S., "Use of Spreadsheets in Introductory Statistics and
Probability," Chem. Eng. Ed., 31, 194 (1997)
4. Bums, M., and J. Sung, "Design of Separation Units Using Spread-
sheets," Chem. Eng. Ed., 29, (1995)
5. Mackenzie, J., and M. Allen, "Mathematical Power Tools, Chem. Eng.
Ed., 32, (1998)
6. Geankoplis, C., Transport Processes and Unit Operations, 3rd ed.,
Prentice Hall PTR (1993) 1

Chemical Engineering Education

Teaching and
research assistantships
as well as
fellowships
available
up to
$20,000. In addition to stipends, tuition and fees are waived. PhD students may get some incentive scholarships. The deadline for assistantship applications is April 15th. G. G. CHASE Multiphase Processes, Fluid Flow, Interfacial Phenomena, Filtration, Coalescence H. M. CHEUNG Nanocomposite Materials, Sonochemical Processing, Polymerization in Nanostructured Fluids, Supercritical Fluid Processing S. S. C. CHUANG Catalysis, Reaction Engineering, Environ- mentally Benign Synthesis J. R. ELLIOTT Molecular Simulation, Phase Behavior, Physical Properties, Process Modeling E. A. EVANS Materials Processing and CVD Modeling Plasma Enhanced Deposition and Crystal Growth Modeling L. K. JU Biochemical Engineering, Environmental Bioengineering S. T. LOPINA BioMaterial Engineering and Polymer Engineering B.Z. NEWBY Surface Modification, Polymer Thin film H. C. QAMMAR Nonlinear Control, Chaotic Processes Product Development P. WANG Biocatalysis and Biomaterials For Additional Information, Write Chairman, Graduate Committee Department of Chemical Engineering The University of Akron Akron, OH 44325-3906 Phone (330) 972-7250 Fax (330) 972-5856 www.ecgf.uakron.edu/~chem Fall 2003 THE UNIVERSITY OF ALABAMA Chemical Engineering A dedicated faculty with state of the art facilities offer research programs leading to Doctor of Philosophy and Master of Science degrees. Research Areas: Biomaterials, Catalysis and Reactor Design, Drug Delivery Materials and Systems, Electrohydrodynamics, Electronic Materials, Environmental Studies, Fuel Cells, Interfacial Transport, Magnetic Materials, Membrance Separations and Reactors, Microelectro- Mechanical Systems, Molecular Simulations, Nanoscale Modeling, Polymer Processing and Rheology, Process Dynamics, Self-Assembled Materials, Suspension and Slurry Rheology, Transport Process Modeling For Information Contact: Director of Graduate Studies Department of Chemical Engineering The University of Alabama Box 870203 Tuscaloosa, AL 35487-0203 Phone: (205) 348-6450 Faculty: G. C. April, Ph.D. (Louisiana State) D. W. Arnold, Ph.D. (Purdue) C. S. Brazel, Ph.D. (Purdue) E. S. Carlson, Ph.D. (Wyoming) P. E. Clark, Ph.D. (Oklahoma State) W. C. Clements, Jr., Ph.D. (Vanderbilt) R. A. Griffin, Ph.D. (Utah State) D. T. Johnson, Ph.D. (Florida) T. M. Klein, Ph.D. (NC State) A. M. Lane, Ph.D. (Massachusetts) M. D. McKinley, Ph.D. (Florida) S. M. C. Ritchie, Ph.D. (Kentucky) C. H. Turner, Ph.D. (NC State) J. M. Wiest, Ph.D. (Wisconsin) M. L. Weaver, Ph.D. (Florida) An equal employment / equal educational opportunity institution Chemical Engineering Education Chemical & Materials Engineering FACULTY & RESEARCH AREAS he Department of Chemical and Materi- als Engineering at the University of Ala- bama in Huntsville offers you the oppor- tunity for a solid and rewarding graduate career that will lead to further success at the forefront of academia and industry. We will provide graduate programs that educate and train students in advanced areas of chemical engineering, materials science and engineering, and biotechnology. Options for an MS and PhD degree in Engineering or Materials Science are available. Our faculty are dedicated to international lead- ership in research. Projects are ongoing in Mass Transfer, Fluid Mechanics, Combustion, Biosparations, Biomaterials, Microgravity Mate- rials Processing, and Adhesion. Collaborations have been established with nearby NASA/ Marshall Space Flight Center as well as leading edge biotechnology and engineering companies. We are also dedicated to innovation in teaching. Our classes incorporate advances in computational methods and multi-media presentations. Department of Chemical Engineering The University of Alabama in Huntsville 130 Engineering Building Huntsville, AL 35899 Michael R. Banish- Ph.D. (University of Utah) Thermo physical property measurements (256) 824-6969, banish@emil.uah.edu Ram6n L. Cero Ph.D. (UC-Davis) Professor and Chair Capillary hydrodynamics, multiphase flows, enhanced heat transfer surfaces. (256) 824-7313, rlc@che.uah.edu Chien P. Chen Ph.D. (Michigan State) Professor Multiphase flows, spray combustion, turbulence modeling, numerical methods in fluids and heat transfer. (256) 824-6194, cchen@che.uah.edu Krishnan K. Chittur Ph.D. (Rice) Professor Protein adsorption to biomaterials, FTR/ATR at solid-liquid interfaces, biosensing. (256) 824-6850, kchittur@che.uah.edu Douglas G. Hayes Ph.D. (Michigan) Associate Professor Enzyme reactions in nonaqueous media, separations involving biomolecules, lipids and surfactants, surfactant-based colloidal aggregates. (256) 824-6874, dhayes@che.uah.edu James E. Smith Jr. Ph.D. (South Carolina) Professor Kinetics and catalysis, powdered materials processing, combustion diagnostics and fluids visualization using optical methods. (256) 824-6439, jesmith@che.uah.edu Jeffrey J. Weimer Ph.D. (MIT) Associate Professor, Joint Appointment in Chemistry Adhesion, biomaterials surface properties, thin film growth, surface spectroscopies, scanning prode microscopies. (256) 824-6954, jjweimer@matsci.uah.edu UAH The University of Alabama in Huntsville An Affirmative Action/Equal Opportunity Institution Web page: http://chemeng.uah.edu Ph: 256*824*6810 FAX: 256-824.6839 Fall 2003 The University of Alberta is well known for its commitment to excellence in teach- ing and research. The Department of Chemical and Materials Engineering has 37 professors and over 140 graduate students. Degrees are offered at the M.Sc. and Ph.D. levels in Chemical Engineer- ing, Materials Engineering, and Process Control. All full-time graduate students in the research programs receive a stipend to cover living expenses and tuition. For further information, contact Graduate Program Officer Department of Chemical and Materials Engineering University of Alberta Edmonton, Alberta, Canada T6G 2G6 PHONE (780) 492-1823 FAX (780) 492-2881 e-mail: chemical. engineering@ ualberta. ca web: www.ualberta.ca/cmeng M. BHUSHAN, Ph.D. (I.I.T. Bombay) Sensor Location Fault Diagnosis Process Safety R.E. BURRELL, Ph.D. (University of Waterloo) Nanostructured Biomaterials Drug Delivery Biofilms Tissue Integration with Materials P. CHOI, Ph.D. (University of Waterloo) Molecular Modeling of Polymers Thermodynamics of Polymer Solutions and Blends K. T. CHUANG, Ph.D. (University of Alberta) Fuel Cell Catalysis Separation Processes Pollution Control I. G. DALLA LANA, Ph.D. (Univ. of Minnesota) EMERITUS Chemical Reaction Engineering Heterogeneous Catalysis J. A. W. ELLIOTT, Ph.D. (University of Toronto) Thermodynamics Statistical Thermodynamics Interfacial Phenomena D. G. FISHER, Ph.D. (University of Michigan) EMERITUS Process Dynamics and Control Real-Time Computer Applications J.F. FORBES, Ph.D. (McMaster University) CHAIR Real-Time Optimization Scheduling and Planning M. R. GRAY, Ph.D. (California Inst. of Tech.) Bioreactors Chemical Kinetics Bitumen Processing R. E. HAYES, Ph.D. (University of Bath) Numerical Analysis Reactor Modeling Computational Fluid Dynamics B. HUANG, Ph.D. (University of Alberta) Controller Performance Assessment Multivariable Control Statistics S. M. KRESTA, Ph.D. (McMaster University) Turbulent & Transitional Flows Multiphase Flows CFD S. LIU, Ph.D. (University of Alberta) Fluid-Particle Dynamics Transport Phenomena Kinetics D. T. LYNCH, Ph.D. (University of Alberta) DEAN OF ENGINEERING Catalysis Kinetic Modeling Numerical Methods Polymerization J. H. MASLIYAH, Ph.D. (University of British Columbia) Transport Phenomena Colloids Particle-Fluid Dynamics Oil Sands A. E. MATHER, Ph.D. (University of Michigan) Phase Equilibria Fluid Properties at High Pressures Thermodynamics E. S. MEADOWS, Ph.D. (University of Texas) Process Control Fuel Cell Modeling and Control Optimization W. C. MCCAFFREY, Ph.D. (McGill University) Reaction Kinetics Heavy Oil Upgrading Polymer Recycling Biotechnology K. NANDAKUMAR, Ph.D. (Princeton University) Transport Phenomena Distillation Computational Fluid Dynamics A.E. NELSON, Ph.D. (Michigan Technological University) Heterogeneous Catalysis UHV Surface Science Chemical Kinetics M. RAO, Ph.D. (Rutgers University) AI Intelligent Control Process Control S. L. SHAH, Ph.D. (University of Alberta) Computer Process Control System Identification Process and Performance Monitoring J.M. SHAW, Ph.D. (University of British Columbia) Petroleum Thermodynamics Multiphase Mixing Process Modeling U. SUNDARARAJ, Ph.D. (University of Minnesota) Polymer Processing Polymer Blends Interfacial Phenomena H. ULUDAG, Ph.D. (University of Toronto) Biomaterials Tissue Engineering Drug Delivery S. E. WANKE, Ph.D. (University of California, Davis) Heterogeneous Catalysis Kinetics Polymerization M. C. WILLIAMS, Ph.D. (University of Wisconsin) EMERITUS Rheology Polymer Characterization Polymer Processing Z. XU, Ph.D. (Virginia Polytechnic Institute and State University) Surface Science & Engineering Mineral Processing Waste Management T. YEUNG, Ph.D. (University of British Columbia) Emulsions Interfacial Phenomena Micromechanics Chemical Engineering Education ROBERT G. ARNOLD, Professor (CalTech) Microbiological Hazardous Waste Treatment, Metals Speciation and Toxicity PAUL BLOWERS, Assistant Professor (Illinois, Urbana-Champaign) Chemical Kinetics, Catalysis, Surface Phenomena JAMES C. BAYGENTS, Associate Professor (Princeton) Fluid Mechanics, Transport and Colloidal Phenomena, Bioseparations WENDELL ELA, Assistant Professor (Stanford) Particle-Particle Interactions, Environmental Chemistry JAMES FARRELL, Associate Professor (Stanford) Sorption/desorption of Organics in Soils JAMES A. FIELD, Associate Professor (Wagenigen Agricultural Univ.) Bioremediation, Microbiology, White Rot Fungi, Hazardous Waste ROBERTO GUZMAN, Associate Professor (North Carolina State) Affinity Protein Separations, Polymeric Surface Science ANTHONY MUSCAT, Associate Professor (Stanford) Kinetics, Surface Chemistry, Surface Engineering, Semiconductor Processing, Microcontamination KIMBERLY OGDEN, Professor (Colorado) Bioreactors, Bioremediation, Organics Removal from Soils THOMAS W. PETERSON, Professor and Dean (CalTech) Aerosols, Hazardous Waste Incineration, Microcontamination ARA PHILIPOSSIAN, Associate Professor (Tufts) Chemical/Mechanical Polishing, Semiconductor Processing EDUARDO SAEZ, Associate Professor (UC, Davis) Polymer Flows, Multiphase Reactors, Colloids FARHANG SHADMAN, Professor (Berkeley) Reaction Engineering, Kinetics, Catalysis, Reactive Membranes, Microcontamination JOST 0. L. WENDT, Professor and Head (Johns Hopkins) Combustion-Generated Air Pollution, Incineration, Waste Management For further information, write to Chemical and Environmental Engineering at THE UNIVERSITY OF ARIZONA TUCSON ARIZONA The Department of Chemical and Enrivonmental Engineering at the University of Arizona offers a wide range of research opportunities in all major areas of chemical engineering and environmental engineering. The department offers a fully accredited undergraduate degree in chemical engineering, as well as MS and PhD degrees in both chemical and environmental engineering. A signifi- cant portion of research efforts is devoted to areas at the boundary between chemical and environmental engineering, including environ- mentally benign semiconductor manufacturing, environmental remediation, environmental biotechnology, and novel water treatment technologies. Financial support is available through fellowships, government and industrial grants and contracts, teaching and research assistantships. Tucson has an excellent climate and many recreational opportunities. It is a growing modern city that retains much of the old Southwestern atmosphere. http://www.che.arizona.edu or write Chairman, Graduate Study Committee Department of Chemical and Environmental Engineering P.O. BOX 210011 The University of Arizona Tucson, AZ 85721 The University of Arizona is an equal opportunity educational institution/equal opportunity employer. Women and minorities are encouraged to apply. Fall 2003 ARIZONA STATE UNIVERSITY Department of Chemical and Materials Engineering A Distinguished and Diverse Faculty A multi-disciplinary research Chemical Engneering environment with opportunities in electronic materials Jonathan Allen, Ph.D., MIT. Atmospheric aerosol chemistry, single-particle measurement processing biotechnology * techniques, environmental fate of organic pollutants processing, characterization, James Beckman, Ph.D., Arizona. Unit operations, applied mathematics, energy-efficient water and simulation of materials * purification, fractionation, CMP reclamation ceramics air and water Veronica Burrows, Ph.D., Princeton. Surface science, environmental sensors, semiconductor purification atmospheric processing, interfacial chemical and physical processes in sensor processing chemistry process control Ann Dillner, Ph.D., Illinois, Urbana-Champaign. Atmospheric particulate matter (aerosols) chemistry and physics, ultra fine aerosols, light scattering, climate and health effects of aerosols Chan Beum Park, Ph.D., POSTTECH, South Korea. Bioprocess in extremist, novel cell-free protein synthesis, biolab-on-a-chip technology Gregory Raupp, Ph.D., Wisconsin. Gas-solid surface reactions mechanisms and kinetics, interactions between surface reactions and simultaneous transport processes, semiconductor materials processing, thermal and plasma-enhanced chemical vapor deposition (CVD) Anneta Razatos, Ph.D., Texas at Austin. Bacterial adhesion, colloid interactions, AFM, biofilms, genetic engineering Daniel Rivera, Ph.D., Caltech. Control systems engineering, dynamic modeling via system identification, robust control, computer-aided control system design Michael Sierks, Ph.D., Iowa State. Protein engineering, biomedical engineering, enzyme kinetics, antibody engineering Materials Science and Engineering James Adams, Ph.D., Atomistic stimulation of metallic surfaces, adhesion, wear, and automotive catalysts, heavy metal toxicity Terry Alford, Ph.D., Comrnell. Electronic materials, physical metallurgy, electronic thin films Nikhilesh Chawla, Ph.D., Michigan. Lead-free solders, composite materials, powder metallurgy Sandwip Dey, Ph.D., Alfred. Electro-ceramics, MOCVD and ALCVD, dielectrics: leakage, loss mechanisms and modeling Stephen Krause, Ph.D., Michigan. Characterization of structural changes in processing of semiconductors Subhash Mahajan (Chair), Ph.D., Berkeley. Semiconductor defects, high temperature semiconductors, structural materials deformation James Mayer, Ph.D., Purdue. Thin film processing, ion beam modification of materials Nathan Newman, Ph.D., Stanford. Growth, characterization, and modeling of solid-state materials S. Tom Picraux, Ph.D. Caltech. Nanostructured materials, epitaxy, and thin-film electronic materials Karl Sieradzki, Ph.D. Syracuse. Fracture of solids, thin-film deposition and growth, corrosion Mark van Schilfgaarde, Ph.D. Stanford. Methods and applications of electronic structure theory, dilute magnetic semiconductors, GW approximation For details concerning graduate opportunities in Chemical and Materials Engineering atASU, please call Marlene Bolf at (480) 965-3313, or write to Subhash Mahajan, Chair, Chemical and Materials Engineering, Arizona State University, Tempe, Arizona 85287-6006 (smahajan@asu.edu). Chemical Engineering Education Graduate Program in the Department of Chemical Engineering University of Arkansas cZ& The Department of Chemical Engineering at the University of Arkansas S. offers graduate programs leading to M.S. and Ph.D. Degrees. I Qualified applicants are eligible for financial aid. Annual Departmental stipends provide up to$15,000, Doctoral Academy Fellowships provide
up to $20,000, and Distinguished Doctoral Fellowships provide$30,000.
For stipend and fellowship recipients, all tuition is waived. Applications
'ars z00 received before April 1st will be given first consideration.

Areas of Research

[1 Biochemical engineering
EN Biological and food systems
EN Biomaterials
EN Chemical process safety
EN Consequence analysis of hazardous chemical releases
EI Electronic materials processing
E[ Fate of pollutants in the environment
El Fluid phase equilibria and process
design
EU Integrated passive electronic Faculty
components
El Membrane separations M.D. Ackerson
E[ Mixing in chemical processes R.E. Babcock
R.R. Beitle
E.C. Clausen
R.A. Cross
J.A. Havens
W.A. Myers
W.R. Penney
T.O. Spicer
G.J. Thoma
J.L. Turpin
R.K. Ulrich

Dr. Richard Ulrich or 479-575-5645

Fall 2003

AUBURN UNIVERSITY

Chemical Engineering

Fd -
Mark E. Byrne Purdue University
Robert P. Chambers University of California, Berkeley
Harry T. Cullinan Carnegie Mellon University
Christine W. Curtis Florida State University
Steve R. Duke University of Illinois
Mark R. Eden Technical University of Denmark
Said S.E.H. Elnashaie University of Edinburgh
James A. Guin University of Texas, Austin
Ram B. Gupta University of Texas at Austin
Gopal A. Krishnagopalan University of Maine
Yoon Y. Lee Iowa State University
Glennon Maples Oklahoma State University
Ronald D. Neuman The Institute of Paper Chemistry
Timothy D. Placek University of Kentucky
Christopher B. Roberts University of Notre Dame
Arthur R. Tarrer Purdue University
Bruce J. Tatarchuk University of Wisconsin
4wi-, is- W i

Research Areas
" Fuel Cell* Hydrogen
" Biochemical Engineering Drug Delivery
" Pulp and Paper Microfibrous Materials
" Process Systems Engineering
" Integrated Process Design
" Environmental Chemical Engineering
" Catalysis and Reaction Engineering
. Materials. Polymers. Nanotechnology
" Surface and Interfacial Science
" Thermodynamics. Supercritical Fluids
" Electrochemical Engineering
" Transport Phenomena

Chemical Engineering Education

DEPARTMENT OF CHEMICAL

AND PETROLEUM ENGINEERING

FACULTY
J. Azaiez (Stanford)
L. A. Behie (Western Ontario)
C. Bellehumeur (McMaster)
P. R. Bishnoi (Alberta)
J.M. Hill (Wisconsin)
A. A. Jeje (MIT)
M. S. Kallos (Calgary)
A. Kantzas (Waterloo)
B. B. Maini (Univ. Washington)
A. K. Mehrotra (Calgary)
S. A. Mehta (Calgary)
P. Pereira (France)
A. Sen (Calgary)
A. Settari (Calgary)
W. Y. Svrcek (Alberta)
M. A. Trebble (Calgary)
H. W. Yarranton (Alberta)
B. Young (Canterbury, NZ)
L. Zanzotto (Slovak Tech. Univ., Czechoslovakia)

degrees in Chemical Engineering (full-time) and the M.Eng. degree in Chemical
Engineering, Petroleum Reservoir Engineering or Engineering for the
Environment (part-time) in the following areas:
Biochemical Engineering & Biotechnology
Biomedical Engineering
Environmental Engineering
Modeling, Simulation & Control
Petroleum Recovery & Reservoir Engineering
Polymer Processing & Rheology
Process Development
Reaction Engineering/Kinetics
Thermodynamics
Transport Phenomena
Fellowships and Research Assistantships are available to all qualified applicants.

Department of Chemical and Petroleum Engineering
University of Calgary Calgary, Alberta, Canada T2N 1 N4

The University is located in the City of Calgary, the Oil capital of Canada, the home of the world famous Calgary Stampede and the 1988
Winter Olympics. The City combines the traditions of the Old West with the sophistication of a modern urban center Beautiful Banff
National Park is 110 km west of the City and the ski resorts of Banff, Lake Louise,and Kananaskis areas are readily accessible. In the
above photo the University Campus is shown in the foreground. The Engineering complex is on the left of the picture, and the Olympic
Oval is on the right of the picture. U

UNIVERSITY OF

0 CALGARY

^^

Fall 2003

I

The Chemical Engineering Department at the
University of California, Berkeley, one of the pre-
eminent departments in the field, offers graduate pro-
grams leading to the Master of Science and Doctor
of Philosophy. Students also have the opportunity
to take part in the many cultural offerings of the San
Francisco Bay Area and the recreational activities
of California's northern coast and mountains.

FACULTY

Nitash P. Balsara
Harvey W. Blanch
Arup K. Chakraborty
David B. Graves
Alexander Katz
C. Judson King
Susan J. Muller
John M. Prausnitz
Jeffrey A. Reimer
Alexis T. Bell

Elton J. Cairns
Douglas S. Clark
Enrique Iglesia
Jay D. Keasling
Roya Maboudlan
John S. Newman
David V. Schaffer
Rachel A. Segalman

Univrsiy o CaiforiaBerele

BIOENGINEERING
Blanch, Clark,
Keasling, Schaffer,
Chakraborty, Muller,

POLYMERS &
SOFT MATERIALS

Balsara, Chakraborty,
Reimer & Segalman

Chairman: Arup K. Chakraborty

http://cheme.berkeley.edu/index.shtml

Chemical Engineering Education

CATALYSIS &
REACTION ENG.

Bell, Chakraborty,
Iglesia, Katz & Reimer

ELECTROCHEMICAL
ENGINEERING
Cairns, Newman &
Reimer

MICROELECTRONICS
PROCESSING &
MEMS

Graves, Maboudian,
Reimer & Segalman

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Department of
Chemical Engineering & Materials Science

UCDAVIS

The multifaceted graduate study experience in the Department
of Chemical Engineering and Materials Science allows students
to choose research projects and thesis advisers from any of our
faculty with expertise in chemical engineering, biochemical engi-
neering, and/or materials science and engineering.
Our goal is to provide the financial and academic support for
students to complete a substantive research project within 2 years
for the M.S. and 4 years for the Ph.D.

SAN /
FRANCISCO

LOCATION:
Sacramento: 17 miles
San Francisco: 72 miles
Lake Tahoe: 90 miles

Davis is a small, bike-friendly
university town located 17
miles west of Sacramento
INTO and 72 miles northeast of
San Francisco, within
driving distance of a
"I multitude of recreational
activities. We also enjoy
WNnES close collaborations
with national
laboratories
SAN EOo including
LBL, LLNL,
and Sandia.

look up our web site at

http://www.chms.ucdavis.edu.

Fall 2003

UNIVERSITY OF

CALIFORNIA

Chemical Engineering IR VINE
and Materials Science and Engineering
for Chemical Engineering, Engineering, and Materials Science Majors
Offering degrees at the M.S. and Ph.D. levels. Research in frontier areas
in chemical engineering, biochemical engineering, biomedical engineering, and materials
science and engineering. Strong physical and life science and engineering groups on campus.
FACULTY
Nancy A. Da Silva (California Institute of Technology)
James C. Earthman (Stanford University)
Steven C. George (University of Washington)
Stanley B. Grant (California Institute of Technology)
Juan Hong (Purdue University)
Enrique J. Lavernia (Massachusetts Institute of Technology)
Henry C. Lim (Northwestern University)
Jia Grace Lu (Harvard University)
Martha L. Mecartney (Stanford University)
Farghalli A. Mohamed (University of California, Berkeley)
Daniel R. Mumm (Northwestern University)
Andrew J. utnam (University of Michigan)
Frank G. Shi (California Institute of Technology)
Vasan Venugopalan (Massachusetts Institute of Technology)
Joint Appointments:
G. Wesley Hatfield (Purdue University)
Noo Li Jeon (University of Illinois)
Sunny Jiang (University of South Florida)
Roger H. Rangel (University of California, Berkeley)
William A. Sirignano (Princeton University)
Russell Chou (Carnegie Mellon University)
Andrew Shapiro (University of Califoria, Irvine)
Victoria Tellkamp (University of Califoria, Irvine)

The 1,510-acre UC Irvine campus is in Orange County, five miles from the Pacific Ocean and 40 miles south of
Los Angeles. Irvine is one of the nation's fastest growing residential, industrial, and business areas. Nearby
beaches, mountain and desert area recreational activities, and local cultural activities make Irvine a pleasant
city in which to live and study.
For further information and application forms, please visit http://www.eng.uci.edu/chems/
or contact
Department of Chemical Engineering and Materials Science
School of Engineering University of California Irvine, CA 92697-2575

Chemical Engineering Education

CHEMICAL ENGINEERING AT

C w1-..dA

FOCUS AREAS

0 Molecular and Cellular
Bioengineering

a Process Systems Engi-
neering (Design,
Optimization, Dynam-
ics, and Control)

Semiconductor
Manufacturing

GENERAL THEMES

0 Energy and the
Environment

g Nanoengineering i

PROGRAMS

UCLA's Chemical
Engineering Department
offers a program of teaching
fundamental engineering
science and industrial practice. Our Department has strong graduate research programs in Bioengineer-
ing, Energy and Environment, Semiconductor Manufacturing, Engineering of Materials, and Process
and Control Systems Engineering.
Fellowships are available for outstanding applicants interested in Ph.D. degree programs. A
fellowship includes a waiver of tuition and fees plus a stipend.
Located five miles from the Pacific Coast, UCLA's attractive 417-acre campus extends
from Bel Air to Westwood Village. Students have access to the highly regarded science pro-
grams and to a variety of experiences in theatre, music, art, and sports on campus.

FACULTY

J. P. Chang
(William F Seyer Chair in
Materials Electrochemistry)
P. D. Christofides
Y. Cohen
J. Davis
(Vice Chancellor for
Information Technology)
S. K. Friedlander
(Parsons Professor of
Chemical Engineering)
R. F. Hicks
L. Ignarro
(Nobel Laureate)
E. L. Knuth
(Professor Emeritus)
J. C. Liao
V. Manousiouthakis
H. G. Monbouquette
K. Nobe
G. Orkoulas
L. B. Robinson
(Professor Emeritus)
S. M. Senkan
Y. Tang
W. D. Van Vorst
(Professor Emeritus)
V. L. Vilker
(Professor Emeritus)
A.R. Wazzan
(Dean Emeritus)

551 -erHl UCL o Lo Angeles CA 9009159
Teehn at (30 8296 or vii us. at wwwhemng ca .ed

Fall 2003

Offering degrees at the M.S. and Ph.D. levels in frontier areas of Chemical, Biochemical
and Biomedical, Advanced Materials, and Environmental Engineering. We welcome you
interest and would be delighted to discuss with you the details of our graduate program,

RESEARCH AREAS
* Bio- and Chemical Sensors
* MEMS/NEMS, Bio-MEMS
* Structural Bioinformatics
* Biomolecular Engineering
* Environmental Biotechnology
* Catalysis and Biocatalysis
* Nanostructured Materials
* Carbon Nanotubes
* Complex Fluids & Colloids
* Electrochemistry
* Zeolites & Fuel Cells
* Membrane Processes
* Aerosol Physics
* Atmospheric Chemistry
* Renewable Fuels
* Water/Wastewater Treatment
* Site Remediation Processes

FACULTY
* Wilfred Chen, Caltech
* David R. Cocker, Caltech
* Marc A. Deshusses, ETH, Zurich
* Robert C. Haddon, Penn State
* Eric M.V. Hoek, Yale
* Mark R. Matsumoto, UC Davis
* Dimitrios Morikis, Northeastern
* Ashok Mulchandani, McGill
* Nosang V. Myung, UCLA
* Mihri Ozkan, UC San Diego
* Jianzhong Wu, UC Berkeley
* Yushan Yan, Caltech

The University of California, Riverside (UCR) is the fastest growing and most ethnically diverse of the 10
campuses of the University of California. UCR is located on over 1,100 acres at the foot of the Box Springs
vibrant and growing Inland Empire, and is within easy driving distance to most of the major cultural and
recreational offerings in Southern California. In addition, it is virtually equidistant from the desert, the mountains,
and the ocean. This is an ideal setting for students, faculty and staff seeking to study, work, and live in a
community steeped in rich heritage, offering a dynamic mix of arts and entertainment and an opportunity for
affordable living.

http://www.engr.ucr.edu/chemenv
or contact:
Department of Chemical/ Environmental
Engineering, University of California
Riverside, CA 92521

Chemical Engineering Education

Chemical Engineering at the

CALIFORNIA

INSTITUTE

OF

TECHNOLOGY

Frances H. Arnold
Anand R. Asthagiri
Mark E. Davis
Richard C. Flagan

John H. Seinfeld
Christina D. Smolke
David A. Tirrell
Nicholas W Tschoegl (Emeritus)
Zhen-Gang Wang

Combustion
Colloid Physics
Fluid Mechanics
Materials Processing
Microelectronics Processing
Microstructured Fluids
Polymer Science
Protein Engineering
Statistical Mechanics

For further information, write
Chemical Engineering 210-41 California Institute of Technology Pasadena, California 91125-4100
Also, visit us on the World Wide Web for an on-line brochure: http://www.che.caltech.edu

George R. Gavalas (Emeritus)
Konstantinos P Giapis
Sossina M. Haile
Julia A. Kornfield

LU
LU
Z

ILI
(I)

Aerosol Science
Applied Mathematics
Atmospheric Chemistry and Physics
Biocatalysis and Bioreactor Engineering
Biomaterials
Biomedical Engineering
Bioseparations
Catalysis
Chemical Vapor Deposition

I

Fall 2003

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Case Wetr Reserv Universit

Research Opportunities

Fuel Cells and Batteries
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Department of Chemical Engineering
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Faculty

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The faculty and students in the Department of Chemical Engineering are engaged in a diverse range
of exciting research topics. Assistantships and tuition scholarships are available to highly qualified
applicants to the MS and PhD degree programs.

Inorganic membranes, nanostructured materials, microporous and mesoporous materials,
thin film technology, fuel cell and sensor materials
El Biotechnology
Nano/microbiotechnology, novel bioseparation techniques, affinity separation, biodegrada-
tion of toxic wastes, controlled drug delivery, two-phase flow
El Catalysis and Chemical Reaction Engineering
Heterogeneous catalysis, environmental catalysis, zeolite catalysis, novel chemical reactors,
modeling and design of chemical reactors, polymerization processes in interfaces, membrane
reactors
0 Environmental Research
Desulfurization and denitrication of flue gas, new technologies for coal combustion power
plant, wastewater treatment, removal of volatile organic vapors

D Membrane Technology
Membrane synthesis and characterization, membrane gas separation, membrane filtration
processes, pervaporation, biomedical, food and environmental applications of membranes,
high-temperature membrane technology, natural gas processing by membranes

El Polymers
Thermodynamics, polymer blends and composites, high-temperature polymers, hydrogels,
polymer rheology, computational polymer science, molecular engineering and synthesis of
surfactants, surfactants and interfacial phenomena
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reaction-based separation processes

Chemical Engineering Education

Full Text

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chemical engineering education VOLUME37 NUMBER4 FALL2003 -------Award Lectures-----B S LLectur e C onocoPhillip s L ectur e The Eq u ations (of C h ange) Don't Change: Future Directions in ChE Education : But the Profession of Engineering Does (p. 242) A New Path to Glory (p 284 ) Arvind Varma W R Schowalter and .. Random Thoughts: Learning by Doing (p. 282) Felder, Br e nt Exceptions to the Le Chatelier Pri n ciple (P 290) Corti, Franses Learni n g in Ind u stry: Returning as a Professor (p 310) Blau, Wankat A Fluid-Mixi n g Laboratory for ChE Undergraduates (p 296) Ascanio Legros, Tanguy Mixing Writing with First-Year Engineering: An Unstable So l ution? (p 248) Lebduska, DiBiasio Factors Influenci n g the Selection of Chemical Engineering as a Career (p 268) Shallcross Particle Tec hn o l ogy Demonstrations for t h e Classroom and Laboratory (p 274) Iveson, Franks Development and [mpleme n tat i on of an Educational Simulator : GLUCOSIM (p. 300) Er z en, Biro! c;: inar Sensi t ivity Analysis in ChE Education: Part 2. Application to Implicit Models (p. 254) Smith, Missen A Batch Fermentation Experiment for L-lysine Production in the Senior Laboratory (p. 262) Shonnard, Fisher, Caspary Simu l ation and Experiment in an Introductory Process Control Laboratory Experience (306) Muske Using Spreadsheets and Visual B as i c App l ications as Teachi n g Ai d s for a Unit Operations Course (p. 316) Hinestroza, Papadopou l os

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Visit us on the \Veb at http://cee.che.ufl.edu/index.html

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EDITORIAL AND BUSINESS ADDRESS: Chemical Engineering Education Department of Chemical Engineering University of Florida Gainesville, FL 32611 PHONE and FAX: 352-392 0 86 1 email: cee@c h e. ujl. ed u EDITOR Tim Anderson ASSOCIATE EDITOR Phillip C. Wankat MANAGING EDITOR Carole Yocum PROBLEM EDITOR James 0. Wilkes U. Michigan LEARNING IN INDUSTRY EDITOR William]. Koros, Georgia Institut e of Technology PUBLICATIONS BOARD CHAIRMAN E. Dend y Sloan, Jr. Colorado School of Mines MEMBERS Pablo Debenedetti Prin ceto n University Dianne Dorland Rowan University Thomas F. Edgar University of Texas at Austin Richard M. Felder North Carolina State U ni versity Bruce A. Finlayson University of Washington H Scott Fogler University of Mi chigan Carol K Hall North Carolina State Unive r sity William J Koros Georgia In st itut e of T ec hnolo gy John P. O Connell Unive r sity of Virginia David F. Ollis North Carolina State Un i versity Ronald W. Rousseau Georgia In stitute of T ec hnolo gy Stanley I. Sandler University of Delawar e Richard C. Seagrave Iowa State University C. Stewart Slater Rowan University Donald R Woods McMaster University Fall 2003 Chemical Engineering Education Volume 37 Number 4 Fall 2003 LECTURES 242 Th e Equations (of Change) Don 't Change: But the Pro fess ion of Engineering Doe s, W R. Schowalter 284 Future Direction s in ChE Education : A New Path to Glory, Arvind Varma CURRICULUM 248 Mixing Writing with First-Year Engineering: An Unstable Solution ? Lisa L e bdu ska, Da vid DiBia sio CLASSROOM 254 S e n s iti v ity Analysi s in ChE Education: Part 2 Application to Implicit Model s, William R. Smith, R o nald W Missen 274 Particle Technology Demon s trations for the Classroom and Laboratory, Simon M Iv eso n George V. Franks 290 Exceptions to th e Le Chatelier Principle David S. Corti, Elias I. Franses 300 D eve l o pment and Implementation of an Educational Simulator : GLUCOSIM Fetanet Ceylan Erzen, Gulnur Bir o l Ali <;ina r 316 Using Spreadsheet s and Visual Basi c Applications as Teaching Aids for a Unit Operation s Course Juan P. Hin est r oza, K yr iak os P apa dop oulos LABORATORY 262 A Batch Fermentation Experiment for L-lysine Production in the Senior Laboratory, Da v id R Shonnard, Edward R. Fisher, D avid W Caspary 296 A Fluid-Mixing Laboratory for ChE Undergraduates, Gabriel Ascanio Rob ert Legros, Philipp e A. Tan guy 306 Simulation and Experiment in an Introductory Proce ss Control Labora tory Experience, K en n e th R Musk e SURVEY 268 Factors Influencing the Selection of Chemical Engineering as a Career Da vid C. Shallcross RANDOM THOUGHTS 282 L e arning by Doin g, R ic hard M. Felder, Reb ecca Brent LEARNING IN INDUSTRY 310 Returning as a Profe ss or Gary Blau Ph i llip Wanka t C H EM I CAL ENG I NEE RI NG EDUCATION ( I SSN 0009-24 79) is publi s hed quart e rly by t i re Chemical E11gineering Division, A m e dc a n Society for Engineering Education, and i s e dit e d at th e U niv ersity of Florida. Co rr es pond e n ce r eg ardin g e dit ori al matt e r c ir c ulation and changes of address s h o uld be se nt to CEE, Chemical E 11 g in ee rin g Department U ni versity of Florida Gainesville, FL 32611-6005 Copy right 2 00 3 by the Chemical E ngin ee rin g Division A m erica n Soc i ety for E n gi ne e ring Ed u c ation Th e s tat e m e nt s and o pini o n s e xpr essed in this periodical are t h ose of th e wr it ers and n o t n ecessa ril y tho se of th e ChE Di v ision ASEE which body assumes no responsibility for th e m Defective copies r e pla ce d if n oti fi e d within 120 days of publication Write f o r inf o rmatwn o n s ubscripti o n costs and for back co p y cos t s and availability POSTM ASTE R : Se nd addr ess changes to Chemical Engineering Ed ucation Chemical Engineering D e partm e nt U niv e rsity of Florida G abr esv ille FL 32611-6005 Peri o dical s Postage Paid at Gaine s ville, Florida and additional po st offices. 241

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Language, Literature, and Communication to work with junior-level chemistry ma jors on their lab reports in two required "writing intensive course s. These con sultants met with chemistry faculty to dis cuss writing practices in that discipline before they began offering feedback to stu dents who produced multiple draft s of their reports before submitting final ver sions for grading. The writing focus in thi s WAC effort targeted upper-cla ss s tudent s and formal lab writing and resulted in bet ter quality lab report s [7 1 A WAC effort in the De p artment of Animal Sciences at the U n iversity of Kentucky similarly targeted upper-class students through a senior-level course but by contrast it emphasized more "real world assignment s that would help students recognize the importance of writ ing in their discipline-an achievement that is often sought by WAC endeavors in engineering and technical programs The Kentucky course stressed the importance of rhetorical context in writing assign ments to improve student intere s t and to clarify assignment objectives. 1 8 1 We started the course with a scavenger hunt that sent student through a successful collaboratio n be tween humanities and engineering faculty at Michigan Tech University.ll 01 Our interactionalist approach involved using some writing activities that taught students to use writing as a means of understand ing what they wanted to say and were ex ploratory. Other activities, by contrast, in troduced them to conventions within the discipline and encouraged them to learn and reproduce those conventions. T h e bal ance, in part, is between teaching students what they need to learn to become practi tioners of an inherited discourse while also giving them the critical thinking skills they need to question and challenge conven tion s Leadership in any field requires in dividuals who can go beyond the mere re production of knowledge by continually reexamining the discipline and, when needed reshaping it. teams to various faculty, the writing center, and some research facilities such as the elec tron microscope facility. Teams collected some technical information from each visit and gave an informal presentation on their findings COURSE OBJECTIVES Students often think of writing and speaking strictly in terms of evaluation, e.g. the lab report or presentation that they must produce to "prove" that they comA much broader more pro g rammatic approach to WAC has been undertaken by the Materials Sci ence and Engineering Department at Virginia Polytechnic Institute, which integrates writing and speaking into eight core courses that students take over a three-year period. The se quence used a combination of formal and informal ( inter personal") communication a s signment s, peer writing consult ants, and supplementa l writing workshops. Their efforts seem to have contributed to the establishment of a required zero credit class for majors that asks s tudents to create a writing portfolio containing their best work in a variety of mode s from their required classes _t 9 1 Historically attempts to understand these varying ap proaches to writing have resulted in two groups : in one, the expressivist model, writing is used as a means of teaching and learning employing free writing and journal s, and in the other, the social constructionist model ," writing pedagogy emphasizes disciplinary or workplace con v entions. Such cat egorization oversimplifies the WAC proces s, with some re searchers turning to an interactionalist approach that com bines elements of both models An interactional approach .. emphasizes that learning is a social process that necessitates active involvement on the part of both the learner and the teacher while also emphasizing the contribution of disciplin ary knowledge in the transaction." l 10 1 At WPI, we attempted to adopt a scal e d-down version of this "interactionalist approach, which had been developed Fall 2003 pleted and understood the science. They have a fairly limited understanding of what communication" can be used for. At the same time, their knowledge of what chemical engineers actually do is equally limited. Because WPI does not offer freshman chemical engineering courses or require writing courses we wanted to design a course that would actively engage students in the profession while improving their ap proach to and understanding of communication as a prob lem-solving tool. Additionally we needed to recognize that although first-year chemical engineering majors do not take any chemical engineering courses they carry one of the heaviest academic course loads on campus, a fact that challenged us to design a one-credit class that would ac h ieve our pedagogical goa l s but still attract st u dents. THE APPROACH Jointly taught by a chemical engineering professor and a writing professor, the course stressed collaboration between chemical engineering and communication in its design and its execution We reasoned that the best way to teach that communication and chemical engineering should inform each other was to demonstrate the integration, so we collaborated on the design and delivery of every assignment. B oth instruc tors attended every class so the students would agai n see the connection between the two disciplines and not think of comrnunciation days versus chemical engineering days." 249

