Chemical engineering education

Material Information

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


Subjects / Keywords:
Chemical engineering -- Study and teaching -- Periodicals ( lcsh )
periodical ( marcgt )
serial ( sobekcm )


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

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
01151209 ( OCLC )
70013732 ( LCCN )
0009-2479 ( ISSN )
TP165 .C18 ( lcc )
660/.2/071 ( ddc )

UFDC Membership

Chemical Engineering Documents


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This is the 22nd graduate education issue published by CEE. It is distributed to chemical engineering seniors inter-
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Ray Fahien, Editor, CEE
University of Florida

Fall 1989
San, McIntire Biochemical and Biomedical Engineering
Kummler, McMicking, Powitz Hazardous Waste Management
Bienkowski, et al. Multidisciplinary Course in Bioengineering
Lauffenburger Cellular Bioengineering
Randolph Particulate Processes
Kumar, Bennett, Gudivaka Hazardous Chemical Spills
Davis Fluid Mechanics of Suspensions
Wang Applied Linear Algebra
Kisaalita, et al. Crossdisciplinary Research: The Neuron-Based
Chemical Sensor Project
Kyle The Essence of Entropy
Rao Secrets of My Success in Graduate School

Fall 1988
Arkun, Charos, Reeves Model Predictive Control
Briedis Technical Communications for Grad Students
Deshpande Multivariable Control Methods
Glandt Topics in Random Media
Ng, Gonzalez, Hu Biochemical Engineering
Goosen Research Animal Cell Culture in Microcapsules
Teja, Schaeffer Research Thermodynamics and Fluid Proper-
Duda Graduation: The Beginning of Your Education

Fall 1987
Amundson American University Graduate Work
DeCoursey Mass Transfer with Chemical Reaction
Takoudis Microelectronics Processing
McCready, Leighton Transport Phenomena
Seider, Ungar Nonlinear Systems
Skaates Polymerization Reactor Engineering
Edie, Dunham Research Advanced Engineering Fibers
Allen, Petit Research Unit Operations in Microgravity
Bartusiak, Price Process Modeling and Control
Bartholomew Advanced Combustion Engineering

Fall 1986
Bird Hougen's Principles
Amundson Research Landmarks for Chemical Engineers
Duda Graduate Studies: The Middle Way
Jorne Chemical Engineering: A Crisis of Maturity
Stephanopoulis Artificial Intelligence in Process Engineering: A
Research Program
Venkatasubramanian A Course in Artificial Intelligence in Proc-
ess Engineering
Moo-Young Biochemical Engineering and Industrial Biotech-
Babu, Sukanek The Processing of Electronic Materials
Datye, Smith, Williams Characterization of Porous Materials
and Powders
Blackmond A Workshop in Graduate Education

Fall 1985
Bailey, Ollis Biochemical Engineering Fundamentals
Belfort Separation and Recovery Processes
Graham, Jutan Teaching Time Series
Soong Polymer Processing
Van Zee Electrochemical and Corrosion Engineering
Radovic Coal Utilization and Conversion Processes
Shah, Hayhurst Molecular Sieve Technology
Bailie, Kono, Henry Fluidization
Kauffman Is Grad School Worth It?
Felder The Generic Quiz

Fall 1984
Lauffenburger, et al. Applied Mathematics
Marnell Graduate Plant Design
Scamehorn Colloid and Surface Science
Shah Heterogeneous Catalysis with Video-Based Seminars
Zygourakis Linear Algebra
Bartholomew, Hecker Research on Catalysis
Converse, et al. Bio-Chemical Conversion of Biomass
Fair Separations Research
Edie Graduate Residency at Clemson
McConica Semiconductor Processing
Duda Misconceptions Concerning Grad School

Fall 1983
Davis Numerical Methods and Modeling
Sawin, Reif Plasma Processing in Integrated Circuit Fabrication
Shaeiwitz Advanced Topics in Heat and Mass Transfer
Takoudis Chemical Reactor Design
Valle-Riestra Project Evaluation in the Chemical Process Indus-
Woods Surface Phenomena
Middleman Research on Cleaning Up in San Diego
Serageldin Research on Combustion
Wankat, Oreovicz Grad Student's Guide to Academic Job Hunt-
Bird Book Writing and ChE Education
Thomson, Simmons Grad Education Wins in Interstate Rivalry