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.,a_5_3..__c l_a_s_s_r_o_o_m ____ ______ ) SENSITIVITY ANALYSIS IN ChE EDUCATION Part 2 Application to Implicit Models WILLIAM R. SMITH, RONALD w. MISSEN ** University of Ontario Institute of Te chno log y Oshawa Ontario Canada LJH 7K4 I n Part 1 of thi s series, 1 we emphasized the importance of sensitivity analy sis ( SA) in chemical engineering peda gogy and described its application to the cl ass of engi neering models expressible in explicit form, y = f(x;p ). Here in Part 2, we consider applications of SA to the more com plex class of models expressed in the implicit form, f(y x ; p)=O (l) where y is the vector of N outputs x i s the vector of J system variables, and p is the vector of K constitutive parameters. Implicit models can take many forms ; their distingui s hing property is that Eq. ( 1) cannot be "so lved analytically" for y in terms of the inputs (although we typically assume that the s olution of the equations is unique ). In Part 1, we showed how to use SA to determine and em ploy the sensitivity coefficient s of the output quantities with respect to x and top. In this paper, we similarly discuss SA in relation to several types of implicit models including sets of nonlinear equations, systems of ordinary differential equa tions, and unconstrained optimization problem s (including regression analysis). For an explicit model determining the sensitivity coefficients is relatively straightforward; for an implicit model this is usually a more complex task. We then demonstrate the use of SA for a particular implicit model arising in thermodynamics concerning two-phase equi librium of a pure substance, for which the underlying model is a set of nonlinear equations with one system variable and several constitutive parameter s Since calculation of the sen sitivity coefficients for an implicit model i s a more complex task, we focus here on their calculation and use for the sys* Part I appeared in Chem. Eng. Ed. 37 (3) 222 2003 *Unive r sity of Toronto Toronto Ontario Ca nada M5S 3E5 tern variable and for the constitutive parameters. We use the former to illustrate the use of SA as a unifying theme, in thi s case involving thermodynamics ; we use the latter to address items la and lb of Part i.c 1 1 Thu s, 1 We show the application of SA to the set of nonlinear equations for vapor-liquid equilibrium (pure sub stance) arising from equating the chemical potentials and pressures of the coexisting pha ses. The resulting implicit model determines the coexistence properties (output quantities ) {p",v 8 ,v e } in conjunction with an EOS involving the three constitutive parameter s : critical temperature T c critical pressure, P c and acentric factor, w. Here p 11 is the vapor press u re, and v 8 and v e are the molar volumes of the vapor and liquid phases respectively. From this model, we calculate the firstand second-order sensitivity coefficients of the output quantities with respect to the single system variable, T 2. We show how SA can be used to calculate the uncertaintie s of the outputs {p 11 ,v 8 ,v e } in terms of the uncertaintie s of the constitutive parameters {T c P c William R Smith is Professor and Dean of Science at the University of Ontario Institute of Technology He received his BASc (Eng. Sci.) and MASc (Chem. Eng.) degrees from the U n iversity of Toronto a n d h is MSc and PhD degrees in applied mathematics from the U n iversity of Waterloo. His research is in classical and statistical thermodynamics He is co-au thor of Chemical Reaction Equilibrium Analysis (1982 1991). Ronald W. Missen is Professor Emeritus (chemical e n gineeri n g) at the U n iversity of Toronto He received his BSc and MSc degrees in chemical engineering from Queen's University and his PhD in physical chemistry from the U n iversity of Cambridge He is co-author of C h emica l R eaction E qui libri um A nalysis (1982, 1991) and Introduction t o Chemica l R eaction Engineering and K i net i cs (1999). -----, "" -,, C ,op yr _, i ,..., gh -:t "" Ch ,-, E"'D"'iv: -, is ...,. io n o """ f A -:-, S "" E "' E '" 2 "' 00 "' 3 ____ 254 Chemical Engineering Education

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w} of a n underlyi n g three-parameter EOS employed in the no n linear equation model for pure-fluid vapor l iqu i d equilibrium. OVERVIEW OF IMPLEMENTATION OF SA FOR IMPLICIT MODELS As disc u ssed in Part 1, the implementation of SA requires calcu l ation of sensitivity coefficients. For an explicit mode l their calculation is re l atively straightforward; for an implicit model, their calculation depends on the particular type of model. We briefly sketch how sensitivity coefficients are cal c ul ated for several implicit models arising in chemical engi neeri n g: sets of n onlinear equations systems of or d inary dif fe r e n t i a l equa ti ons, and u nconstrained optimization The r s ul ting expressions are scattered in the literature, and it is u sefu l to present them all here For an implicit model defined by a set of nonlinear alge braic or transcendental equations i = 1 2 .. N (2) the first-order sensitivity coefficients of y with respect to x or p are obtai n ed by partial differentiation using t h e chain ru l e T hu s, for t he system variables x i = 1,2, ... ,N; j = 1 2 ... J (3) where denotes evaluation at the solution to Eqs. (2) Equa tions (3) are a set of NJ linear algebraic equations in the se n sitivity coefficients ay/cJxi' The result for the sensitivity co efficie n ts ay/a p j is analogous to Eqs. (3) We ill u strate be l ow the u se of Eqs. (3) by means of a numerical examp l e A n im p l ici t m o d e l d efi n ed by a system of first-order ordi n ary differe n tial equa t io n s (ODEs) is expressed as dy ctt = gi{y t; x, p ) i = 1 2 ... ,N Yi(O)=Yoi i=l,2 .. N (4) (5) T h e first-or d e r sensitivity coefficients ofEq. (4) with respect to t h e co n stitutive parameters p are obtained by differentia tio n ofEq. (4) t o give i = 1,2, ... N; j = 1,2 ... ,K (6) ( ay 1 l 1 j(O)= 0 api (7) Fall 2003 SA can ser v e as a unifying theme for v arious topics in v ol v ing engineering models since among other things it can show the relati v e importance of changes in input quantities as the y affect output quantities ( the solution ) The corresponding equations for ay/ax j are obtained by re placing p with x J J We can also consider the initial conditions of Eq (5) as additional constitutive parameters; the sensitivity coefficients with respect to these are given by the ana l ogs ofEqs. (6) a n d (7), ( ay1 l _I j (O) = 8ij OYo j i,j= 1 2 ... N (9) where 8 .. is the Kronecker delta. I J Equations { (6)(7)} and { (8)(9)} are initial-val u e prob l ems for sets of first-order nonlinear ODEs for the se n s i tivity co efficients, which may be solved n u merically s im u l taneo u sly with the model, Eqs. { ( 4)(5)}. They appear in the literature in various places relating to differential equations; a relatively early treatment is given by Cukier et al. l 2 1 For an implicit model defined by an unconstrai n ed optimi zation prob l em min f(y; p ) y (10) the outp u ts are the values at the optimal sol ut ion, y T h e first-order necessary conditions for optimization are af (y; p )= 0 ayi i = 1 2 ... ,N (11) To calculate the se n sitivity coefficients of the optimal sol u tion to changes in the constitutive parameters p we can treat Eqs. ( 11) as a set of nonlinear equations and app l y Eqs (3) to give i = 1 2 .. N ; k = 1 2, .. ,K (12) Equations (12) are a set of linear algebraic eq u ations for ay t /ap k involving the second-order coefficients of f at t h e optimum, (a 2 f/ay i ay / and (a 2 f/ay i ap J. 255

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We can a l so consider changes involving functions of the output variables yin an implicit model. For example a typi cal parameter-estimation problem involving an engineering model can be viewed as an implicit model in which the pa rameters are outputs y obtained by minimizing the sum of sq uares of deviations of a model from a set of observed data. The values of the objective function at parameter values near the optimal so lution are important in determining their joint confidence regions 131 (their uncertaintie s in a statistical sense). Thus, the change in the residual-sum-of-squares objective function, M, from the optimal value is given approximately by the Taylor expansion where the first-order term vanishes because of Eqs (11). Equation (13), involving the second-order sensitivity coeffi cients defines an ellipsoidal confidence region for the pa rameters for a specified value of M. This region defined by the set of all parameter values such that the right side of Eq. (13) is less than or equal to the left side, can be viewed as the parameter region that yields an acceptable uncertainty in the residual sum of squares -1SENSITIVITY COEFFICIENTS FOR COEXISTENCE PROPERTIES OF VAPOR-LIQUID EQUILIBRIUM For a pure fluid, {p",v g, v e } are output quantities arising from a model consisting of a set of three nonlinear equations involving an EOS that is assumed to be applicable to both liquid and gas/vapor phases. The model equations result from equating the chemical potentials and the pressures of the co existing phases (at a given T). The former equality gives rise to Maxwell 's equal-area rule 1 4 l (first enunciated independently by MaxweUC 51 and by Clausius l 6 l ) f v & (T-p] p 0 [T; p J( vg[T; p]v e [T ; pl) = P( v, T;p )dv v 1 (T ; p] (14) where P(v,T;p) represents the EOS, and we explicitly denote the dependence of the outputs on the system variable T and the constitutive parameters of the EOS, p. (Equation 14 was given, in effect, by Planck. 171 ) The pressure equality results in two additional equations involving the EOS 256 p 0 [T ; p] = P(v g [T ; p] T) p 0 [T; p] = P( v e [T ; p], T) (15) (16) The numerical solution of Eqs. (14) to ( 16) is part of the cal culations described in the following example. We now turn our attention to the sensitivity coefficients for this implicit model. Equations ( 14) to (16) are three equa tions in the three outputs {p",v g .v e }, with the system vari able T, for a given set of constitutive parameters, p (which we consider to be fixed in thi s section, and for simplicity suppress their appearance in the following equations). We carry out a first-order sensitivity analysis of the model by differentiating the equations with respect to T to give a s et of three linear equations for the sensitivity coefficients in the form of Eqs (3). The notation signifies evaluation at the solution of Eqs. (14) to ( 16). These are ordinary (as op posed to partial) derivatives s ince there is a single system variable, T. Differentiation of Eq ( 14 ) ( involving differentiation of the integral) gives d O f v 8 (a P J _P_( vg v e ) = (v T)dv dT v oT V (17) Differentiation of Eqs ( 15) and (16) (involving application of the chain rule) gives (18) (19) In these equations with respect to the derivative s on the right side, u denotes along the saturation curve," and superscripts g and f refer to evaluation at (v g, T ) and (v e T) respec tively ; all quantities are evaluated at the s aturation conditions corresponding to {p ",v g ,v e T} The s ensitivity coefficients are available analytically from Eqs (17) to (19) as dpcr dT f v g (a PJ (v,T)dv v 1 oT V (20) (21) Chemical Engineering Education

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dpo (aP) e d'faT v = ( av ) t dp 0 + ( ~ ) t ( aP ) t aP T dT aT p av T (22) where the cyclic derivative rule has been u s ed to obtain the final terms in each of Eqs (21 ) and ( 22). (Equations of the type of 21 and 22 were obtained by Planck l7 1 ) E qu ations (20) through (22) can be differentiated again to obtain the second-order sensitivity coefficients on the satu ration curve, which are given by -2 UNCERTAINTY ANALYSIS OF VAPOR PRESSURE WITH RESPECT TO ( 2 4) (25) THE CONSTITUTIVE PARAMETERS (Pc T c, w ) The sensitivity coefficients of y i with respect to the consti tutive parameters p can be obtained by differentiating Eqs. J (14) through (16) at each T. The normalized sensitivity coefFall 2003 ficients {c)p 0 /ap av s /c)p av t Jap } are given by the ana l ogs J J J of Eqs. (20) through (22) as (26) (27) (28) The derivatives c)P/op on the right side are eval u ated from J the EOS holding fixed v and T, and all parameters other than P r The derivatives (oP/ov )y are evaluated at fixed values of all constitutive parameters, as in Eqs. (20) through (22). If we denote the relative uncertainties in the three co n stitu tive parameters by u(ln p ), the relative uncertainties i n the J three output quantities, u(ln y ), are given by the analog of Eq. (9) of Part 1 c i i 2 L 3 ( alny Y 2( ) u(lny;)= l --'Julnpi a ln pl 1 = 1 (29) where we assume that the input uncertainties are uncorre l ated. The upper and lower (95 % ) uncertainty limits for yi are then calculated from Y; (upper)= Yi exp[ 2u(ln Yi)]; Yi (lower)= Yi exp[-2u(ln Yi)] (30) NUMERICAL EXAMPLE As a numerical example of items 1 a and 1 c of Part 1 111 or 1 and 2 above we consider the calculation of {p",v & ,v t } for toluene their sensitivity coefficients with respect to {T c ,P c ,w} as functions ofT from the triple-point tempera tu re, T,, to Tc, and the use of the latter in uncertainty analysis in co n j un tion with the Peng-Robinson EOS 181 where a ( T ) P= RT a(T) v b v( v + b) + b( v b) 2 2 0.45724 R T c a(T) P c (31) (32) 257

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b 0.07780 RT C (33) P c a(T) ( I+ K(w)[l-(Tff ) 05 ]) 2 (34) K(W) 0 37464 + 1.54226w 0 26992 w 2 (35) The derivatives required in Eqs. (26) through (28) are given from Eqs. (31) through (35) by clP RT ( cl ln b I ( cl ln b I 2 ba(T)( v b) clp j = b ( V b )2 la ln p j j + la In p j j [ v( V + b) + b( V b) J2 a(T) ( a In a(T) I v( V + b) + b( V b) l a In p j j a ln a(T) 2+ a In a(T) =2 +[a(T))-0 .s K(w{ _..:!:_ J cl ln T c clln T c Tc cl In a(T) a 1n pc 1 cl In a(T) = cllna(T) Hlf ][";,:~)]= cl ln w cl lnw 200 [ I -[ _!_ r} 1.54226-0.53984 ro) [ a(T)]05 T c cl In b =-l clln Pc clln b =0 clln w ( clPJ RT 2a(T)(v+b) ilv T =(v-b) 2 + [v(v+b)+b(v-b)) 2 (36) (37) (38) (39) (40) ( 41) (42) (43) We have used Maple l 91 to calculate the coexistence proper ties {p a-,vs,v e } from Eqs. (14) through (16) and their sensi tivity coefficients from Eqs (26) through (28) with pj = T P w in turn. A Maple script is availab le on the web site at c' c Figure 1 shows the normalized sensitivity coefficients with respect to the constitutive parameters {P c ,T c ,w} as functions of T from the triple-point temperature T 1 to T c using the nominal parameter values for toluene of! 101 { 42 .3 65 kPa, 593 95 K, 0 26141} (w was calculated from the vapor pres sure equation given by Goodwinl 1 01 ). The ordinate values can 258 8lnp" / 81nP = I ----------------10 ;;: .9 -20 'b. -30 -40 -50 +--~~--~--..---~c-----n----, 100 200 T, 50 40 30 ff 20 '!, 10 ll~ 11 / 8lnw --0 300 400 T / K 500 T 8 1n v'/ 81n T -------------8ln v'/ 8 1n P = -I 700 -10 -l--~~--..----,---,----,-,-----, JOO 200 300 T, 400 T / K 500 00 T 700 10~-----------------, 8 1n v' / 8 1n w 81nv' / 8 1nP = 1 -10 -20 8 1 nv' / 81nT .9 -30 -40 -50 -1---~..---~c---~---r----+,----, I 200 T, 100 300 400 T / K 500 600 T 700 Figure 1. Normalized sensitivity coefficients with respect to {P "' T "' w} for toluene from PR EOS over entire liquid range (T, = 293.15 Kto T c = 593 95 KJ: (a) for p "; (b) for VS; (c) for v l Ch e mi c al Engineering Education

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be interpreted as the % change in the output for a 1 % change in the input. L 1 l The most important parameter for all three output variables is T c For p" (Fig ure la), the sensitivity coefficient with re spect to T c is negative and increases in magnitude from about 7% near T c to over 28.5 % at the triple point (T, = 178 15 Kl 101 ). The corresponding coefficients of v g (Figure lb ) and v e (Figure le) both become infinite in magnitude at T c At lower temperatures, the coefficient of v 8 is much larger in magnitude than that of v f The latter coefficient decreases from 0.9 at T 1 to become negative at T = 461 K and increases rapidly in magnitude as T approaches T c The former coeffi200 300 T, 400 T / K 500 0 0 T Figure 2a. Vapor pressure (p ) for toluene (178 .15 K(T ) to 593.95 K (T )); central curve (nominal value) obtained from PR EOS; points are experimenta1! 101 outer curves define 95 % uncertainty bands (see text) 700 .------------------~ 600 ---500 400 ,.. 300 200 u' 1~ 1~ ,~ ,~ 1~ 1~ 1~ ,~ ,~ ,~ ,~ ,~ u/ L mo1 1 Figure 2b Liquid-vapor binodal curve for toluene {T-v co ordinates}; centra l curve (nominal value) obtained from PR EOS; points are experimenta]/ 101 outer curves define 95 % uncertainty bands (see text}; the inset shows the breakdown of the first-order SA expansion for the uncertainty bands near T c (see text). Fall 2003 cient is always positive starting at 28.5 at T 1 going through a minimum at T = 486 K and rapidly increasing in magnitude as T approaches T c Voulgaris, et al .,[ 111 have also reported on the "extreme sensitivity of p to T c" for various fluids al though they did not use SA in their investigation. The sensitivity coefficients with respect to P c are much smaller in magnitude than those with respect to T c and all have con s tant numerical values (+1 for p and -1 for v 8 and v e ), results not anticipated prior to the numerical calcula tions. In retrospect, however, it was realized that this follows from the fact that the Peng-Robinson EOS is in effect, a two parameter EOS with the acentric factor w incorporated into the parameter a via a function of the reduced temperature, T, = T/f c For all such EOS including a strict ly two-param eter EOS such as the van der Waals, the reduced vapor pres s ure p /P c is a universal function t ofT and w p 0 =P c ,(T r, m) Differentiation of Eq (44) then gives as in Figure la (44) (45) Similarly as in Eq ( 44) the liquid and vapor saturation volumes are also universal functions ofT and w r (46) Also the Peng-Robinson or similar EOS each h as a univer sa l value of the compressibility factor at the critical point (47) Taking logarithms and differentiating both members of Eq. (46) and Eq. (47) with respect to In P c we obtain am V g aJn V i --=--=-1 a1n P c a In Pc as in Figures lb and le. (48) The sensitivity coefficients with respect tow are also much smaller in magnitude than those with respect to T c with that of p being the largest. This coefficient (Figure la) is nega tive and increases from -5.2 % at T to zero at T. The coeffi' C cient of v 8 with respect tow (Fig ure lb) is positive and decreases from 5.2 % at T to zero at T ; for v f it is negative and l C very small (of magnitude less than 0.06 % ) Figure 2 shows the output quantities p (Figure 2a), and v e and v 8 (Figure 2b) in the form of the T-v binodal curve, to gether with uncertaint y bands calculated from Eqs. (29) and (30) assuming 2.5 % uncertainties in each of the constitutive parameters {P c T c w} i. e., with2u(lnp i ) =0.05. Theexperi mental points in Figure 2a, for comparison with the calcu259

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M i x i ng Writing with First-Ye a r E n g ineer i ng Continued from page 253. was s ubj ected to morally s timul ating sit u ations which made me think, whic h is n ove l and frightening Andfinal/y I was presented w ith two proj ec t s that wou ld b e assign e d to eve r y da y c h e mi c al e ngin ee rs. I n m y op ini on I fee l that I have learned so m e thin g about th e c h e m. eng prof ess ion and that I mu s t remember to commu ni cate m y id eas to o th e r s s u cc in c tl y and clearly as I tak e the rolle r coas t er rid e of e du ca tion towards th e tunn e l of real life working e n v ironm e nt s. C ONC LU SION S For both s tudent s and faculty, thi s course experiment see med to mo ve in a promi si n g direction. On a profes sio nal development level the activity le sse ned the widening gulf of mutual incomprehen s ion between sc ientist s and human ist s that C.P. Snow sa id threatened the quality of intellectual life. 1161 DiBiasio and Lebdu s ka eac h gained insight into how the other half lived, into the prioritie s informing engineering and humanitie s education, and on how the two s ides too of ten thought of dichotomou s l y, might speak to each other in the cla ssroo m Equally important was the opportunity to al low s tudent s to hear the conversation-that is, to experience chemical engineering as a practice that is informed b y hu manitie s va lue s, including clear a nd ethical communication. Our conclusion is that mixing writing and fir s t-year engi neering is certainly a stable solution when the experiment is properly conducted. In our opinion, the un s table solution, represented by segr egated te c hnical writing courses and en gineering writing that emphasizes only lab report s, i s not as producti ve Ensuring sta bilit y take s energy time, and com mitment from the faculty, how ever-it's a c hallenging and difficult proce ss, but it is rewarding an d fun. The students will also be challenged, not just b y trying to understand a profession they think they want to pur s ue but also by being engaged in thinking through writing Generally that 's a new concept for most of them. For the mo s t part, the activities we de sig ned accomplished our original goals while providin g u s with greater in s ight into fust-year s tudent s. In her eva luation of the portfolio s, the external writing s pecialist not e d Such opportunities for s tu den t s t o r eflect on their l earn in g-what th ey l e arned wha t it means w h y it i s impor t ant, etc.--are c ritical co mpon en ts of effective portfolios, and they dis tin g uish portfolios from other kinds of student learn ed assessment (tests, essays, and so on)J 12 1 The course experience, in other words, not only provided s tu dents with information about chemical engineering, but it offered them an opportunity to gai n knowledge about it that is, a mean s by which they could reflect about the infor mation and place it within the context of their overall live s. De s pite problem s such as course lo gis tic s, s tudent s' time constraints, and a kind of cultural resis tance to writing, mo st s tudents demon s trated growth in their know ledge of the proFall 2003 fession and their use of communication a s a learning tool. Additionally, we discovered that a collaboration between seemingly unrelated disciplines aids in faculty development (a n opportunity to see how the other half thinks), but to be truly effective this approach needs to be transported be yond the two in v olved faculty members to a more global ized WAC endeavor. Recently the chemical engineering department voted to expand the course and now offers a full 3-credit introduction to chemical engineering on a two-year trial basis. The course counts toward graduation requirements and it is expected to become a permanent part of the department's c u rricul u m REFERENCES I. R o b erts, S.C., "A Su ccessfu l Intr o du c tion to Chemical Engineering First-Semester Course Focusing o n Connection Communication, and Preparation ," Pr ocee din gs of 2000 Annual Me e ting of AIChE Lo s Angeles, Chemical Engin eer ing in th e New Millenium, 406 ( 2000 ) 2. Young, V L., "Technical Comm unic atio n and Awareness of Social I s u es for Sophomores ," Pr ocee d i n gs of 2000 Annual Meeting of AIChE Los Angeles, Chemical Engineering in the New Mill e nium 399 (2 000 ) 3. Y oko moto C.F., M Ri z kalla C. O Laughlin, M El Sharkawy and N Lamm, Developin g a Motivational Fre s hm a n Course in Usi n g the Prin c ipl e of Attached Learni n g," J Eng. Ed. 88 (2), 99 4 B al l ey, R ., and C. Gei s l er, "A n Approach to Improving Communica tion Skills in a Laboratory Setting," J. Chem. Ed ., 6 8 (2) I SO (I 991 ) 5 Herrington A., reprinted from 19 85, Writing in Academic Setting s: A Study of the Contexts for Writing in Two College Chemical Engi n eering Courses, Landmark Essa ys on Writing Across th e Curricu lum Charles B aze rrn an and D avid Ru sse ll e d s., Herrnagora s Pre ss, D avis, CA (1994) 6 Mair, D. and J R a do vic h De ve l op in g Indu s tri a l Case s for Technic a l Writing on Campus," JAC 6 (I 985) 7. Labi a nc a, D.A ., Writing Across the Curriculum: A Heretical Perspec tive ," J Chem. Ed., 62 (5), 400 ( 1985 ) 8. Aaron, D K ., "Writi n g Across the Curriculum: Putting Theory into Practice in Animal S cie n ce Courses, J Animal Sci., 74(11 ), 2810 ( 1 996) 9. Hendricks, R.W. a nd E .C. P a ppa s, "A dvan ce d Engineering Educa tion : An Int eg rat e d Writing a nd Communication Program for Materi als Engineers, J Eng Ed ., 85 (4), 343 (1996) 10 Flynnm, E A ., K Remlin ger, a nd W. Bulleit, Interaction Across the Curriculum," JAC 1 7.3, 11. Gurland S.T. Bridg e Proj ect: Communications and Chemical Engi n ee rin g," unpublish e d external evaluation (20 00 ) 1 2. Williams Julia Final Evaluation: Ch e mical En g ineering and Com munic a tion Brid ge Course, unpubli s h e d external evaluation (2000) 1 3 Texaco Settles Bia s Suit, Po s ted IS November 1996; Accessed 13 October 1 999: 14 Villanueva Victor On th e Rh etoric and Precedents of Raci s m, Col l ege Composition and Communication 50 (4), 645 (1999) IS Bro oke, Robert Underlife and Writing Instruction ," College Com pos iti on and Communication, 38 (2), 1 41 (1987) 1 6. Snow C.P., The Two Cultures, Cambridge University Pres s, Cambridge E n g l a nd (1959) 0 261

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OVERVIEW OF THE EXPERIMENT The L-lysine batch fermentation experiment is shown sche matically in Figure 1. It is conducted using a 5-liter bioreac tor (New Brunswick Scientific BioFlow3000) and a data ac quisition and control system ( New Brunswick Scientific BioCommand). With this system, students study the kinetics of microbial growth and L-lysine production under controlled conditions of temperature, pH dissolved oxygen (DO), and agitation Auxiliary equipment includes a mobile autoclave sterilizer (New Brunswick Scientific) and a media microfiltration unit (Fisher Scientific). Approximately 60 to 100 senior-year chemical engineer ing students annually conduct the batch fermentation experi ment in the "Chemical Plant Operations Laboratory" course. Due to the complexity of this experiment, students work in TABLE 1 Schedule for L-lysine Experiment Orientation Propo sa l preparation Pre-laboratory check-in Laboratory experiment Post-laboratory oral pres e ntation Final report preparation Week 1 W eeks I a nd 2 Start of week 3 During week 3 During week 4 Weeks 4 a nd 5 r----------------------------------------------------------------------0 l r---------------------------~ i, + i L-aspartic------+ asparty l ---+ aspartyl L-homoserine ---+ L-threonine acid phosphate sem ir ehyde 1 dihydrodipicolinate a-ketobutyrate +='= j -------------------L-lysine L-methionine L-isoleucine Figure 2. Feedback inhibition for regulation of L-lysine syn thesis within the cell. Dashed lines indicate feedback inhi bition of key enzymes in the metabolic pathway (solid lines). TABLE2 Experiment Plan for Cell Growth and L-lysine Production (Amino acid base case values are L-threonine (150 mg/L ), L-methionine (40 mg/L ), and L-leucine (100 mg/L) A111i110 Acid Co11ce11tratio11 1. Low (50% lower) 2 Base case 3 High (50% higher) Fall 2003 Glucose Co11ce11tratio11 (g!L) 20 30 Team 2 Team l Team 3 Team 5 Team4 Team 6 teams comprised of two 4-member groups. The fermentation experiment requires two to three days of continuous opera tion to complete due to the slow kinetics of cell growth and L-lysine production. Table 1 shows the sequence of events for this experiment. PEDAGOGICAL OBJECTIVES The first pedagogical objective for the fermentation experi ment is to introduce the students to biochemical process equip ment and to explain the key steps for production of a bio chemical product. Because most of the graduating seniors have little or no biochemistry or biochemical engineering experi ence, the experiment objectives are geared toward an intro ductory treatment. Prior to conducting the experiments, we give a 2-hour orientation and provide background informa tion on L-lysine production using Corynebacterium glutamicum (American Type Culture Collection ATCC No. 21253) we conduct a tour of the laboratory, and hold a dis cussion of experiment objectives. We give background information in an oral presentation to the 8-member student team and describe cell growth in the context of the major growth stages: lag, exponential, decel eration, stationary, and death Specific metabolic character istics of C. glutamicum are described as shown in Figure 2 P 1 We further explain that due to a mutation in the cellular DNA by chemical treatment, this cell cannot convert aspartyl semialdehyde to L-homoserine In order to grow the cells on a glucose minimal medium L-methionine L-isoleucine, and L-threonine must be added in trace amounts. Once these supplemented amino acids are consumed by growth, any re maining glucose is converted to L-lysine rather than cell mass. We explain that concerted feedback inhibition of the enzy matic conversion ofL-aspartic acid to a aspartyl phosphate is relaxed as L-threonine is consumed, thus allowing overpro duction ofL-lysine. When these concepts are understood, we tell the students that cell growth and product formation are expected to occur separately in the batch culture. One of the objectives for the student teams is to test this hypoth esis and also to determine if the amount of supplemented amino acids controls the maximum concentration of cells in the fermentation. The second part of the orientation is a tour of the labora tory facilities. We describe each piece of equipment and ex plain its purpose in the production of L-lysine. We empha size the importance of maintaining sterile conditions and show the students the two methods of sterilization used; steam au toclaving for the bioreactor and microfiltration for the growth media We discuss scale-up and the need for coordinating processes at smaller scales to support production at a larger scale (e.g., flask-scale cultures for inoculating the fermenter and the associated equipment). Finally, we explain that the safety aspects of the laboratory are consistent with Biosafety Level I requirements (Center for Disease Control, CDC). The 263

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last part of the orientation is a di sc u ssion of handout materi als (availab l e upon request by e-mail from ) and a schedule for meeting the re quirements as o utl ined in Table 1. Another pedagogical objective is to test the effects of ini tial glucose a nd amino acid concentrations on L-lysine pro duction and cell growt h in a design of expe riments. As shown in Table 2, this design of experiments involves six teams dur ing th e semester. The goal is to involve the student teams in a Safety is integrated into all aspects of the undergraduate chemical engineering laboratory experience .. In the design phase ... a thorough safety review of the bioprocessing equipment, procedures, chemicals, and biological organisms was conducted co ntinuou s improvement exercise and to increase their un derstanding of h ow fermentation parameters affect cellular growt h a nd L-lysine production Each team conducts an ex periment at different initial glucose and amino acid concen trations. Durin g the semester, as experiments are completed a nd re s ult s be co m e availab l e, sharing the data with the other s tudent teams is intended to increase the level of understand ing about this fermentation proce ss for the entire class. Stu dent teams s har e their results by attaching report s and pre se ntation s to an e-mail to the instructor-the cumulative re su lt s (as shown later in Table 6) are then organized and dis se min ate d by the instructor to the s tudent teams (by e-mail attachment) durin g the final days of the semester. EXPERIMENTAL METHODS Following the orie ntat io n each team prepares and submits a propo sal in whic h s tud ents demonstrate their familiarity wi th the process equipment the objectives, laboratory safety (c hemi cal, physical and biol ogical hazards) samp l e calcu lations, and th e market aspects of their product. Because of sc hedulin g limitations, during the 52-hour experiment the teams are split into two groups. One group from the team initiates the fermentation over a 4-hour period. This involves formulating the grow th medium assembling and autoclav ing the bioreactor steri lizin g the medium and transferring it to the bioreactor u sing microfiltration calibrating 0 2 and pH probe s, and fi nall y inoc ul ating with flask-grown cells. Dur ing the next 48 hours all students in the team periodically sample for cell growth, g lu cose consumption, and L-lysine produ ction (no samp lin g is done between midnight and 8 a.m., howe ver). Each run in the ex perim ent plan is conducted under identi cal co ndition s of temperature (30C), pH (7 .0) dissolved 264 oxygen (50% of saturation with air), and duration (52 hour s). The experiment objectives given to each team are s hown in Table 3. The maximum specific growth rate is obtained by applying the Monod equationl 61 to the definition of the spe cific growth rate, as I dX x dt (1) where X is the concentration of cells in the medium (g/L). The Monod equation is S A =max Ks + S KA + A (2) where ax is the maximum s pecific growth rate constant (hr 1 ), S and A are the concentration of glucose and supple mented amino acids, respectively (g/L), and K s and K A are the half saturation constants (g/L). At the start of the fermen tation S>>~, A>>KA, and therefore = ax in Eq. (1) The so lution to Eq. (1) for exponential growth is X l!n-=maxt Xo (3) For cell growth, sa mple s from the bioreactor are taken at 2-ho u r intervals on the first day and at 4-hour intervals on the second a nd third days. Mass concentrations are obtained by first measuring the absorba n ce (at 500 nm wavelength, A 500 Milton Roy Spectronic 21D) and converting those val ues using the conversion factor, y (g dry cell wt.IL) = 0.5x, where x is A 500 Every 8 hour s, samples are taken for glucose TABLE3 Fermentation Expe riment Objectives I. Determine maximum specific growt h rate, m "' (hr ) 2. Measure g lu cose cons umption (g/L) 3. Measure L-ly sine production (g /L ) 4. Determine cell growth yie ld Y XJs 5. Determine L-lysine production y i e ld Y P is TABLE4 Major Steps in the Ex periment Procedure for L-lysine Production in Batch Culture 1 Assembly of fermenter and microfi l ter for steam steri lization 2. Steam steri li zation of fermenter a nd microfilter 3. Media preparation 4. Filter ster ili zation of culture media 5 Calibration of pH and dissolved oxygen probes 6 Initialize data acquis iti on 7 Fermentation 8 Sampling for cell, g luc ose and L-lysine 9. Analysis of g lu cose and L-lysine samp l es I 0. Shutdown and clean-up of fermenter Chemical Engineering Education

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and L-lysine analysis by filtering 5 ml of cell culture solution through a 0 2 m (polycarbonate, 25 mm dia. Millipore GITP02500) membrane and into a closed capped vial (20 ml) to remove cells. These samples are then stored in a re frigerator (4C) until the end of the experiment, when they were analyzed together by the second group of the team. Glu cose concentration is analyzed using the hexoskinase/glucoseTABLES Composition of Defined Minimal Media for L-lysine Production using C. glutamicum. ( All values are per liter of final so lution ) 20 grams D-glucose 5 g (NH 4 ) 2 SO 4 8 g K.,HP0 4 4 g KH,P0 4 0.2 g Mgso 7 tt,o 1.0 g NaCl 0.5 g ci tri c acid 20 mg FeSO 4 7 H,O 50 mg CaCl 2 2 H,O 150 mg L-threonine 40 mg L-methionine 100 mg L-leucine l mg biotin l mg thiamine HCl 10 ml I00x trace sa lts I OOx Trace Sa lt s Solution per liter of distilled water 200 mg MnSO 4 6 mg H,B0 3 4 mg (NH 4 ) 6 Mo,0 2 4 4 H,O 100 mg FeC1:i 6 H,O I mg ZnSO 4 7 H,O 30 mg CuSO 4 5 H,0 (pH of this so lution adjusted to 2 to avoid precipitation) 25 :::::. 20 C: m C: .S! 15 1 E+00 !:; i ... c 10 Q) (J C: 5 0 0 0 C: Q) ...J gm 0 ....... 1 E-01 o -a; 1--+--+-+=F~=t:=+::'.~=:=~;::i 1,E-02 5 10 15 20 25 30 35 40 45 50 0 0 Time (hours) ---Glucose --+Lysine _._ Cells i Figure 3. Results for cell growth, glucose consumption, and L-lysine production for initial concentrations of 20 g/L of glucose and base case amounts of amino acid supplements. Fall 2003 6-phosphate dehydrogenase method (INFINITY Glucose Reagent, Sigma Scientific) and L-lysine concentration by using the saccharopine dehydrogenase assay (Sigma Scien tific S-9383) The yield of cell growth on glucose consumed (Y Xis ) is calculated as Y Xis = !l.XI !l.S and the data are taken over the exponential and deceleration growth stages. The yield of L-lysine produced on glucose consumed (Y P s) is calcu lated as Y P t s = !l.P/!l.S and the data are taken over the entire fermentation period, but especially during deceleration and stationary stages of cell growth (when L-lysine produc tion occurs). Although different student groups conducted the initiation and sample analyses portions of the experi ment, the group that was not "on duty" was encouraged to drop into the laboratory to observe the activities of the other group, a nd many st udent s did so when their class sched ul es permitted. The major steps in the fermentation procedure are shown in Table 4. Table 5 shows the composition of the defined medium for the fermentation per liter of sol ution. Handout material s for this experiment can be obtained in electronic format (PDF file) by contacting the author at Materials available include an over view of the semester-long experiment plan, an introduction to bioprocess safety issues, and detailed steps in the fermen tation preparation, start up and sample analysis. RESULTS AND DISCUSSION Figure 3 shows a set of results for the cell growth glucose consumption, and product formation for these experiments using Corynebacterium glutamicum. Cell data shows four stages of batch growth: exponential, deceleration, stationary, and declining. Glucose is cons umed fastest during the expo nential and deceleration stages and more slow ly during the stationary and declining stages. L-lysine production is most rapid during the deceleration stage and increases to the greatest amount during the decline stage. This observation is consis tent with the metabolic pathway shown in Figure 2, with lysine production in Corynebacterium glutamicum being greatest after the added amino acids are largely consumed and cell growth ceases, and during the period that concerted feedback inhibition of the L-lysine metabolic pathway is re leased. The students are made aware of the difference be tween growth -a ssociated versus non-growth-associated product formation Figure 3 provides an example of mixed growth-associa ted product formation-that is, intermedi ate between the two types. Re s ults from the remaining experiments (for the most part) showed similar trends for the batch culture data. Table 6 shows the results for all six teams from the se mes ter-long experiment plan. For the 20 g/L initial glucose con centration experiments the maximum cell concentration de creased (from 9.5 to 4.0 g/L) when the initial amino acid con centration was decreased by 50 %, but cell concentration did 265

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not increase (it decreased slightly from 9.5 to 8.5 g/L) as ex pected from the metabolism shown in Figure 2 when the initial amino acid concentration was increased by 50 % The abse nc e of this additional cell growth may be due to the in crease in L-lysine production An increase in the initial amino acid concentration of 50 % did increase the ultimate L-lysine concentration (from 2.09 to 7.5 g/L) whereas a decrease in the initial amino acid concentration did not significantly change the L-lysine concentration. For the 30 g/L initial glucose experiments, again the maxi mum cell concentration decreased (from 8.0 to 3 9 g/L) when the initial amino acid concentration was decreased by 50 %, but (contrary to the 20 g glucose/L results) the ultimate lysine concentration increased (from 2.55 to 10 0 g/L) The results for 30 g glucose/Land 150 % amino acid concentra tion were compromised because the dissolved oxygen probe failed during the run, causing the culture to become anaero bic and changing the cell growth and L-lysine production characteristics. This team proceeded in the same manner as the other teams. They measured cell concentration, plotted a cell growth curve measured glucose consumption and lysine production and calculated all growth and yield parameters The purpose for doing this in this case was to measure effects of anaerobic growth conditions on fermentation performance. The cell growth yield, Y XJS varied from 0.27 to 0.99 for these experiments, with the exception of the last experiment, which became anaerobic, as mentioned previously These values are in the range typically found for aerobic culture on glucose and similar growth substrates .r 6 l The highest value violates a carbon mass balance however which predicts a maximum biomass yield of Y g bio. 72gC O 8 b / xis -. g 10 gsugar 0 5 gC l 80gsugar for typical values for biomass dry weight fraction carbon of 49-51 % Most likely, this erroneous result came from mea surement error on glucose, as the cell mass measurement is more accurately obtained. The L-lysine production yield var ied over the range of 0.14 to 0.60 for the various experiments tion although it did not increase with increasing amino acid concentration. Additional experiments are needed to reduce uncertainty in measured results which may help explain the higher-than-possible biomass yield observed in one of the experiments Enhanced L-lysine production was observed compared to the ba s ecase conditions for two experiments 20 g glucose/L, 150 % amino acid concentration and 30 g glu cose/L 50 % amino acid concentration From the results thus far, however the exact mechanism for this enhanced produc tion is not yet understood Table 6 along with a summary narrative of the results from the entire set of experiments was developed by the instruc tor and disseminated by e-mail attachment at the end of the semester to the students who participated in the fermentation experiments. The narrative contained a summary of key re sults for these fermentation experiments: 1. The supplem e ntal amino acids limit the maximum c ell con c entration that is achieved during fermentation. 2 Cell growth and L-l y sine production appear to occur in separate stages of the fermentation. 3 It is possible to increase L-l y sine concentration by the end of the fermentation by altering initial glucose and amino acid con c entrations. This end-of-semester summary provided the cumulative results needed to address the two most important experiment objectives: testing the hypothesis that maximum cell concen tration in the fermentation is affected by the initial concen tration of supplemented amino acids and identifying whether initial glucose and amino acid concentrations could be al tered to enhance L-lysine production. The Department of Chemical Engineering at Michigan Tech has an assessment program for the evaluation of student learn ing outcomes As required by ABET 2000 Criteria we use these assessments to monitor student proficiency in master ing chemical engineering fundamentals and for improving faculty teaching effectiveness. In this assessment program there are eight major efforts TABLE6 The results from this ex periment plan for cell growth and L-lysine pro duction confirm the student's prior understand ing regarding metabolism for this culture as shown in Figure 2 Maximum cell growth did decline ap proximately in proportion to the decrease in the ini tial amino acid concentraSummary of Student Team Results from the Fermentation Experiment Plan ( Ba se c a se co 11 ce 11trati o 11 s of amin o a c id s [L thr eo 11 i 11 e, L-m e thi o nin e, an d L l e u c in e) a r e g i ve n in Tabl e 5 ) Team] Team2 Team3 Team4 Teams Team6 Initi a l Gluco se Concentration ( g/L ) 20 20 2 0 30 30 30 Initi a l Amino Acid Concentration B as eca s e 1/ 2 Baseca se 150 % Ba s eca s e Baseca s e I /2 B a s eca s e 150 % Basecase Maximum L-lysin e Concentration ( g/L ) 2 09 2 .2 1 7 51 2 55 10.0 0 M ax imum C e ll C o ncentration ( g/L ) 9.5 4 0 8 .5 8.0 3 9 2.1 """ ( I/hr ), M ax Spe c ific Growth Rate 0.38 0.50 0 33 0.43 0.42 0.30 'tct ( hr ) Doubling Time 1.8 2 1.39 2. 09 1.6 1.64 2.31 Y XJS ( g c ells/g glu c ose ) 0.47 0 .33 0 .3 5 0 27 0.99 0 0 2 Y Pts (g L-ly s ine/g g lu c o se) 0 .1 4 0 60 0 .32 0 2 3 0.60 0 266 Chemi c al Engin e ering Edu c ation

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kA ... 51111113._s_u_r_v;_e....:y:.._ ___ __ ) FACTORS INFLUENCING THE SELECTION OF CHEMICAL ENGINEERING AS A CAREER DAVID C. SHALLCROSS University of Melbourne Melbourne, Victoria 3010, Australia A round the world a range of strategies has been pro posed and adopted in an effort to attract more s tu dents into chemical engineering. These strategies range from distributing brochures videos, and interactive CD ROMs to secondary school careers teachers to running ac tivities for either the school students or their mathematics and science teachers. In Australia in the early 1990s, the Joint Victorian Chemi cal Engineering Committee commissioned a short video, This is Chemical Engineering ," that was later distributed to all secondary schoo l careers teachers,P 1 and in 1997, to cel ebrate the 75th anniversary of the Institution of Chemical Engineering, that UK based body prepared and distributed a C D-R OM aimed at secondary school students.f2 1 More re cently the Institution of Chemical Engineers has established an innovative website aimed at attracting secondary school students into the profession (found at )_l3 1 The American Institute of Chemical En gineers has a similar, but less interactive, site at _l 4 J Some universities, such as North Carolina State University run s u mmer engineering camps for school students and their teachers. rsi R ather than targeting the students another strategy involve s wo r king with secondary school math and science teachers to raise the profile of the profession in the secondary school community. The Faculty of Engineering at the University of Me lb o u rne has followed this strategy since 1994. In that year, the faculty b egan running one-day seminars for secondary school math and science teachers to introduce them to engi neering. l 6 7 l More rece n tly, a book (jointly written by a chemi ca l e n gineering academic and four practicing secondary schoo l math teachers) has been published that introduce s teachers and st u dents of years 9 to 11 (ages 15 to 17) to real engi n eering applications of mathematics. l 81 The problems presen t ed to the readers relate to the design of a bulk liquid chemical storage facility, i.e., a tank farm. A s a nother strat egy, the Tufts University Center for Engineering Educational Outreach has been involved in a project pairing gra duate level engineering a nd computer science st udent s with sec ondary school classroom tea c hers. l 91 But which of the se strategies is most effective? While en gineering graduates have been s urveyed to identify the fac tors that led them to study engineering at the undergraduate leve1 r 101 or a t the postgraduate le ve l,U 11 and to identify the main work activities in their professional careers,l 121 no studies have been reported in the literature that investigate the career choices of currently enrolled chemical engineering under graduate s tudent s. This paper reports on the results of a s urvey aimed in part at identifying the mo s t effective strategies. Between October 2000 and October 2001, over 2,500 undergraduate chemical engineering students s tudying at 15 universitie s in seven coun tries were surveyed. The s urvey sample was drawn from all year levels and included students who had left their home country to study. The aims of the two-page survey were three fold: To investigate student perceptions of the chemica l engineering profession To investigate the k ey factors that influ enced the student's decision to be come a c hemi ca l e ngineer Dav i d Sh all c r os s is Associate Professor in the Department of Chemical and Biomolecular En gineering at the University of Melbourne and is Associate Dean (International) of the Faculty of Engineering. The author of three books he is active in the secondary school community de veloping teaching material aimed at raising the profile of the engineering profession for school students. Copyright ChE Division of ASEE 2003 268 Chemical Engineering Education

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TABLE 1 Survey Questions Indicate the extent to which you agree or disagree with these statements: Chemical e n g in ee ring i s a well-paid profe ss ion Chemical e n g in eering offe r s scope to express my c r eativity I am h appy with my c hoi ce of chemica l engineering as a caree r Chemical e n gineers are concerned with sustaining/en h ancing th e qu a lit y of our environment. Chemical e n g in eeri n g is im port ant to th e well-being of soc iety Chemical engineering w ill allow m e t o work and travel internati o nalJ y. Chemical e n g ine er in g i s different t o w h at I th o u g ht it was when I applied to enter the co ur se Chemical e n g in eering is a we ll respected profession. Chemical e n gi n eering is of more va lu e to soc iet y than other fonns of e n g ine er in g. Chemical e n ginee r s need communica tion s kill s of a hi g h s tand ard I would r ecom m end othe r s to s tud y c h emica l engineering. I ex pect that within t e n years of g raduatin g, I will hav e m ove d o ut o f e n gi n ee rin g into a management role I chose chemical engineering because I was in sp ir ed by a member of my fami l y t o st ud y c h emical e n gineering I was in sp ir ed by a "role model" c h e mi ca l engi n ee r ( n ot a fami l y m e mber ) whom I a dmir e. I r ea ll y li ked c h e mi stry at sc ho ol. Chemica l e ngine e ring is invo l ved in a range of diver se indu s trie s. I wanted t o d o e n gi neerin g, but didn 't like/tak e ph ys i cs at sc ho o l. I wanted to do e n gi n eeri n g, but the o th er e n g in eer in g di sc iplin es didn't a ppeal t o m e A c h emistry t eac h er a t my schoo l tri ggered my interest in c hemi ca l e n gi n ee r ing. A caree r s teacher at m y sc h oo l s ugg es ted th a t I co n si der c h e mic al e n g in eeri n g. I wa s in s pired b y v i s iting a terti ary information sess i on/event. I at tend ed a n e n g in ee rin g ca mp/ summer sc h oo l type eve nt. C h emical engineer in g i s a "clea n fonn o f e n g ineerin g. I was told to stu d y chemical e n g in ee rin g by a family member I wi ll b e ab l e to make a positive diff e ren ce in ca rin g for the e n v iron ment. F a ll 2003 To determine w hich of a list of fifteen indu s trial sectors the students most and least want to wo rk in upon co mpletion of their degree Thj s paper examines the key factors that influenced the s tudent s to choose chemical engi n eering as their profe ssio n The result s from the other sec tion s of the survey are published elsew h ere. 11 3 14 1 SU RVEY METHODO L OGY The s urvey con s isted of a si n g les heet two-page form prepared in English German, Ru ss ian and Vietnamese It was only give n to s tudent s currently e nrolled in an under gra duate che mical e n gineeri ng course. The s tudent s were asked to identify their gender, their grade level and w heth er or not the y were studying in their own country. The que tions asked of students are s hown in Table 1 Some thirt y uru vers iti es in a range of countries that included Australia, Canada Ger many New Zealand, Ru ssia, Thailand, the Umted Kingdom, the United States, and Viet nam were contacted and asked to participate in the s urvey. A number of uruversities de clined for a variety of reasons, includjng univer s ity policies against conducting external s urvey s and concerns over the pri vacy rights of their s tudent s. Fifteen of the sixteen uru versities that agreed to parti ci pate are li ste d in Table 2 ( the Uruversity of Hanoi also par ticipated in the survey, completing about 500 forms but they were lost by the Vietnamese po s tal s ervice and were not received for proce ssing.) Table 3 su mmarize s the number of responde nt s b y gen der and national origin. In a ll countries except Vietnam, the Engli s h-language versio n of the s u rvey was u sed. There i s a total of eleven uru versity c hemical engineering department s in Australia and New Zealand, so the four participating in the s urvey provided a statistically significant sa mple of the s tud e nt population from thls region. The s ame i s true for the United KingTABLE2 Summary of Survey Respondents Gender Student Origin Not Not Country Total Male Female Stated Local Foreign Stated Total 2584 1538 10 3 7 9 1 940 459 185 Monash University Australia 98 63 35 0 57 39 2 Un i versity of Melbourne A u s tr a li a 300 150 150 0 230 69 1 University of Queensland Australia 130 90 39 l 114 15 1 McMas t er U n ivers i ty Canada 82 44 38 0 72 7 3 University of Alberta Canada 158 95 63 0 148 3, ,.. 7 Universi t y of Canterbury New Zealand 65 39 25 1 57 2 6 Prince of Songkla University Thailand 87 50 37 0 82 0 5 Imperial College London UK 337 247 90 0 195 138 4 uruverstty ofBirmtnisww Ul\. Tl!! IS3 ;/J2 0 9 ..,,,. ,I, U ni versity of Lou g hborou g h UK 5 3 34 1 9 0 45 6 2 University of Nottingham UK 124 92 32 0 -:81 l6 I University of Surrey UK 65 43 2 1 I 32 31 2 Clemson University USA 42 24 18 0 41 0 I Iowa State U ni ve r sity USA 23 5 140 94 I 213 12 IO Ho Chi Minh City Univ of Tech Vietnam 683 344 334 5 478 67 138 269

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Inspired by family member Inspired by role model Liked chemistry at school Diverse range of industries Didn't like / take physics Didn't like other disciplines Chemistry teacher Careers teacher Tertiary information event ... ~ .. ... -~ -. = I I I I I .. ,. ,, -. '-, .. .. I .. I i i I ~ I D Australia & New Zealand Attended engineering camp Chemical engineering is clean Told t o do chemical engineering Positive difference for environment .. ~ ll'!Canada D United Kingdom l
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take phy s ic s a t sc hool pl aye d n o part in the se l ection of chernical engineering as a career ranged from 58.0 % in Viet nam to 74 .3% in th e UK. In A u stralia, New Zealand C a nada and Vietnam around 15 % of stude nt s were strong l y influ enced by th is factor (see Figure 4). There were di ffere n ces between the ge nder s in a ll co untri es bu t particularly in the UK where ju s t 8.1 % of males were s trongly influ e n ce d by thi s factor while for females it was 23 .0 % More female students th a n males we r e stro n g l y influenced by the fact that the y wanted to s tud y e n gi n eeri n g but th e other discipline s didn t a ppeal to them. In Canada 17.6 % of m a l es and 34 1 % of fe m a le s were strong l y influenced by thi s fac tor, while the corresponding figures for th e U K were 19 .8% and 31.0 % for male s and females, respectively. Of the 70 s tudent s from Australia and N ew Ze a l a nd who were stro n g l y influenced in thi s respect only five indicated th ey were n ot influenced at all. When co upl e d with th e responses to the preceding s tatement re gard in g ph ysics, it is a pp are nt that chemical engineering owes a s i g nj fica nt proportion of its appeal to the fact that of all the major e n gi n ee rin g disciplines, it i s the one in which a so und fo und ation in physics is the lea s t important. Kumagai cond u cted focus gro up meetings wit h over 500 fe m ale undergraduate st udent s a t e i g ht differ ent universitie s 11 31 and fo und that wome n w h o h a d c h ose n chernical or environme nt al engi n eer in g did so b eca u se of negative ex p eriences in physics at secon dar y sc h oo l s. Fig ur e 5 presents the distribution of responses for the five regio n al gro up ings In Australia, New Zeala nd a nd th e U nited Kin g dom, the influence of a c h ernistry teacher was relatively lo w co mpared to a much grea t er influence in Vietnam (see Figure 6 ) Just one-third of a ll Australian and New Zealand s tudent s re spo nd e d that they were influenced to so m e exte nt by their chemistry teachers This is all the more s urpri si n g b eca u se nearly 90 % of these stude nt s said that th ey really liked chem i stry at sc h ool. The se stat i s tic s s u ggest that in a ll co untrie s ot h er than Vietnam sig nifi cant opporturuties exist to work wit h c h ernistry teachers to raise the profil e of chemical engi neering as a pro fess i o n Thjs cou ld b e ac hj eved b y running profe ss ional development sessio n s for c hemi stry t eac her s w h ere c h emical e n gi n eeri n g is s h owcase d or b y d eve loping material for th e seco ndar y sc hool c h e mi s try classroom that i llu strates ho w c h ernical engi n ee r s u se ba s ic co nc e pt s tau g ht in c h ernistry in real-life applicatio n s. Distribution of Responses to Statements 80 70 .; i 60 t 8. 50 I l 1 "' 1, 'o 40 il, 3 0 i:E 20 10 [ n Au st/NZ Ca nada U K US Viet n am IJ S tro ng influ ence 0 So m e influen ce D No in flu ence Figure 2 I was inspired by a member of my fami l y. 80 ,------------~ 70 1 60 8. 50 'o 40 il, ;S 30 20 10 A u st/NZ Ca nada U K US V ietnam 0 S tron g influ e n ce 0 So me influen ce D No influ enct= Fig u re 5. I wa nt ed to do engineer ing, but the other disciplines didn't appeal to me. 272 70 ] 60 8. 50 'o 40 il, E 30 20 10 Au st/NZ C anada UK US Vie tna m Stro n g infl u e n ce Some i n fluence D No in fluenc e Figure 3. I really lik ed chemis try at schoo l ." 80 ,-----------~ 70 160 i 50 "' 'o 40 il, 30 l 20 1 0 Aust/NZ Ca n ada U K US Vie tn am S tr o n g influ e n ce 0 Some in fl uence No i nflu ence Figure 6. A chemistry teacher at m y school triggered m y int erest." A u st/NZ Cana da UK US Vie tnam Strong i nflu e n ce 0 Some i nflu ence No i nflu ence Figure 4 I wanted to do engineering, but didn t l ike / take physics ." 1 00 90 80 I 70 60 50 f 40 JO 20 10 Aust/NZ Canada UK US V i et nam S tr o n g innucnce 12 Some i nflu e n ce D No influ e n ce Figure 7. A c areers teac h er suggested I consider chemica l e n gineering." Ch e mi c al Engineerin g Edu c ation

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Perhaps the most important conclusion that can be drawn from this survey relates to the different extent that an enjoyment of chemistry at school and the role of chemistry teachers influences students to study chemical engineering. School ca r eers teach e r s pla y a r e l ative l y in s i g nificant role in s t ee rin g s tudent s toward chemica l enginee rin g (see Figure 7). In North America 87 % of a ll re s p onde nt s were not influ e n ced a t a ll by them while in th e UK th ey were mor e effec ti ve ha vi n g h a d s ome l eve l of influ e nc e ove r 36 % of the s tu dent s It i s p oss ibl e that m a n y of the North A m e ri ca n r es pon dent s mi s und erstood th e t erm "ca r eers t eac h ers" as thi s i s not a term in co mmon u se th ere. In other parts of the world th e t er m i s well under s t ood. One co nclu s i o n that can be drawn from th ese r es ults i s that the in s titution s a nd profe ss ion a l bodie s in a ll co untri es s hould wo rk mor e c l ose l y with ca reer s teacher s Many ed u ca tional in s titution s put a l o t of effo rt into eve nt s s u c h as uni ve r s it y open days Th e re s ult s pre se nt e d in Figure 1 a nd Table 4 s ho w that in Vietn a m in particular the se eve nt s are e ffective with 19. 8 % of Vietn a m ese r es pondent s bein g s trongly influ e n ced and 34.6 % influ e n ced to so m e degree. At th e o th er ex tr e me only 5.1 % of U.S. s tud e nt s were s tron g ly influ e n ce d by s uch events, compar e d t o 76.4 % who were not influenced at a ll. It s h o uld be n oted, h oweve r th a t th e term u se d in the s ur vey, t er ti a r y in forma ti on sess i o n/ eve nt ," ma y ha ve been mi s interpr ete d s o that re s p on d e nt s did not con s id er it to encompass uni ve r s it y ope n day s a nd th e like On e of the bigge s t differenc es in r es p o n ses b e t wee n ge der s wa s ob se rved for the role of th e e n g in eer in g ca mp/ s um m er sc h oo l-t ype event. Ju s t 20 % of mal e U K s tudent s indi ca t ed th ey were influ e nc ed to so me ex tent b y s uch eve nt s, while nearly 45 % of the female UK s tud e nt s were influenced A s imilar difference in respon ses b etwee n ge nder s was ob se r ved for U S. s tud e nt s. In Au s trali a, Canada and New Ze a land s uch eve nt s h ad ve ry littl e influ ence "C h e mi ca l e n g ine er in g i s a cl ea n fo rm of e n gineeri n g" i s the sec ond of the two s tatement s not directly framed in re spo n se to th e o pening s tat e ment. Th e r es p o n ses indic a t e that thi s p e rcepti o n h as relatively littl e influ e n ce on the s election of c h emica l e n g ineerin g as a career, with le s s than 7 % of students in eac h of the gro upin gs b e in g s trongly influen ce d by thi s factor. Of tho se few who were s tr o n g ly influenced by this perception, howe ver, so m e two-third s were also stro n g ly influ enced by th e perc e ption that as c h em i ca l engineer s they will be a bl e t o make a positive difference in the environment. Very few respondents cho se t o s tud y c h e mi ca l engineer in g because th ey were told to by a family m e mber. The g reat est d eg ree of influenc e occurred a m ong Vi e tnamese respon dent s. Acro ss a ll co untri es fem a l es a dmitted to being mor e s tron g l y influ e nced th a n m a l es. F a ll 2003 The perception that the re s pondents will be able to make a po s iti ve difference in caring for the environment had rela t i vely high ave rage score s across all five groupings In Viet n a m nearl y 40 % of the r es pondent s indicated that they were s trongly influ e nced b y th e p e r cep tion Across most country gro upin gs, females were influenc e d s ignificantly more than mal e students by thi s per ce ption In Australia, high proportion s of s tudents are enrolled in combined de gree pro gra m s in which they can pursue two degrees s imultaneou s ly. The se programs have been described more fully elsewhere. 11 41 No s tati s tic a lly s ignificant difference s in the factors l eading to th e se le c tion of chemical engineer in g were observed betw ee n s tudent s currently enrolled in s in g l e and co mbined d egrees. No s tati s tically s i g nifi ca nt differences were observed be tween st udent s enrolled in different year levels. This is as expec t e d s ince the factors leading to a s tudent s selection of a particul a r course should not vary s ignificantly in the space of five years. CONCLUDING REMARKS The re s ult s of thi s internation a l s urvey clearly s how the factor s that influence a s tudent to s tudy chemical e ngineer in g differ between countries. Some of the se differences may ar i s e due to cultural factor s a nd hi s torical influence s. Viet n a m ese s tudent s are mor e s tron g l y influenced in their choice of c h e mical engineering than s tudents in other countries by their chemistry te ac her s, by tertiary information events, and by the perception that they will be able to make a positive difference to the environment. In the UK the role of careers teachers is much more important than in Australia, New Ze a l a nd or Canada. Gender i ss u es are also import a nt with the responses from male and female student s differin g considerably in several in s tance s. A number of workers in the pa s t h ave studied the gen der i ss ue s related to course se lection a t school. Lewi s 11 71 stated Ir i s a t th e c ru c i a l adales ce nt age w h e n f e mal es s ee k int e rr e l at ed n ess and mal es see k ind e p e nd e n ce that w e ask s tud e nt s to m a k e th e ir subject c h o i ces. Gi rl s w h o c h oose th e ph ys i c al s c i e n ces o r e n g in ee rin g 11 0 1 o nl y hav e 1 0 s h ow a s trong sense of ind e p e nd e n ce bv c h oos in g a 11 0 111radi1ional s ubj ec t th ey ar e also as k e d 1 0 c h oose a se t of m a th a n d sc i e n ce subj ec t s whi c h a r e c hara c t e ri se d as abstra c t l aws di sco nn ec t e d fro m th e ir so c ial and ph ys i c al wo rld s. B oys. 0 11 th e oth e r hand, ca n mak e a dec i s i o n in tun e w ith 1h e ir p ee r gro up and ove rlappin g th e ir n ee d fo r e m o ti o n a l separatio n t hrou g h dis co nn ec t e d abstra c t law s. ---------------Con tinu ed o n pag e 28 1. 273

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.ta .. b_._c_l_a_s_s_r_o_o_m __________ ) PARTICLE TECHNOLOGY DEMONSTRATIONS For The Classroom and Laboratory SIMON M. IVESON, GEORGE V. FRANKS University of Newcastle Callaghan NSW 2308, Australia 0 ne of the joys of teaching a course on powder tech nology is the abundance of quick and simple experi ment s that can be used in lectures to demonstrate the fundamental phenomena being di sc ussed These can be u se d a s breaks part way through a lecture or as an interest arousing introduction to a new topic Demonstrations can be u se d to highlight the often counter-intuitive behavior of pow ders by asking the students to break into groups and try to predict a priori how they expect a given system to behave. The often quite different behavior that they subsequently observe will then challenge them to understand the causes of their mis conceptions and arouse their intere s t in the lecture material. 11 2 l There are more than enough s uch demonstrations to fill a s pot in every lecture of a one-semester introductory course on powder technology Mo s t however are referred to only in passing in references scattered throughout the literaturer e.g .36 l or are passed on by word-of-mouth from one practitioner to another Klinzing f 71 has provided a partial list of such demon st ration s, and a recent CD by Rhodes and Zakharir s i contains video clips of many others Thi s paper seeks to provide a comprehensive compilation of demonstration s to act as a reference for new instructors in particle technology. Demonstration s related to wet-powder sys tems are presented first, followed by dry-powder sys tems. Wet-powder system behavior covered includes single-particle se ttling hindered and lamella settling, sedimentation, the ef fect of surface chemistry on slurry rheology powder wet ting, and wet-granule coalescence Dry-powder system be havior covered includes flow from hoppers, percolation and elutriation segregation, the Brazil-nut effect, surface fric tion, and powder compaction Where pos s ible the source of the idea s presented is acknowledged either by reference to a publication or mention of the person who first told the au thors. Many of these ideas have been around so long, how ever, that it i s difficult to identify their origin, and we apolo gize in the se cases for not acknowledging their original source WE~POWDERSYSTEMS Sing l e -Pa rti cl e Settling ( in-class demonstration) Most courses on fluid-particle interactions begin by exam ining the settling of a single sp herical particle. The effect of fluid viscosity can be demonstrated by using glass marble s in two identical perspex tube s about 40 cm long one filled with water and the other with glycerol ( or any other tran s par ent viscous fluid).r 9 J Start by asking the students in groups to estimate the settling time of each marble. Most will correctly guess that the marble will settle more slowly in the glycerol. When asked why they will probably refer to either glycerol 's greater density or its greater viscosity compared to water If students think that density difference is the cause, then a s imple buoyant force balanc e can be used to calculate how long it would take the marble to fall under the influence of g ravity alone. For p = 1 g/cm 3 p 1 1 = 1 .25 g/cm 3 and wa t er g yce r o p 1 = 2.5 g/cm 3 the increase in fall time in the glycerol due g as s to its greater density would be only 10 % The calculated setS i mon I v eson completed his Bachelor of Chemical Engineering in 1992 and his PhD in 1997 both at the University of Queensland Since then he has been a research fellow and lecturer in the Department of Chemical Engi neering at the University of Newcastle. His re search interests are in the field of particle tech nology, with his focus being on the agglomera tion of fine particles by the addition of liquid binders George F r anks completed his BS in Materials Science and Engineering at MIT in 1985 and his PhD in Materials at the University of California at Santa Barbara in 1997 He has been a senior lecturer in the Chemical Engineering Department at the University of Newcastle since 1999 His research interests include colloidal processing of ceramics mechanical behavior of wet pow der bodies and mineral processing processes such as flocculation Copyrigh t ChE Division of ASEE 2003 274 Chem i c al En g in eer in g Education.

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ticles s maller than about 0.1 micron s, Brownian motion dominate s gravita tional settling so that a stable suspen sion results Use a suitable cationic poly mer to flocculate the s uspen sion so a clear supernatant results. The st udent s should calculate the size of the largest particles in the s ample assum ing that the time for the first noticeable s ediment bed to form correspond s to the time that the largest particle s settle the di s tance from the top of the tube to the bot tom. Using that velocity and Stokes law or Newton' s law, the size of the largest particles can be calculated. They s hould also calculate the size of the smallest par ticles based on the velocity of the s u spen s ion/clear supernatant interface Then pro vide them with the measured particle s ize distributions of the silica samples and ask them to compare their calculated largest and smallest particle sizes with the s ize distribution data provided. The compari s on is surprisingly good. lnterparticle Force Effects on Colloidal Suspension Rheology (laboratory module) Many chemical engineers are not trained to con s ider how the chemical nature of the fluid medium can influence the rheologi cal behavior of a suspe nsion. pH is one of the easiest properties of a slurry to mea sure on-line and it can also dramatically affect s uspen sio n properties. A simple laboratory project that illustrate s thi s ef fect by comparing the slumping behavior of zircon suspensions as pH is varied i s s hown in Table 1. Wetting Behavior of Dry Powders (in-class activity or laboratory module) The wetting behavior of liquids on dry powders is important in applications s uch as mixing pigments into paints and the for mation of agglomerates in agitated granu lator s. If the paint pigments do not wet well, then they will not disperse and in stead form clumps of dry powder with trapped air inside. This detrimentally af fect s the paint quality. In granulation the initial wetting behavior can have a large effect on the final product s ize produced in a granulator. Drop s that penetrate the 276 TABLE 1 Laboratory Module: Interparticle Force Effects on Colloidal Suspension Rheology Few chemjcal e ngine e r s a r e trained to c on s ider how the c hemical n a ture of th e fluid medium ca n influence the rh eo l ogical beh av ior of a s uspen s ion. pH i s o ne o f the eas i es t propertie s of a s lurr y to m eas ure on-line and it ca n also have a dramatic effect. Th e s tud e nt s m eas ure the yield s tr ess o f a 0.40 vo lume fr ac tion of so lid s zircon s u s pen s ion over a range of pH va lue s The average size of th e z i rcon i s about 6 micron s, so th e int e rparticl e s urf ace forces a r e imp ortant in determining the rh eo logi ca l beh avior. Th e d e n s it y of zircon i s 4400 kg/m 3 Th e yield stress can b e m eas ur ed by the s lump m e thod 1111 In thi s m e thod th e p as t e -like s u s p e n sio n i s fi ll e d into a cy linder o n a flat s urf ace and the cylinder i s li fte d off th e s u s pen s ion The r es ultin g s lump height i s m easu r ed (see Figure Al). The y ield s tre ss i s r e l a t e d to the s lump h e ight b y (Al) where -r v i s th e y i e ld s tre ss, pi s th e suspension den s ity, g i s th e gra vitational acceleration (9 .8 ml s 2 ), and H and s are indicated in Figur e A 1. The s tudent s s hould m eas ure the yield stress of the s u s p e n s i o n at pH v a lue s of approximately pH 7, pH 6, pH 5, pH 4 a nd pH 3. Use HCl and N aO H t o a dju s t th e pH b ei ng careful n o t t o overshoot the pH and come back s ince thi s will a dd sal t to th e s u spe n s i o n an d thu s affec t th e interparticle forces a nd thu s th e y i e ld s tr ess Make s u re the s u spension i s we ll mixed The zeta p o tenti a l s o f the powd e r as a fun c tion of pH can b e provided to the st ud e nt s as s ho w n in Figure A2. Ask th em t o co mpar e th e mea s ur e d y ield stress val u es with the zeta potentials. They sho uld comment on th e b e ha v i o r in th e ir r e p o rt Abbreviated Laboratory Report: Figure A3 i s a phot o of th e s lump te s t being perf o rmed b y o n e of th e a uth o r s. Th e den sity of th e s uspen s ion can be calc ul ated as P s u s = cj)pzircon + EP H 20 3 3 3 Psus = 0.4 (4400 kg/ m ) + 0.6 (1000 kg/ m ) = 2360 kg/ m The initi a l cy linder h eig ht ( H ) was 0.103 m. Th e s lump (s) wa s measured w ith a rul e r over a ra n ge of pH values from 3 to 7. The mea s ur e d s lump was u sed to calc ul a t e the y i e ld stress ( u s in g Eq A 1 ). The y i e ld stress i s plotted against pH in Fi g ur e A4. T h e m ax imum y i e ld s tr ess co rrel a te s with the i soe lectri c p o int (w h e r e the ze t a p o tential i s zero). At thi s pH o nl y va n der W aals attrac ti o n i s operating betw ee n the particl es c reatin g a s tron g attrac ti o n a nd thu s a hi g h y i e ld s tr ess Th e y i e ld s tre ss decrea ses as th e pH i s mo ve d away from th e i soe l ectric point. This i s b e c a u se as the charge o n th e s urfa ce of th e parti c l es increases, the electrical d o ubl e l aye r r e pul s i o n also increa sesthu s redu c ing the ma g nitud e of the a ttraction and thu s th e y i e ld s tr ess See Shaw 1121 Hunt e r 1131 or Johnson et al. 1 1 41 for mor e detail s. Figure A1. Dim e n sio n s u se d in c alculation of yie ld st ress from s lump t es t 20 ~ --------10 -10 .40 -50~-c--"-~~~-,~~~ ~~ pH Figure A2. Zeta potentials of z ir co n Figure A3. Slump t es t in progress 600 ~---------500 ,oo 300 200 5 pH Figure A4. Y i e ld s tr esses of z ir con. Chemica l Engineering Educa ti o n

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bed surface quickly are more likely to form individual nu clei-hence controlling the drop size controls the granule size. Slow penetration can lead to pooling of liquid on the powder surface resulting in widely size d initial nuclei and widely sized final product. [ 15 1 The rate of penetration of a liquid into the pores of a pow der bed can be estimated by equating the capillary pressure driving force from the Young-Laplace equation Af' = 2YLv cos0 cap r (3) with the viscous resistance to laminar flow predicted from the Hagen-Poiseuille equation ~p = 8 uI VIS [ 2 (4) to give a form of the Washburn equation di ryLvcos0 u = = ~=--'--dt 41 (5) where u is the liquid velocity, r is the effective pore radius, 'Y Lv is the liquid-vapor surface tension 0 is the so lid-liquid contact angle, 1 is the length of pore filled, and is the liq uid viscosity. The effects of the parameters in Eq. (5) can be demonstrated by asking students to measure the penetration times of drop s of water, honey, and alcohol onto a number of different pow der beds e .g. coarse and fine s ugar, ground pepper and parmesan cheese (see Figure 2). [ 161 The coarse and fine s ugar demonstrate the effect of pore size r. The rate of liquid pen etration is approximately proportional to the particle size. Hence the water penetrates the fine s ugar more s lowly than the coarse sugar. (Note: if an alternative powder that is in soluble in water is available in two different particle sizes, Figure 2. The non-wetting behavior of drops of water (front row) and sugar solution (middle row) co mpared with the rapid wetting of alcohol (back row) on a bed of grated parmesan cheese. Dye added to liquids to enhance visibility. Fa/12003 thi s may be preferable to u si ng s ugar. ) The water and honey demon s trate how increasing viscosity s lows down the rate of penetration The water and alcohol on the cheese and pep per demonstrate the important effect of contact angle 0. Wa ter does not wet or penetrate into either of these two pow ders, but alcohol wets both powders because it has a lower contact angle due to its lower s urface tension as seen by a force balance at the contact line between the three phases ( the Young-Dupre equation) cose = Yvs -YL s YLV (6) where the s ub scri pt s V, S and L refer to the vapor, solid, and liquid pha ses, respectively A more comprehensive predictive model for the penetra tion time of a liquid drop onto a powder surface is presented by Hapgood et al. [ISJ This could form the basis of a labora tory module for s tudent s in more advanced powder technol ogy s ubjects where they would be required to measure the powder s ize and bed porosity. Granulation Coalescence Behavior ( in-class demon strat ion) Wet granulation is performed by s praying a liquid binder onto an agitated powder mas s. There is great interest in being able to predict the rate at which these granules grow as they are agitated. This depend s on how likely it is for granules to coalesce during collisions of varying velocity. In more advanced powder technology subjects students may be introduced to two of the model s available for predict ing wet-granule coalescence The Ennis model considers the collision of two equi-sized elastic spheres of radius r collid ing head-on at a relative speed of 2u. c 1 7 J Each sphere is sur rounded by a layer of fluid of v isco si ty and thickness h The s urface of each s phere has a roughness of h ., which lim its how close they can approach together. The spheres have a coefficient of re s titution e, and a density, p Solving Newton 's second law of motion, it is predicted that coalescence will occur when the viscous Stokes number, St v, is less than some critical viscous Stokes number, st ; where St = 8pm V 9 and (7) This model predicts that reducing the impact speed acts to increase the likelihood of coalescence. This behavior can be demonstrated by dropping a rubber ball from different heights onto a flat surface coated with a layer of honey. Below a thresh old impact velocity (release height), the ball will not rebound Liu et al., [I SJ model colliding granules as elastic-plastic spheres that are initially surface dry, but then have liquid squeezed to the surface during collisions. This model pre dicts that low-velocity collisions are less likely to result in coalescence. This is because very little permanent plastic de formation occurs and hence the area of contact formed be277

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the difficulty of achieving uniform compaction in presses and dies can then be discussed. A variation of this demonstration is to tape a thin sheet of tissue paper over one end of the tube fill the tube with the powder and then ask for a volunteer who thinks he or she is strong enough to push the powder bed through the tissue paper. Segregation During Hopper Flow ( in-class demonstration) Another counter-intuitive behavior of powders is that flow and agitation often cause segregation, rather than mixing. Segregation during discharge of material onto a stockpile or into a hopper is a well-known phenomena. Many workers have used transparent 2D hoppers to demonstrate the her ring-bone" pattern formed due to a combination of percola tion of fine particles and the lower angle of repose of the coarse particles (see Figure 3) .Le .g .. 7 8 1 9 23 l The small particles percolate between the larger ones and this causes the fine ones to become concentrated in the center of the bed. During the periodic avalanches, large particles tend to roll further down the sloped surface of the bed because of their higher inertia and lower angle of repose. During these avalanches, the fine par ticles tend to settle out along the way. This causes the large particles to become concentrated at the base of the pile and also gives rise to the alternate bands of fine and coarse material. A third and less-often demonstrated mechanism of segre gation is the elutriation or fluidization of ultra-fine particles in the upflowing air displaced by the downflowing solids. This can result in the ultra-fine particles settling out after the other particles and forming a layer on top of the heap. With an airtight 2-D hourglass arrangement and correct choice of particles elutriation and percolation segregation phenomena can both be demonstrated simultaneously in the same appa ratus Figure 3 shows the demonstration midway through the Figure 3. Elutriation segregation of-20 micron hollow glass spheres (fluidized bed in the upper chamber] and forma tion in the lower chamber of a segregated "herring-bone pattern of 200-400 micron beach sand (light color] and 50100 micron hematite / iron-ore particles (darker c olor] dur ing discharge from a sealed hopper. Fall 2003 discharge process. The back flow of air has elutriated the ul tra-fines from the material flowing through the opening. The ultra-fines have instead formed a fluidized bed in the upper hopper. As a result they are the last particles to flow from the hopper and hence they deposit on the top surface of the heap and flow down to the base at each edge. Before performing this demonstration, the students should be asked to predict where in the heap they think the different size fractions of material will be preferentially deposited. Then they can compare their predictions with the final result. Dis cuss the difficulties this behavior causes in obtaining repre sentative samples from a poured heap of granular material. Representative samples can only be obtained by sampling at random intervals of time the full cross-section of a powder stream when it is in motion. Vibrational Segregation (in-class demonstration) The well-known Brazil nut" effect can be easily demon strated by covering a steel ball bearing with sand and then v ertically tapping the container. The steel ball will rise to the surface, in spite of its greater density The cause of this phe nomena is not fully understood, but is believed to be linked to the inertia of the object causing it to "punch through" the expanded bed during the upstrokes whereas the packing of the powder prevents it from descending during the downstroke ts, 24 25 J Shinbrot and Muzziol 25 l suggest a variation to this demon stration. If a low-density object is also added to the container, then the behavior of the two objects varies depending on whether the container is shaken horizontally or vertically Under vertical vibrations, the steel ball rises and the low density object sinks Under vigorous horizontal vibrations, the steel ball sinks and the light object rises! The cause of this reversal is unclear, but is probably due to the bed dilating and becoming fluidized during horizontal vibration The class can be asked to predict beforehand which of the two objects will rise or sink when the jar is "shaken (without specifying how). Then the instructor can deliberately shake the jar in a direction that gives a result counter to the majority class opin ion, in order to arouse their interest. Fluidization ( in-class demonstration) Fluidization can be demonstrated in the classroom using a small bed connected to a portable compressor, or if the bed is small enough a willing volunteer s lungs. (7 1 Behavior that can be displayed includes the way the fluidized bed remains level as the bed is tilted and the floating and sinking of ob jects of different density when the bed is fluidized. This can be contrasted with the behavior of these objects in the bed when it is vertically vibrated (see Vibrational segregation above). Bubbling behavior can be demonstrated by filling a long tube most of its length with a Geldart Group A powder. In verting the tube will result in a slug slowly rising up the length of the column. L 61 Again, students could be asked beforehand 2 7 9

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to predict what will happen when the tube of fine powder is inverted. Many may expect the powder to move as a solid plug from one end to the other. Fl o w I mp rove m ent D ue to Powder Agglomeration (in-class demonstration) The dramatic improvement in the flow properties of granu lated versus ungranulated materials can be demonstrated by setting two hoppers side-by-side, one with the raw fine pow der and the other with the same powder after it has been granu lated. When inverted, the raw powder arches and does not flow without tapping whereas the granulated product flows freely (see Figure 4). Small batches of granules for use in this demonstration can easily be prepared at home in a do mestic food processor. OTHER RESOURCES FOR POWDER TECHNOLOGY EDUCATION If you do not have the resources or time to build and per form these demonstrations, many of them are shown as video clips on a CD produced by Rhodes and Zak:hari .1 8 1 An ex panded version of this CD is due out soon that will include interactive problems. The Particle Technology Forum of the American Institute of Chemical Engineers has established a website with many good educational resources for particle technology.r2 61 For ideas on how to construct and structure an introductory course on powder technology, we suggest reading the papers by Chase and Jacob 1 31 and Donnelly and Rajagopalan, 141 and also the textbook by Rhodesc 2 31 that was written specifically with the purpose of being an introductory undergraduate textbook. CONCLUSIONS Instructors of powder technology courses have no excuse for not using visual, hands-on demonstrations to introduce a little more variety and interest to their teaching. Most of the demonstrations mentioned in this paper can be built at little cost using materials readily available in most engineering de partments No expensive or hazardous chemicals are needed, and most of the powders can be found at your local beach or supermarket. Asking students to guess the powder behavior before the demonstration is performed is an effective tool for engaging their interest. REFERENCES I. Felder, R ., "How About a Quick One? Chem. Eng Ed., 26(1) 18 (I 992) 2. McKeachie W. J ., Tea c hin g Tips 8th ed. D.C. Heath & Co., Lexing ton, MA (1986) 3 Cha se, G C ., and K Jacob "Undergraduate Teaching in Solids Pro cessing and Particle Technology : An Academic/Industrial Approach Chem. Eng. Ed., 32 118 (1998) 4 Donnelly A.E ., and R. Rajagopalan Particle Science and Technol ogy: Educational Initiative s at the University of Florida," Chem. Eng. Ed., 32 122 (1998) 5. Fan L.-S ., "Particle Dynamics in Fluidization and Fluid-Particle Sy s 280 Figure 4. Granulated powder (left-hand side) flows easily into lower hopper whereas raw powder arches and does not flow (right-hand side). terns: Part I. Educational Issues ," Chem. Eng. Ed., 34 40 (2000) 6. Fan L.-S. Particl e Dynamics in Fluidization and Fluid-Particle Sys tems: Part 2 Teaching Examp l es," Chem. Eng. Ed., 34 128 (2000) 7. Klinzing, G., "Experime nt s, Demonstrations, Software Packages and Videos for Pneumatic Transport a nd Solid Processing Studies ," Chem Eng. Ed. 32 114 (1998) 8. Rhode s, M ., and A. Zakhari, "Labora tory Demonstrations in Particle Technology ," CD Mona s h University Melbourne, Australia ( 1999 ) 9. Idea introduced to the authors b y Profe ssor Nafis Ahmed formerly of the University of Newcastle, Australia (1998) 10. Idea introduced to the a uthor s by Professor Kevin Galvin University of Newcastle, Australia ( 1 998) 11. Pa s hia s, N., and D.V. Boger "A Fifty-Cent Rheometer for Yield Stress Measurement ," J. Rh eol. 40, 1179 (1996) 12. Shaw, DJ., Intr oduction to Colloid and Surface Chemistry 4th ed., Butterworth Hein e mann (1992) 13. Hunter RJ ., Int roduction to Modern Colloid S c ience Oxford Science Publi cat ion s ( 1992) 14 Johnson, S.B., G.V. Franks PJ. Scales, D .V. B og h er, and T.W. Heal y, Surface-Chemistry-Rheolo gy R e l at ion s hip s in Concentrated Mineral Suspensions," Int J. Miner. Process., 58 267 (2000) 15 Hapgood K.P. J.D Litster, S.T. Biggs, and T. Howe s, "Drop Penetra tion into Porous Powder Bed s," J. Colloid & Int erface Sci., 253, 353 (2002) 16 Idea introduced to th e a uth ors by Dr. Bryan Ennis and Professor Jim Litster during one of their industrial short courses on granulation ( 1999) 17. Ennis BJ. G.l. Tardos and R. Pfeffer "A Micro-Level Based Charac terization of Granulation Phenomena ," Powder Technol. 65 257 ( I 991) 18 Liu L.X., S.M. Iveson J D Litster, and BJ. Ennis, "Coa le scence of Deformable Granules in Wet Granulation Proce sses," AJChE J. 46 529 (20 00 ) 19 Jenilee & Johansen, Westford, Massachusetts 20. Idea mentioned to the authors by Profe sso r Martin Rhodes Monash University, Australia (2000) 21. Reynold s, 0. "Exper iment s Showing Dilatanc y, a Property of Granu lar Materials Po ssib ly Connected with Gravitation ," Pro c. R oy. In st 11 354 (1886) 22. Nagel, S., Shiftin g Sands, New Scientist, 53 Jul y (2000) 23 Rhode s, M., Intr oduction to Particle Technolog y," Wiley (2000) 24. Liffman K ., D Gutteridge, MJ. Rhode s, and G. Metcalfe, The Bra z il Nut Effect," CHEMECA 98, Paper #122 25. Shinbrot T ., and FJ. Muzzio, "No n-Equilibrium P a ttern s in Granular Mixing and Segregation Ph ys i cs Today, 53 25, March (2000) 26. 0 Chemical Engineering Education