Fall 1982
Hightower Oxidative Dehydrogenation Over Ferrite Catalysts
Mesler Nucleate Boiling
Weiland, Taylor Mass Transfer
Dullien Fundamentals of Petroleum Production
Seapan Air Pollution for Engineers
Skaates Catalysis
Baird, Wilkes Polymer Education and Research
Fenn Research is Engineering

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Chemical Engineering Education

Chemical Engineering Education
Department of Chemical Engineering
University of Florida
Gainesville, FL 32611

EDITOR: Ray W. Fahien (904) 392-0857
MANAGING EDITOR: Carole Yocum (904) 392-0861


E. Dendy Sloan, Jr.
Colorado School of Mines

Gary Poehlein
Georgia Institute of Technology

Klaus Timmerhaus
University of Colorado

Richard M. Felder
North Carolina State University
Jack R. Hopper
Lamar University
Donald R. Paul
University of Texas
James Fair
University of Texas

J. S. Dranoff
Northwestern University

Frederick H. Shair
California Institute of Technology
Alexis T. Bell
University of California, Berkeley

Angelo J. Perna
New Jersey Institute of Technology
Stuart W. Churchill
University of Pennsylvania
Raymond Baddour
Massachusetts Institute of Technology

Charles Sleicher
University of Washington

Leslie W. Shemilt
McMaster University

Library Representative
Thomas W. Weber
State University of New York

Chemical Engineering Education

Volume XXIV

Number 4

Fall 1990


176 Biochemical Engineering Education Through Videotapes,
G.D. Austin, P.B. Beronio, Jr., and G. T. Tsao

198 Applied Mathematics: Opportunities for Chemical Engineers,
Doraiswami Ramkrishna

224 The Dispersion Model Differential Equation for Packed Beds: Is It
Really So Simple? William J. Rice


180 A Consortium to Address Multidisciplinary Issues of Waste
Management, Ron Bhada, Ricardo Jacquez, Larryl Matthews,
J. Derald Morgan

188 Stoichiometry Without Tears, Richard M. Felder

212 A Course on Multimedia Environmental Transport, Exposure, and
Risk Assessment, Yoram Cohen, Wangteng Tsai, Steven Chetty

220 The Chemical Engineering Summer Seminar Series at Virginia
Polytechnic Institute and State University,
Kirk H. Schulz, G. Gregory Benge

228 Transferring Knowledge: A Parallel Between Teaching Chemical
Engineering and Developing Expert Systems, P. R. Roberge


184 The Chemical Engineering Curriculum 1989,
George A. Coulman


204 Numerical Simulation of Multicomponent Chromatography Using
Spreadsheets, Douglas D. Frey


208 Polymer Science and Engineering at the University of Cincinnati,
J. R. Fried

187 Division Activities
196 Letter to the Editor
197 In Memoriam Lee C. Eagleton
207 Book Review
223 Stirred Pots

CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engi-
neering Division, American Society for Engineering Education and is edited at the University of Florida. Cor-
respondence regarding editorial matter, circulation, and changes of address should be sent to CEE, Chemical
Engineering Department, University of Florida, Gamesville, FL 32611. Advertising material may be sent di-
rectly to E.O. Painter Printing Co., PO Box 877, DeLeon Springs, FL 32130. Copyright 1990 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 CEE, Chem. Eng. Dept., University of Florida, Gainesville, FL 32611.