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~S=i lecture ) -----------FUTURE DIRECTIONS IN CHE EDUCATION A New Path to Glory This is the 2003 ConocoPhillips Lecture, presented at Oklahoma State University, Stillwater Oklahoma on April 25, 2003 AR.VIND VARMA University of Notre Dame Notre Dame, IN 46556 T he chemical engineering profes s ion is in the midst of great change. Chemical engineers u se d to focus on making large quantities of small, relatively simple molecules (commodity products) With increasing frequency, in the future they will have to make smaller quantities of more complex, possibly biologically active, molecules and nanostructured materials (specialty products). Further, we used to only scale things up; now we must also scale down, as in lab-on-a-chip devices and portable fuel cells. In addi tion developments in science and other engineering disci plines-such as nanoscale synthesis and characterization tech niques molecular biology and information technology-in fluence progress in our field. There is also a continuing need to consider what will be the energy so urces for the future conventional fuels such as oil, gas, and coal, or others such as nuclear biomass, and solar? Finally, growing environmen tal considerations in society make us aware of the long-term and global implications of our manufacturing practices I would like to discuss how all these factors, currently at play, will impact the education of chemical engineers pri marily at the undergraduate level although some remarks will also be made toward graduate education and research opportunities. THE DEVELOPMENT OF CHEMICAL ENGINEERING Before turning toward the future it is instructive to first examine how the discipline of chemical engineering evolved. Fascinating detailed accounts of early developments in the curriculum and the profession have been presented in many so urces 1 61 so I wi11 keep this discussion brief. It is generally agreed that chemical engineering as a dis tinct di sc ipline began in January of 1888 when George E. Davis gave a series of twelve lectures on the subject at the 284 Manchester Technical School in England He had previously coined the term "chemical engineer" in 1880 and promoted it (unsuccessfully) to found a soc iety of chemical engineers. The first four-year undergraduate chemical engineering de gree program was established at MIT by the chemistry pro fessor Lewis Mills Norton in 1888 It was soon followed by those at the University of Pennsylvania (1892), Tulane (1894), Michigan (1898), and others including our own at Notre Dame (1909) Most early curricula had their origin in chem istry departments, although there are examples of some evolv ing from mechanical (e.g., Colorado 1904) and electrical (e.g. Wisconsin 1905) engineering departments as well. The early chemical engineering curricula included an amal gam of courses taken by chemists and mechanical engineers, with those in industrial and applied chemistry in the third and fourth years being unique to the field. The discipline re ceived its first unifying theme with development of the con cept of"unit operations," which is often called the first para digm of chemical engineering. It grew out of the realization that purely physical operations of chemical processing, whether to produce smaller quantities of fine or larger amounts of heavy chemicals, all depended on certain common prin ciples of physics and chemistry. A s first noted by Arthur D Little (1915) in the Chemical Engineering Visiting CommitArvlnd Varma is the Arthur J Schmitt Profes sor of Chemical and Biomolecular Engineer ing and Director of the Center for Molecular l y Engineered Materials at the University of Notre Dame Author or coauthor of more than 230 archival journal research articles and three books, he has received a variety of recogni tion for his teaching and research including the Wilhelm Award of AIChE (1993) and the Chemical Engineering Lectureship Award of ASEE(2000). Copyrig ht C h E Divi s ion of ASEE 2003 Ch e mi c al Engineering Edu c ation

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~b=i classroom ) ------------EXCEPTIONS TO THE LE CHATELIER PRINCIPLE DAVID s. CORTI, ELIAS I. FRANSES Purdue University West Lafayett e, IN 47907-2/00 W hen studying chemical reaction s within a single phase chemical engineers require knowledge of the equilibrium constants. For a given tempera ture and pressure equilibrium compositions may then be cal culated for all relevant reactions. If the temperature, pres s ure or composition of one of the components changes, how ever, the equilibrium position usually shifts. The direction of s uch shifts can be calculated by direct computation of the new equilibrium state. Observations of the direction of shifts in the equilibrium position led to the formulation of a general statement referred to as the Principle of Le Chatelier ,"[ 1 J or sometimes as the "Principle of Le Chatelier and Braun. 12 l Le Chatelier's prin ciple can be stated as follows:[ll In a system at equilibrium, a c han ge in one of the variab l es that determines the equilibrium wi ll shift the equilibrium in the direction counteracting the change in that variable T h e above statement is useful in inferring without direct calculation, the effects of changes in a system initially at equi librium Yet, still not widely known particularly in the chemi cal engineering literature, is that Le Chatelier's principle is not universally valid, and exceptions are known to occur. (See, however, SandlerC 2 l and Tester and ModeW 31 as examples of current chemical engineering textbook s that highlight the limi tations of the above statements. Exceptions to Le Chatelier 's principle appear to be more widely known in the physical chemistry literature and have been di sc ussed for some time. See, for example, de HeerC 4 l and Liu, et al.,(5 1 for an historical account of Le Chatelier's principle.) Consider, for example, the ammonia sy nthesis reaction N 2 +3H 2 <=>2NH 3 in which equilibrium has been established at a given ternperature, T and pre ss ure P Le Chatelier's principle predicts that the reaction will shift to the right (i.e., more ammonia will be produced ) upon the addition of more nitrogen to the reaction vessel. If the initial mole fraction of nitrogen ex ceeds 0.5 and the given T and Pare held fixed, however the reaction instead proceeds to the left producing more nitro gen, as predicted from rigorous equilibrium constant calcu lations (the value of 0.5, as shown later i s calculated assum ing ideal gas behavior ). This s hift to the left is a clear excep tion to the principle of Le Chatelier, which has not been rig oro u sly proven [ 4 l Proofs of this unexpected shift have been given before [ 4 6 l Most chemical engineering texts do not provide a proof, ex cept, for example Tester and Modell [ 3 J which does provide a detai l ed proof. The most widely referenced and reproduced proof is by Katz [ 6 l ( the procedure followed in Liu et al.,l 5 l i s nearly the s ame as the approach by Katz, although the auDavid 5 Cort i is Assistant Professor of Chemi cal E ngineering at Purdue University. His re search interests include molecu l ar thermody namics of liquids (both stable and metastab l e) glasses, and complex fluids droplet conden sation and bubble nucleation and the devel opme n t of molec u lar simulation algorithms. H e teac h es courses on Thermodynamics and Sta tistical Mecha n ics. Elias I. Fr anses is Professor of Chemical Engi neering at Purdue University. His research in terests include adsorption eq u ilibria and dynam ics of surfactants and proteins at air / water inter faces, with applications to lung surfactants a n d the surface chemistry a n d physics of adsorbe n ts at l iq u id / solid interfaces for bioseparatio n s. He teaches courses on Co ll oidal a n d l nterfac i a l P h e n omena Thermodyna m ics and C h emica l R eaction Engineering Copyright ChE Di vision of ASEE 2003 290 Chemical E n gineering Education

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To add re s s th e tec hnical and educational issues of L e Chatelier s principle we therefore pr e sent i n th i s paper a ne w and conceptuall y more straightforward anal y sis of the direction of the equilibrium shift for the ammonia s y nthesis reaction as an example. thors were apparently unaware of Katz) Thjs proof makes use of a "reaction quotient that has the same functional form as the ratio of mole fractions at equilibrium and is applicable whether or not equilibrium has been established The value of trus reaction quotient, defined in Eq. (3) varies if a change occurs, b u t must equal the equilibrium constant when the sys tem ret u rns to an equilibrium state. The direction that the re action quotient takes to restore itself to the equilibrium value determines the direction of reaction for the given change. The use of a reaction quotient can be confusing to students, partic u larly to students exposed to reaction equilibria for the first time. To address the technical and educational issues of Le Chatelier's principle we therefore present in this paper a new and conceptually more straightforward analysis of the direction of the equilibrium shift for the ammonia synthesis reaction as an example. Our approach is however, more gen eral. In contrast to the other methods, changes at constant T a n d P are now considered in which the value of the reaction quotient is strictly held fixed and equal to the equiljbrium constant. Hence the analysis makes no use of a separately defined reaction quotient (that is applicable whether equilib rium is or is not established) and s hould be easier for stu dents to understand The analysis also involves finite, as well as infinitesimal, changes which can be the basis of future experimental tests that may demonstrate more viv idly t h e key thermodynamic laws (see del Pino, et al., 171 for an example of a simple experiment concerning shifts of chemica l equilibrium) Le C h atelier's princip l e can be reformulated in a more gen eral way that becomes universally valid, l 4 51 although it bears little resemblance to the statement given earlier. For peda gogical reasons, we briefly discu s s trus new general state ment in the last section of this paper. An excellent overview and proof, of this new general statement is given by de Heer 141 It is, however, only valid for infinitesimal changes from the initial equilibrium state .l5 1 In this paper, we also consider the ammonia synthesis reaction for the case of adding nitrogen in fini t e amounts (Liu, et al.,' 51 considered finite additions as well, but the present analysis provides a more straightfor ward and quantitative discussion) The value of 0.5 for the mole fraction of nitrogen, above which the reaction proceeds to the left wrule below the reaction proceeds to the right, is shown to be true for infinitesimal additions of njtrogen. For finite changes no universally valid statement on the direction i n which the reaction shlfts can be formulated, a n d thus each case must be considered individually. In such cases Fall 2003 instructors should advise ignoring the reformulated Le ChateUer s principle and instead should calculate, in general, the shift in the equilibrium state directly from the relatio n s of chemical equilibrium. AMMONIA SYNTHESIS REACTION Exception to the Principle of Le Chatelier Let us consider the ammonia synthesis reactio n and ass u me for simplicity that the components comprise an i d eal-gas mix ture Analyses for nonideal mixtures, although possible, h ave not been reported. Let species l represent nitrogen species 2 hydrogen and species 3 ammonia. The chemical potential of each species i i, in the ideal-gas mixture is given byf 81 (I) where f i (T) is the chemical potential of pure componen t i, as an ideal gas at the temperature T (and a fixed reference pres sure P 0 ) R is the ideal gas constant, Pis the system press u re, and y i is the mole fraction of species i. At equilibri u m, the chemical potentials of the components participating in th e chemical reaction must satisfy l 31 I vii =0 (2) where vi is the stoichlometrically balanced coefficie n t of species i in the reaction ( v 1 = -1, v 2 = -3, v 3 = 2). Upon s u stituting Eq (1) into Eq (2), rearrangement yields 2 = P 2 K(T) = Kp(T P) Y1Y2 (3) where K(T) is the equilibrium constant and ~(T,P) is a fu n tion ofT and P. The ratio of mole fractions on the far left side of Eq (3) is the "reaction quotient." Now, let the system be at equilibrium at a give n T and P. At the initial equilibrium state, there are n 1 n2, and n 3 moles of each species with mole fractions yj', y~, a n d y 3 satisfy ing Eq. (3) Next we consider the addition of mo l es of nitrogen (1) while keeping T and P constant. As t h e sys t em re-equilibrates the reaction proceeds so that the final mole numbers of each species will be given by l 8 1 n2 = n~ 31; Il 3 = Il3 +21; (4) 291

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where s is the extent of reaction starti ng from the above initial equilibrium state; s is defined to be positive if the reaction proceeds to the right, i.e., nitrogen and hydro gen are consumed while ammonia is produced, and nega tive if the reaction proceeds to the left. The above rela tions imply that the final mole fractions are given by \ n f+b-S yf+b'-s' YI= n +b-2S = l+b'-2s' Y2 3s' Y2 = l+b'-2s' Y3 + 2S' Y 3 -l+b'-2s' (5) where n=nf+n 2 +n 3 b 1 =bln, and s'=sln; b' and s' are dimensionless quantities Since T and Pare held constant, Eq (3) implies that (6) Equation 6 is valid for all values of t,,.' and can be used to determine the value of s' for a given choice of b'. The sig n of s', however determines the direction in which the reaction shifts, and its value determines the extent of the reaction triggered by the addition of nitrogen. First we focus on how the extent of the reaction varies when an infinitesimal amount of nitrogen, i.e., t,,.' 0 is added. One can solve Eq. (6) for various values of t,,.' and then determine the sign of s' as t,,.' 0. But since s' 0 as t,,.' 0, we instead determine ds' I dt,,.' ana lytically for b' 0. To proceed and for ease of further manipulations we first rewrite Eq. (6) as (y3+2s'}2(1+t,,.'-2s') 2 yf(Y2)3 = (Y3 )2 (yf +t,,.' -s')(yz -3s') 3 (7) We now differentiate both sides ofEq. (7) with respect to b' for constant yf, y 2 and y 3 letting 1'I = ds' I db'= dS /db. We then take the limit for b' 0, with s' 0 as well, and finally solve for ri. After a few lines of algebra, we obtain dS Y3Y2(1-2y?) ri= dt,,. = 4yfyz(l-y3)+Y2Y3+9yfy3 (8) Since the denominator in Eq (8) is always positive, the sign of ri is given by the sign of ( 12yf ). Therefore, for infinitesimal additions of nitrogen, we conclude that 292 0 1 when Y1 <-, ri>0 : 2 reaction proceeds to the right consistently with th e Le Chatelier Prin c iple o l when y 1 > ri < 0: 2 reaction proceeds to the left, against the Le Chatelier Principle 0 1 when y 1 = ri = 0: 2 no reaction takes place, against the Le Chatelier Principle (9a) (9b) (9c) Hence the exception to Le Chatelier's principle occurs when the initial equilibrium mole fraction of nitrogen is equal to or ex ceeds 0.5 and is independent of the mole fractions of the other species or of the values of the temperature and pressure. Why the reaction reverses direction can be understood qualita tively[11 by considering the form of the reaction quotient in Eq. (3). The addition of nitrogen increases the mole fraction of nitro gen, y 1 but also causes a decrease in y 2 (hydrogen) and y 3 (am monia). Since y 2 is cubed in the denominator of the reaction quo tient, the decrea se in y 2 may have a more significant effect on the reaction quotient than the increase in y 1 or decrease in y 3 When the mole fraction of nitrogen is s mall the change in y I upon addi tion of some nitrogen yields a proportionally larger change in y 1 as compared to the decreases in y 2 and y 3 To compensate, and so ensuring that the reaction quotient must remain equal to Kr(T,P), the reaction proceeds to the right, reducing some of the added nitrogen and producing more ammonia. When the mole fraction of nitrogen is large so that the mole fraction of hydrogen is small, the proportional decrease in y 2 is greater than the increase in y 1 The decrease in y 2 is magnified by the appearance of y /, and so the reaction proceeds to the left generating more nitrogen and -0.001 -0 002 -0.003 -0.004 -0.005 -0.006 -+--.--,--,--,-......,..........,..........,..........,....-,--,---,---.---.--.--.--,,-,.--,--,--, a a 0 1 0 2 o.3 o.4 o 5 o.6 0 1 a a o.9 1 0 t,,.' Figure 1. Extent of reaction versus the amount of nitrogen added for y 1 = 0.5. Chemical Engineering Education

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The purpose of this experiment consists of determining the mixing time with two impellers providing different flow patterns. The mixing time defined as the time needed to reach a specified degree of homogeneity, can be determined b y various techniques tion of the impeller. As can be seen in Figure 1, a standard mixing configuration is used as a starting point with the im peller placed on the vesse l centerli n e at 1/3 of the liquid height. The agitation torque is measured by a non-contact type torquemeter(range between 0.1 and 1.42 N.m) fitted between the motor and the agitation shaft. Newtonian fluids consist of aqueous s olutions of corn sy rup having a viscosity of 1 5 Pa.s, while aqueous sol ution s of carboxy methyl cell ulo se (CMC) are employed as non-New tonian fluids The mixing times are measured w ith a colored tracer consisting of Methylene Blue diluted in both sol ution s. The two so lution s, together with the tracer, are prepared prior to the experiments and allowed to settle at least 24 hours in order to eliminate air bubble s. The rheological properties of the fluids are determined by a Bohlin Visco 88V visco meter using a con centric cylinder configu ration. Rheologic a l mea s urement s and the ex periments are performed at room temperature (aro und 24 C) The cost of the labora tory mixer and the so lu tions u sed for the experi ments is about $5,000 and$20, respectively. MOTOR TORQUEMETER LIQUID LEVEL TRANSPARENT VESSEL I T H N p ppN 3 D5 a nd pND 2 R e= -(2) where Pi s the power in Watts, pis the fluid d ensity in kg/m 3 D is th e impeller diameter in m and i s the dynamic v i scos ity in P a s. The l aminar and transition regimes must be identified after plotting Np as a function of Re on a log log scale;c 3 4 1 the constant K for each impeller can be calculate d b y p KP= Np R e (3) Mixing Times The purpose of thi s experiment consists of determining the mixing time with two im peller s providing differ Hff = 1 orr = 113 C=D RUSHTON TURBINE PROPELLER ent flow patterns. The mixing time defined as the time ne e ded to reach a s pecified de g re e of ho mogeneity, can be deter mined by vario u s technique s based on the mea s urements of concentra tion, density elect ric al cond u ctivity, tempera ture, or by colorimetry optical methods thermal method, etc The colorim EXPERIMENTS Figure 1. Experimental setup. etry technique is a quali tative method to deterPower Consumption Thi s experiment consists of d etermining the power con s umption for both radialand axial-flow impellers with New tonian fluids For that purpose the fluid under study must be added to the H level of the tank (see Figure 1) and then the mixer s peed is set to zero rpm and the torquemeter to zero N.m The impeller speed is gradually c han ged from 15 to 700 rpm a nd the torque readin g for eac h s peed is used to calc ul ate the power cons umpt ion by means of P = 2 1trNT (1) where r is the impeller radius in m, N is the rotational spee d in rp s, and Tis the torque in N m The power co n s umption is correlated to the impeller spee d by means of the dimen sionless power number (Np) and the Reynold s number ( R e), defined by Fall 2003 mine the mixing time by adding a s mall amount of a color tracer to the fluid that is being mixed The overall fluid color will change, and mixing time corresponds to the time w h en the tracer is judged to have com pletel y di s per sed within the fluid. The detailed pro cedure for measuring the mixing time is 1. Use the config ur atio n show n in Figure 1 with the Ru shto n turbine 2. Add fluid (aqueous com sy rup or aqueous CMC) up to the H l eve l. 3. Prepare the color tracer so luti on by dissolving 10 mL of Methylene Blue in 100 mL of fluid to be stu died 4. With the mixer at rest, ad d 15 mL of the color tracer sol ution to the t a nk containing the fluid 5 Set impeller speed at 100 rpm and switc h the mixer on. 6. Measure the mixing time at this s pe ed 7. Repeat Steps 3 to 5, u sing different s peeds. The speed range 297

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for this experiment is from 100 rpm to 600 rpm with increments of 100 rpm 8 Repeat the experiment for the marine propeller. As proposed by Moo-Young et a1., r 5 i mixing time can be corre l ated with the impeller speed by means of a dimension less mixing time defined as (4) where tm is the mixing time in s, N is the impeller speed in rps, Re is the Reynolds number and a and 13 are adjustable parameters She ar R ate of non Newtonian Fluids The purpose of this experiment is to find out the effective shear rate for non-Newtonian fluids in the vicinity of the im peller by the Metzner-Otto correlation.( 61 They developed a general relationship to correlate the impeller speed and the shear rate of a non-Newtonian fluid in the laminar regime Based on the single knowledge of the power curve for Newtonian fluids this relationship can be used to interpret and correlate power draw data for non-Newtonian fluids. This method assumes that there exists an average mixer shear rate developed in the vicinity of the impeller, which corresponds to the power consumption. This shear rate is directly propor tional to the impeller speed through YA= k s N (5) where k is the mixer shear rate constant. s The average shear rate y A, defines an apparent viscosity which is used in the definition of the Reynolds number for power consumption prediction for non-Newtonian fluids. The apparent viscosity is determined from viscometric measure ments at the appropriate shear rate and used directly for plot ting the power curve. The determination of the average shear rate, y A, involves the following steps (see Figure 2): p P ---< -' I I ,I.. I I I I I I N' log Np N Re' 1. For a given impeller speed a power number (Np ) is calculated from the P vs. N for non-Newtonian fluids. 2. Using this power number Np ', a Reynolds number (Re ) is obtained from the power number-Reynolds number corre lation for Newtonian fluids 3. Finally the average shear rate can be determined from the viscometric data and, using the impeller speed, the mixer shear rate constant, k can be calculated from Eq. (5). The procedure for this experiment consists of the following manipulations: 1. Mount the Ru s hton turbine at the end of the shaft and locate it in the center of the vessel, as in the fust experiment. 2 Add the aqueous CMC to the H level. 3. Gradually change the speed record the torque for each speed, and calculate the impeller power con sumption from Eq. (1). 4. Plot the power consumption (P) vs. impeller speed (N) 5 By using the viscometer with the same fluid, record the apparent viscosity for each shear rate and plot the A vs. YA curve 6. Following the steps mentioned above, determine the average shear and calculate the mixer shear rate constant k from the Metzner-Otto correlation (Eq. 5). 7. Repeat the experiment using the propeller FULL REPORT AND ORAL PRESENTATION As mentioned before, students are asked to prepare a pre liminary report after finishing the experimental work. A week later they must deliver a full report or give an oral presenta tion. The full reports must contain : --------log Re YA y 211N P Np'=--, D 2 N'p A-~ k = 'YA 298 D 5 (N Jp s N (a) (b) (c) Figure 2. Determination of the shear rate constant k : a) non-Newtonian pow e r consump tion b) Newtonian power consumption c) non-Newtonian viscometry. Ch e mi c al En g ine e rin g Edu c ation

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An abstract, including the objectives the methodology used to achieve the objectives, and result s and conclu sions in relation to the proposed objective s The objectives must be clearly stated. A theoretical perspective different from the one presented in the laboratory manual. Main results for discussion and anal y sis including graphs and tables. An example of a set of experimental data obtained by students is shown in Figures 3 and 4 The power curves in terms of the dimensionless power number (Np) as a function of the Reynolds number ( Re) are shown in Figure 3. After performing linear regres sion with the experimental data a good correlation can be observed between Np and Re. It must be noted that a slope of -1 should be obtained between Np and Recor responding to the laminar region. An error of 5 .4 7 % and 0.53% in the slope is obtained for the Rushton turbine 10 .-----~-~-~-~~-~-,--_-_-_-__ -_-_-_::-_::-_-_-_-~--, Np= 32 705Re 1 5 47 R = 0 9948 --+-Rushton turbine --0-Propeller Q. z Np= 12.649Re -0 9947 R 2 = 0 9997 R e 10 Fig ur e 3. Experimental power c urves for th e Rushton turbine and the propeller. 3000 ---+Rushton turbine 2500 N 1m = 3x10 6 Re -4 1303 --0Propeller R 2 = 0 9939 2000 1500 z 1000 500 4 N t,,, = 6x10 3 Re R 2 = 0.997 6 10 12 14 Re F i g ur e 4. Dimensionless mixing time as a function of the Reynolds number for Newtonian fluids. Fal/ 2003 and the propeller, respectively. Figure 4 shows t h e di mensionless mixing time as a function of the Reynolds number for both impellers with a Newtonian fluid. From the linear regression results it can be observed that the larger coefficients ex and [3 correspond to the Rushton turbine which is in good agreement with the res u lts re ported in the literature .1 2 1 Interpretation anal y sis, and discussion. These elements should be presented in great detail in a quantitative way, including the experimental error encountered. In the case of the experiments of power consumption and shear rate of non-Newtonian fluids, the torque should be meas u red at least three times in order to determine the experimen tal error. Re c ommendations. This feature is used as feedback chan nel, so the students should suggest another experiment to perform or modifications to the experimental set u p in order to improve the experiments Appendix. All the raw data must be presented so the re viewer can verify if the data were well processed. On the other hand, the oral presentation is evaluated in terms of the form and the content. The introduction and objectives, presentation structure illustrations, conclusions and ques tions are all considered in the form. The subject knowledge, theoretical basis and references and analysis capability are considered as parts of the presentation. CONCLUSION Because mixing is a unit operation involved in many in dustrial applications, a good understanding of this operat i on is central for a successful process. The proposed experimen t s give the students a general introduction to the fluid mechan ics of mixing with Newtonian and non-Newtonian fl u i d s, using impellers that provide different types of flow. In fl u id mixing technology as in other process design areas, dimen sionless groups are used to correlate scale-up parameters. For that reason, experimental results must be presented in terms of these dimensionless numbers to be useful to the process designers The proposed mixing experiments enable e n gi neering students to gain excellent insight into the use of dimensionless groups. REFERENCES 1. Coul s on, J.M J F. Richard s on J.R. Backhurst and J.H. Harker Chemi c al En g in ee rin g, Vol. 1 Pergamon Pre ss, p. 225 (1990) 2. Hamb y, N ., M F. Edward s, and A W. Nienow Mixing in th e Process Indu s tri e s 2nd e d. Butterworth Heinemann (1992 ) 3. Rushton J H ., The Use of Pilot Plant Mixing data ," Chem. En g Prog. 47 No. 9 p. 485 ( 1951 ) 4. Ru s hton, J.H., E W. Costich and H.J. Everett, Power Characteristics o f Mixing Impeller s, Part l Chem. Eng. Prog ., 46 No 8. p 395 (1950) 5. Moo-Young, M. K. Tichar and F.A.L. Dullien "The Blending Effi ciencies of Some Impellers in Batch Mixing," AJChE J 5 4 139 (1976) 6. Metzner A.B. and R.E. Otto Agitation of Non-Newtonian Fluids A!ChE J 3( 1 ) 3 (1957) 0 299

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l!j9:::j classroom ) -----iii-.------DEVELOPMENT AND IMPLEME NTATION OF AN EDUCATIONAL SIMU LATO R : GLUCOSIM FETANET CEYLAN ERZEN' GOLNUR BIROL, ** ALI QINAR Illinois Institute of Technolog y Chicago, IL 60616 T he quality of student learning can be enhanced sig nificantly by simulation of complex systems with u ser friendly software. Complex real-world problems and solutions can be introduced to s tudent s by u si ng sim ulation sys tems to conduct virtual experiments These virtual experi ments are especially useful when their real-world analogs are expensive and/or dangerous Simulation involves the use of the model of a system to observe the system's response to changes in properties and inputs to the system. Simulations can introduce realistic prob lem situations and support a particularly active form oflearn ing by letting students manipulate the conditions of the sys tem and observe the consequences of those variations. The availability of a reliable and realistic mathematical model is essential to conduct simulations and understand the be havior of the system. We have developed a dynamic simulator for glucose-insu lin interactions in a healthy person and a Type-1 diabetic pa tient. The aims of this public domain simulator are to provide assistance to bioengineering students in learning glucose-in sulin interactions in the human body to offer a tool for engi neeri n g students in learning system dynamics and to pro vide an illustrative tool to diabetic patient s. The simulator cannot be used for adjusting a patient 's insulin dosage regu lation in real life but may be helpful for patient education. Both MATLAB-based-stand-alone and web-based graphi cal user interfaces (GUI) are software designs that yield in teractive systems. Despite many similarities between the two designs, there are also many differences. Simulators with web based GUis are more accessible over the internet, but stand alone software can also be distributed widely while giving Phann Tech In c /4048 P e1 r onel/a Dr. Liberlyville, IL 60048 ** Nor/hwes/ern Uiversity, Biom ed i cal Engg ., Evanston IL 60208 the developer/de sig ner an opportunity to keep track of th e users Furthermore, si nce the s tand-alone GUi s are in a d fined frame the de signer controls where the u ser goes when browsin g among the links, while in web-based GUi s, the user ha s all the control and in many typical situations there is a high pos si bility that he or s h e may branch out to an arbitrary website while brow sing. Modeling glucose-insulin interactions requires an und er s tanding of the physiological and metabolic processes that determine observable beh avior. 111 Mathematical models de scri bing carbohydrate metabolism are available in the litera ture. f2-4J We have u sed and extended two mathematical mod els ba se d on pharmacokineti c diagrams of glucose and insu lin in the human body. Mass balances for both glucose and insulin resulted in a set of ordinary differential eq uation s, and the models are implemented in a computer pro g ram writ ten in MATLAB 5.3. The mathematical details of these mod els are available elsewhere. 11 51 ODE23 (low-order Runge Kutta routine ) is used for so lving differential equations. The model s are then integrated with a GUI that is re s ponsible for presenting information to the u ser in a clear and friendly way. Fetanet Ceylan Erzen received a BS degree in chemical engineering from the Middle East Technical University (1999) and an MS degree from Illinois Institute of Technology (2000). Her thesis studies included model ing and simulation of glucose-insulin interaction in the human bod y and graphical user interface development G ii lnu r B i ro / received BSc MSc and PhD degrees in chemical engi neering from Bogazici University in 1990 1992 and 1997 respectively. Her current research interests include glucose biosensors investigation of retinal vascular occlusion and the relationships between oxidative and glycolytic metabolism in the retina on animal models. A ll C ina r received a BS degree in chemical engineering from Robert Col lege Turkey(1970) and MEng (1973) and PhD ( 1976) degrees from Texas A&M University. His teaching and research interests are process model ing and control statistical process monitoring and fault diagnosis and use of knowledge-based systems for real-time process supervision and control. C opyrig ht C hE Div1SJ o n o f ASEE 2003 300 Chemica l Engineering Edu ca tion

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SIMULATOR [] System Availability GLUCOSIM was originally developed in MATLAB 5.3.1 on a PC platform. It requires three MB of hard di sk s pace. A demonstration of the package is available on the web at . The sim ulator can be obtained by writing to Ali <;:inar (e-mail at cinar@iit.edu). [] User Interface Design A computer is limited not b y its power to compute but rather by its power to communicate with its human users. f 61 The main requirement for wide acceptance and use by the stuSTART l Tutorial & Information Files Dem( ~imulator filI67, I ~ User Inputs Simulation Models Norma l Man Diabetes Patient OGTT 1 Output Figure 1. Structure of the simu lator. TABLE 1 Program Features Large Database Related internet sites Diabetes dictionary Carbohydrate va lu es Over 100 references Operational Modes Demo Sim ul ator Experimental Modes Oral gl u cose tolerance test Healthy person ypeI diabetic p atient Inputs Car bohyd rate co nt ent Time of meal and injection Insulin type and dose B ody we i ght Duration of exe r cise and sim ul atio n Save Options and Outputs Continuous graphical display Saving in ASCII and graphic modes Recall/display profiles from previous runs Fall 2003 dents is an easy-to-learn, easy-to-use efficient interface.f7 1 A simple and natural dialogue for modem computer systems with GUis can be achieved by a good graphic designf 81 and consistent screen layout s. Several guidelines are followed for this purpose while designing the GUI in this work: Consistency of the u ser interface. Similar objects and colors are u se d to perform s imilar functions throughout the sim ul ator to facilitate recognition. If users know that the same command or the s ame action will always have the same effect, they will feel more confident in using the system. 1 9 1 Also, the design is limited to a small number of consistently applied colors. Ease of navigation. The user is able to navigate without getting lost or worrying about causing harm Importanc e of h el p and documentation is kept in mind If stude nt s need to refer to documentation for h elp or for background information, there is sufficient and compre hen sive, but brief documentation throughout the simulator. Navigation is also available between the documentation; for example, u se rs can return to the tutorial while reading a help file. Dialog boxes have a quit and/or back button. This gives user s a feeling of being in control since the user rather than the computer decide s where to go, what to see, and when to lea ve The structure of the s imulator is illustrated in Figure 1 and its capabilities are outlined in Table 1. There are three cat egories of windows in the simulator: information windows transition windows, and input/output windows. A detailed de sc ription of these windows is presented later in this paper. [] Model Equations The pharmacokinetic models for glucose and insulin are based on mass balance equations on various physiological compartments such as heart, lungs and arteries (H), nervous system (NS) (for glucose), or subcutaneous tissue (SC) (for insulin), liver (L), pancreas (PN), gastrointestinal tract (GT), kidney ( K) and periphery (P R ) (skeletal muscle and adipose tissue) For example, the circulating blood insulin concentra tion, l 8 is described by VB dIB =Qsc(Isc -IB) +QK(IK-IB)+ dt QpR(IPR -1B)+QLIL -(QHA +QpN +QGT)IB (1) where Q denotes the blood-flow rate (di/min), V denotes the volume (di), t denotes time (min), and I denotes the insulin concentration (mg/dl). Subscripts B and HA denote blood and hepatic artery, respectively. The mass balance in su bcutane ous tissue is Ysc disc = Qsc(IB -Isc) + r1A dt (2) w here r denotes a metabolic source or sink rate, and the s ub script IA denotes insulin absorption The detailed model con sists of a system of ordinary differential equations represent301

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ing mas s balance equation s in all c ompartment s. Th e o v e ra ll model i s derived by a s sumin g th a t th e m ass balanc es in each tis s ue are in qua s is teady s tate (i e., dl/dt = dG/dt = 0 ) The resulting algebraic equation s for g lucose and in sulin concentrations are combined into the glucose and insulin balance s in the blood yielding a n overall model with two differential equation s. Two model s of insulin relea s e were taken from the literatur e, modified and u s ed in the c urrent simulator for he a lth y hu mans The first one is based on i s let in s ulin s ecretion model developed by Nomura e t aL. ,lJOJ for rat i s l e t s, and the se c ond one is ba s ed on the pancreatic in s ulin rele as e model devel oped by Car s on and Cramp. 1 1 1 1 [] Features A MATLAB based user-friendly GUI wa s designed and integrated with the MATLAB code written for the mathemati cal model. The interaction of the user with the s oftwar e ha s been kept a s simple as po ss ible. Menu s, button s, and s lider s are widely u s ed as controlling element s. Value s are di s pl a yed graphically with a save option. Help windows through out the program are available and the u s er can quit the pro gram at any time Furthermore, the s imulation can be s topped at any time by using the "s top bu t ton on the simul a tion progress bar. The main window ( s ee Figure 2 ) i s de s igned to familiarize the user with the environment. There are three button s About ," Tutorial ," and B a ck ground Information. The About button g i ves a bri e f i troduction to the program ; Tutorial provide s inform a tion about the model used along with a short literature review ; and the Background Information button i s linked to an other window where it i s po ss ible to s earch for the definition of a word related to diabete s from the datab ase c reated ( Fi g ure 3 ) to view the relevant web link s ( Figure 4 ) o r to g e t information about the references used on the development of both the mathematical model and the s imulator. Figure 2. Main wi ndo w 3 0 2 By u s in g the NEXT button placed in the bottom left hand s ide of th e main window (se e Fi g ure 2 ), the u s er can c ho os e b e tween DEMO and SIMULATOR mode s. The purpo s e of the DEMO which con s i s t s of s nap s hot s, i s to give the u s er a general idea of the simulator 's capabilitie s and a preview of how the s imulator function s. By s electing the SIMULATOR mod e, th e u s er goe s from the information mode to an experiment mode. Her e, there are three options for the virtual experiment s. The fir s t option perform s the Oral Gluco s e Toleranc e Te s t ( OGTT ), the s econd and third opI 1.L 11111 ', IM ll 1 dnm.1 1 H~........ ....I ... .:J Hom o glo b n AIC (H bA l(,j fin '1111, ,, r, t !, 11 ;!f"l 11,,,' jl1l't i11,l!1 i/11 tJO, 'IJ j1J ,f 1'11 1 11! ,, 1 1;11 !1, ,I :111 1 Iii "I H 1 ,!' I \,..,.: -', rn, r,'h .,\ 11 lt1 TI i r,1,-.i, ur,! h1r11-111!t,lJ11, ,\II /.1,,.,, ..... 1, I 1t,., i, r 11 1.-, 0 11.q,, 11:1,,,d ,(1J ".,, :, \,lI .,.-, I f. I lh;:I p, 111 cj JI 11111, Figure 3. Di c tion ary kf'f-E EMIMPIF w [', tdl (loo,_, 1"' 5'U9' Htl> 1,1 !Ztl&t H 8 a 14 t1 Cl lrll[i'i ,i !l Organizations 'It I Mffu t I OlaltiNfo\ hdtneriM 'Q. !!!!,..IW4ft lt b4.-.rd I MCk .. ~: ::: \ :-::~::= r Tkh1rt -.tt at B Sa llil .\frb Ob l ~tn \ ,,_,.lwM t ildrftll Ofllbffi.-:. t'd t i'.e L il. l ttlbdb ....... .. ,iw-' .... ,,Uh .. \ li -,ta Q 1' t--'O.b1 : tft\ll.a1N'1' Kl Klilhhllllla ~ 'H'. J~fia Di~N l Htitr 1 1ae Ob brt n ft'IIN fiHld. l w b rhh iJ I WabttV h ~Nl t kttl Olebetn Physiology h lr1 \l edit.1 D iahffl p !"!!I' Is l ets K kvnli \l da...d .t bki l t,olet l I NdKtlM \ \.l.!JUfh 1tMI \ U I Gl,ntH \ T t l Jrl Nacbt..._ \ nut P ... latklWTMrDb~ h Pa~ _, I .Jri 1 n.,,aa t.tt1&, Wht'" '' \\ It ~ o.bcfc-, h lN ~ \l f'dit-al 1-'N'l,--lh \ ll.NI OM;loe Figure 4. Lin ks v,, ..J.J.!!l I I ,.J Che mi ca l E n g in ee rin g E du c ati on

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tions simulate a Healthy Person" and a "Diabetic Patient respectively The user has the flexibility to choose between the two different models for the healthy mode (Model I and Model II) and between the two different models for the Type1 diabetes mode (detailed model and overall model). For OGTT, the only input is the weight of the person There is also an option where the user can load his or her own pre viously saved data. Inputs for the other two modes (Figures 5 and 6) are I Carbohydrate content of the meal. There is also a nutritional database where the user can find the carbohydrate content of a specific meal. 2. Time of meal and injection. The user can enter a value between 0-24 hours for time of meal and insulin injection. 3. Insulin type and dose. Two types of insulin are available, i.e. regular and ultralente. 4. Bod y weight 5. Duration of e x ercise. The exercise option which is I 1,1 1 11 ll',IJ<,4 ll,.,l.d,, l'.,h, ,,1 '.,,-,,,1 ,,,.,,, 11,,,,.i ... :,,t M Type-I Di~b-lc,, Melhtu Fig u re 5. Main window for T y pe-1 diabetes mode. F i g u re 6. Main window for healthy person mode Fall 200 3 specifically designed for moderate exercise,[12 1 is available for only Type-I diabetes mellitus mode. 6. Duration of simulation. It is possible to simulate the dynamics of the diabetic patient and a normal person for a maximum of 24 hours with up to four injec tions in diabetes mode. The outputs of the simulation are displayed by continu ously updating the figures displayed on the screen (Figure 7). Once the simulation is finished, data can be saved in ASCII and/or graphic form to make the recall and display of the profiles possible for further analysis. IMPLEMENTATION [] Overview of the Cou r se The course focuses on application of engineering principles to biochemical and biomedical systems Biochemical engi neering topics include biological systems, enzymes and mi crobial kinetics and design and analysis of biological reac tors Biomedical engineering topics include flow properties of blood transport in human cardiovascular systems, and analysis and design of artificial organs. Half of the semester is spent on biomedical engineering, while the other half is used for biochemical engineering. Details of the course are documented elsewhere .1 131 The average number of students registering for this class is around twelve every semester. The primary learning goals of the course are to provide students with basic principles in cellular biology of micro bial cells bioreactor operations and transport phenomena in living systems, and enzyme and microbial kinetics and phar macokinetics-in short, to provide them with a working knowledge of bioengineering applications. The course was designed to achieve these learning objec tives that were assessed using fairly traditional methods (i.e., homework assignments examinations and term projects) Figure 7. Output window. 303

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.M ... ij 11111 3.._1a_b_o_,-,_a_t_o_r.:.y ________ ) Simulation and Experiment in AN INTRODUCTORY PROCESS CONTROL LABORATORY EXPERIENCE KENNETH R M USKE Villanova University Villanova PA 19085-1681 T here are several advantages to integrating classroom and laboratory exposure. For many students, under standing concepts taught in the classroom improves significantly when they have the opportunity to gain hands on experience in a laboratory. A laboratory exercise also pro vides an opportunity to apply the theory they have learned in the classroom to an actual engineering problem. Finally, com paring experimental data and dynamic simulation results is an effective way to reinforce process dynamics education in a laboratory exercise. The wider incorporation of pro cess dynamics into the curriculum is considered to be a key component in process control education of chemical engineering studentsY 1 There are a number of simulation-based chemical process dynamics experiments presented in the engineering educa tion literature. They range from modules incorporated into a commercial process control computer system, 1 2 1 case studies illustrating various process control concepts programmed using MATLAB/SIMULINK, 1 3 5 1 and workshops based on real-time simulation of industrial unit operations. 161 Although there are benefits of simulation-based experiments, a major disadvantage is the lack of an actual physical process that the students can watch hear, and touch while it is operating. Understanding the dynamic behavior of a process is greatly enhanced by observing the physical process operation Visu alization provides a significant benefit to many students as they attempt to apply the theoretical concepts taught in the classroom P 81 This aspect was one of the main motivations for developing the experience documented in this work. A review of the equipment-based chemical process dynam ics experiments presented in the engineering education literature reveals a wide range of complexity in the processes considered. They range from relatively simple liquid-leveJl 91 and stirred-tank 1 01 systems, multiple tank systems, 1111 quite complex reaction 11 21 and distillationfl 31 systems, and combi nations of simple, more complex, and simulated systems. 1141 Because this experience is intended to be an introductory exposure to process dynamics, simulation, and control, us ing an easily modeled, simple, physical process that incorpo rates the introductory concepts from the process control and simulation course is appropriate. For this reason, a single tank liquid-level system was chosen. Feedback control is performed using a proportional-only controller. Proportional control provides two benefits for this introductory experience. The first is that a proportional con troller is easily simulated. The additional complexity required in the simulation of integral action in the controller provides little, if any, benefit to the understanding of process dynam ics and dynamic simulation in an introductory experience The second benefit is that proportional control results in steady-state offset of the tank level. This concept is often dif ficult for some students to initially grasp in the classroom The ability to observe this phenomenon on a real physical system can be very helpful for these students. Kennet h Mus ke is Associate Professor of Chemical Engineering at Villanova University, where he has taught since 1997 He received his BSChE and MS from Northwestern (1980) and his PhD from The Univer sity of Texas (1990) all in chemical engineering. Prior to teaching at Villanova he was a technical staff member at Los Alamos National Labo ratory and worked as a process control consultant for Se/point Inc. His research and teaching interests are in the areas of process modeling control and optimization. Copyright C hE Di vis ion of ASEE 2003 306 Chemical Engineering Education

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disturbance that is about the same as the initial steady state inlet flow rate. From the instructor's perspective, it is desirable to have as much variation in the selected disturbances between groups as possible to make the students' semester-end oral reports on this experiment more interesting In practice other than discouraging the one large bucket, prompting by the instructor in order to provide this variation has seldom been necessary. Prior to implementing their chosen disturbance the tasks of time keeper, data logger, and disturbance initiator are distributed by the group members among themselves. Their selected disturbance is then implemented on the tank sys tem under closed-loop level control. The initial data point is collected after the disturbance has been completed. In the case of the buckets, this point is the time when all of the water has been emptied into the tank Because two students (and sometimes the instructor) are required to empty the bucket contents into the tank, the time-keeping and data logging tasks are performed by one student at the begin ning of the experiment. For the other disturbances, the ini tial data point is taken immediately after the valve position or controller tuning parameter has been changed Data is collected at intervals often to twenty seconds until the tank level reaches steady state. The experimental phase of this exercise is typically completed well within the three-hour laboratory period. PROCESS SIMULATION The second phase of this exercise involves the dynamic simulation of the closed-loop tank system with the distur bance chosen by the group. This phase is carried out during the laboratory period immediately following the experimen tal session Process simulation begins with an unsteady state material balance over the tank Assuming a constant cross-sectional area of the tank A c and the same constant density for all water streams, a macroscopic mass balance results in dh A c -=F;n -F o ut dt (l) where h is the height of water in the tank, Fin is the inlet volumetric flow rate, and F o ut is the outlet volumetric flow rate. The inlet volumetric flow rate of water is determined by the position of the control valve Although this control valve is linear the inlet flow rate is not a linear function of valve position over the entire valve position range due to varia tion in the water supply pressure as the valve position changes. The students are given a calibration curve, shown in Figure 2 that is used to relate the inlet flow rate to the control valve position. Over the linear operating range of the valve, the following correlation can be used to deter30 8 mine the inlet flow rate (2) where F. is the flow rate in units of gpm and V is the control ,n p valve position in units of % open. If the disturbance flow was selected, there is a second constant inlet flow rate that must be added to this relationship. The outlet volumetric flow rate is assumed to be propor tional to the square root of the pressure drop across the manual outlet valve due to the static head of fluid in the tank (3) where F o ut is the flow rate in units of gpm, K v is the proportion ality constant, h is the height of the water in the tank in units of feet, and the bottom of the tank is 19 inches above the outlet valve. The proportionality constant K v is determined from the measured outlet flow rate and water height when the tank level is at steady state. The control valve position is determined by the level con troller on the tank For the proportional-only controller, the valve position is determined from the controller equation (4) where V is the valve position in units of % open B is the p controller bias in units of % open, K c is the proportional gain in units of % open/ % level, S is the water level setpoint in p units of% level, and L is the level of the water in the tank in units of % level. In practice the controller gain is kept at a value around 1 % / % to prevent the control valve position from moving out of its linear operating range during the transient response due to the disturbance. Simulation of the process is carried out by numerical solu tion of Eqs. (1) through (4) Before they can be solved, how ever the units must be made consistent throughout all of the 10 m iii a: 5 i Ca l i b r at ion D at a o Linear Model 10 g w ro n oo 1 00 Va l ve Pos iti on ( % ope n ) Fig u re 2. Inlet water control valve calibration curve. Ch e mi c al En g ine e rin g Education

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relationships The controlled variable for the controller is con figured to be in units of % while the tank dimensions are given to the students in units of feet and the flow rate calibrations are given in units of gpm. This variation in the units given to the students is intentional. Numerical solution is typically carried out by the student groups using MathCad which is used by the department in the introductory material balance and the nu merical methods prerequisite courses, although they are free to use any of the other mathematical software packages such as MATLAB, EXCEL, and Maple that are available on the engineering college server. EXAMPLES AND DISCUSSION OF RESULTS Example experimental and simulation results are shown in Figures 3 and 4. Figure 3 present s the re s ults for the large bucket impulse disturbance. In this example, the large bucket was only about half full. Figure 4 presents the results for a reduction in the outlet flow rate from closing the manual outlet valve. In 70 Experimental Data o S1mutatlon R esult 65 55 50 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Time ( m i nutes ) Fig u re 3. Experimental and simulated closed-loop tank level for the large bucket impulse disturbance. 64 62 60 54 52 E x perimental D ata o Simu l ation Result 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Time (minutes) Figure 4. Experimental and simulated closed-loop tank level for a change in the outlet valve position. Fa/1200 3 both cases the experimental and s imulated responses are very similar. These results are typical for most of the student lab groups. In addition to pre se nting their experimental and simula tion results, the student groups are asked to discuss the sources of error in this experiment in their group memo report. Examination of the experimental and simulated dy namic respon ses reveal s that the simulation leads the ex perimental response. Because there are dynamics associ ated with the level sensor and control valve that are not included in the simulation model this result would not be unexpected The effects of valve friction, sensor noise and the precision of the liquid level value displayed by the con troller can also contribute to error a s well as the assump tion of a perfect s quare root relationship and a constant K v value for the outlet flow rate that may not be valid over the liquid level ranges encountered in the experiments Experi mental error in the timing of the collected level data samples is also present. Almost every s tudent group mentions the valve, sensor noise and sampling error as sources of error in their report Some groups also mention the outlet flow relationship used in the si mulation model. Few groups dis cus s the dynamic effect of the valve and sensor. STUDENT RESPONSE As part of the student evaluation of the process simula tion and control course a number of supplemental ques tions concerning the value of the text and controller simu lation software used in the course, the laboratory experi ence documented here and the preparation received in the required prerequisite courses are included. The evaluation scores ranged from 5=Very Effective to l=Very Ineffec tive The average scores from the last four years are: pre sentation and explanation of concepts in the textbook 3.04; use of CStation for class examples, 3 .2 5; use of CStation for homework problem s, 2.96; process control experiment in Lab II 4.02 CStation [I 6 l is the process control simulation software package used in the course, Essentials of Proc ess Contro[ l' 71 was the course text at the time of these evaluations, and the process control experiment in Lab II is the experience docu mented in this work. The average score given by the students for this labora tory experience is considerably higher than for the text and process control simulation package and is essentially the same as the average score of 4 10 for the value of the pro cess control and simulation course over the same period. It should be noted that a number of s tudents have provided somewhat negative comments concerning the length of the loop tuning homework assignments requiring the use of CStation. These feelings may have had some influence on the CStation scores. It should also be noted that only one --------------Continued on pa ge 315. 309

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It s h ould be noted that although we have chosen Excel, Version 2000, for all examples in this paper, other spread s h eet programs such as Quattro Pro and Lotus will perform eq u al l y well. DESIGN OF ABSORPTION COLUMNS T h e design of absorption using the McCabe-Thiele diagram can be co n sidered as a graphical solution to a series of se q u entia l n onlinear equations. 1 41 Spreadsheets have been used i n so l ving sim u ltaneo u s nonlinear equations due to their in corporation of a variety of mathematical functions and the ease of i n teractive programming, modification and rapid graph generation .C 51 Exa m ple 10.3 from Geankopolis 161 is used here to illustrate th e u se of spreads h eets in t he design of absorptio n un i t s. T h e pro bl e m req u ires remova l of acetone from an aceto n e air gas stream u si n g water in a co u ntercurrent stage tower. The pro cess sc h ematic and spreadsheet used for solving this prob lem are shown in Figure 1. The initial data p rovi d ed in t h e problem, such as the percentage of recovery an d t h e flows and composition of the entering gas and liq u id streams, are shown in the upper portion of the spreadsheet u n der d es i g n parameters. Assumptions include a constant mo l ar overflow in the tower, negligible solubility of air in t h e wa t er, a n d a phase equilibrium relationship that could be re p resen t ed by Henry s Law The compositions of acetone in the l iq uid and vapor outlets x N and Y N + J can be obtaine d from a m ass balance as shown in cells D8 and D9 of t h e sp r eads h eet; the equations have been added to the respec t ive co mm e n t bubbles on the graph The equilibrium and operating lines are p l otted usi n g Henry s Law and Equation 10 3 13 from G ea n kop li s, as show n in the D 15-E25 cell ra n ge of t h e sprea d s h ee t an d th e respective comment bubbles. Using Excel s "c h art wizar d ," an X-Y plot can be readily constructed showi n g th e e qu i l i b rium and operating lines B C D E F G H K L M N 26 27 28 29 30 31 32 33 34 42 43 44 Fall 2003 Absorption of Acetone in a Countercurrent Stage Tower DESIGN PARAMETERS % Recovery L [kg mol/h] V[kg mol h ) x0 yN+1 x N y 1 80 90 0 0 00267 2 53 = ( 1 D5/100)'E7 C A L C U LA TI ON OF THE OPE RATING A N D EQ UI LI BR I UM LIN E y Operating 0 00000 0 00 2 0 0 00133 0 0060 0 00267 0 0100 0 00400 0 0140 0 00533 0 0180 0 0300 3 0 0 01 0 0250 0 00200 0 0200 0 0150 0 0100 0 0050 0 00667 0 0 2 20 y Equilibrium 0 0000 0 0034 0 0067 0 0101 0 0135 0 0169 0 0202 0 0000 0 0020 0 0040 0 0060 0 0080 0 0100 0 00800 0 0260 0 00933 0 0300 0 0236 X 0 01067 0 0340 0 0270 0.01200 0 0380 0 01333 0 0420 =C25.($0$6/$E$6)+$E$6 =C25.$D$9 0 0304 --~-------?" =:;_ :==::::::=:;:~ ..::;...: 0 :.;; 0 :.:. 3377 ~~l~~~:;he # stages using Function =FDRECAST(E7 G30 : G42 F30 : F42) CA LC ULA TING THE CONCENTRATION OF ACETONE PLA T E BY PLATE C oncentration i n Concentration in the Number X the Liquid Phase y Vapor Phase o f Stages 0 000000 0 000000 xO 0 000000 0 000000 0 000000 y 1 0 002000 x1 0 000791 0 002000 =D32($0$6 / $E$6)+$E$8 0 00 0 791 y2 0 004372 x2 0.001728 0 004372 0 001728 y 3 0 007184 3 x3 0 002839 0 007184 0 002839 y4 0 010518 4 x4 0 004157 0 010518 0 004157 y 5 0 014472 5 x5 0 005720 0 014472 0 005720 y6 0 019161 6 x6 0 007573 =+F 4 2/$0$9 =+F42 Stage 2 Stage N YN +1 Figure 1. Spreadsheet used for ilustrating absorption of acetone in a countercurrent stage tower. 317

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The next step involves the plate-by-plate calculation of the co n ce nt ration of acetone in the liquid and vapor pha ses. In hand calc ul ations, this step is made graphically,f 41 but in thi s case advantage is taken of th e fact that both the operating and eq uilibrium lin es are expressed as mathematical function s, so the concentration in the liquid and vapor phase s can be easily determined numerically as s hown in the D29-F42 cell range of the spreads h eet. The (x,y) data ser ie s i s added to the existing graph, thus completi n g a numerical McCabe-Thiele diagram also s ho wn in Figure 1. Finally, the number of ideal s tages required for the desired percentage of recovery is determined using the built-in "F ORECAST function, which operates as a linear interpola tor. The series in the i nterpol ation represents the number of stages and the concentration of the vapor phase (col umn s start ing at F29 and G29), w hil e the value to be interpolated is the calc ulat ed concentration at the exit of the tower (E 7). On ce the spreads h eet is built severa l "w hat-if sce narios can be analyzed. For in sta nc e, in this example an increase in the recovery requirement as well as a moderate increase in the gas flow will readily s how that the number of stages re quired will increase significantly. Also, a large decrease in the liquid flow rate or an increa se in the gas flow rate will demonstrate that the se paration i s impossible to achieve as the operating line and the equilibrium line cross eac h ot h er. INTERFACIAL COMPOSITIONS IN MASS TRANSPORT BETWEEN TWO PHASES Trial and-error iterative procedures for determining the composition of the interface between immiscib l e phases are freq u ently req uir ed in mass-transfer-based separation pro cesses. To demonstrate the versatility of sprea d sheets in ac complishing this task, we u se Example 10.4-1 from Geankoplis, f 6 1 as shown i n Figure 2. The objective of this prob lem is to determine the interfacial concentrations of the va por and liquid pha ses y Ai and x Ai' respectively, in a wettedC O E G K Iterative calculation of interface compositions in interphase mass transfer Equlllb rium Data Gas phase film mass transfer coefficient LI uld hase mass transfer coefficient 0 1 0 38 ky= kx= ITERATIVE CALCULATION 0 001465 Kg mol A/ s m 0.001967 K mol A/ s mJ xa ya 0.000 0.000 0 050 0.022 0 100 0 052 0 150 0 08 7 0 200 0.131 0 250 0 187 Fonnula First Ite rat ion Secon ration T h ird Iteration Fourth lteratJon 0 300 0 265 I n itial Guess 0 4 0 258376 0.257171 0 350 0.385 yl 13 (1-xai) (1-ya1) C a lculated Slo pe from Equation 10-4-8 16 x equiliblum y equl (From slope 17 calculations) y equl (from Equilibrium correl atio n) Error 0 350 0.300 0 250 0 200 0 .1 50 0.100 0 050 Initial Guess =((1-$D$6)-(1-E11)) / LN (( 1-$D$6) /( 1 -E 11 )) =((1-E12)-(1 $D$7)) / LN((1-E12)/(1-$D$7)) =-{$FS5/E 13 )/($F$4/E 14) =+ E 15"(E 16-$D$6)+$D$7 =8 1414"E 16'3-1 4 766.E 16'2+0 6184 E160 0022 =+ E17 E18 "2 y = 8 .1 414 x' -1.47 66x + 0 6184x-0 0022 R = 0 9994 0 9 0 73989 1 0 285002 0 000 -----------------..... 0 090 0 140 0.190 0 240 0 290 0.340 X 0 275350 0 794537 0 670966 -1 133842 0 258376 0 200427 0 200427 0 818259 0 705984 1 158433 0 257171 0 197928 Sub INTERPHASE_COMPOSITION () INTERPHASE COMPOSITION Macro Macro recorded 9/22/2002 by JPH Range("G27'') Select lc ucK HERE TO I SOLVE PERFORM THE ITERATION CALCULATION Error between the value of y from Equation 10-4-8 and the value predicted by the equilibrium correlation This Is the target call for the SOLVER routine and the objective is to minimize tt SolverOk SetCell : ="$E$19" MaxMlnVal : =3, ValueOf : = o ByChange : ="$ E$16 SolverSolve SolverOk SetCell : =$F$19' ', MaxMinVal : =3, ValueOf : ="0", ByChange : ="$F$16" SolverSolve SolverOk Se1Cell : ="$G$19" Ma x M inV al : =3 ValueOf : "0", ByChange : =$G$16" SotverSotve SolverOk SetCell : =$H$19 ", MaxM i nVal : =3, ValueOf : ="0", ByChange : ="$H$16 SolverSolve End Sub Figure 2. Spreadsheet and Macro used for interative ca l cu lation of interface compositions in interphase mass transf er. 318 Chemical En gi neering Edu ca t ion PAGE 81 wall tower. Experimental equilibrium data ar e provided a s well as the gas and liquid pha s e film ma ss -tran s fer coeffi cients. In this problem the s olute A diffu s es through s tag nant B in the gas phase and then through a liquid film. The first step in solving thi s problem involve s initial gue s ses for x A i and y Ai In solving the problem by hand the s e gue ss e s are crucial to the rapid convergence of the iterati v e proces s Spreadsheets are less sensitive to the initial gue ss e s a s a large number of iterations can be proc es sed and vi s ualized in fr a tions of seconds. In Figure 2, cells D13-D19 di s pla y the equations and col umns E H display results from four iteration s Once the initial guesses are selected (cell s El 1 and E12) the slope for the line connecting the bulk concentration and the assumed interfacial concentrations i s calculated a s s hown in cell EIS. With the slope from EIS and point P ( the bulk concentration in cells D6 and D7) on the x-y plot in the lower-right comer of Figure 2, an equation for a s traight line i s deduced a s s hown in cell D 17 A third-order polynomial wa s u s ed to fit the equi librium data (cell D18) The Excel function SOLVER i s u s ed to s olve s imultaC D Rectificat i on o f a B enzene-Toluene Mixt u re DESIGN PARAMETER S zoo m oVh neousl y the equation s in cell s D17 and D18 by minimizing the error between the v alue s of cell s E16 and El 7. SOLVER can use a Newton or a conjugat e numerical procedure to find the answer; the default Newton procedure was chosen for thi s example. When comparison between the values for xAJ and y Ai from thi s procedure ( c ell s E 15 and E 16 ) and the initial g ue s se s ( c ell s E 12 and E 13 ) s how s a discrepancy an additional iteration i s required. The latest calculated value s for xAi and y Ai ( cell s EIS and El6 ) are used a s the new initial gue ss e s. Due to the e a se of modification of spread s heets, the cells containing the equation s can be copied and pasted into the next columns as many time s as necessary. In this example, four iteration s provide a reliable answer (less than 0.1 % be tween the late s t and penultimate calculated values). What-if s cenario s in thi s example include how an increase in the liquid-film ma ss -tran s fer coefficient will readily show that the v alue for the interfacial concentration s x Ai and y Ai increa s e and how a large decrease in the bulk concentration will produce a s ignificant decrease in x A i and y A i" In order to automate the iteration process a MACRO was created using 1 0 -~ F "' w R Ultnt Heal T, T, 0 t 5 0 1 3 2 0ff KJ /K g 151 KJ / Kg-mol 327 1 K 31i&.700K CLICK HERE TO SOLVE FOR THE I OVERALL MASS BALANCE AND THE INTERCEPT BE1WEEN THE Q ) AN D ENRICHING LINE 0 9 0 8 0 7 Calculatln U,11 Dl1tlllat 11nd Bottom s FlowratH 70 5H21401 Overal Ma ss Balance 5 '50098E-05 :QS-C15-C16 0 6 129 41173 Component Mass Balance 2 3696 E -05 =05 06C15-07-C16-08 Error 3 6Sll59E-09 e1s-e1e 2 1 1;,4 "'(010,.0 1 1 (013-012))1010 6 163 -CHl/(C19-1) >-~+---~-------2 oo s +D6-C2o oe ~l c uMl ti ng the In t ercept between ttw En rk hlng and UM q U ne 0, 8 00 + 09/(09+1) f--..,-i:;:,:;;=t=~ -----..:; 0 "-'1 90 "! +0 7/(09+1) x l nten:ept 0 4 20510204 y from q lkle D 526408163 sC20" E 23+C21 Y from the enriching lil'le 0 526-401!1 1 63 .. czee2J+C29 i: ::.:::.. ________ .cc '-' c.c c.c aa-= (E24E25) 2 1 330-4 04 33 1 =(03E2 4)1{08-E23) Number of Plates FORECAST(D7 M35 : M4J 7 373l452!i2 135 : 143) -0 03304043 3 E 2 ,t -C31 E23 Ude reeslin1 Enriching UM Stri in Line Line B38 ..,$C$2!1"B31$C 30 "'$C$32 B31 $C$33 $C 21"B31$C$22 0 0 0 1 g -0 033CMCM33 -2 065273889 0 23 0 08 0 2S4 0 0733{11913 -1 5722111952 0 5 0.4 0.3 0 2 0 1 0 0 0 0 0 2 0.4 0 6 0 8 1.0 0 08 0 25 0 4 8 5 0 7 9 0 5 14 0 25 0 73 0 904 0 4 85 0 79 0~;7~ :s~9;;o8: 5 7 -~ : :;;:~:~ 1 1P.!!'$u '!" b !'!' M acro o; !!!' '!!! till .a1 '!" ionQ ________________ 0 822 1 017{178988 2 803641847 l--a~ f------'-------'-----'----o "" ", ----~ ~ ~ ~ '~ ~ -------'' 0 ~ 07 ~ 01 ~ 05 ~"J 1 'Macro0istill a tionMacro .:I F (K3 5 >l35.K35 L35) '"4 3 3 92 130"'5. 12 5 39 130"4 (J3~ $C$33)1$C$32 : (C30$J$3 0 )1 $C$ 29 1 4 22& "1 30'"3 8 496 2' 1 30"2 + 3 48 99"130 0 1 0 2 7 50 434 9 2 0 23157 1 8 4 9 0 1063 043 85 0 .231571 8 49 0 49140 9759 0 3 94 20 38 12 0 37 8 782 1 99 0 39420 3 81 2 0.85 753 5069 0 5 1 90 71899 0 58 88 3 7 0 5844188 3 7 0 798732 7 1M 0 6 25 20 33 37 0 7609 1 59 93 0 7 60915 993 0 89191,t543 0 89 5 2 43 50{1 0 8773{13178 0 8 77 3931 78 0 9379 9 581 0 7298 8 05 4 9 0 93 4994 783 0 93-4994 783 0 96268 4 8 33 0 74343 8 082 0 96S85604 1 0 98 SB S6041 0 97 8 5 9 585 5 0 780397821 0 98S7 g 0 98574481 {1 0 990439 7 52 0 7893001 1 0005 4 969 St1 es M acro recorded 912912002 by JPH SOLVING THE MASS AND COMPONE NT BALANCES TO OBA T IN D AN D W SolVtlrOk SetCeil : =<"SF $18" M axMinVal:=<2 ValueOf : = cr 8yChang e : =SC$1 6 : SC$1 r SolverSolve SOLVI N G THE INT ERC EPT BETWEEN TH E q LIN E A N D THE EN R I C HING LINE SolvelOk Se!Cell "'"$F$27", M axMinV a l : ::2 ValueOl' : = "O" B yC h ang e : ="$ F$24 SolverSolv e En d Sub Figure 3. Spreadsh ee t and Ma c ro us e d for di s tillation o f a b e n ze n e -t o lu e n e mixtur e F a ll 20 0 3 3 19 PAGE 82 VBA; its text is also shown in Figure 2. To create a user-friendly interface, a button is inserted into the spreadsheet using the 'FORM TOOLBAR menu from Excel and assigning the Macro to it. The button allows the user to run several "what-if scenarios by changing the de sign parameters DISTILLATION While interfacial composition calculations used a VBA program and the absorption example was based on cell and formula manipulation of the spreadsheet in this example a combination of both approaches is used for the design of a distillation unit. Such design is made using the McCabe-Thiele diagram with special considerations for the location of the feed and the types of condenser and reboiler. [ 6 1 Example 11.4-2 from Geankoplis' book is chosen to illus trate use of spreadsheets in the design of distillation towers The problem requires the rectification of a benzene-toluene mixture Initial data of the problem include the flow and con dition of the feed stream as well as its composition. The re flux ratio and the compositions of the distillate and bottoms are also specified. These design parameters are located in the upper portion of Figure 3 under design parameters. It is as sumed that a constant molar overflow is present in the tower. Solving the overall mass balance (cell Fl5) and a benzene mass balance (cell Fl6) simultaneously with SOLVER pro vides the values for the distillate and bottom-stream flow rates (cells Cl5 and Cl6). In this example we take advan tage of the capabilities of SOLVER for multi variable calcu lations. The error cell (cell Fl 7) is set as the target cell and the SOLVER should change the values of cells Cl5 and Cl6 until the value ofF16 becomes negligible. The multivariable optimization capabilities of SOLVER are implicit, which is very useful since no additional programming is required After calculating all flowrates, the next step is to build the equilibrium and operating lines. The equilibrium line is con structed using experimental equilibrium data and fitted to a fifth-degree polynomial using the TRENDLINE option of Excel. The "q line" is calculated by using a boiling point dia gram and the physical properties of the feed stream. Cells B 18 to D2 l show the calculations performed to obtain the value of q and hence the slope and intercept of the "q line The enriching line is constructed using Eq. 11.4-8 from Geankoplis,r 61 as shown in cell range B26 to D27 Once the slope and intercept of the q and enriching lines are deter mined a numerical method is used to calculate the intercept between these two lines SOLVER is again used as shown in cell range E21 to G25. Since this problem requires the use of SOLVER twice, a VBA program is built and assigned to a button so these calculations are automated with a single click by the user. The stripping line is constructed using the initial conditions of the problem and the intercept between the q and the enriching lines as shown in cell range B28 to D 30. 320 The table containing the data as well as the formulas used to determine the equilibrium enriching, stripping, and q lines is shown on cell range B32 to G38 To calculate the number of plates required for the rectification the following proce dure is followed, as shown in cell range B40 to F50. The initial point (cell B42) corresponds to the bottoms concentra tion xw, Y Eq u is calculated using the equilibrium equation (cell C42), and the equations for the enriching and stripping lines are used for cells D42 to E50. For every iteration an IF state ment is used to select the larger value for x. This IF statement initially selects the stripping line as the operating line, but once the q line is reached the enriching line becomes the operating line. The number of plates is calculated using the FORECAST function as shown in cells E29 to G29. Based on the spreadsheet, what-if scenarios can be considered and the student is able to visualize the effect of changes in the design parameters such as concentrations, flowrates, reflux ratios etc., on the number of plates required for a desired separation Concepts such as the pinch point and the mini mum reflux ratio can also be analyzed. CONCLUSIONS MS Excel Macros and Visual Basic for Applications en hanced the educational experience of students in a junior level separation processes course, teaching them to develop simple software and providing them with an intermediate step between doing hand calculations and using commercially available packages Distillation, absorption and interfacial mass-transfer problems were solved using spreadsheets and were incorporated into a web-based learning platform In addition to analyzing several what-if' scenarios, these teaching tools can also be slightly modified to solve the in verse problems. For example, in the absorption case, the num ber of stages as well as the inlet flowrates and concentrations can be given as design parameters, and then the students can be asked to determine the concentration of the outlet streams. Also in the distillation case, the number of plates in the en riching and stripping sections can be fixed, and the students can be asked to determine the appropriate reflux ratio and inlet flowrates to achieve a certain degree of purity in the top or bottom streams REFERENCES I. W a nk a t P "Teachin g Separation s: Why What, Wh e n and How ? Ch e m En g. Ed. 35 168 ( 2001 ) 2. Rive s, C. and D Lack s, Teaching Proce ss Control with a Numerical Approach Ba s ed on Spread s heets Ch e m En g Ed ., 36 242 ( 2002 ) 3 Mit c hell B.S ., U se o f Spr ea dsheet s in Intr o ducto ry Stati s tic s and Prob a bilit y," C h e m. E n g. E d., 31 194 ( 19 9 7 ) 4 Burn s, M ., a nd J Sun g, De s i g n of S e paration Unit s U s ing Spr e ad sheet s," Ch e m. En g Ed ., 29 (1995 ) 5. Mackenzie J. and M All e n Mathematical Power Tool s Ch e m En g. Ed. 32 ( 1998 ) 6. Geankoplis C. Tran s p o rt Pr oces s es and Unit Op e ration s, 3rd ed. Prentic e Hall PTR ( 1993 ) 0 Ch e mi c al En g ine e rin g Edu c ati o n PAGE 83 Graduate Education in Chemical Engineering Teaching and research assistantships as well as industrially sponsored fellowships available up to$20,000 In addition to stipends, tuition and fees are waived. PhD students may get some incentive scholarships. The deadline for assistantship applications is April 15th. For Additional Information Write G.G CHASE Multiphase Proces ses, Fluid Flow Interfacial Ph e nomena Filtration Coalescence H.M.CHEUNG Nanocomposite Materials, Sonochemical Processing P o l yme rization in Nanostructured Fluids, Supercritical Fluid Pro cess ing S S C. CHUANG Cata l ysis Reaction Engineering, Environmentally Benign Synthesi s J. R. ELLIOTT Molecular Simulation, Pha se Behavior Ph ys ic a l Properti es, Proce ss Modeling E A EVANS Materials Proce ss in g and CVD Modeling Pla s ma Enhanced Depo s ition a nd Crystal Growth Modeling Chairman, Graduate Committee L.K.JU Biochemical Engineering Environmental Bioengineering S.T.LOPINA BioMaterial Engineering and Polymer Engi n eering B.Z.NEWBY Surface Modification, Polymer Thin film H.C.QAMMAR Nonli n ear Control Chaotic Processes Product Development P. WANG Biocatalysis and Biomaterials Department of Chemical Engineeri ng The University of Akron Akron, OH 44325-3906 Phone (330) 9727250 Fax (330) 972-5856 www.ecgf.uakron .e du/~chem Fall 2003 32 1

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THE UNIVERSITY OF ALABAMA Chemical Engineering A dedicated faculty with state of the art facilities offer research programs leading to Doctor of Philosophy and Master of Science degrees. Research Areas: Biomaterials, Catalysis and Reactor Design, Drug Delivery Materials and Systems, Electrohydrodynamics, Electronic Materials, Environmental Studies, Fuel Cells, Interfacial Transport, Magnetic Materials, Membrance Separations and Reactors, Microelectro Mechanical Systems, Molecular Simulations, Nanoscale Modeling, Polymer Processing and Rheology, Process Dynamics, Self-Assembled Materials, Suspension and Slurry Rheology, Transport Process Modeling For Information Contact: Director of Graduate Studies Department of Chemical Engineering The University of Alabama Box 870203 Faculty: G. C. April, Ph.D. (Louisiana State) D. W Arnold, Ph.D. (Purdue) C. S. Brazel, Ph.D. (Purdue) E. S. Carlson, Ph.D. (Wyoming) P. E. Clark, Ph.D. (Oklahoma State) WC. Clements, Jr., Ph.D. (Vanderbilt) R. A. Griffin, Ph D. (Utah State) D. T. Johnson, Ph.D. (Florida) T. M. Klein Ph.D. (NC State) A. M. Lane, Ph.D. (Massachusetts) M. D. McKinley, Ph.D (Florida) S. M. C. Ritchie, Ph.D. (Kentucky) C. H. Turner, Ph.D. (NC State) J.M. Wiest Ph.D. (Wisconsin) M. L. Weaver, Ph.D. (Florida) Tuscaloosa AL 3548 7 -0203 Phone: (205) 348-6450 An e qu a l e mploym e nt I e qu a l e ducation a l opportun i ty institu t ion 3 2 2 C h e m ic al E n g in ee rin g E d uca ti on

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University of Alberta Chemical and Materials Engineering The University of Alberta is well known for its commitment to excellence in teach ing and research. The Department of Chemical and Materials Engineering has 37 professors and over 140 graduate students. Degrees are offered at the M.Sc. and Ph.D. levels in Chemical Engineer ing, Materials Engineering, and Process Control. All full-time graduate students in the research programs receive a stipend to cover living expenses and tuition. 324 For further information, contact G radu a t e Program Offic e r D epartment of Chemi c al and Mat e rials Engineering University of Alberta Edmonton, Alberta Canada T6G 2G6 PHONE (780) 492-1823 FAX (780) 492-2881 e-mail: c hemical. eng inee ring@ualberta. ca web: www ualb e rta. c a/cm e ng M. BHUSHAN Ph D ( I.I.T. Bomba y) Se11sor locatio11 Fault Diag11osis Process Safety R.E. BURRELL Ph D. (U niver s ity of Waterl oo) Na11ostr u ct ur ed Bi o m aterials Drug Deliv ery Bi ofi lm s 7issue Im egratio11 w ith Materials P. CHOI, Ph.D (U niver si t y of Waterloo) M o l ec ul ar Modeli11g of Polymers Then11ody11amics of P oly m e r So luti o n s a11d Bl e 11d s K. T. CHUANG, Ph D. (U niversity of Alberta ) Fu el Cell Catalysis Separatio11 Pr ocesses P oll uti o 11 Co ntrol I. G. DALLA LANA, Ph D ( Univ of Minne so ta) EMERITUS Chemical R eactio 11 E11gi11eeri11g H eterogeneous Catalysis J. A. W. ELLIOTT, Ph D (U niversity of Toronto) Th e rm o d y nami cs Statisti c al Thermodynamics /11t erfac ial Ph e 11om e 11 a D. G. FISHER Ph.D (U ni ve r s it y of Michigan ) EMERITUS Pr ocess D y nami cs a11d Cont r ol R ea l-7im e Computer Applications J.F. FORBES Ph.D ( McMa s ter University) CHAIR R eal7ime Optimi za tio11 Scheduli11g a11d Pl a nnin g M. R. GRAY, Ph.D. (Cal iforni a In s t. of Tech.) Bior e a c tors Ch e mi cal Kin e ti cs Bitum en Pr ocess in g R. E. HAYES, Ph.D (U niversity of Bath) Nu m e ri ca l A11al y sis R eactor Modeling Computational Fluid D y nami cs B. HUANG, Ph D. (U niversity of Alberta) Controller P erfo rma11 ce Assessme11t Multivariable Control Statisti cs S M. KRESTA, Ph.D. (Mc Master University) Turbul elll & Tra11sitional Flows Multiphase Flows CFD S. LIU, Ph.D (University of Alberta) Fluid-Particl e D y 11ami cs Tr a n spo rt Ph e 11om ena Kin e ti cs D. T. LYNCH, Ph.D. (University of Alberta) DEAN OF ENGINEERING Catal ys is Kin e ti c Modeli11g Nu m e ri cal Methods P oly m e ri z atio11 J. H. MASLIYAH, Ph.D (University ofBriti s h Columbia ) Tr a 11sport Ph e 11 o m e 11a Colloids Parti cle -Fluid D y 11ami cs Oil Sa11ds A. E. MATHER Ph D (U niver s ity of Michigan) Pha se Equilibria Fluid Pr ope rti es at Hi gh Pr ess ur es Then11ody11amics E. S. MEADOWS Ph D. (U ni versity of Te xas) Pr ocess Control Fuel Ce ll Modelin g a11d Contro l Optimizatio11 W. C. MCCAFFREY, Ph D. (McGill University) R eac tion Kin e ti cs H eavy Oil Upgradi11g P o l y mer Re cycl in g Biot ech 11 ology K. NANDAKUMAR, Ph.D. (Princeton University) Tra11sport Ph e 11 o mena Distillation Computational Fluid D yna mi cs A.E. NELSON Ph.D. ( Michigan Techno l ogica l Univer s ity ) H ete r oge n eo us Catalysis U HV Surface Scien ce Chemical Kin e ti cs M. RAO, Ph.D. (Rutgers Un i versity) Al l ntellig e lll Co 11tr ol Pr ocess Co 11trol S. L. SHAH, Ph D (U niver s ity of Alberta) Computer Pr ocess Control System ld e 11tifi c ation Pro cess and P erfor m ance Mo11itoring J.M. SHAW, Ph.D (U niversity of British Columbia) P e troleum Thermody11amics Multiphase Mixi11g Pro cess Modeling U. SUNDARARAJ, Ph.D. (University of Minnesota) P oly m e r Pro cess in g Polymer Bl e 11ds l lllerfacial Ph enome 11 a H. ULUDAG, Ph D (University of Toronto ) Bi o mat e rial s 7issue E11gi11eering Dru g D elivery S. E. WANKE, Ph D. (University of California, Davi s) H ete r oge11eous Catal ys is Ki11 e ti cs P olymeri z atio11 M. C. WILLIAMS, Ph D. (U niver sity of Wi sco n s in) EMERITUS Rheolo gy P oly m e r Characterization P oly m e r Pr ocess i11 g Z. XU, Ph D. (Virginia Polytechnic In s titute and State University) Surfa ce Scie11ce & Engi11eeri11 g Mi11eral Pr ocessi 11 g Waste Mana ge m elll T. YEUNG, Ph D (U niversity of British Columbia) Emulsions lnt erfacia l Phe11ome11a Mi c romechanics Chemical Engineering Education

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FACULTY/RESEARCH INTERESTS ROBERT G. ARNOLD, Professor (Ca lTe ch) Chemical and Environmental Engineering Microbiologi ca l Ha za rd o us Wast e Tr eat m e nt M e tals Sp ec iati on and To xic i ty at PAUL BLOWERS, Assistant Professor ( Illinoi s, Urbana-Champaign ) Chemi c al Kinetics Catal ys is Surfa ce Ph e nomena ARIZONA JAMES C. BAYGENTS, Associate Profe ss or ( Princeton ) Fluid Mechani cs, Transport and Colloidal Ph e nom e n a, Bi osepa rati o n s WENDELL ELA, Assistant Pro fessor ( Stanford) Particl e -P article Intera c tion s, Environmental Chemistry JAMES FARRELL, Associate Professor (Stanford) Sorptionldesorption of Organics in Soi l s TUCSON ARIZONA JAMES A. FIELD, Associate Pro fessor (Wage nig e n Agricultural Univ .) Biorem ediation, Mi c robiolo gy, Whit e Rot Fungi, Ha zar dous Wa ste ROBERTO GUZMAN, As s ociate Pro fessor ( North Carolin a State ) Affinity Pr otein Separations Pol y m er ic Surface S c i e n ce ANTHONY MUSCAT Associate Profes so r ( Stanford ) Kineti cs, Surfa ce Ch e mi s try, Surf ace Engineering S emico ndu c tor Pr ocessing, Mi croco ntamination KIMBERLY OGDEN, Profes sor ( Colorado) Bior eacto r s, Bi oremediation, Or ga ni cs R e mo va l from So il s THOMAS W. PETERSON, Profe ssor and Dean (Ca lT ec h ) Aerosol s, Ha z ardous Waste In cineration, Microcontamination ARA PHILIPOSSIAN, Associate Professor ( Tuft s) Chemi ca l / M ec hani c al Polishin g, Semicondu cto r Pro cess in g EDUARDO SAEZ Associate Profe ssor ( UC D avis) P olymer Flows Multiphase R e a cto r s, Colloids FARHANG SHADMAN, Profe ssor ( Berkel ey) R eactio n Engineering Kineti cs, Catal ys i s Rea c ti ve M e mbran es, Mi c rocontamination JOST 0. L. WENDT, Profe ssor and Head ( Johns Hopkin s) Combustion-Generated Air Polluti on, In cinerat i on, Wa ste Mana ge ment For further information. write to http ://www c he.ari zo na .e du or w rit e Chairman Graduate Study Committee Department of Chemical and Environmental Engineering P.O. BOX 210011 The University of Arizona Tucson, AZ 85721 Th e University of Arizo n a is an eq u a l o pportunity e du ca ti o n al institution/equal opportu nit y em pl oyer. W o m en and ntin orities a r e e n co ura ge d to app l y Fall 200 3 The D epartme nt of Chemical and Enrivonmental Engineering at the University of Arizona offers a wide range of research opportunities in all major areas of chemical engineering and environmental engineering. The department offers a fully accredited undergr ad u ate d egree in chemical engineering as well as MS and PhD degrees in both chemical and environmental engineering A s ignifi cant portion of research effort s is devoted to areas at the boundary bet ween c h emica l and environmental engineering including environ mentall y b enig n se miconductor manufacturing, environmental remediation environme ntal biotechnology, and nov e l wa t er treatment technologies. Financial support is available through fellowships, government and industrial grants and contracts, teaching and research assistantships. Tu cs on has an excellent climate and many recreational opportunities. It is a growing modern c i ty that r e tains mu c h of th e old Southwestern atmosphere. 3 25

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ARIZONA STATE UNIVERSITY Department of Chemical and Materials Engineering A Distinguished and Diverse Faculty Chemical Engineering Jonathan Allen Ph D. MIT. Atm os ph e ri c aeroso l c h e mi s tr y, si n g l e -p ar ticl e m e a s urem e nt t e chniqu es, e nvironmental fat e o f or g ani c p o llut a nt s James Beckman Ph.D ., Arizon a U nit o p e rati o n s, a pplied math e mati cs, e n e r g y-effici e nt w a t e r purifi ca ti o n fr a cti o nation CMP r e cl ama ti o n Veronica Burrows Ph D ., Prin ce t o n Su rface sc i e n ce e n v ironm e nt a l s en s or s, se mi c ondu c t o r p rocess in g, int e rf ac ial c h e mi ca l and ph ys i ca l p rocesses in se n so r pro cess in g Ann Dillner Ph D. Illin o i s, U rb anaChamp aig n A tm os ph e ri c parti c ul a t e m a tt e r (aeroso l s) c h e mi s tr y a nd ph ys ic s, ultr a fin e aeroso l s, li g ht sc att e rin g, clim a t e and h ea lth e ff ec t s of aeroso l s Chan Beum Park Ph.D ., POSTI EC H So uth K o r ea. Biop ro ce ss in ex tr em i s n o v e l ce ll fr ee p ro t e in sy nth es i s, bi o l a b-ona-c hip t ec hn o l gy Gregory Raupp Ph D ., Wis co n s in. G as-so lid s urf ace reac ti o n s m ec hani s m s a nd kin e tic s, int erac ti o n s b e t wee n s urf ace r eac ti o n s and s imult a n eo u s tran s port pro cesses, se mi c ondu c t o r m a t e ri a l s pro cess in g, thermal a nd pl as m a-e nh a n c ed c h e mi c al v apor d e p os ition ( CVD ) Anneta Razatos Ph D ., T ex a s at Au s tin B ac t er i a l a dh es i o n c olloid interaction s, AFM bioftlm s, ge n e ti c e n g in ee rin g Daniel Rivera Ph D ., C alt ec h C o ntr o l sys t e m s e n g in eeri n g, d y nami c m o d e lin g v i a sys tem id e ntifi ca ti o n robu s t co ntr o l co mput e r -ai d e d co ntr o l sys t e m d es i g n Michael Sierks Ph D ., Io wa St a t e. Pr o t e in e n g in ee rin g, b i o m e di c al e n g in ee rin g, e n zy m e kin e ti cs, a n ti b o d y e n gi n ee ri ng Materials Science and Engineering James Adams Ph.D ., Atomi s ti c s timul a ti o n of m e talli c s urf a c es, adh es ion w e ar and automoti ve ca t a l ys t s, he avy m e t a l to x i c it y Terr y Alford Ph D. C orn e ll El ec tr o ni c m ate ri a l s, ph ys i c al met a llur gy, e l ec troni c thin film s Nikhilesh Chawla Ph D ., Mi c hi ga n L ea d fr ee so ld e r s, co mpo s it e m a t e rial s, p ow d e r metallur gy Sandwip Dey Ph D ., Alfr e d El ec tr o cera mi cs, MO CV D and ALC V D di e l ec tri cs : l e ak age, l oss m ec h a ni s m s and mod e lin g Stephen Krause Ph D ., Mi c hi gan C h arac t e ri za ti o n o f s tru c tural c han ges i n pro cess in g o f se mi co ndu ctors A multi-disciplinary research environment with opportunities in electronic materials processing biotechnology processing, characterization, and simulation of materials ceramics air and water purification atmospheric chemistry process control Subhash Mahajan ( Chair ), Ph.D ., B e r ke l ey. Se mi co ndu c t o r d e f ec t s, hi g h t e mper a tur e s emic o ndu c t o r s, s tru c tu ra l ma t e ri a l s d efo rmati o n James Mayer Ph.D ., Purdu e Thin film p rocess in g, i o n b e am modifi c ati o n of m a t e ri a l s Nathan Newman Ph D. St a nford. Growth c h arac t e ri za tion and modelin g o f s olid -s t a te mat e rial s S. Tom Picraux Ph D. Ca lte c h. N a n os tru c tur e d m a t e ri a l s, e pit axy, a nd thin film e le c tronic mat e ri a l s Karl Sieradzki Ph D S yrac u se F rac tur e of so lid s, thin film d e po s iti o n a nd g ro w th c orr os ion Mark van Schilfgaarde Ph D. S t a n for d. Me th o d s a n d a ppli ca ti o n s of e l ec tr o ni c s tru c tur e th eo r y, dilut e m ag n e ti c semico ndu c t o r s GW a ppr o xim a ti o n For details concerning graduate opportunities in Chemical and Materials Engineering atASU please call Marlene Bolf at (480) 965-3313 or write to Subhash Mahajan, Chair, Chemical and Materials Engineering Arizona State University Tempe, Arizona 85287-6006 (smahajan@asu.edu). 326 C h emica l E n g i nee rin g Ed u cat i on

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Graduate Program in the Department of Chemical Engineering University of Arkansas The Department of Chemical Engineering at the University of Arkansas offers graduate programs leading to M.S. and Ph.D Degrees Qualified applicants are eligible for financial aid. Annual Departmental stipends provide up to $15,000, Doctoral Academy Fellowships provide up to$20,000, and Distingui shed Doctoral Fellowships provide $30,000. For stipend and fellowship recipients, all tuition is waived. Applications received before April 1st will be given first consideration. Areas of Research [I Biochemical engineering [I Biological and food systems [I Biomaterials [I Chemical process safety [I Consequence analysis of hazardous chemical releases [I Electronic materials processing [I Fate of pollutants in the environment [I Fluid phase equilibria and process design [I Integrated passive electronic components [I Membrane separations [I Mixing in chemical processes Faculty M.D. Ackerson R.E. Babcock R.R. Beitle E.C. Clausen R.A. Cross J.A. Havens W.A. Myers W.R. Penney T.O. Spicer G.J. Thoma J.L. Turpin R.K. Ulrich For more information contact Dr. Richard Ulrich or 479 575-5645 Chemical Engineering Graduate Program Information: http://www.cheg uark.edu/graduate.asp Fall 2003 327 PAGE 90 328 Mark E B y rn e Purdu e Universiry Robert P C hamb e r s University of Ca lif ornia, B erke l ey Harr y T C ullinan Carnegie Mellon Un i versity C hri s tin e W C urti s Florida State Universiry S t ev e R Duk e University of Illi nois Mark R E den Technical Universiry of Denmark Sa id S E .H. E lna s haie Unive r sity of Edin bur gh Jam es A. G uin Univers i ty of T exas, Austin Ram B G uptaUniversity of Texas a t Austin G op a l A. Kri s hna g opal a n Un i ve rsit y of Maine Yoon Y. Lee I owa State Univers i ty Gl e nn o n M aple s O kla h oma Sta t e Univers i ty Ronald D Ne uman The In stit ut e of Pap e r Chemistry l T im o th y D. PlacekUniversiry of K en tu cky C hri s topher B. Robert s Unive r s i ry of Notre Dam e A rthur R. Tarr e r Purdu e U ni vers i ty Bruce J. T a tarchuk University of Wisconsin I Research Areas Fuel Cell Hydrogen Biochemical Engineering Drug Delivery Pulp and Paper Microfibrous Materials Process Systems Engineering Integrated Process Design Environmental Chemical Engineering Catalysis and Reaction Engineering Materials Polymers Nanotechnology Surface and lnterfacial Science Thermodynamics Supercritical fluids Electrochemical Engineering Transport Phenomena Chemical Engineering Educat i on PAGE 91 DEPARTMENT OF CHEMICAL AND PETROLEUM ENGINEERING FACULTY R. G. Moore Head (Alberta) J. Azaiez (Stanford) L.A. Behie (Western Ontario) C. Bellehumeur (McMaster) P. R. Bishnoi (Alberta) J.M. Hill (Wisconsin) A. A. Jeje (MIT) M. S. Kallos (Calgary) A. Kantza s (Waterloo) B. B. Maini (Univ. Washington) A. K. Mehrotra (Calgary) S. A Mehta (Calgary) P. Pereira (France) M. Pooladi-Darvi s h (Alberta) A. Sen (Calgary) A. Settari (Calgary) W. Y. Svrcek (Alberta) M.A. Trebble (Calgary) H. W. Yarranton (Alberta) B. Young (Canterbury, NZ) L. Zanzotto (Slovak Tech. Univ Czec h oslovakia) The D epartment offers graduate programs leading to the M.Sc. and Ph.D. degrees in Chemical Engineering (full time) and the M.Eng. degree in Chemical Engineering Petroleum R eservoir Engineering or Engineering for the Environment (part-time) in the fo ll owing areas: Biochemical Engineering & Biotechnology Biomedical Engineering Upgrading, Catalysis and Fuel Cells Environmental Engineering Modeling, Simulation & Control Petroleum Recovery & Reservoir Engineering Polymer Processing & Rheology Process Development Reaction Engineering/Kinetics Thermodynamics Transport Phenomena Fellowships and Re sea rch Assistantships are available to all qualified applicant s For Ad ditional Informa tion Write Dr. W.Y Svrcek Associate Head, Graduate Studies Department of Chemical and Petr o leum Engineering Univers i ty of Ca l gary Calgary, Alberta, Ca n ada T2N 1N4 E-mai l : gra d s tud @ u calgary.ca Th e University is located in the City of Calgary, the Oil capita l of Canada the home of the world famous Calgary Stampede and the 1988 Winter Ol y mpic s. The City combines the traditions of the Old West with the sophistication of a modem urban cente r. B ea utiful B anff National Park is 110 km west of the City and the ski resorts of Banff, Lake Louise.and Kanana skis a r eas are r ea dil y accessible. In the above photo the University Campus is shown in the fo r eground Th e Engineering comp l ex is on the left of the picture and th e Ol y mpic O va l is on th e ri ght of the picture. Fall 2003 329 PAGE 92 University of California, Berkeley The Chemical Engineering D epart m ent at the University of California B erke l ey, one of the pre emine nt departments in the fie ld offers graduate pro grams leading to the Master of Science and Doctor of Philosophy. Students also have the opportunity to take part in the many c ultural offerings of the San Francisco B ay Area and the recreational activities of California 's n ort h ern coast a nd mountains. FACULTY Nitash P. B alsara Harvey W. Blanch Arup K. Chakraborty David B. Graves Alexander Katz C. Judson King Susan J Muller John M. Prausnitz Jeffrey A. R eimer Alexis T. Bell E lt on J Cairns Dougla s S. Clark Enrique Igle sia Jay D. Keasling Roya Maboudlan John S Newman Clayton J. R adke David V. Sc h affer Rachel A. Segalman Chairman: Arup K. Chakraborty BIOENGINEERING Blanch Clark Keasling Schaffer Chakraborty Muller Prausnitz & Radke KINETICS THER,IODY\A:\IICS TRANSPORT PHENOMENA Ql1AYrt ,1 & STATISTICAL ,1ECHA;\ICS SPECTROSCOPY POLYMERS & SOFT MATERIALS Balsara Chakraborty Muller Prausnitz Radke Reimer & Segalman CATALYSIS & REACTION ENG Bell Chakraborty Iglesia Katz & Reimer ELECTROCHEMICAL ENGINEERING Cairns Newman & Reimer ENVIRONMENTAL ENGINEERING Bell Graves Iglesia Keasling & King MICROELECTRONICS PROCESSING & MEMS Graves Maboudian Reimer & Segalman FOR FURTHER INFORMATION, PLEASE VISIT OUR WEBSITE: http://cheme.berkeley.edu/index.shtml 330 Chemical Engineering Education PAGE 93 Dam E. Block. Associate Professor Ph.D., University of Minnesota I 9IJ2 Industrial fermentation, biochemical processes in pharmaceutical industry Roger B. Boulton, Professor and Endowed Chair Ph D. University of Melbourne, 1976 W,ne technol ogy,fermenJatiion kinetics, biochemical Nigel D. Browning, Professor Ph.D. University of Cambridge, U.K., 1992 Materials structure-prop erty relati011Ships at atomic-scale atomic resolution and sensiti1ity imaging electron microscopy Stepbanle R. Dungan, Professor Ph.D., Massachusetts Institute of Technology. I 9IJ2 Thermodynamics and transport in micel/ar and microenudsions syslfms, su,factant in/fractions with biological and food macromolecules Roland FaDer, Assistant Professor Ph.D., Max-Planck Institute for Polymer Research, 2000 Molecular modeling of soft-condensed matter Broce C. Gates, Distinguished Professor Ph.D. University of Washington. Seattle, 1966 Catalysis su,face chemistry, catalytic materials nanomaterials. kinetics chemical reaction engineering Jeffery C. Glbeling, Professor Ph.D. Stanford University, 1979 DeformaJion, fracture and fatigut of metals, layered composiles and bane JOIDD8 R. Groza, Professor Ph.D., Polytechnic Institute. Bucharest, 1972 Plasma activated sintering, processing of nanostructured materials and microstructure characterization Mlchael A. Hlckner, Assistant Professor Ph.D .. Vrrginia Tech, 2003 Polymer science fuel cells, mem brane transport Brian G. Higgins, Professor Ph.D., University of Minnesota, 1980 Fluid mechanics and inte,facial phenomena, sol gel processing, coating flows Dam G. Howitt, Professor Ph.D University of California, Berkeley, 1976 Forensic and failure analy sis, electron microscopy, ignition and combustion processes in materials Alan P. Jackman, Professor Ph D ., University of Minnesota, 1968 Eni ironmental transport, nutrient cycling, protein production in plant cell cultures, bioremediation Tonya L Kuhl, Associate Professor Ph.D., University of California, Santa Samara, 1996 Biomaterials membrane interactions intermolecular and intersu,face Jorres in complex fluid syslfms Enrique J. Lam'llia, Professor Ph.D Massachusetts Institute of Technology, I 986 S vnthesis of struc tural materials and composites, nanostructured materials and composites, thermal spray processing Marjorie L. Longo, Associate Professor Ph.D ., University of California, Santa Samara, I 993 Hydro phobic protein design for active control, su,factant microstructure, and interaction of proteins and DNA with biological membranes Karen A. McDonald, Professor Ph.D ., University of Maryland, College Park, 1985 Biochemical engi neering, plant cell cultures, cyanobacterial cultures Amlya K. Mukherjee, Distinguished Professor D.Phil., University of Oxford, 1962 Mechanical behav ior, creep, superp/asticity, nanocrystalline metals and ceramics Zuhalr A. Munir, Distinguished Professor Ph.D., University of California, Berkeley, 1963 Synthesis and processing of materials, field effects in mass transport, nanostructures composiles and FGMS, simulation of field-activated synthesis Alerndra Navrotsky, Distinguished Professor and Endowed Chair Ph.D., University of Chicago, I 967 Thermodynamics of solid malfrials nanomaterials phase equilibria and metastability, high-tem pelTIIIUe calorimetry A1unet N. Paluoglu, Professor Ph.D., Rensselaer Polytechnic Institute, 1984 Process control and process monitoring Ronald J. PblDips, Professor Ph.D Massachusetts Institute of Technology, 1989 Transport processes in bioseparations, Newtonian and non-Newtonian suspension mechanics Robert L Powell, Professor and Chair Ph.D .. Johns Hopkins University 1978 Rheology, susptnsion mechanics, magnetic resonanct imaging of suspensions Subbasb H. Rlsbud, Professor PhD., University of California, Berkeley, 1976 Semiconductor quan tum dots, high T superconducting ceramics, polymer composilfs for optics Dewey D .Y. Ryu, Professor Ph.D Massachusetts Institute ofTechnology, 1967 Biomoltcular process engintering and recombinant bioprocess lfchnology Julie M. Schoenug, Associate Professor Ph.D Massachusetts Institute ofTechnology, 1987 Materi als systems analysis, pollution prevention and waste minimization, process economics James F. Shackelford, Professor Ph.D., University of California, Berkeley, 1971 Structure of materi als, biomattrials nondestructive testing of engintering materials J.M. Smith, Professor Emeritus Sc.D., Massachusetts Institute of Technology, I 943 Chemical kinetics and reactor design Pieter Stroeve, Professor ScD Massachusetts Institute of Technology, 1973 Membrane separations, se/f-asmnbly, colloid and su,face science, nanotechnology, su,face modification, biotechnology Sleplien Whitaker, Professor Emeritus PhD., University of Delaware, 1959 Multiphase transport phenomena Fa/12003 Department of Chemical Engineering & Materials Science I UCDAVIS I The multifaceted graduate study experience in the Department of Chemical Engineering and Materials Science allows students to choose research projects and thesis advisers from any of our faculty with expertise in chemical engineering, biochemical engi neering, and/or materials scie nce and engineering. Our goal is to provide the financial and academic support for students to complete a substantive research project within 2 years for the M.S. and 4 years for the Ph D Davis is a small, bike-friendly university town located 17 miles west of Sacramento NTO and 72 miles northeast of San Francisco within driving distance of a OE multitude of recreational SAN FRANCISCO activities We also enjoy close collaborations LOCATION: Sacramento : 17 miles San Francisco : 72 miles Lake Ta hoe: 90 miles \.. SAN with national laboratories including LBL, LLNL, and Sandia. For information about our program, look up our web site at http://www. chms. ucdavis. edu. or contact us via e-mail at chmsgradasst@ucdavis edu 331 PAGE 94 UNIVERSITY OF CALIFORNIA Graduate Studies in JR VINE Chemical Engineering and Materials Science and Engineering for Chemical Engineering, Engineering, and Materials Science Majors Offering degrees at the M.S. and Ph.D levels. R esea r c h in frontier areas in chemical engineering, biochemical engineering, biomedical engineering, and materials science and engineering. Strong physical and life science and engineering groups on campus. FACULTY Nancy A. Da Silva (California Institute of Technology) James C. Earthman (Stanford University) Steven C. George (University of Washington) Stanley B. Grant (California Institute of Technology) Juan Hong (Purdue University) Enrique J. Lavernia (Massachusetts Institute of Technolog y) Henry C. Lim (Northwestern University) Jia Grace Lu (Harvard University) Martha L. Mecartney ( Stanford University) Farghalli A. Mohamed (University of California, Berk eley) Daniel R. Mumm (Northwestern University) Andrew J. utnam (University of Michigan) Frank G. Shi (California Institute of Technolog y) Vasan Venugopalan (Massachusetts In stitu te of Technolog y) Joint Appointments: G. Wesley Hatfield (Purdue University) Noo Li Jeon (University of Illinois) Sunny Jiang (University of South Florida) Roger H. Rangel (University of California, Berkeley) William A. Sirignano ( Princeton University) Adiunct Professors Russell Chou (Carnegie Mellon University) Andrew Shapiro (University of Califoria, Irvine) Victoria Tellkamp (University of Califoria, Irvine) The 1,510-acre UC Irvine campus is in Orange County, five miles from the Pa cific Ocean and 40 miles south of Los Angeles. Irvin e is one of the nations fastest growing residential i ndustrial and business areas Nearby beaches, mountain and desert area recreational activities, and local cultura l activities make Irvin e a pleasant city in which to live and study. For further information and application forms, please visit http://www .e ng.uci.edu/chems/ or contact Department of Chemical Engineering and Materials Science School of Engineering University of California Irvine, CA 92697-2575 Biomedical Engineering Bioreactor Engineering Bioremediation Ceramics Combustion Composite Materials ContJ'Ql and Optimization Environmental Engineering Fuel Cell Systems lnterfacial Engineering Materials Processing Mechanical Ptoperti.es Metabolic Engineering Microelectronics Processing and Modeling Microstm:tureof Materials Mbttifuiictiona Maferials Nanocrystaltine Materials Nanoscale Electronic Devices Nucle8tkin, CliiBli Pi()cess P~ Power and Propulsion Materials Recombbiai1tCell Tealtaotogy Separation Processes Sol-Gel~ Two-Phase Flow Water Pollution Control 332 Chemi c al Engineering Education PAGE 95 CHEMICAL ENGINEERING AT FOCUS AREAS Molecular and Cellular Bioengineering Process Systems Engi neering ( De s ign Optimization Dynam ics and Control ) Semiconductor Manufacturing GENERAL THEMES Energy and the Environment Nanoengineering PROGRAMS UCLA 's Chemical Engineering Department offers a program of teaching and research linking fundamental engineering science and industrial practice. Our Department ha s strong graduate research programs in Bioengineer ing, Energy and Environment Semiconductor Manufacturing Engineering of Material s, and Proce ss and Control Systems Engineer ing. Fellowships are available for outstanding applicants intere s ted in Ph D degree program s. A fellowship include s a waiver of tuition and fees plus a sti pend. Located five miles from the Pacific Coa s t UCLA's attractive 417-acre campus extends from Bel Air to Westwood Village. Students have access to the highly regarded science pro grams and to a variety of experiences in theatre, music, art, and s port s on campus. CONTACT FACULTY J.P. Chang (Wi lliam F. Se ye r C hair in Mat e rials Electrochem i stry) P. D. Christofides Y. Cohen J. Davis (Vice Chan ce llor fo r l nfonnation Technology) S. K. Friedlander ( Par sons Profe sso r of Chemical Engin ee ring) R. F. Hicks L. Ignarro ( Nobel Laur e ate) E. L. Knuth ( Prof e ssor Em e ritus) J.C. Liao V. Manousiouthakis H. G. Monbouquette K. Nobe G. Orkoulas L. B. Robinson ( Professor Emerillls) S.M.Senkan Y.Tang W. D. Van Vorst ( Prof essor Em e ritus) V. L. Vilker ( Professor Emeritus) A.R. Wazzan ( D ea n Emeritus) Admissions Office Chemical Engineering Department 5531 Boelter Hall UCLA Los Angeles, CA 90095-1592 Telephone at (310) 825-9062 or visit us at www.chemeng.ucla.edu Fall 2003 333 PAGE 96 University of California, Riverside Department of Chemical and Environmental Engineering Offering degrees at the M.S and Ph.D levels in frontier areas of Chemical, Biochemical and Biomedical, Advanced Materials, and Environmental Engineering. We welcome you interest and would be delighted to discuss with you the details of our graduate program your admission into our graduate program or your interest in our research RESEARCH AREAS FACULTY Bioand Chemical Sensors Wilfred Chen Caltech MEMS/NEMS Bio-MEMS Structural Bioinformatics David R. Cocker Caltech Biomolecular Engineering Marc A. Deshusses ETH Zurich Environmental Biotechnology Catalysis and Biocatalysis Robert C Haddon Penn State Nanostructured Materia l s E r ic M.V. Hoek Yale Carbon Nanotubes Complex Fluids & Colloids Mark R. Matsumoto UC Davis Electrochemistry Dimitrios Morikis Northeastern Zeolites & Fuel Cells Membrane Processes Ashok Mulchandani McGill Aerosol Physics Nosang V. Myung UCLA Atmospheric Chemistry Renewable Fuels Joseph M. Norbeck Nebraska Advanced Vehicle Technology Mih r i Ozkan UC San Diego Water/Wastewater Treatment Advanced Water Reclamation J i anzhong Wu UC Berkeley S i te Remed i ation Processes Yushan Yan Caltech The University of California Riverside (UCR) is the fastest growing and most ethn i cally diverse of the 1 O campuses of the University of California UCR is located on over 1 100 acres at the foot of the Box Springs Mountains about 50 miles east of Los Angeles Our picturesque campus provides convenient access to the vibrant and growing Inland Empire and is within easy dr i ving distance to most of the major cultural and recreational offerings in Southern California. In addition it is virtually equ i distant from the desert the mountains and the ocean. This is an i dea l setting for students faculty and staff seeking to study work and live i n a community steeped in rich heritage offer i ng a dynamic mix of arts and entertainment and an opportunity for affordable living 3 34 For more information and application mater i als please visit: http://www.engr.ucr.edu/chemenv or contact: Graduate Advisor Department of Chemical/ Environmental Engineering, University of California Riverside, CA 92521 Chemical Engineering Education PAGE 97 Chemical Engineering at the CALIFORNIA INSTITUTE OF TECHNOLOGY '~t the Leading Edge" Frances H. Arnold Anand R. Asthagiri John F. Brady Mark E. Davis Richard C Flagan George R. Gavalas (Emeritus) Konstantinos P Giapis Sossina M. Haile Julia A. Kornfield Aerosol Science Applied Mathematics Atmospheric Chemistry and Physics Biocatalysis and Bioreactor Engineering Biomaterials Biomedical Engineering Bioseparations Catalysis Chemical Vapor Deposition John H. Seinfeld Christina D. Smolke David A. Tirrell Nicholas W Tschoegl (Emeritus) Zhen-Gang Wang Combustion Colloid Physics Fluid Mechanics Materials Processing Microelectronics Processing Microstructured Fluids Polymer Science Protein Engineering Statistical Mechanics For further information writ e __________________ Fa ll 2003 Director of Graduate Studies Chemical Engineering 210-41 California Institute of Technology Pasadena California 91125-4100 Also visit us on the World Wide Web for an on-line brochure : http: // www che caltech edu 335 PAGE 98 '1 .......... ~~~--::: ............... . .. .. . . . .... ... \ ....... PAGE 99 Case Western Reserve University M.S. and Ph.D. Programs in Chemical Engineering Research Opportunities Advanced Energy Systems Fuel Cells and Batteries Micro Fuel Cells Batteries Hydrogen Infrastructure Energy Storage Membrane Transport Membrane Fabrication Biomedical Engineering Transport in Biological Systems Biomedical Sensors and Actuators Wound Healing Inflammation and Cancer Metastasis Neural Prosthetic Devices Biomaterials Biomemetics Advanced Materials and Devices Diamond and Nitride Synthesis Coatings, Thin Films, and Surfaces In-Situ Diagnostics and Sensors Fine Particle Science and Processing Polymer Nanocomposites Electrochemical Microfabrication Self Assembly Chemistry Fall 2003 For more information on Graduate Res ea r ch, Admission, and Financial Aid, contact: Graduate Coordinator Department of Chemical Engineering E-mail: grad@cheme.cwru.ed u Web: http://www.cwru.edu/cse/eche Faculty John Angus Harihara Baskaran Robert Edwards Donald Feke Daniel Lacks Uziel Landau Chung-Chiun Liu J.Adin Mann Heidi Martin Peter Pintauro Syed Qutubuddin Robert Savinell Thomas Zawodzinski Case Western Reserve University 10900 Euclid Avenue Cleveland, Ohio 441067217 337 PAGE 100 O p p ortunities for G ra d uate Stud y in Chemical Engine e ring at the UNIVERSITY OF CINCINNATI M.S. and Ph.D. Degrees in Chemical Engineer i n g Faculty Carlos Co Joel Fried Rakesh Govind Vadim Guliants Daniel Hershey Chia-chi Ho Sun-Tak Hwang Yuen-Koh Kao Soon-Jai Khang William Krantz Jerry Y. S. Lin Neville Pinto Peter Smirniotis The faculty and students in the D epartment of Chemical Engineering are engaged in a dive rs e range of excit in g research topics. Assistantships and tuition scholarships are availab l e to highly qualified applicants to the MS and PhD degree programs. A d va nc e d M at e rial s Inor ganic membranes, nanostructured materials, microporous and mesoporous materials, thin film technology, fuel cell and sensor materials Biot e chnolo gy Financial Aid Available Nano/microbiotechnology, novel bioseparation techniques, affin i ty separation, biodegrada tion of toxi c wastes, cont r o ll ed drug delivery, two-phase flow C atal ys i s and C h e mical R e ac t ion E n g in eer in g 338 Th e University of Cincinnati is co mmitt ed to a poli cy of non-discrimination in awarding financial aid. Fo r A dmi ss i o n Info r m a ti on Director, Graduate Studie s Department C h e m ical and Materials E n g i neering PO Box 210171 University of Cincinnati Cincinnati, Ohio 45221-0171 E -m a il : deena.good @ uc .e du or ykao@alpha.che.uc.edu H e t eroge neou s ca tal ys i s, env ironm enta l ca tal ysis, z eolite catalysis, novel chemical reactors, modeling and design of chemical reactors, polymeri z ation processes in interfaces, membrane reactors E n vi ronm e ntal R ese arch D es ulfuri zat ion and denitrication of flue gas, new technologies for coal combustion power plant, wastewater treatment, removal of volatile organic vapors Me mbran e Te chnolo gy Membrane synthesis and charac t e ri zat i o n membrane gas separation, membrane filtration pro cesses, p e r vapo ration, biomedical, food and environmenta l applications of membranes hi gh-tem peratur e membrane technology, natural gas processing by membranes Pol y m e r s Th ermo d yna mi cs polymer blends and composites, high-temperature polymers hydrogels, polymer rheology, computat ional polymer science, molecular engineering and synthes i s of surfactants, surfactan t s and interfacial phenomena Se p a ration Tec hnolo g i es Membrane separation adsorption chromatography, separation system synthesis, chemical rea ction -ba sed separation processes Chemical Engineering Education PAGE 101 Chemical Engineering at The City Colleg e of New York CU NY (The City University of New York) A 154-year-old urban University, the oldest public University in America, on a 35-acre Gothic and modern campus in the greatest city in the world FACULTY RESEARCH: 0 Andreas Acrivos* oos Rheolo gy of co nc e ntrated s u s pen s i o n s; Dielectro phore s i s in flo w ing suspensions ; Dynamical sys tems theory and c haoti c particle motions Alexander Couzis: Pol ymo rph selective templat e d crystallization; Molecularly thin organic barrier la yers; Surfactant facilitated wetting of hydrophobic surfaces; soft materials 0 Morton Denn oo :s: Pol y mer science and rheolog y ; non-Newtonian fluid mechanics Lane Gilchrist: Bioengineering with cellular material s ; Spectroscopy-guided molecular engineering; Structural studies of self-assembling protein s; Bioproce ss in g Robert Graff: Coal liquefaction; Pollution prevention ; Remediation Leslie Isaacs: Pr e par atio n and charac terization of n ove l optical materials; Recycling of pavement materials ; Application of thermo -a nalytic technique s in materials re searc h Jae Lee: Th eo ry of reactive distillation; Process design and control ; Separations; Bioproce ss ing ~ Charles Maldarelli: lnterfacial fluid mechanics and stability ; Surface tension driven flows and rnicrofluidic applica tions; Surfactant adsorption, phase be havior and nanostructuring at interface s Irven Rinard: Proce ss design methodol-ogy; Dynami c process simulation; Micro-re ac tion technology ; Proces s control; Bioproces s ing David Rum sc hitzki: Transport and reaction aspects of arterial disease; Fall 2003 Interfacial fluid mechanics and stability; Catalyst d eac tivation a nd reaction engineering Reuel Shinnaroo: Advanced proce ss design methods ; Chemical reactor co ntrol ; Spinodal decomposition of binary solve nt mixtures ; Process economics; Energy and env ironment systems Caro l Steiner: Pol y mer solutio n s and hydrogels; Soft biomaterials Controlled release technology Gabriel Tardos: Powder technology; Granulation; Fluid particle systems, Electrostatic effects; Air pollution Sheldon Weinbaum 00 : Fluid mechanics, Biotran sport in living ti ss u e; Modeling of ce llular mechanism of bone growth ; bioheat transfer; kidney function Herbert Weinstein: Fluidization and multiphase flows: multiphase chemical reactor analysis and design Multiphase reactor ana l ysis and design ASSOCIATED FACULTY: 0 Jimmy Feng: (Mechanical En g ) Liquid crystals 0 Joel Koplik : ( Phy s ic s) Fluid mechanics ; Molecular modeling; Tran s port in random media 0 Hernan Makse: (Physics) Granular mechanics 0 Mark Shattuck: (Physics) Experimental granu lar rheology; Computationa l granu lar fluid dynamics ; Experimental s patio-temporal co nt rol of panems 0 Levich In stitute Natio nal Acad e m y of Sciences oo National A c adem y of Engineering ,, Ameri c an Academy of Arts and Sciences CONTACT INFORMATION: Department of Chemical Engineerin g City College of New York Convent Avenue at 140th Street New York NY I 0031 www-che.engr.ccny cuny.edu c he.hr@aol.com t ~.A I "' .. ,' .. __ .......... .. .. __ .,.,.. ... .. ... ,,,,,..,..,., ... ... .... .. .. .. ,.. I .. -. ~... I I .. ",. ... .. .. # ~ t. ,. ,, .. ---....... I--:-. ,; -,, ~11::'.;. .. .... ___ ...... 1,. ..... ... ,. ,._ ..... '...: -:' ,, : ,, ,, ..:.:,;, .. .. ... :, .... :, .. ,,, ...... 2" ~~-. ., ,. I .. 339 PAGE 102 Cleveland State University Graduate Studies in Chemical and Applied Biomedical Engineering CSU Faculty A. Annapragada (University of Mi c hi gan) J.M. Belovich (University of Michi ga n ) G. Chatzimavroudis ( Geor g i a In sti tut e of Technology) G.A. Coolman ( C ase W es tern R eserve Univer s ity) J.E. Gatica (State University of New York at Buff a l o) B. Ghorashi (Ohio Stat e University) E.S. Godleski (Corne ll Univer s it y) R. Lustig (Instit ut e of Therm o a nd Fluiddynarnics of the Ruhr-University Bochum Germany) D.B. Shah ( Michigan State University ) O. Tatu ( Arizona State Univer s it y) S.N. Tewari ( Purdue Univ ers ity ) S. Ungarala ( Michigan Technol og i ca l U ni ve r s ity ) CCF Collaborating Faculty J. Arendt ( Ohio State University) B. Davis (Pe nn sy l vania State U niver s i ty) K. Derwin (University of Mi c hi ga n ) A. Fleischman (Case Western R ese rv e University) B. Gopakumaram (Ohio St a te University) M. Grabiner ( Univer s it y of Illinoi s) S. Halliburton ( Vand e rbilt University ) C. McDevitt (U niver s ity of L o ndon U K .) C. McMillin ( Case We s tern Re se rv e Univers it y) A. Ramamurthi ( Oklahom a State University ) S. Ro y ( Ca se We s tern Re se rv e Univer s it y) R. Setser ( Wa s hington U ni ve r s it y) R. Shekhar ( Ohio State University) W. Smith ( Cleveland State Univer s it y) A. van den Bogert (University of Utrec ht The Netherlands) I. Vesely ( University of W es t e rn Ontario Ca nad a) P. Stephen Williams ( Uni ve r s ity of Wale s, U.K.) G. Yue ( University of Iowa ) Engineering Degrees M.Sc. D.Eng. D.Eng. Chemical Engineering Applied Biomedical Engineering Chemical Engineering F e nn College ha s more than 80 years of ex perience in providing outstand in g engineering education Graduate Studie s in Chemical and Applied Biomedical Engineering at Cleve land State University 's (CSU s) Fenn College of Engineering offers a wealth of opportunity in a stim ulatin g environment. Re se arch op portunitie s are available in co ll aboration with the Biomedical -~ r, \ .. >~ ....... 1;\ Engineering Department of the renowned Cleveland Clinic Foundation (CCF), Cleveland 's Advanced Manufacturing Center local and n a tional industry and Federal agen cies to nam e a few. Assistantships and Tuition Fee Waiver s are available on a competitive ba sis for qualified students I_ .. -. ..... \ 'I ; 1 I ,-/ f \".._,, b I f' ,:, ', ~ I Cleveland State University has 16 000 stude nt s enro ll ed in it s academic programs It is lo cated in the centerofthe c it y of Cleveland with many outstanding cu ltural a nd recreational opportu nitie s nearby. RESEARCH AREAS Adsorption Proce sses Agile Manufacturing Artificial Heart V a lve s Biomechanic s Bioreactor Design Bio se paration s Blood Flow Combu s tion Computational Fluid Dynamic s Dru g Delivery Sy s tems Environmental Pollution Control Material s S y nthe sis and Proce ss ing Medical Imaging MEMS Technology Orthopedic Device s Process Modeling and Control Reaction Engineering Stati s tical Mechanics For more information. write to: Surface Phenomena and Mas s Transfer Thermod y namic s and Fluid Phase Equilibrium Tissue Engineering 340 Graduate Program Director Department of Chemical and Biomedical Engineering Cleveland State Univer s ity Cleveland, OH 44115 Telephone : 216-687 -2 569 E-mail: che @cs uohio.edu http://www .csuohio.edu/chemical_engi ne ering/ Tribology Ventricular Assist Device s Zeolite s: S y nthe sis, Adsorption, and Diffu s ion Assistantships and Tuition/Fee Waivers are ava ilable on a competitive basis for qualified st udent s Che mi ca l Engineering Education PAGE 103 University of Colorado at Boulder The Boulder campus has a controlled enrollment of about 22,000 undergraduates and 5,000 graduate students. The beautiful camp u s has 200 buildings of rough-cut sa ndstone with red-tile roofs. The excellent educational opportunities and beautiful location a ttr act outstanding students from every part of the United States and 85 countries. The University of Colorado has its main campus located in Boulder, an attractive community of 90,000 people located at the base of the R ocky Mountain s. Boulder ha s over 300 day s of sunshine per year, with relati vely mild and dry seasons. The city is an active and innovative town that pro vides a rich array of recreational and cultural activities. Department of Chemical and Biological Engineering ~------Fall 2003 Faculty and Research Interests Kristi S. Anseth P o l ymers, Biomat erials, Tissue Engineering Christopher N. Bowman Pol ymers Membrane Materials David E. Clough Pro cess Control, Applied Statistics Robert H. Da vis Fluid Mechanics Bi otechnology, Membranes John L. Falconer Catalysis, Z eolite Membranes R. Igor Gamow Bioph ysics Hi gh Altitude Physiology, Huma n Performance, D iving Ph ysio l ogy Steven M. George Surface Chemistry, Thin Films Nanoengineering Doug Gin Pol y mers Ryan Gill Biote c hnolo gy Christine M. Hrenya Fluidization, Granular Systems, Fluid Mechanics Dhinakar S. Kompala Biotechnology Animal Cell Cultures, Metabolic Engineering J. W ill Medlin He terogeneous Catalysis, Solid-State Sensors, Computational Chemistry Richard D. Noble Membranes Separations W. Fred Ramirez Process Control, Biotechnology Theodore W. Randolph Biotechnology, Supercritical Fluids Robert L. Sani Transport Ph enomena, Applied Mathematics Daniel K. Schwartz lnterfa cial and Colloid Science Alan W. Weimer Ceramics Energy, R eaction Engineering Graduate students ma y participate in the interdisciplinary Bi otechnology Training Program and the interdisciplinary NSF Indu stry/University Cooperative R esearch Center for Membrane Applied Science and Technology and the Center for Fundamentals and Applications of Photopol yme ri zations. For information and application Graduate Admi ss ions Committee Department of Chemical and Biological Engineering University of Colorado Boulder CO 80309-0424 Phone (303) 492-7471 Fax (303) 492-4341 E-mail chemeng@spot.colorado.edu http://www Colorado.EDU/che/ 341 PAGE 104 :Faculty R.M. Balct,\in (CSl\I. 19-5) A.L. Bunge (lkrkdey. 198:!) A.M. Dean (Han anl. 1 PAGE 105 Fall 2003 M.S. and Ph.D. programs in chemical engineering RESEARCH IN .. Advanced Proces s Control Biochemical Engineering Biomedical Engineering Chemical Thermodynamics Chemical Vapor Deposition Computational Fluid Dynamics Environmental Biotechnology Environmental Engineering Magnetic Resonance Imaging Membrane Separations Metabolic Engineering Polymeric Materials Porous Media Phenomena Thin Films Tissue Engineering FINANCIAL AID AVAILABLE Teaching and re searc h assis t a nt s hip s pa ying a monthly s tipend plus tuition reimbursement. For applications and further information write Graduate Advisor, Department of Chemical Engineering Colorado State University Fort Collin s, CO 80523-1370 tate University Graduate students in Chemical Engineering at Colorado State University work closely with scientists and engineers who have an international reputation for academic and re search excellence. As a member of this community you will have the oportunity to explore research interests, share ideas and discuss new scientific directions with l eaders in their fields-not only in chemical engineering but also in microbiology chemistry, engineering, and other sciences. The interdisciplinary nature of the research carried out by the chemical engineering faculty at CSU and the cultu r e of cooperative research facilitate this access to experts across departments and colleges. Chemical engineering faculty members and students work jointly with research g roups in electrical, mechanical, and civil engi n eering, mi crobio lo gy, environmental health sciences, chem i stry and veterinary medicine. FACULTY Brian C. Batt, Ph.D. University of Colorado Laurence A. Belfiore, Ph.D. University of Wisconsin David S. Dandy, Ph.D. California Institute of Technology M. Nazmul Karim, Ph.D. University of Manchester James C. Linden, Ph.D. Iowa State University Vincent G. Murphy, Ph.D. University of Massachusetts Kenneth F. Reardon, Ph.D. California Institute of Technology Kristina D Rinker, Ph.D. North Carolina State University A. Ted Watson, Ph.D. California Institute of Technology Ranil Wickramasinghe, Ph.D. University of Minnesota 343 PAGE 106 344 University of Connecticut CHEMICAL ENGINEERING DEPARTMENT Graduate Study in Chemical Engineering BIOCHEMICAL ENGINEERING AND BIOTECHNOLOGY James D. Bryers, Ph.D., Rice University (Joint Appointment ) Biochemical Engineering Biofilm Processes, Biomaterials Ranjan Srivastava, Ph.D., Univ e rsity of Maryland Experimental and Computational Biology, Biomolecular Network Analysis, Stochastic Biological Phenomena, Evolutionary Kinetics Thomas K. Wood, Ph.D., North Carolina State University Microbiological Engineering, Bioremediation with Genetically Engineered Bacteria, Enzymatic Green Chemistry, Biochemical Engineering, Biocorrosion COMPUTER APPLICATIONS Luke E. K. Achenie, Ph.D., Carnegie Mellon University Modeling and Optimization, Molecular Design, Artificial Intelligence, Flexibility Analysis Thomas F. Anderson, Ph.D., University of California at Berkeley Modeling of Separation Processes, Fluid-Phase Equilibria Douglas J. Cooper, Ph.D., University of Colorado Process Modeling, Monitoring and Control Suzanne Schadel Fenton, Ph.D., University of Illinois, Urbana-Champaign Computational Ruid Dynamics, Tu eTw flow ENVIRONMENTAL AND ENERGY ENGINEERING Can Erkey, Ph.D., Texas A & M University Supercritical Fluids, Catalysis, Nanotechnology James M. Fenton, Ph.D., University of Illinois, Urbana-Champaign Electrochemical and Environmental Engineering, Mass Transfer Processes, Electronic Materials, Energy Systems, Fuel Cells Joseph J. Helble, Ph.D., Massachusetts Institute of Technology Air Pollution, Aerosol Science, Nanoscale Materials Synthesis and Characterization, Combustion POLYMER SCIENCE Patrick T. Mather, Ph.D., University of California, Santa Barbara Polymers, Microstructure and Rheology, Liquid Crystalinity, Inorganic-Organic Hybrids Richard Parnas, Ph.D., University of California, Los Angeles Composites, Biomaterials Montgomery T. Shaw, Ph.D., Princeton University Polymer Rheology and Processing, Polymer-Solution Thermodynamics RobertA.Weiss,Ph.D., Un1uAre;tyof University of Massachusetts T """_,.. Polymer Structure-Property Relationships, Connecticut Ion-Containing and Liquid Crystal _____________ Polymers, Polymer Blends Lei Zhu, Ph.D., University of Akron Polymer Phase Transitions, Structures of Block Copolymers, Polymeric Nanocomposites, Biodegradable Block Copolymers for Drug Delivery Emeritus Professors C.O. Bennett, J.P.Bell, A T Di Benedetto G M. Howard, R.W. Coughlin, M B Cutlip School of Engineering University of Connecticut 191 Auditorium Road, Unit 3222 Storrs, Connecticut 06269-3222 Tel: (860) 486-4020 Fax: (860) 486-2959 www.engr.uconn.edu/cheg cheginfo@engr.uconn.edu Chemical Engineering Education PAGE 107 At Cornell University, graduate students in chemical engineering have the flexibility to design research programs that take full advantage of Cornell 's unique interdi sci plinary environment and enable them to pur s ue individualized plans of study. Cornell graduate programs may draw upon the resources of many excellent depart ments and research centers such as the Biotechnology Center, the Cornell Center for Materials Research the Cornell Nanofabrication Facility the Cornell Supercomputing Facility, and the Nanobiotechnology Center Degrees granted include Ma s ter of Engineering, Master of Science and Doctor of Philosophy All Ph D students are fully funded with tuition coverage and attractive stipends. R ese ar c h A r e a s Advanced Materials Processing Bioreactor Engineering Electronic Materials Processing and Microchemical Systems Fluid Dynamics, Stability, and Rheology Polymer Science and Engineering Reaction Engineering: Surface Science Kinetics, and Reactor Design Situated in the scenic Finger Lakes r egion of New York State, the Cornell campus is one of the most beautiful in the country Students enjoy sailing, skiing, fishing, hikin g, bic y cling boating, wine-tasting, and many other activities. For further information, write: ( '/Jl'/11" ul u11t! //1111110/t, 11/u1 l.11t:111c1 nit: ,ei A. Brad Anton Lynden A. Archer P a ulette Clancy '-t; Claude Cohen Ill .... :::! b.o s::: .... ... '5 Lance Collins Matthew P. DeLi sa T. Michael Duncan Jame s R Engstrom Fernando A Escobedo Emmanuel P. Giannelis Yong LakJoo Donald L. Koch Kelvin H. Lee Leonard W. Lion Christopher K. Ober William L. Olbricht David Putnam Michael L. Shuler t, Paul H. Steen Abraham D. Stoock Larry Walker Ulrich Wiesner t member, National Academy of Engineering t member, A m e ri ca n Academy of Arts & Science Director of Graduate Studies, School of Chemical Engineering, Cornell University, 120 Olin Hall Ithaca NY 14853-5201 e-mail: DGS@CHEME.CORNELL.EDU, or "visit" our World Wide Web server at: http://www cheme.comell.edu Fall 2003 345 PAGE 108 Graduate Study & Research in Chemical Engineering at Dartmouth's Thayer School of Engineering 346 Dartmouth and its affil i ated professional schools offer PhD degrees in the full range of science disciplines as well as MD and MBA degrees. The Thayer School of Engineering at Dartmouth College offers an ABET-accredited BE degree, as well as MS Masters of Engineering Management, and PhD degrees The Chemical and Biochemical Engineering Pro gram features courses in foundational topics in chemical engineering as well as courses serving our areas of research specialization: Biotechnology and biocommodity engineering Environmental science and engineering Fluid mechanics Materials science and engineering Process design and evaluation These important research areas are representative of those found in c hemi cal engineering departments around the world. A distinctive feature of the Thayer School is that the professors, students, and visiting scholars active in these areas have backgrounds in a variety of engineering and scientific subdiscip lin es. This intellectual diversity reflects the reality that boundaries between engineering and scientific subdisciplines are at best fuzzy and overlapping It also provides opportu nities for students interested in chemical and biochemical engineering to draw from several intellectual traditions in coursework and research Fifteen full-time faculty are active in research involving chemical engineering fundamentals. Faculty & Research Areas Ian Baker (Oxford) Structure/property relationships of materials, electron microscopy John Collier (Dartmouth) Orthopaedic prostheses, implant/host interfaces Alvin Converse (Delaware) Kinetics & reactor design, enzymatic hydrolysis of cellulose Benoit Cushman-Roisin (Florida State) Numerical modeling of environmental fluid dynamics Harold Frost (Harvard) Microstructural evolution, deformation, and fracture of materials TiUman Gerngross (Technical University of Vienna) Engineering of glycoproteins, fermentation technology Ursula Gibson (Cornell) Thin film deposition, optical materials Francis Kennedy (RPI) Tribology, surface mechanics Daniel R. Lynch (Princeton) Computational methods, oceanography, and water resources Lee Lynd (Dartmouth) Biomass processing, pathway engineering, reactor & process design Victor Petrenko (USSR Academy of Science) Physical chemistry of ice Horst Richter (Stuttgart) Thermodynamics, multiphase flow, energy conversion, process design Erland Schulson (British Columbia) Physical metallurgy of metals and alloys Charles E. Wyman (Princeton) Biomass pretreatment & hydrolysis, cellulase synthesis & kinetics, process design For further information, please contact: Chemical Engineering Graduate Advisor Thayer School of Engineering Dartmouth College Hanover, NH 03755 http://thayer.dartmouth.edu/thayer/research/chem-biochem Chemical Engineering Education PAGE 109 University of Delaware www.che.udel.edu/ Faculty Mark A. Barteau (Robert L. Pigford Professor; C h air) Surface Chemistry, Cata l ysis, Kinetics, Spectroscopy, Scanning Probe Mic r oscop i es, Materials I Mfl'' \ .. --~ \ \\ \ l'"P __ -.-., Q; .. Antony N. Beris Fl ui d Mec h a n ics, Viscoelasticity No n equilibri u m T h e r modynamics Numerical Me th ods, P ara ll el Computing Douglas J. Buttrey O x.i d es, Thermodynamics, Crysta l Grow th Str u c t ure Cata l ysis, S u perconducto r s Jingguang G. Chen (Materials Science and E n gineering; Director, Center for Catalytic Scie n ce and Tec h no l ogy) Nanoscale Mic r oe l ectro n ic Devices, Catalytic Ma t e r ials, E n vironmental Cata l ysis Costel D. Denson Materia l s, P o l ymers, Composites, Transport Separa t ions Prasad S. Dhurjati Bio t ech n o l ogy Bioreactors, Modeling, B ioinformatics, Fault Diag n osis, Expert Systems Fall 2003 The Department of Chemical Engineering Th e U n ive r s i ty of Delawar e offer s M.C h. E. and Ph D. degr e e s in Ch e mical Engineerin g Both d eg r ees in v ol v e re s earch and cour se work in e ng i ne e ring and relat e d s ciences The Delaware tradition i s on e of s trong interdi sci plinary r es earch on both fundam e ntal and applied problems. Jeremy S Edwards Quantitative Analysis of Metabolism and Cellular Fate Processes; Bioinformatics and Genomics; Biotechnology and Metabolic Engineering Eric M. Furst Microrheology of Complex Fluids Cellular Mechanics and Movement Structure and Dynamics of Colloidal Crystals lnterfacial Phenomena Eric W Kaler (Elizabeth Inez Kelley Professor ; Dean College of Engineering) Colloids Surfactants, Polymers Thermodynamics Biomolecules Jochen A. L auterbach combinatorial catalysis and high throughput screening, fabrica t ion of conducting polymer nanofilms non-linear phenome na in heterogeneous cata l ysis spectral imaging of diffusion processes in polymers. Abraham M Lenhoff Protein Biophysics, Separations Colloids, Thermodynamics and Transport Raul F. Lobo Adsorption Catalysis, Zeolites, Microporous Materials, Inorganic Materials Synthesis Babatunde A. Ogunnaike Process Control Modeling and Simulation Systems Bi o logy Applied Statistics Christopher J Roberts Kinetics and Statistical Thermodynamic s of Liquids Amorphous Solids (Glasses) Proteins; Kinetics and Thermodynamics of Protein Degradation ; Prediction of Physical and Chemical Stability of Proteins Anne S. Robinson Biochemical Engineering, Biomo l ecule Interactions, Bioreactor Control, Molecular E n gineering, Cellular Engineering T.W. Fraser Russell ( Allan P Co l burn Professor of Chemical Engineering ; Vice Provost for R esearch) Photovoltaics Multiphase Fluid Mechanics Stanley I. Sandler (Henry Belin duPont Chair; D irector Cente r fo r Molecular and Engineeri n g Thermodynamics ) Thermodynamics Statistical Mechanics Comp u tational Chemistry, Environment, Separations, Bioseparations Annette D. Shine Electrorheology Polyme r Processing, Rheology, Supercritical Fluids Dionisios G. Vlachos Surface Chemistry Combustion, Po ll ution Abatement Reactor Design; Nucleation and Growth of Nanophase Materials and Membranes ; Numerical Methods Bifurcation Theory Patterning of Materials Norman J. Wagner Colloid and Polymer Scie n ce, Rheology Statistical Mechanics of Complex Fluids The r modynamic s Biopolymers Brian G. Willis Chem i ca l Physical Mechanisms of Copper Metalization and Semico n d u ctor Interconnect Materials Computational Chemistry Models ofCVD Growth Mechanisms Materials Processing research of Compound Semiconductor Materials for System on a C h ip Integration. Richard P. Wool Polymers Composites, Adhesion, Interfaces, Materials from Renewable R esources Biodegradable P l astics 347 PAGE 110 DTU ... ... .... The Technical University of Denmark (DTU) is a modem technological university which operates at a high international level in a wide array of activities. The University has 6000 st ud ents preparing for Bachelor and Masters degrees, 600 PhD st ud ents and takes 400 foreign students a year on English-taught courses. The DTU campus is located a few kilometers north, but within easy reach of the city of Copenhagen, the capital of Denmark. Research areas and research groups at the Department of Chemical Engineering (KT) http://www.kt.dtu.dk Aerosol Technology, Combustion Processes, Catalysis Bio Process Engineering, Process Control, Systems Engineering Chemical Product Engineering, Combustion Processes Emission Control Polymer Chemistry & Technology, Transport Phenomena Applied Thermodynamics, Oil and Gas Production Membrane Technology Aerosol/lCAT CAPEC CHEC DPC IVC-SEP Membrane Group A satisfactorily completed MSc program is a requirement for admission to the PhD programs at DTU. The Department of Chemical Engineering offers the following MSc programs: MSc in Chemical Engineering Coordinator: Stig Wedel E-mail: sw@k t.dtu dk Web: http://www.adm.dtu.dk/studier/ik/studin/msc/msc chem_eng.htm MSc in Petroleum Engineering Coordinator: Erling H. Stenby E-mail: ehs@kt.dtu.dk Web: http://www.ivc-sep.kt.dtu.dk/petroleum/ MSc in Polymer Engineering and Science Coordinator: Ole Hassager E-mail: oh@kt.dtu.dk Web: http://www.polymers.dk/education/intl-master/ 348 Chemical Engineering Education PAGE 111 DREXEL UNIVERSITY M.S. and Ph.D. Programs in CHEMICAL ENGINEERING RESEARCH AREAS Biochemical Engineering Biomaterials Biomedical Engineering Colloids and lnterfacial Engineering Molecular Dynamics Simulations Plasma Processing Polymer Science and Engineering Process Control and Dynamics Rheology and Fluid Mechanics Safety Engineering Systems Analysis and Optimization Tissue Engineering Transport Phenomena ABOUT DREXEL: Full financial support available FACULTY Charles Weinberger, Head (University of Michigan) Cameron Abrams ( University of California) Richard Cairncross (University of Minnesota) Donald Coughanowr (University of Illinois) Nily Dan (University of Minnesota) Yosseff Elabd (Johns Hopkins University) Elihu Grossmann (University of Pennsylvania) Anthony Lowman (Purdue University) Stephen Meyer (Clemson University) Rajakkannu Mutharasan (Drexel University) Giuseppe Palmese (University of Delaware) George Rowell (University of Pennsylvania) Masoud Soroush (University of Michigan) Margaret Wheatley (University of Toronto) Steven Wrenn (University of Delaware) Department is experiencing a dramatic growth in research funding. Drexel is located in downtown Philadelphia with easy access to numerous cultural activities and major pharmaceutical, chemical and petroleum companies. FOR MORE IN FORMATION WRITE TO: Professor Rich Cairncross cairncross@drexel.edu Department of Chemical Engineering Drexel University, Philadelphia PA 19 104 Or visit us at: http://www.chemeng.drexel.edu Fall 2003 349 PAGE 112 UNIVERSITY OF FLORIDA Graduate Studies in Chemical Engineering leading to M.S. and Ph.D. degrees TIM ANDERSON semiconductor processing thermodynam i cs SEYMOUR S. BLOCK Professor Emeritus biotechnology JASON BUTLER complex fluids flu i d dynam i cs surface phenomena ANUJ CHAUHAN flu i d mechan ics, i nterfac i al phenomena bio mate ri als OSCAR D. CRISALLE process contro l, sem i co n ductors pulp and paper polymer process i ng RICHARD B. DICKINSON ce ll u l ar engineering biomedical engineering ARTHUR L. FRICKE Professor Emeritus polymers pulp & paper characterization GARHOFLUND catalys i s surface s ci ence semiconductors LEWIS JOHNS transpcrt pheno m e n a app l ied mathema ti cs DALEKIRMSE computer -aided des i gn process contro l DMITRY KOPELEVICH 3 50 multi-scale and molecular mode l ing TONY LADD statistical mechanics fluid mechanics, biomechanics ATULNARANG kinetics of microbial growth, env i ronmental bioengineering RANGA NARAYANAN transport phenomena applied mathematics, low gravity processes MARKE.ORAZEM electrochemical engineering CHANG-WON PARK fluid mechanics, polymer processing RAJ RAJAGOPALAN colloid physics, particle science FAN REN semiconductor device fabrication and characterization DINESH. SHAH surface sciences, biomedical engineering SPYROS SVORONOS wastewater treatment particle separations process control JASON F. WEAVER heterogeneous catalysis dynamics of solid C h e mi ca l E n gi n eeri n g Ed u ca t io n PAGE 113 Fall 2003 35 1 PAGE 114 Graduate Studies in Chemical Engineering Join a small, vibrant campus on Florida's Space Coast to reach your full academic and professional potential. Florida Tech, the only indepen dent scientific and technological university in the Southeast, has grown to become a university of international standing. Faculty P.A. Jennings, Ph.D. J.R. Brenner, Ph.D. D.R. Mason, Ph.D. (emeritus) M.E. Pozo de Fernandez, Ph.D R.G. Barile, Ph.D. M.M. Tomadakis, Ph.D. J.E. Whitlow, Ph.D. J .H. Maysilles, Ph.D. Research Partners NASA/Kennedy Space Center Florida Solar Energy Center Florida Institute of Phosphate Research Department of Energy Florida Space Grant For more information, contact Florida Institute of Technology College of Engineering Dept. of Chemical Engineering 150 West University Boule vard Melbourne, Florida 32901-6975 (321) 674-8068 http://che.fit.edu 352 Graduate Student Assistantships and Tuition Remission Available Research Interests Spancraft T l'l"hnolog~ \lkrnatin~ Encr<>\' S ,-,, Olll"l'l'S !\lakrials Sl'iclll'l' Emin F mml'ntal ll"llll'l' ,-.., 1111g Explrt S skms > -.- --_ ______ ....,.. ______ ,..., Chem i cal Engineering Education PAGE 115 Pradeep K Agrawal: hetereogenous catalysis sur face chemistry, reaction kinetics ; Sujtt Banerjee: environmental issues related to the forest products industry; Sue Ann Bidstrup Allen : microelectronics polymer processing; Andreas Bommarius : biocatal ysis, bioprocessing ; Victor Breedveld: complex flu ids, microfluids ; Yulin Deng : colloid and surface science polymer synthesis ; Charles A Eckert: molecular thermodynamics chemical kinetics sep arations; Jeff Empie : chemical and energy recov ery ; Larry J Forney : mechanics of aerosols buoy ant plumes and jets ; Martha A. Gallivan: process control interfacial science ; Dennis W. Hess : m i cro electronics process i ng thin film science and tech nology plasma processes ; Clifford L. Henderson : microelectronics processing patterning, imaging materials, thin films; Jeffery S Hsieh: pulp and paper ; Christopher W. Jones : catalyst develop ment for polymer synthesis organo-metallic chem istry ; Paul A Kohl : photochemical processing chemical vapor deposition ; William J Koros : struc ture-permeability relationships for polymers ceramics, polymer-ceramic hybrid substrates for mation of composite and integrally skinned asym metric membranes ; Jay H Lee : process control, integrated sensing, system identification; Charles L. Liotta : synthesis and properties of polymeric materials computer modeling of chemical process es ; Peter J Ludovice : molecular modeling of syn thetic and biological macromolecules ; J Carson Meredith : colloid and polymer science, technology related to thin films and nanotechnology ; John D Muzzy : polymer engineering energy conservation economics ; Sankar Nair: novel materials nanoscale systems; Athanasios Nenes : atmos pheric modeling ; Robert M Nerem: biomechanics, mammalian cell structures; Mark R. Prausnitz : bio engineering drug delivery, tissue permeabilization ; Matthew J Realff : optimal process design and scheduling; Ronald W. Rousseau: separation processes crystallization ; Athanassios Sambanis: b i ochemical engineering microbial and animal cell structures ; Robert J. Samuels: polymer science and engineering ; F Joseph Schork: reactor engi neering process control, polymerization, reactor dynamics ; Arnold F. Stancell : membranes, poly mers, process economics ; Daniel W. Tedder: process synthesis and simulation chemical sepa ration, waste management, resource recovery; Amyn S Teja: thermodynamic and transport prop erties, phase equilibria supercritical extraction ; Mark G White: catalysis kinetics reactor design; Timothy M Wick: tissue engineering, bioreactor design cell-cell interactions biofluid dynamics ; Ajit P Yoganathan: biofluid dynamics, rheology, trans port phenomena Georgia DD1J@u ulliJu@ @11 Tech D1J@D@~~ SCHOOL OF CHEMICAL AND 8IOMOLECULAR ENGINEERING ate Degree Progr 'f i. .-.,_ ster e,nce .-}: '.;;., { I octot of Philosophy MS in Bioengineering c MS in Polymers l'hD in Bioengineering :PhD in Paper Science and Engineering ,,.. PhD in Polymers n-line Graduate Application .che.gatech.edu/grads.htm ontact Information Dr. Ronald W. Rousseau, Chair School of Chemical and Biomolecular PAGE 116 UNIVERSITY of HOUSTON Chemical Engineering Graduate Progra111 N. R. AMUNDSON (CULLEN PROFESSOR) Chemical Reactions ; T ransport ; Mathematical modeling V. BALAKOTAIAH (JOHN & REBECCA MOORES PROFESSOR) Chemical Reaction Engineer i ng ; Applied mathemat i cs A. T. CAPITANO (ASSISTANT PROFESSOR) Tissue Engineering : In Vitro Toxicology V. M. DONNELLY(PROFESSOR) Plasma Processing: Electron i c Mater i als C. EHLIG-ECONOMIDES (PROFESSOR) Petroleum Engineering ; Simulating Reservoir Flow Behavior M. J. ECONOMIDES (PROFESSOR) Petroleum Engineering ; Energy D. J. ECONOMOU (JOHN & REBECCA MOORES PROFESSOR) Electronic Materials ; Composites and ceramics M. p. HAROLD (Dow PROFESSOR, CHAIRMAN) Chemical Reaction Systems 354 E. J. HENLEY (EMERITUS PROFESSOR) Reliability Engineering ; Biomedical engineering R. KRISHNAMOORTI (ASSOCIATE PROFESSOR) Polymeric Materials ; Biomater i als D Luss (CULLEN PROFESSOR) Chemical Reaction Engineer i ng K. K. MOHANTY (PROFESSOR) Fluid flow in porous media ; Biomaterials M. NIKOLAOU (ASSOCIATE PROFESSOR) Computer aided process engineering J. T. RICHARDSON (PROFESSOR) Catalysis & reaction eng i neering f. M. TILLER (EMERITUS PROFESSOR) Fluid/particle separation P. VEKILOV (ASSOCIATE PROFESSOR) Protein crystallization & Phase transit i ons R. C. WILLSON (ASSOCIATE PROFESSOR) Biomolecular Recognition ; Environmental biotechnology Houston Dynamic Hub of Chemical Engineering Houston offers the educational, cultural business, sports and entertainment advantages of a large and diverse metropolitan area with significantly lower costs and crime rates than average. Houston Is the dominant hub of the US energy and petrochemical industries, as well as the home of NASA's Johnson Space Center and the world-renowned Texas Medical Center. The Chemical Engineering Department at the University of Houston offers excellent facilities competitive financial support and an environment conducive to personal and professional growth. For more information Visit: www chee uh edu Email: grad-che@uh.edu Write: Graduate Office Chemical Engineering University of Houston Houston, TX 77204-4004 C h emica l E n g in ee r ing E d uca ti o n PAGE 117 Chemical Engineering at Where modern instructional and research laboratories, to gether with computing facilities, support both student and faculty research pursuits on an eighty-nine acre main cam pus three miles north of the heart of Washington DC. --Faculty and Research Interests------John P Tharakan, Profes so r and Interim Chair PhD University of California, San Diego Bioproce ss engineering protein separations biological ha za rd o us waste treatment bio-environmental engi neering Mobolaji E. Aluko, Professor PhD University of California, Santa B arbara R eactor modeling crys talli zation microelectronic and ceram i c materials processing process co ntrol r eact ion e ngineerin g analysis Joseph N. Cannon, Pro fessor PhD University of Colorado Transport phenomena in environmental systems computationa l fluid mechanics heat transfer Ramesh C. Chawla, Profes sor PhD, Wayne State University Mass transfer and kinetics in environmental systems bioremediation incineration air and water pollution con trol William E. Collins, Associate Professor PhD University of Wisconsin-Madison Polymer deformation, rheology, and surface science biomaterials bio se parations materials science Robert J. Lutz, Visiting Profes sor PhD, University of Penn sylvania Biom e dical engineering hemodynamics drug delivery pharmacokinetics For further information and applications, w rite to M.S. Program Director. Graduate Studies Chemical Engineering Department Howard University Washington. DC 20059 Phone 202-806-6624 Fax 202-806-4635 Fall 2003 355 PAGE 118 UIC The University of Illinois at Chicago Department of Chemical Engineering MS and PhD Graduate Program FACULTY Piergiorgio Uslenghi, Professor and Interim Head Ph.D., University of Michigan, 1967 E-Mail: uslenghi @ uic.edu Urrnila Diwekar, Professor Ph.D., IIT, Bombay, 1988 E-Mail: urmila@uic.edu John H Kiefer, Professor Emeritus Ph.D., Cornell University, 1961 E-Mail : Kiefer@uic.edu Andreas A Linninger, Associate Professor Ph.D ., Vienna University of Technology, 1992 E-Mail: Linninge@ uic.edu G. Ali Mansoori Professor Ph.D., University of Oklahoma, 1969 E-Mail : Mansoori@uic.edu Sohail Murad, Professor Ph.D., Cornell University, 1979 E-Mail: Murad@uic.edu Ludwig C. Nitsche Associate Professor Ph.D., Massachusetts Institute of Technology, 1989 E-Mail: LCN@uic.edu John Regalbuto, Associate Professor Ph.D., University of Notre Dame, 1986 E-Mail : JRR @ uic .edu Satish C. Saxena, Professor Emeritus Ph.D ., Calcutta University, 1956 E-Mail: Saxena@uic.edu Stephen Szepe Associate Professor Ph.D., Illinois Institute of Technology, 1966 E-Mail: SSzepe@uic.edu Christos Takoudis Professor Ph.D., University of Minnesota, 1982 E-Mail : Takoudis@uic.edu Raffi M Turian Professor Ph D., University of Wisconsin, 1964 E-Mail: Turian@uic.edu Lewis E. Wedgewood Associate Professor Ph.D., University of Wisconsin, 1988 E-Mail : Wedge@uic.edu RESEAR.CH AllEAS Transport Phenomena: Transport properties of fluids, s lu rry transport and multiphase fluid flow. Fluid mechanics of polymers and other viscoe la stic media Thermodynamics: Molecular simu l ation and statis tical mechanics of l iquid mixtures Superficial fluid extraction/retrograde condensation asphaltene c har acteriza tion Kinetics and Reaction Engineering: Gas-solid reaction kinetics Energy transfer processes, l aser diagnostics, and combustion chemistry Environmental technology s urface chemistry and optimization. Catalyst preparation and characterization, supported metals Chemical kinetics in automotive engine emissions Biochemical Engineering: Bioin s trumentation Bioseparations Biodegradable polymer s Nonaqueous enzymology. Optimization of mycobacterial fermentations. Materials: Microelectro ni c materials and processing heteroepitaxy in group IV material s, and in sit u s urf ace spectroscopies at interfaces. Combustion sy nthesis of ceramics a nd sy nthesis in supercritical fluids Product and Process Development and design computer-aided modeling and simulation pollution prevention --------------For more information, write to 356 Director of Graduate Studies Departm ent of Chemical Engineering University of Illinois at Chicago 810 S. Clinton Chicago IL 60607-7000 (3 12) 996-3424 Fax (312) 996-0808 URL: http://www.uic edu/ dept s/chme/ Chemical Engineering Education PAGE 119 UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN _,,:;:: 'F t ~ ... ... :~' \ "'~ Ir --~' Chemical and Biomolecular Engineering The combination of distinguished faculty outstanding facilities, and a diversity of research interests results in exceptional opportunities for graduate education at the University of Illinois at Urbana-Champaign. The Chemical and Biomolecular Engineering Department offers graduate programs leading to the M.S. and Ph.D degrees. For Information and Application Forms, Write to: Department of Chemical and Biomolecular Engineering University of Illinois at Urbana-Champaign 114 Roger Adams Laboratory Box C 3 600 South Mathews Avenue Urbana IL 61801-3602 www chemeng uiuc.edu Department of Chemical & Biomolecular Engineering ~ :: ~ !!!I., THE UNIV E RSITY OF I LL INOI S AT URBANA -C HAMPAIGN Fa ll 2003 I FACULTY Richard C Alkire Electrochemical Eng1neer111g Richard D Braatz Advanced Process Control Steve Granick Polymers and Bro polymers. Nanorl1eoloov Tr,bology. and Surface Spectroscopies Jonathan J L. Higdon Fluid Mechanics ancl Computational Alooritl1ms Paul J. A. Kenis M1croreactors. Microfluirlic Tools. ancl M,crofahricat,011 Sangtae Kim Bioi nf o rmat i cs. M icrof I u irJi cs 1 Nan of I u id ics Mark J. Kushner Plasma Cherrnstry and Plasma Materials Processing Deborah E Leckband Bioeng,neerrng ancl Biophysics Jennifer A Lewis Colloidal AssemlJly. Complex Fl1r,cJs. allCf Mesoscale Fabrication Richard I. Masel Kinetics. Catalysis. Microfuel Ce l ls ancl Mrcroct1e111ical Svstems Daniel W Pack B10111olecular En(Jineer1ncJ ancl Biotechnnlogv Nikolaos V Sahinidis Opt1n11Lation and Process Systems E n gineer r ng Kenneth S Schweizer Macromolernlar Collo1rfal and Complex Fluid T11eory Edmund G. Seebauer M1croelectron1cs Processing and Nanotechnology Michael S. Strano Nanofabricated Materials. Molec u la r Electron r es ancl Fullerene r,J3noteclrnologv Huimin Zhao Molecular B,oenqineering ,rnd Biotectinology Charles F Zukoski Colla r d and lnterfac,al Science 357 PAGE 120 GRADUATE STUDY IN CHEMICAL AND ENVIRO NMENTAL ENGINEERING AT Illinois Institute of Technology THE UNIVE RSITY Pri vate, coed ucational and research univer si ty 1900 under grad uate s tudent s 3200 graduate students Campus recog nized as an architectural landmark Three miles from downtown Chicago and one mile west of Lake Michigan THE DEPARTMENT Among the oldest chemical engineering programs in the nation Merger of chemical and environmental engineering departments in 1995 created s tate-of-the-art, interdisciplinary research and educa tion programs M S., Professional M as ter and Ph.D. degree s in c hemical and environmental engineering New food process engi neering program New double Master's degree program in chemi cal engineering and computer science New internet Master's pro gram in gas engineering Fellowships and assistantships available 358 APPLICATIONS Graduate Admissions Coordinator Chemical and Environmental Engineering Department Illinois Institute of Technology 10 W. 33rd Street Chicago IL 60616-3 7 93 Phone : 312-567-3533; Fax : 312-567-8874 http ://www. chee iit edu / e-mail: chee@iit.edu FACULTY AND RESEARCH AREAS Chairman Hamid Arastoopour Associate Chair for Undergraduate Affairs Fouad Teymour Associate Chair for Graduate Affairs SaJish Parulekar Javad Abbasian; separation processes, gas clea11ing, air pollution Nader Aderangi; unit operations, c h emical processes P a ul R. Anderso n ; precipitation kinetics, evaluat io11 of oxide adsorbents for water and wastewater treatment Hamid Arastoopour; computational multiphase flow, fluidization mat e rial processing, particle technology fluid-particle flow Barry Bernstein ; compu tational fluid mechanics material properties polymer rheology Donald J. Chmielewski; process control, pollution prevention Ali Cinar; chemical and food process contro l nonlinear i11put-output modeling, statistical process monitoring Dimitri Gida s pow ; hydrod y namics of fluidi z ation using kinetic theory, gas-solid transport Henry R. Linden;fossil fuel technologies, energy and resource econo mics energy and enviro nmental policy Demetrio s J. Moschandrea s; ambie11t and indoor air pollution statistical ana l ysis, envi ronm ental impact assessment Allan S. Myerson; crystallization from sol uti on, nucleation, molecular modeling Kenneth E Noll; air resources engineering, air pollution meteorology, ha z ardous waste treatme11t Kri s hna R. Pagilla ; water and wastewater e n gi11ee ri11 g, environme11tal microbi o lo gy, soil rem edi ation sludge treatment Satish Parulekar ; biochemical e11gineering chemical reaction engineering Victor H Perez-Luna ; biomedical and tissue engineering J ai Prakash ; solid state chemistry, materials synthesis and c hara cter i zation for energy conve r sion and storage applications Jay D Schieber; kinetic theory, polymer rheology predictions transport phenomena, non -N ewtonian fluid mechanics Fo u ad A. Teymour; polymer r eaction engineering mathematical model in g, nonli11ear d ynamics David C Venerus; polymer rheology and processing, transport phenomena i11 polymeric sys tems Dar s h T. Wasan; thin liquid films; interfacial rheology; foams em ulsion and dispersion, environmental technologies Research Faculty and Lecturers Said Al-Hallaj In a n e Biro! Michael Caracotsios William Franek George I vanov Ted Knowlton Harold Lindahl R obe n Lyczkowski Zoltan Nagy Alex Niko l ov Gi se ll e Sandi Rob Selman Charle s Sizer Eugene Smotkin Praka s am Tata Allen Tulis Hwa-Chi Wang C h emica l Engineering Education PAGE 121 Graduate program for M.S. and Ph.D. degrees in Chemical and Biochemical Engineering F ACU L TY Gary A. Aurand North Carolina State U. 1996 Supercriti c al fluids / High pressure biochemical reactors C. Allan Guymon U of C ol orado 1997 P o l ymer reaction engineering / UV curable coating s / Po l ymer l iquid cry stal co mposites David Rethwisch U o f Wiscon sin 1985 Membrane science / Polymer science / Catalysis Audrey Butler U of Iowa l 989 Chemical precipitation pro c esses Stephen K Hunter U. of Utah 1989 B i oartificial organs / Microencapsulation technologies V.G.J. Rodgers Washington U. 1989 Transport phenomena in bioseparations / Membrane separations Greg Carmichael U. of Kentucky 1979 Global change / Supercomputing / Ai r pollution modeling Julie LP Jessop Michigan State U. 1999 Pol y mers / Microlithography / Spectros c opy Alec B. Scranton Purdue U 1990 Photopolymerization / Reversible emulsifiers / Polymerization kinetics Chris Coretsopoulos U of Illinois at Urbana Champaign l 989 Photopolymerization / Microfabrication / Spectroscop y David Murhammer U. of Houston 1989 Insect cell culture / Bioreactor monitoring Ramaswamy Subramanian Indian Institute of Science l 992 Structural enzymol ogy / Structure function relationship in proteins r 1. ~ \:,. "\ Vicki H. Grassian U. of California Berkeley 1987 Surface chemistry / Heterogeneous processes Tonya L. Peeples Johns Hopkins 1994 Bioremediation / E x tremophile physiol ogy and b i ocata l ysis John M Wiencek Case Western Reserve 1989 P rotein crystallizati o n / Surfactant techno l ogy For information and application : T H E UNI VE RS 11Y O Fl OWA Graduate A d missions C h e m ica l a nd Biochemical Engine e ring 4133 Seamans Center Iowa City IA 52242 1527 1 800 553 IOWA ( l 800 553 4692 ) chemeng @ icae n .uiowa edu www.eng in ee rin g uiowaedu / chemeng / PAGE 122 IOWA STATE UNNERSITY () ~: S (~ I E NC: E A N D EC H N () L () (i Y Cliemical Engineering ;t:= Graduate Program ::;;: ---Brown, Robert C. fo:,c Rodney O Oleta Chertea a Gonzalea, Ramon Hebert Kurt R Hlll,JamHC. HIiiier, Andrew C Jolla, Kenneth R Lamm Monica H Mllllapra .. da, Surya K N rHlmh~ S.1 11 Rellly. Peter J Rottlne Ditnld; K. Sohr d.,. Glenn L Shanita. Br..-t H 8 h nb, J oqueUne V Vltlll, R Denni Whfflock Th o mae D R obert C Brow n Michigan State L. K. D oralswa m y Wisconsin Ro dn ey O F o x Kansas State Gradu a te Admissi o ns Committee Department o f Chem i ca l E ng i nee ri n g Iowa State Univers i ty Ames, Iowa 50011 515 294-7643 Fax : 515-294-2689 chemengr @ lastate edu www iastate edu/~ch_e Ch a rl es E G latz Wisconsin Ramon G o nzalez Chile K u rt R. Hebert Illinois Ja m es C HIii Washington Andrew C. H Iiiier Minnesota K enneth R. J oll s Illi no i s M o ni c a H. La m m North Carolina State Surya Mall a praga d a Purdue B alajl N a r as imh an Purdue Pet e r J. R ei ll y Pennsylvania ,; i .I f.. I j D e rri ck K. Rollln s Ohio State Gl e nn L. Schrade r Wisconsin Brent H. S hank s Cal Tech Jacquel i n e V. Shan ks Cal Tech R Denn is Vigil M i chigan Thom as D Wheelock Iowa State PAGE 123 Graduate Study and Research in Chemical and Biomolecular Engineering at Johns Hopkins The Johns Hopkins University's Department of Chemical and Biomolecular Engineering, estab lished in 1936, features a low student-to-faculty ratio that fosters a highly collaborative research experience. The faculty are internationally known for their contributions in the traditional areas of chemical engineering research, such as thermodynamics, fluid dynamics, and rheology, and at the forefront of emerging technologies, such as membrane-based separation processes, recombinant DNA technology, tissue engineering, and molecular/cellular biomedical engineering. Mammalian, Insect CeU, and Stem Cell Culture Metabolic Engineering and Biotechnology Apoptosis Glycosylation and Glycomics Michael J. Betenbaugh PhD U ni ve r s it y of Del aware Molecular Thermo d ynamics Adsorption Supercritical Processing Self Assembl y Marc D. Donohue PhD Uni ve r s ity o f Californi a, B e rkele y Active Control of Interfaces Surface Forces and Adhesion Electrochemistry and lnterfacial Electrostatics Joelle Frechette PhD Princ e ton Uni ve r s it y Micro/Nanotechnology Self-Assembly Surface Science of Soft Materials David Gracia s, PhD Uni v er s ity of C a lifornia Berkele y Biomolecular Modeling Protein-Protein Docking Protein-Surface Interactions Self-Assembled Na nomaterials and Devices Jeffrey J Gray, PhD Univer s ity of Texa s a t Au s tin Biomaterials Synthesis Targeted Drug Delivery Biotransport Phenomena Ju s tin S. Hanes PhD Ma ss a c hu s ett s In s titute of Te c hnolo gy Biomaterials and Nanocomposite Materials Macromolecular Transport Rheology of Soft Materials Modeling of the Microcirculation James L. Harden, PhD Unive s ity of California Santa Barbara Nucleation Crystallization Flame Generation of Ceramic Powders Joseph L. Katz, PhD Uni v er s ity of Chica g o Th e John s H op k.in s U ni vers i1 y does n ot discrim in a te on the basi s o f race. co l o r sex re li g i on sex u a l orie n tatio n n a ti o n al or e thn ic origi n age disab il i t y or vetera n status in any s tud e nt p rogra m or activity ad mini s t ere d b y th e U ni ven. it y or w ith regard t o ad m ission or e mp l oy m e nt De fense De partm e nt d i sc rimin a t io n i n R OTC programs o n th e basis of homosex u a lit y con fli cts w ith thi s uni vers it y po l icy. The u n i versi t y i s commi tt ed 1 0 enco ura g i n g a c h an ge in the Def e n se Departm e ni po li cy. Qu est i o n s re gard in g Ti tl e VI litl e IX and Section 504 shou l d be referred to Yconne M Th eodo re Affirmat ive A c ti o n O ffice r 205 G ar l a nd H a ll (4 1 0-5 1 6-8075) Fall 20 0 3 Cell and Molecular Engineering Functional Genomics Fluid Mechanics in Medical Applications Cancer Metastasis Thrombosis and Inflammation/Bacterial Infection Kon s tantino s Kon s tant o poulo s, PhD Ri ce Univer s it y Molecular Bioengineering Protein Engineering Molecular Evolution Marc O s t e rmeier PhD Unive rs it y of Texa s at Austin Surfactant/Supercritical Fluid Phase Behavior Computational Molecular Thermodynamics Polymer/Protein Thermodynamics M ic hael E Paulaiti s, PhD Uni v er s it y of Illinoi s Surfactants and Interfaces Growth and Assembly ofNanoparticles Marangoni Effects K a thl ee n J Steb e, PhD Th e Cit y U ni v er s ity of New York Cell Adhesion and Migration Cystoskeleton Receptor-Ligand Interactions Cancer Epstein-Barr Virus Infection New Proteomics Tools New Microscopies D e ni s Wirt z, PhD Stanford Uni v er s ity For further information contact: John s Hopkin s Uni v er s ity Whitin g S c hool of Engineering Department of Chemical and Biomolecular Engineering 3 400 N Charle s Street Baltimor e, MD 21218-2694 410-516 7170 che @ jhu e du http : //www jhu edu/~cheme OHNS HOPKINS 36 1 PAGE 124 Graduate Study in Chemical and Petroleum Engineering at the UNIVE R SITY OF KANSAS The University of Kansas is the largest and most comprehensive university in Kansas. It has an enrollment of more than 28,000 and almost 2,000 faculty mem bers. KU offers more than JOO bachelors', nearly 90 masters', and more than 50 doctoral programs. The main campus is in Lawrence, Kansas, with other cam puses in Kansas City, Wichita, Topeka, and Overland Park, Kansas. Graduate Programs [I M.S. degree with a thesis requirement in both chemical and petroleum engineering [I Ph.D degree characterized by moderate and flexible course requirement s and a stro ng research emphasis Cl Typical completion times are 16-18 months for a M.S. degree and 4 1/2 years for a Ph.D. de gree (from B.S.) Faculty Kenneth A. Bishop ( Ph .D., Oklahoma) Kyle V. Camarda (Ph.D., Illinois) John C. Davi s (Ph.D. yoming) Stevin H. Gehrke (Ph.D. Minnesota) Don W. Green (Ph .D. Oklahoma) Colin S. Howat (Ph.D., Kansas) Jenn-Tai Liang (Ph. D ., Texas) Carl E. Locke, Jr. (Ph.D., Texas) Trung V. Nguyen ( Ph.D. Texas A&M) Karen J. Nordheden ( Ph.D. Illinois) Ru ssell D. Osterman (Ph.D. Kansas) Marylee Z. Southard (Ph.D ., Kansas) Susan M. Williams (Ph.D. Oklahoma) Bala Subramaniam, Chair (Ph.D ., Notre Dame) Shapour Vossoughi (Ph.D., Alberta Canada) G Paul Willhite (Ph. D. Northwestern) Research Catalytic Kinetics and Reaction Engineering Catalytic Materials and Membrane Processing Controlled Drug Delivery Corrosion, Fuel Cells, Batterie s Electrochemical Reactor s and Processes Electronic Materials Processing Enhanced Oil Recovery Proce sses Fluid Pha se Equilibria and Proce ss De sign Molecular Product De sig n Process Control and Optimization Protein and Tissue Engineering Supercomputer Applications Supercritical Fluid Applications 362 Financial Aid Financial aid is available in the form of research and teaching assistantships and fellowships/scholarships s uch as those noted below. Madison & Lila Self Graduate Fellowship Mission: identify, recruit, and provide development opportunities for exceptional Ph D stude nt s. Four-year award consisting of an annual$20,600 stipend plus full tuition and fees. An additional bonu s of up to $10,000 per year is possible For additional information a nd application: http://www unkans.edu/~ se lfpro/home/index html Kansas and Missouri High School Graduates Scholarship of$22,000 annually, plus full tuition and fees. Contacts Website for information and application: http://www.cpe.engr.ku.edu/ Graduate Pro gram Chemical and Petroleum Engineering University of Kansas-Learned Hall 1530 W. 15 t h Street, Room 4006 Lawrence, KS 660457609 phone : 785-864-2900 fax: 785-864-4967 email: cpeinfo@ku.edu Chemical Engineering Education

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. .,. '" .. .. '. '! ... ... ,. .. Durl a nd H a ll H o m e of C h e mi ca l E n gi n ee rin g KANSAS STATE UNIVERSITY M.S. and Ph.D. Programs Chemical Engineering with Interdisciplinary Areas of : Systems Engineering Environmental Engineering Material Science and Engineering For More Information Write To Professor J. H. Edgar Durland Hall Kansas State Univers i ty Manhattan KS 66506 or visit our web site at http : / / www.engg ksu edu / CHEDEPT / Fall 200 3 Areas of Study and Research Biopolymers Biotechnology Catalytic Hydrocarbon Conversion Chemical Reaction Engineer i ng Crystal Growth o f Semiconductors Environmental Pollution Control Hazardous Waste Treatment Membrane Separations Multiphase Flow Polymeric Mater i als Properties Process Systems Engineering and Art i ficial Intell i gen c e Separat i ve Reactors I i .. 363

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University of Kentucky Department of Chemical & Materials Engineering Catalysis Environmental Engineering Biopharmaceutical & Bi ocellular Engineering The Chemical Engineering Faculty Tate Tsang Chair University of Texas Materials Synthesis Advanced Separatio n & Supercritical Fluids Processing K. Anderson Carnegie-Mellon University D. Bhatta c haryya Illin ois Institut e of Technology A. Geertsema University of Karlsruhe Membranes & Polymers Aerosol s 364 For mor e informa tion: E. Grulke Ohio Stat e University D Kalika University of California Berk e ley M Keane National University of Ir e land R Kennode Northwestern University B Knutson Georgia In stitute of Technology S. R a nkin University of Minnesota A. Ray Clarkson University Paducah KY, Program P Dunbar University of Tennessee R Lee-Desautels Ohio State University D. Silverstein Vanderbilt University J Smart University of Texas Web : http://w ww.e ngr.uky .edu/cme E-mai l : cme-admit@engr.uky.edu Address : Department of Chemical & Materials Engineering Director of Graduate Studies, Chemical Engineering 177 Anderson Hall University of Kentucky Lexington KY 40506-0046 Phone (859) 257-8028 Fax (859) 323-1929 Chemical Engineering Education

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LEHIGH UNIVERSITY Synergistic, interdisciplinary research in ... Bi oc h emical Engineering Catalytic Science & Reaction Engineering Environmental Engineering Interfacial Transport Material s Synthe s i s Characterization & Proce ss ing Microelectronic s Proce ss in g P olymer Science & Engineering Pro cess Modeling & Control Two-Phase Flow & Heat Transfer ... leading to M.S., M .E. and Ph.D d eg rees in Chemical Engineering and P olymer Science and Engineering Highly attractive financial aid packages, which provide tuition and stipend, are available. Philip A. Blythe University of Manchester fluid mechanic s heat transfer applied mathematics Hugo S. Caram, University of Minnesota high temperature processes a nd material s e nvironmental processe s reaction engi n eering Marvin Charles, P olytechnic In stitute of Brooklyn bioproce ss de sign cGMP R & D Manoj K. Chaudhury, SUNY-Buffalo William L. Luyben, University of D elawa r e process design and control di s tillation Anthony J. McHugh, University of D e laware polymer rheology and rheo -o ptics p o l ymer pro cessi ng a nd modeling membrane formation drug delivery William E. Schieser, Prin ceton University numerical a lgorithm s and software in chemical engineering A rup K. Sengupta, University of H ouston adhesion thin films s urface chemistry John C. Chen, University of Michigan use of adso rbent s ion exchange reactive polymers membranes in environmental pollution two-phase vapor-liq uid flow fluidization radiative heat transfer env ironm e nt t ec hn ology Cesar A. Silebi, Lehigh University se paration of co ll oidal particle s e l ectrop h ores i s mass transfer Mohamed S. El-Aasser, M cGill University polymer co ll oids and films emulsion copolymerization polymer sy nthesis and characterization James T. Hsu Northwestern University bioseparations applied recombinant DNA technology Andrew Klein, North Carolina State University em ul sio n polymerization colloidal and s urface effec t s in polymerization Mayuresh V. Kothare California In stitute of Technology model predictive co ntrol constrained control microchemical sys tems Shivaji Sircar, University of P ensy l vania adsorption gas and Equid separa tion Harve y G. Stenger, Jr. Massachusetts In sti tut e of Technolog y reactor engi n eering Kemal Tuzla Technical University of Istanbul heat transfer two-pha se flows fluidization Israel E. Wachs, Stanford University materials c har acterization s urf ace c h emistry h e terogeneou s cata l ysis e n vironmental catalysis Additional information and application may be obtained by writing to: Dr James T. H su, Chairman Graduate Committee D e partm e nt of Chemical Engineering Lehigh University 111 R esearch Dri ve Iacocca Hall B e thlehem PA 18015 Fax: (610) 758-5057 E-Mail: inc he gs@ lehigh. e du Website: www3.lehigh.edu/engineering/cheme/ Fall 2003 365

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I LOUISIANA STATE UNIVERSITY I Gordon A. and Mary Cain Department of Chemical Engineering Baton Rouge is the state capitol and home of the major state institution for higher education LSU. Situated in the Acadian region, Baton Rouge blend s the Old South and Cajun Cultures. Baton Rouge is one of the nation's busiest ports and the city's economy rests heavily on the chemical oil pla stics, and agricul tural industries The great outdoors provide excellent recreational activities year-round, especially fishing, hunting, and water s port s. The proximit y of New Orlean s provides for s uperb nightlife especially during Mardi Gras. The city i s also only two hour s away from the Mis s is si ppi Gulf Coast, a nd four hours from either Gu l f Shores or Houston THE DEPARTMENT------M S. and Ph.D. Program s Approximately 60 Graduat e Students Average research funding more than $2 million per year DEPARTMENTAL FACILITIES Departmental computing-with more than 80 PC s Extensive laboratory facilities especially in reaction and environmental engineering, transport phenomena and separations, polymer, textile a nd materials procesing, biochemical engineering thermodynamics TO APPLY, CONTACT DIRECTOR OF GRADUATE INSTRUCTION Gordon A. and Mary Cain Department of Chemical Engineering Louisiana State University 366 Baton Rouge LA 70803 Telephone: 1(800 ) 256-2084 FAX : ( 225) 578-1476 e-mail: gradcoor @ che.lsu.edu FACULTY A.B. CORRIPIO (Ph .D. Louisiana State University) Control Simulation, Computer-Aided Design K.M. DOOLEY (Ph.D., University of Delaware) Heterogeneous Catalysis High-Pressure Separations G.L. GRIFFIN (Ph D ., Princeton University) Ele c tronic Materials Surfa ce Ch e mistry CVD D.P HARRISON (Ph.D., University of Texas) Fluid-Solid R eactions Ha z ardou s Waste Treatment M.A. HJORTS0 ( Ph.D ., University of Hou sto n ) B iochemical R eaction Engine e ring, Applied Math F.C. KNOPF ( Ph D ., Purdue Univers ity ) Supercritical Fluid Extraction Ultrafast Kinetics B.J. McCOY (Ph.D. University of Minnesota) Separation, Transport Rea c tion Engineering R.W. PIKE ( Ph D. Georgia Institute of Technology) Fluid D y namics R eaction Engineering, Optimi z ation E.J. PODLAHA (P h D ., Columbia University) El ec trical Phenomena, Allo y and Composite Material s D.D. REIBLE ( Ph.D. California Institute of Technology ) Environmental Transport, Transport Modeling J.J. SPIVEY (Ph.D ., Louisiana State University) Catalysis L J. THIBODEAUX (P h .D. Louisiana State University) Chemodynami cs, Ha z ardous Waste Transport K.E. THOMPSON (P h D ., University of Michigan) Transport and R eaction in Porou s Media K.T. VALSARAJ (P h.D ., Vanderbilt University) Environmental Transport, Separations D.M. WETZEL ( Ph D ., University of Delaware ) Ha z ardous Wast e Treatment, Drying M.J. WORNAT ( Ph.D ., Ma ss achusetts Institute of Technology ) Combustion H eterogeneous R e a c tions FINANCIALAID -------Assistantship s a t$ 17 500 $29,200, with waiver ofout-of-state tuition Chemical Engineering Education PAGE 129 UNIVERSITY OF---LQUJSJANA Lafayette MS in Engineering Chemical Engineering Faculty C.S Fang, PhD University of Houston TX (1968) F.F. Fars h ad PhD University of Oklahoma OK ( 1975 ) J D Garber (Head), PhD Georgia In st itute of Technology GA ( 1971 ) A.G. Hill PhD Loui s iana Technical University, LA ( 1980 ) R.D.K. Misra PhD University of Cambridge UK ( 1984 ) B.L. Newman PhD University of Virginia, VA ( 1988) A B Ponter DSc Birmingham University, UK (1986) PhD Manchester ( 1966 ) J.R. Reinhardt PhD University of Arkansas AR ( 1977 ) Research Centers Corrosion R ese ar c h Center Dr. J D Garber Director Center for Metal s, Pol y m ers and Composites R esearch Dr R D K Mi sra, Director Edith Garland Dupre Library For more information: Research Areas Corrosion Ga s and Oil Well Modeling Pipeline Steels H ydrogen -Induced Cracking Materia l s: Structure/Processing/Performance Irr a di at ion of Polymers with UV /Ozone Deformation Behavior of Polymers a nd Composites Formability and Fracture Toughnes s of High-Strength Steels Cold Work Embrittlement of Interstitial Fr ee Steel s Casting of Precious Metals and Alloy s Fluid Flow and Transport Phenomena Ph ase Inversion Drop Coale sce n ce Liquid Spreading Multiphase Flow Surface Roughness Thermodynamics and Process Engineering Pha se Equilibria in Multiphase Systems Chemical Reactor De s ign Stability and Dynamic s Proce ss Simulation and Design Department of Chemical Engineering University of Louisiana at Lafayette PO Box 44130 Lafayette LA 70504-4130 www.lo ui siana engr.edu/chee/ or e-mail: drnisra@louisiana .e du (Graduate Coordinator) Fall 2003 367 PAGE 130 MANHATTAN 368 COLLEGE This well-established graduate program emphasizes the application of basic principles to the so lut ion of mod em engineeri n g problems, with new fea tur es in engi neering management, environmental management and biochemi cal engineering T Financial aid is available incl ud ing industrial fellowships in a one-year program involving participation of the following companies: ABB Lummus Global Inc. Air Products and Chemicals, Inc. Chevron Texaco Global ConocoPhillips Consolidated Edison Co. Kraft Foods Merck & Co., Inc Pfizer Inc. For information and application form write to Graduate Program Director Chemical Engineering Department Manhattan College Riverdale, NY 10471 chmldept@manhattan.edu http://www .e ngineering .ma nhattan.edu Offering a Practice-Oriented Masters Degree Program zn Chemical Engineering Manhattan College is located in Riverdale, an attractive area in the northwest section of New York City. Ch e mi c al En g in ee rin g Edu c ation PAGE 131 CHEMICAL ENGINEERING UNIVERSITY OF Faculty and Research Areas Ra y mond A A domaiti s (IIT) Systems modeling and simulation methodologies; semiconductor manufacturing Mikhail A A nisimo v (Moscow) Critical phenomena and phase transitions in fluids and fluid mixtures Timoth y A. Barbari (Texas-Austin) Membrane science, polymer science, biomaterials William E. Bentle y (Colorado) Biochemical/metabolic engineering, applications of molecular biology Richard V Calabrese (Massachusetts) Multiphase flow, turbulence and mixing K y u Yong Choi (Wisconsin) Polymer reaction engineering Panagiotis Dimitrakopoulo s (Illinois-Urbana) Biofluid mechanics, biophysics and microrheology Sher y l H. Ehrman (U C LA) Aerosol and nanoparticle technology John P. Fisher (Rice) Tissue engineering, biomaterials James W. Gentr y (Texas-Austin) Aerosol science and engineering Sandra C Greer (Chicago) Physical chemistry, polymer science, biomacromolecules, phase equilibria Maria I. Klapa (MIT) Metabolic engineering, bioinformatics, modeling of biological networks Peter Kofinas (MIT) P olymer science and engineering Thomas J. McA v o y ( P rinceton) Process control, fault detection Trace y R. Pulliam Holoman (Maryland) Biochemical engineering and bioremediation Jan V. Senger s (U. Amsterdam) Critical phenomena, thermophysical properties of fluids and fluid mixtures Srinivasa R. Ragha v an (N C. State) P olymers, colloids, complex fluids, self assembly Nam Sun Wang (Caltech) Biochemical engineering William A. Weigand ( IIT ) Biochemical engineering, bioprocess control and optimization E v anghelos Zafiriou (Ca l tec h ) Process control, identification and optimization Location: The University of Maryland is l ocated in close proximity to the nation's ca p i t al, W as h ing ton D.C. and a number of government la b oratories, including NIST, NIH, NRL, ARL, US D A, a n d F DA. For Applications and Further Information, Write Graduate Admissions Director Department of Chemical Engineering Room 2113 Building 090 University of Maryland College Park, MD 20742-2111 http://www.ench.umd.edu Fall 2003 369 PAGE 132 370 UMBC University of Maryland Baltimore County EMPHASIS The Department of Chemical and Biochemi cal Engineering at UMBC offers graduate programs leading to M .S. and Ph D. degree s in Chemical Engineering. Our research i s heavily focused in biochemical biomedical, and bioproces s engineering and covers a wide range of areas including fermentation, cell culture, downstream proces si ng drug delivery protein engineering, and bio -o ptic s. Unique programs in the regulatory-engineer ing interface of bioprocessing are offered as well. FACILITIES The Department offers sta te-of-the-art facilities for faculty and graduate student research. These modern facilities have been developed primarily in the la st six years and comprise 6,000 square feet of laborator y space in the Technology Re searc h Center plus 7 000 square feet of departmental laboratorie s in the new Engineering and Computer Science building LOCATION UMBC i s located in the Baltimore-Washing ton corridor and within easy access to both metropolitan areas. A number of government research facilities such as NIH, FDA, USDA, NSA and a large number of biotechnology companies are located nearby and provide excellent opportunities for re searc h interac tions. FOR FURTHER INFORMATION CONTACT: Graduate Program Coordinator Department of Chemical and Biochemical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore Maryland 21250 Phone: (410) 455-3400 FAX: (410) 455-1049 Graduate Study in BIOCHEMICAL ENGINEERING For Engineering and Science Majors FACULTY D. D. FREY, Ph.D. California-Berkeley Biochemical separations; Chromatography of biopolymers T. GOOD, Ph.D. University of Wisconsin-Madison Cellular Engineering; Protein Aggregation: In Vitro Models of Disease M. R. MARTEN, Ph.D. Purdue Proteome analysis; Cellular, bioprocess, and bio medical engineering. A. R. MOREIRA, Ph.D. Pennsylvania rDNA fermentation; Regulatory issues; Scale-up; Downstream processing G. F. PAYNE, Ph.D.* Michigan Biomolecular engineering; Biopolymers; Renew able resources. G. RAO, Ph.D. Drexel Fluorescence-based sensors and instrumentation; Fermentation and cell culture. J.M. ROSS, Ph.D. Rice Cellular and biomedical engineering; Cell adhesion; Tissue engineering Joint appointment with the University of Maryland Biotechnology Institut e Chemical Engineering Education PAGE 133 Come to Chemical Engineering at the University of Massachusetts Amherst 1 \mlll'rst is a prett) New England college tmrn in Western l\lassadmsetts. Set amid farmland and rolling hills, the area offers pleasant living conditions and extensive recreational fadlities, and urban pleasures are easily accessible. Fall 2003 Faculty M.F. Malone (Massachusetts), Head S.R. Bhatia (Princeton) W.C. Conner, Jr (Johns Hopkins) J.M. Davis (Princeton) J M. Douglas, Emeritus (Delaware) N.S. Forbes (Berkeley) M.A. Henson (UC Santa Barbara) R.L. Laurence, Emeritus (Northwestern) D. Maroudas (MIT) P.A. Monson (London) S.C. Roberts (Cornell) J.J. Watkins (Massachusetts) P.R. Westmoreland (MIT) H H. Winter (Stuttgart) C urr ent Areas of MS and Ph D R esearch Proce ss design : Methods, distillation, process control Materials: Polymers and inorganics multiscale modeling Kinetics and reaction engineering : Catalytic biological noncatalytic Molecularly based modeling: Stati s tical mechanics quantum chemistry, molecular simulations Fluid mechanics and polymer rheology Bioengineering and biomaterials Supercritical fluid processing For application forms and further information on fellowships and a ssis tantship s, academic and research programs, and stu d ent housing, see: http://www.ecs.umass.edu/che or w rite: Graduate Program Director Department of Chemical Engineering 159 Goessmann Laboratory, 686 N. Pleasant St. University of Massachusetts Amherst, MA 01003-9303 Th e University of Massachu se tt s Amherst prohibit s di sc rimination on the basi s of race, color religion, creed, s ex, sexual orientation age, marital s tatus national origin di sa bilit y or handi cap, or veteran stat u s, in any as pe ct of the admission or tre atme nt of stude nts or in emp lo y ment. 371 PAGE 134 372 Chemical Engineering at \1/T i.1 located i11 Cambridge, just acros tile Cliarll'.1 Rfrer.fi o111 B11.1t1111. a.It ll' 111i1111tc.1 by 11bway.fi dow11t1111 Bo.1t1111 a11d llanard Squarl'. Tile arl'a i.1 11 11rld-r1'11ow11cd .fiir it.1 collcgc.1, lw ,pital.1, rc ,carcli ./<1cilitic 1, and high tcc/11111/ogy i11d11 ,tril' 1, and 11/f'<'n a11 1111l'mli11g raril'ly 11/' tlicatcr 1 c1111ccrts, rl'.1tt11ira11t.1, 11111.11'11111.1, b1111k.1torcs, .1porti11g '1c11ts, libraries, and rl'c rca ti o 11a I .f PAGE 135 McMaster Graduate Studies In Chemlcal Engineering University ENGINEERING We offer a Ph. D. program and three Master's options (Thesis, Project, Internship) in the following research areas : Bloaaterlala: Tissue engineering, biomedical engineer i ng, blood-material interactions J.L. Brash, K. Jones, H. Sheardown, Bloproce .. l g: Membranes environmental engineering, bioseparation fermentation, recombinant proteins L. Crossley, C. Fillpe, R. Ghosh, Transport Plle oae a: Heat transfer experimental & computational fluid mechanics membranes J. Dickson, A. N. H,ymak, P.E. Wood Polyaer Sde ce: Pulp & paper science, polymerization polymer characterization synthesis A. E. Hamielec (Emeritus), R. H. Pelton, S Zhu, K. Kostanski (Adjunct) Polyaer E gl eerl g: Polymer processing, rheology, CAD/CAM methods extrusion A. f. Hamfelec (Emeritus), A. N. Hrymal<, M. Thompson, J. Vlachopoulos, S. Zhu Procen Syateaa Engineering: Multivariate statistical methods, computer process control optimization J. F. MacGregor, T. f. Marfin, Y Samyudia, C. L Swartz, P. Taylor, T. Kourti (Adjunct) We will provide financial support to any successful applicant who does not already have external support In addition we have a limited number of teaching and research assistantships Why choose McMaster? Hamilton is a city of over 400,000 situated in Southern Ontario We are located about 100 km from both Niagara Falls and Toronto McMaster University i s one of canada s top 8 research intensive universities An important aspect of our research effort i s the extent of the interaction between faculty members both within the department itself and with other departments at McMaster Faculty are engaged in leading edge research and we have concentrated research groups that collaborate with international industrial sponsors : Centre for Pulp and Paper Research Centre for J\c.lvanced Polymer Processing & Design (CAPPA-D) McMaster Institute of Polymer Production Technology (MIPPT) McMaster Advanced Control Consortium (MACC) FOR ON-LINE APPLICATION FORMS AND INFORMATION PLEASE CONTACT I 'i''cu Fal/ 200 3 Graduate Secretary Department of Chemical Engineering McMaster University Hamilton, ON LBS 4L 7 CANADA Phone: 905-525-9140 X 24292 Fax: 905-521 -1 350 Email: chemeng@mcmaster ca Http://www.chemeng.mcmaster.ca 373 PAGE 136 Faculty [I Ronald G. Larson Chair, Theoretical, Computational and Experimental Complex Fluids Re sea rch Complex fluids, polym e rs, fluid me c hanics, surfactants, biomol ecules, transport theor y, rheolog y, instabilities constitut iv e theory [I Mark A. Burns Microfabricated Chemical Analysis Biochemical separations, field-enhanced separations, micro fabricated c hemi cal analysis systems, DNA genotyping and sequencing [I H. Scott Fogler Flow and Reactions Catalyzed dissolution, gellation kinetics, fused chemical r eactions, oil pipeline deep sea pluggin g and remediation [I Sharon C. Glotzer Computational Nanoscience and Soft Materials Asse mbl y of nanoscale systems; molecular motion in pol y m ers, colloids, and complex fluids; nan ost ru ctu red and nano-filled materials [I Erdogan Gulari DNA and Peptide Synthesis & Reactions at Interfaces Micro-array design and engineering, ca talysts for fuel ce lls, cata l ys ts for clean air; biochips, thin films [I Nicholas A. Kotov Nanomaterials Synthesis and applications of nanorods and nanoparticles for materials and pharmaceuti ca l applications [I Joerg Lahann Biomaterials Synthesis of organic coatings for for mi c rofluids and biotissu e applications [I Jennifer J. Linderman Receptor Dynamics R eceptor -mediated phenomena mathematical modelin g, immunology [I David J. Mooney Tissue Engineering Bi omaterials, ce ll adhesion, tissue engineering [I Phillip E. Savage Kinetics and Mechanisms for Environmental Systems Chemical reactions in high-temperatur e and supercritical water [I Johannes W. SchwankCatalysts, Fuel Cells, and Fuel Conversion H ete rogeneous catalysis, thin fi lm s, and chemical sensors, fuel ce lls [I Michael J. Solomon Experimental Complex Fluids Research Polymeric, colloidal, and multiphase fluids [I Levi T. Thompson Catalysts, Reactors, and Fuel Cells Nitride/carbide cata l ys ts fuel processing, micro-fuel ce lls and micro-reactors [I Henry Y. Wang Bioprocess Engineering Pharmac e utical engineering, bioprocessing for sustainable development, biochemical engineering [I Ralph T. YangAdsorption, Reactions Hydrogen Storage New adsorbents, environmental catalysis, gas-carbon rea ct ion s, car bon nanotubes [I Robert M. Ziff Theoretical and Computational Complex Fluids and Transport Research Aggregation kineti cs, ca tal ysis, thermodynamics, statistical me c hani cs, mathematical methods, computer simulation, diffusion in polymers For more information contact: ----------------------------Graduate Program Offi ce, Department of Chemical Engineering The University of Michigan / Ann Arbor, MI 48109-2136 734764-2383 Web: http://www.engin umich edu/dept/cheme 374 Che mi c al Engine e ring Edu ca tion PAGE 137 Graduate Stud y in Chemical Engineering and Materials Science The Department of Chemical Engineering and Materials Science is located on the picture s que campus of Michigan State Univer s ity the pio neer United States land grant institution founde d in 1855. A collegial department at mosphere allows the student to pursue gradu ate studies in six general areas of faculty ex pertise: Nanoscale Materials Biobased Chemi cals an d M aterials, B ioengi n eering, Joining and Processi n g of Metals and Ceramic s, Materials Charac t erization and Microscopy and Poly mers an d Composites. Our goal i s to provide students with the education to excel in their professional careers. Advanced educational courses, exceptional laboratory facilities inter discip l inary i n teractio n s, and industrial collabo ratio n s are all availab l e to allow the students to achieve their professional aspirations Competitive gradua t e assistantships and tuition wavers are available, together with University paid health i n surance. FO R AD DITIO NAL I NFO R MAT IO N WRITE C hairper s on Department of C hemical E n g in e erin g a nd M aterial s S cienc e 2527 E n g ine e ring Buildin g Michigan State Uni v er s it y E a s t Lan s ing Michigan 488 2 4-1 226 e-mail: grad_rec@egr.msu.edu www: h ttp : //www chem s. m s u.edu/ MSU is an Affirmative Action/Equal Opportuni ty In stitution Fall 2003 M. BAUMANN Ph.D 1 988, Case Western R eserve Unive r sity Biomaterials Ceramic Bone Substitutes, Bone Ti ss ue Engineering, Colloidal Processing of Ceramics and Ce r amic Composites K.A. BE R GLUND Ph.D., 1 98 1 I owa Stat e University Applied Spectro sco py Food and Biochemical Engineering Crystallization from Solution New Uses of Agricultural Crops T. R. BIELER Ph D. 1989 University of California Hi gh Temperature Creep; Superpla sticity; Te x ture of Metal s, lntermetallics and Composites; Solder and Electronic Heat Sink Materials; Metal Matrix Composite Fabrication; Hi gh Strain Rate Deformation D.M BRIE D IS Ph.D., 1981 Iowa State University Bio c h emica l Engineering, Bioba se d Industrial Products Biomass Conversion Life Cycle Analysis E.D CASE Ph.D. 19 80, I owa Stat e Un i vers i ty Microcracking in Ceramics, Thermal Fatigue, Ceramic/Ceramic Joining, Bioceramics, Microwave Pr ocessing of Ceramics and Ceramic Composites C CHAN Ph.D. 1 990, University of Pennsylvania Metabolism and Diabete s, Alzheimer and Parkin so n 's disea se, Metabolic Engineering, Tissue Engineering Bioinformatic s and Multivariate Analysis M.A CRIMP Ph.D. 1 987, Case W es tern R eserve University Tran s mission Electron Microscopy, Diffraction a nd Channeling Studie s using Scanning E l ectron Micro sco py, Deformation and Fracture Int ermetallic Alloys, Magnetic Multilayer Structures L.T. D R ZAL Ph.D ., 1974 Case W es rem R eserve University Surface and Int erfacial Ph enomena Adhesion Polymer Composite Material s, Surface Character ization Surface Modification of P olyme r s, Polymer Composite Processing, Ad he s i ve B o ndin g D.S. G R UMMON Ph.D ., / 986 U ni versity of Michigan Superelasticity a nd Shape-Memory in Titanium-Nickel Thin Films Microactuators, Therm oe la s ti c Martensite Tran sfo rmation s, Ion Be am Surface Modification of Material s, Surface Effects in Fatigue Crack in itiation, Mechanical Metallurgy M C. HAWLEY Ph.D. 1964 Michi gan Srate University Kinetics, Cataly s i s, Reaction s in Plasm as, Polymeri zatio n Reaction s, Composite Processin g, Bi omass Conver s ion, Reaction Engi n eeri n g K. JAYARAMAN Ph.D / 975, Prin ceton University Polymer Rh eo l ogy, P rocessing of Polymer Blends and Composite s, Computational Methods I. LEE Ph.D ., 2000, University of Delawar e Adhesion at Polyme-Solid Int erfaces; Sticker and Recepter Group Effect s A LEE Ph.D 1987 University of Illin ois at Urbana C hampai gn ln orga n ic-Orangic H ybrid Polymer s, Physical and Mechanical Characterization Dynamics of Polymeric Gl asses C T LIRA Ph D ., 1 985, Un i ve rsity of Illinois at Urbana-Champaign Thermodynamic s and Pha se Equilibri a of Complex Systems Adsorption Supercritical Fluid Studie s J.P LUCAS Ph.D. 1981 University of Minn esota Microstructure Evolution/Char ac t e rization of Pb-Fr ee Solders Alloys and their Compo s ite s; Nanoindentation Characterization of Deformation in Small-Volumes and Thin Films; Moisture Effects in R esin Matrix Composite s; Metal Matrix Composite M E MACKAY Ph.D., 1 985, University of Illinois at U rbana -Champa i g n P olyme r Rheology and Thermodynamics, Nanotechnology, Dendrimer s, Hyperbranched Polymers, Surface Prop erties D .J. MILLE R Ph.D. 19 82 University of Florida Kinetics and Catalysis Re action Engineering, Catalyti c Conve r sion of Bioma ss -Based Materials R NARAYAN Ph.D 19 75, University of Bombay P olyme r Blend s and Alloys Biodegradable Plastic s, Biofiber Composite s, Extrusion Polymeriza tion and R eactive Compounding, Biodegradation and Composting Studie s J OGAMI Ph D., 1986 Stanford University Electronic Materials Scanned Probe Microscop y, Surface Characterization, Growth of Nano s tructured Materials R. Y. OFOLI Ph.D., 1994 Carnegie Mellon Univers i ty Colloid and Interf ac i a l Science: Colloid Stability Adsorption of Prot ei n s, R eceptor -Ligand Inte ractions a t the Liquid-Liquid lnterface Micellar Solubilization C.A PETTY Ph.D., 1970, University of Florida Fluid Mechanics, Turbulent Transport Phenom ena Solid-Fluid and Liquid -L iquid Separations, H ydrocyclones K.N. SU B RAMANIAN Ph .D., / 966, Michigan Stare Un i ve r sity Mechanical Prop erties of Metal s and Cerami cs, Crys t allization of Gla ss e s, Erosion Composite Materials Lead-Free Electronic Solders R .M WO RD EN Ph.D. 1 986, Un i versity of T e nn essee B iochemical Engineering Microbial Transport Process es, Synthesi s Ga s Fermentations, Metabolic Engineering, Microbial Ecology 375 PAGE 138 Leadership and Innovation in CHEMICAL ENGINEERING AND MATERIALS SCIENCE at the UNIVERSITY OF MINNESOTA FACULTY Rutherford Ari s ( Emeritus ) Theoretical studies of chemical reactors Frank S. Bate s Thermod y namics and d y namics of polymers and polymer mixtures Robert W C arr ( Emeritu s) Chemical kinetics reaction engineering C. Bar ry C arter Defects and interfaces in semiconductors, metals and ceramics, growth of thin films, glass, reactions TEM AFM and SEM James R. Chelikowsk y Materials at the nanoscale, theory of advanced e l ect r onic mate r ials Robert F. C ook Mechanical behavior of materials, fracture mechanics contact mechanics thermomechanics Edward L. Cussler Mass t ransfer, novel separation processes John S. Dahler ( Emeritus ) Nonequilibrium statistical mechanics Prodromo s Daoutidis Non li near process cont r ol, p r ocess ana l ysis and design H. Ted Davis Colloid and interface science, statistical mechanics Jeffr ey J. Derb y H igh performan ce computing, materials processing Lorraine Falter Francis Biomaterials, ceramic and composite pro cess ing coatings Arnold G. Fredrickson ( Emeritus ) Biochemical engi n eering, mi cro bial populations C Daniel Frisbie Molecular materials and interfaces, organic semiconduc tors, molecular electronics, atomic fo r ce microscopy William W. Gerberich Fracture microme c hani cs and interfacial defect s Wei-ShouHu Biochemical enginee r ing Y ianis Kaznes s i s Computer modeling of biological systems, structu r a l bioinformatics molecular recognition phenomena E fro s ini Kokkoli Targeted drug deli very Sati s h Kumar Transport and interfacial phenomena, complex mater i als, nanojluidics and microjluidics C hris Leighton Magnetic and electronic properties of thin film magnetic materials and hete r ostructures Timoth y P. Lodge Pol y mer structure and d y namics polymer characteriza tion C hristopher W. Macosko Polymer p r ocessing, rheology, polymer blends, interfaces and networks Jennifer Ma y nard Biotechnology protein engineering, infectious diseases Richard B. McClurg Thermodynamics and kinetics of phase changes Alon V. McCormick Rea c tion engineering of materials synthesis, spectroscopy, molecular simulation Da v id C. Mor s e Statistical mechanicsand dy n a m ics of polymer fl u ids David J. Norris Photonic crystals, nanomaterials Richard A Oriani (Emeritus ) Corrosion thermodynamics of so li ds, low-energy nuclear reactio n s C hri s topher Palmstrlfm Epitaxial growth proc esses and heterostru c ture formation, properties of thin film Lanny D. Schmidt R eaction engineeri n g, surface c h e mi stry, h e t eroge neous catalysis L. E. S criven Fluid me c hani cs and rheology colloid and interface science, transport reaction and stress phenomena, m aterials processing: coat i ngs David A Shore s High temperature corrosion, fuel cells John M Si v ertsen (Emeritu s) Magnetic microelectronic and tribolog i cal mate r ia l s Willi a m H. Sm y rl Electrochemical engineering, modeling electrochemi cal systems, microvisuali z ation of reactive surfaces Friedrich Srienc Biochemical engineeri n g, cell cycle kinetics Robert T. Tranquillo Cardiovasc u lar and neural tissue engineering Michael Tsapatsis Materials, separations, cata l ysis Michael D. Ward Molecular mate r ials crystal growth, electrochemistry Renata M. Wentzcovitch Theory of materials at high p r essure and temperature For additional information, visit our web sik at http://"" \\.ccms.umn.cdu 376 Chemical Eng i neer i ng Education PAGE 139 Graduate Studies in Chemical Engineering . Envi r onmental R e m e diati o n Ele c tr o kin etics, C h e mical Ex tr ac ti on, Stabilization/ Solidifi ca ti o n Waste Treatment H eavy Metal Soils W Todd French Assistant Research Professor Appli e d Mi c robi o l ogy, Bi o r e mediati o n Indu s trial Microbiolo gy, Mi crob ial Enhanced Oil R ecovery Clifford E. George Professor Industrial Bi o te c hnol ogy, Indu s trial Appli ca ti ons of Microwave P ower /H eati n g and El ec troc h emistry Pr ocess C o ntrol Chemical Plant/Oil R efinery Op erat i o ns and Safety Rafael Hernandez Assistant Professor Integ r at e d Rem e diati o n T ec hnolo gies, Chemical/Ph ys i ca l Tr ea tm e nt Pr ocesses, Environm e ntal Catalysis Bi ofue l s and Co-products Priscilla J. Hill Assistant Professor Crystalli z ation P rocess D esign So lid s Pr ocessing Irvin A. Jefcoat Professor and Henry Cha i r P o lluti on Pr evention/Waste Minimization Adrienne R. Minerick Assistant Professor Electrokinetic Separation s of Biofluids Medi cal Dia g n ostic Mi c r o d ev i ce D eve l o pm e nt Mississippi State University located in the Golden Triangle region of Northeast Mississippi, is the largest of eight public institutions of higher learning in the state. I t is one of two land-grant institutions in Mississippi. Area residents e njo y numerou s university sporting and c ultural events, as well as scenic and re c r eat ional activities along the Natche z Tra ce Parkwa y and Tennessee Tombigbe e Waterwa y. The Dave C. Swaim School of Chemical Engineering is poised for unprecedented growth in the next decade. A new$18 million facility recently was completed specifically for Chemical Engineering. The school offers both the M S. and Ph.D. degrees in Chemical Engineering and an M.S in Industrial Hazardous Waste Management. For more information contact The Dave C. Swaim School of Chemica l Engineering Mississippi State University P.O. Box 9595 330 Swaim President's Circle Mississippi State Mississippi 39762 Phone: (662) 325 2480 Fax: (662) 325 2482 Email : gradstudies @ che.msstate.edu www che msstate.edu Rudy E Rogers Professor Natural Gas Storag e and Transport F o rmation Rat es in O ce an Sediments CO Sequeste ri ng Natural Gas Pr od u c tion from S ea b e d H y drates . . . . Kirk H. Schulz D i rector and Deavenport Chair Surfa ce Scie n ce, Catalysis Electronic Materials Hossein Toghiani Associate Professor Composite Materials Catalysis Fuel Cells Thermodynamics of L iq ui d Mixtures Rebecca K. Toghiani Associate Professor Thermod y nami cs, S e parations Mark E. Zappi Texas Olefins Professor Waste Treatment Industrial Biote c hnolo gy, Chemical Oxidation Biotr ea tm e nt H y ph e nated Rem e diation Te c hniques Fall 2003 For a graduate application contact The Office of Graduate Studies Phone (662) 325 7404 www.msstate.edu/depl/grad/application.htm '11,,1,,111111 .\r111r l 11111r1/!1 11 di/ 1 (//11il fl/'l'''i!!!l!/1\ 1u,.11:11,.,,,,, 377

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University of Missouri Columbia Rak esh K. Baipai Ph .D. (IIT, Kanpur) Biochemical Engineering Hazardous Waste Paul C.H. Chan Ph.D (CalTech) Reactor Analysis Fluid Mechanics Patricia A. Darcy Ph.D. (Iowa) Protein Crystallization Bi otechnology Eric Doskocil Ph.D. (Virginia) Catalysis Reaction Engineering William A. Ja coby Ph.D. (Colorado) Photocatalysis Transport Sunggyu Lee Ph.D (Case Western) Supercritical Fluids Polymers Fuels Stephen ,T. Lombardo Ph.D. (California-Berkeley) Ceramic Composites Transport Kinetics Sudarshan K. Loyalka Ph.D. (Stanford) Aerosol Mechanics Kinetic Theory Richard H. Luecke Ph.D. (Oklahoma) Process Control Modeling Thomas R. Marrero Ph.D. (Maryland) Coal Log Transport Conducting Polymers David G. Retzloff Ph.D. (Pittsburgh) Reactor Analysis Materials Truman S. Storvick Ph.D. (Purdue) Nuclear Waste R eprocessing Thermodynamics Galen ,T. Suppes Ph.D (Johns Hopkins) Biofuel Processing Renewable Energy Thermodynamics Dabir S. Viswanath Ph.D. (Rochester) Applied Thermod y namics Chemical Kinetics Hirotsugu K. Yasuda Ph.D. (SUNY, Syracuse) Polymers Surface Scienc e Qingsong Yu Ph.D (University of Missouri-Columbia) Surface Science Plasma Technology The University is one of the most comprehensive institutions in the nation and is situated on a beautiful land grant campus halfwa y between St. Louis and Kansas City, at the foothills of the O z ark Mountains and the recreational Lake of the O z arks. The Chemical Engineering Department offers M.S and Ph.D programs in a wide variety of research areas including surface science nuclear waste, wastewater treatment, biodegradation indoor air pollu tion, supercritical processes, plasma polymerization, polymer processing, coal transportation (hydraulic), fuels, chemical kinetics, protein crystallization, photocatalysis, ceramic composites, and polymer composites. For details contact: The Director of Graduate Studies Department of Chemical Engineering University of Missouri Columbia, MO 65211 Tel: (573) 882-3563 Fax: (573) 884-4940 E-mail: preckshotr@missouri.edu Website: www.rnissouri.edu/~chewww 378 Incentive scholarships available in the form of teaching/research assistantships and fellowships. Ch e mi ca l Engineering Education

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University of Missouri-Rolla G ra d uate St udies in Chemical Engineering Offering M.S. and Ph.D Degrees Established in 1870 as the University of Missouri School of Mines and Metallurgy, UMR has evolved into Missouri's technological univer sity UMR is a medium-si zed campus of about 5 000 students located a l ong I nterstate 44 approximatel y JOO miles from St. Louis and Spring field. I ts proximity in the Missouri Ozarks pr ovi des pl e nty of scenic and recreational opportunities. The University ofMissouri-Rolla's mission is to educate tomorrow's leaders in engineering and science. UMR offers a full range of experi ences t hat are vital to the kind of comprehensive education t hat turns young men and women into leaders. UMR has a distinguished faculty dedicated wholeheartedly to the teaching research and creat i ve activi ties necessary for scholarly learning experiences and advancements to the frontiers of knowledge. Teaching and Research Apprenticeships available to M S and Ph.D students. Fo r a d d itional information: Address: Web: E-mail : Graduate Studies Coord inator Department of Chemical and B io lo gical Engin eering University of Missouri-Rolla Ro ll a MO 65409-/230 http://1vww.umr.edu/c hemengr adminche@umr. ed u Online Appli ca tion : http ://www. umr. ed 11 /-cisapps/gra dappd htm/ Nell L. Book Associate Professor, Ph.D. Colorado Computer Aided Proce ss Design, Chemical Proces s Safety, Engineering Da ta Management Daniel Forciniti Associat e Profmor, Ph.D. Notti, Carolina State Bio se p ara tion s Thermod ynamics Sta tis tical Mechan ics A.I. Liapis Professor, Ph.D. ETH-Zurich T rans port Phenomen a, Adsorption/Desorpti o n Fundamentals and Pr oces se s, Bio se paration s, Chrom a tographic Separations Capillary Electrochrom a tography Chemical Rea c tion Engineering L y ophilization Douglas K. Ludlow Professor and Chair, Ph.D Arizona Stau Surf a c e Ch arac teri za tion o f Ad so rbents an d Ca tal y sts, App li cation s o f Fra c tal G eo m e try t o Surface M o rph o logy Nicholas C. Morosoff Professor Emtrilus, Ph.D. Brooklyn Polyt,ch Pl asma Pol y merizati o n Membranes Parthasakha NeQRi Professor, Ph.D. Carntgi,-Mellon lnterfacial Phenomen a, Drug Delivery XB Reed,Jr. Proftssar Emuitlls, Ph.D. Minnmlta Fluid Mechanic s, T ran s port Phenomena and Chemical Reaction Enginee ri n g, including those o f Particl es, Drops and Bubbles Laige-Scale Structure of S h ear Turbulence and Impact o f Fine Scale Structure on Chemical Reaction s Y.T.Shah Professor and Provolt, Ph.D. MIT Chemical Reaction and Reactor Engineering OUver C. Sitton Associate Profmor, Ph.D. Missouri-Rolla Bioengineerin g Jee-Ching Wang Assislant Professor, Ph.D. Penn State Mol ecu l ar Simulations of Tran s port in Confined Sy s tem s, Molecular Simulation s of Surf a ctant S ys tem s, Molecular Properties of Materials Yangchuan Xing Assislant Professor, Ph.D. Yak Synthesis Proce ss ing and Characterization of Nanomaterial s Fall 2003 379

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380 The department offers graduate programs leading to both the Master of Science and Doctor of Philosophy degrees. Exciting opportunities exist for interdisciplinary research. Faculty conduct research in a number of areas including: Polymer science/ engineering Membrane technology Hazardous waste treatment Particle technology Pharmaceutical engineering Nanotechnology at lJew Jersey-lnstHufe offechnology The Faculty: P. Armenante; University of Virginia B. Baltzis; University of Minnesota R. Barat; Massachusetts Institute of Technology C. Gogos; Princeton University T. Greenstein; New York University D. Hahn; Agri Univ. of Wageningen (Netherlands) D. Hanesian; Cornell University M. Howley; Rutgers University M. Huang; University of Massachusetts K. Hyun; University of Missouri-Columbia H. Kimmel; City University of New York D. Knox; Rensselaer Polytechnic Institute G. Lewandowski; Columbia University N. Loney; New Jersey Institute of Technology A. Perna; University of Connecticut R. Pfeffer; New York University L. Simon; Colorado State University K. Sirkar; University of Illinois-Urbana R. Tomkins; University of London (UK) J. Wu: University of Delaware M. Xanthos; University of Toronto (Canada) For further information contact: Dr Reginald P T Tomkins Department of Chemical Engineer i ng New Jersey Institute of Technology Un i versity He i ghts Newark NJ 07102 1982 Phone : (973) 596-5656 Fax : (973) 596-8436 E-mail : tomk i nsr @ adm.njit.edu IIT New Jersey Institute of Technology NJIT does not discriminate on the basis of gender sexual orientation, race, handicap veteran s status, nat}Onal or ethnic origin or age in the administration of student programs Campus facilit ies are accessible to the d isab led Chemical Engineering Education

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NEW MEXICO STATE UNIVERSITY Faculty and Research Areas ____________ 382 Paul K. Andersen, Associate Professor, University of California, Berkeley Transport Phenomena, Electrochemistry, Environmental Engineering Ron K. Bhada, Professor Emeritus, University of Michigan Joe L. Creed, Assistant Dean, New Mexico State University Engineering Design Francisco R. Del Valle, College Professor Massachusetts Institute of Technology Food Engineering Shuguang Deng, Assistant Professor, University of Cincinnati Separations, Purification, and Fuel Cell Technology Charles L. Johnson, Professor and Head, Washington University-St. Louis Richard L. Long, Professor and Associate Head Rice University Transport Phenomena, Biomedical Engineering, Separations Martha C. Mitchell, Associate Professor University of Minnesota Advanced Materials, Statistical Mechanics, Molecular Modeling Stuart H. Munson-McGee, Professor University of Delaware Advanced Materials, Separations John T. Patton, Professor Emeritus Oklahoma State University David A. Rockstraw, Associate Professor University of Oklahoma Separations, Environmental Engineering, Kinetics Rudi V. Roubicek, Professor Emeritus Technical University of Prague Edward F. Thode, Professor Emeritus, Massachusetts Institute of Technology D. Bruce Wilson, Professor Emeritus Prin ceton University LOCATION------~ Southern New Mexico 350 days of sunshine a year For Application and Additional Information Internet http://chemeng.nmsu.edu/ E-mail chemeng@nmsu.edu PO Box 30001, MSC 3805 Department of Chemical Engineering New Mexico State University Las Cruces, NM 88003 New Mexjco State University is an Equal Opportunity Affirmative Action Emp l oyer Chemical Engineering Education

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Fall 200 3 383

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384 GRADUATE STUDY IN CHEMICAL ENGINEERING in the Heart of Boston Faculty Nurcan Bae Gilda Barabino Daviel D. Burkey Rebecca L. Carrier Carolyn Lee-Parson s Albert Sacco Jr. Ronald J Willey Katherine S. Ziemer Northeastern Univer s ity Chemical Engineering Department is the home of CAMMP (Center for Advanced Microgravity Materials Processing)-a NASA-sponsored Commer cial Space Center It i s one of 16 NASA centers at major univer s itie s nation wide and the only one exclusively focused on material s The Department offers full and part-time graduate programs leading to M.S and Ph.D. degrees. M.S. stu dents may have the opportunity of co-op experience. The faculty of the chemical engineering program are committed to providing state-of-the-art research areas. Research Areas Biochemical Engineering Biomedical Engineering Cataly s i s Microgravity Advanced materials Nanocompo s ite Membrane s Semiconductor Material s Selected Research Topics Pharmaceutical compounds from plant cell cultures Carbon Nanotube s Mixed-Matrix Membrane Separation Sickle Cell Adhe s ion Surface Acidity
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Chemical Engineering at L ui s A N A maral Ph.D., Boston U