Fall 1990




Purdue University
West Lafayette, IN 47907

Biochemical engineering is now well-established
in the chemical engineering curriculum, and the
move to improve its instruction is already under way
[1,2]. The use of videotapes at Purdue to supplement
chemical engineering courses based on the lecture
method has been described [3], and its usefulness in
the modernization of chemical engineering has been
identified [4].
The use of videotapes to supplement a course
in introductory biochemical engineering was
proposed and developed by the authors during
a graduate level course at Purdue on educational
methods in chemical engineering, and it resulted in
the incorporation of a two-week learning module
into the fall 1988 offering of the course "Biochemical
Although the videotapes were not profession-
ally made, they proved to be of good quality and
educational value. However, since none of the au-
thors had any previous experience in videotape pro-

Glen D. Austin is a PhD candidate in the School of
Chemical Engineering at Purdue University, working
in the Laboratory of Renewable Resources Engi-
neering. He received his BSc (Eng.) in biological en-
gineering from the University of Guelph (Ontario,
Canada) and his MS from Purdue University. His
present research is in the area of monitoring and
control of fermentation processes using mass spec-

Peter B. Beronio, Jr., is a PhD candidate in the
School of Chemical Engineering at Purdue Univer-
sity and works in the Laboratory of Renewable Re-
sources Engineering. He received his BS in chemical
engineering from Lehigh University and his MS from
Purdue University. His PhD thesis topic is on bio-
energetic modeling of oxygen-limited metabolism.

duction, many hours were required to overcome tech-
nical problems that arose.
The concept for the course originated from a
term project in the graduate course on educational
methods which required development of an educa-
tional tool based on teaching methods which were
discussed during the course and which could be
applied within the chemical engineering curricu-
lum. The authors had become interested in the self-
paced method [5] as applied to an introductory bio-
chemical engineering course. Because of the lack of
adequate biochemical engineering laboratory facili-
ties at most universities, the authors felt that video-
tapes could provide exposure to laboratory experi-
ence without the need to equip a laboratory for a
large lecture class.
The authors proposed a three-week, self-paced
learning module on the topics of microbial kinetics
and metabolism. The module's centerpiece was a
series of videotapes and a companion study guide
which introduced the student to theoretical develop-
ments and appropriate laboratory demonstrations.
The material was derived from prominent textbooks
[6,7] and instructor's notes.
There was enough interest generated by the
concept to adapt the module for implementation into
an introductory biochemical engineering course which
is offered each fall semester and usually has be-
tween forty and sixty senior-level and graduate stu-
dents. The subject matter of the course begins with
the basics of biochemistry, progresses to cells and

George T. Tsao is professor of chemical engineer-
ing, food and agricultural engineering, and Director
of the Laboratory of Renewable Resources Engi-
neering at Purdue University. He received his PhD
in chemical engineering at the University of Michi-
gan in 1960.

Copyright ChE Division, ASEE 1990

Chemical Engineering Education

The concept for the course originated from a term project in the graduate course on educational
methods which required development of an educational tool based on teaching methods which were
discussed during the course and which could be applied within the chemical engineering
curriculum. The authors had become interested in the self-paced method
as applied to an introductory biochemical engineering course.

their metabolism, and culminates in bioreactor de-
sign and downstream processing of products. His-
torically, the course has been taught by using the
lecture method, and no laboratory is offered. Final
grades are based on two term tests, a final exam,
and a term paper on course related subjects of inter-
est to the students.
During the introduction of cell kinetics, it is
important for the student to understand the scales
of time and space of the microbial world. In chemical
engineering, reactions times are generally rapid and
the size of equipment and catalysts are relatively
large, so the long reaction times and microscopic cell
sizes in biochemical engineering can be quite hard to
grasp. Since no laboratory is available to provide
this exposure, and since lecture demonstrations are
impractical, videotape can help the student to better
understand these new concepts.


The format adopted for the module was based
on a two-week section of the course, with each week
focusing on the topics of one videotape. The class did
not meet during the first period of each week, but
the students were expected to view the week's video-
tape before the required second class-period. During
this second period, class time was devoted to intro-
ducing extensions of the topics on the videotapes
and to an informal question-and-answer session. The
optional third class period each week provided an
opportunity for students to ask the instructor spe-
cific questions pertaining either to the topics or to
the required homework for that week.
The basic concepts of microbial kinetics and
metabolism are introduced in the first videotape,
beginning with cell measurement techniques. Labo-
ratory equipment used for growing and maintaining
cultures are also demonstrated. Videotaping of
these sequences was completed by using portable
equipment and videotaping (with narration) the nor-
mal operations in the Laboratory of Renewable
Resources Engineering. To aid in the final editing,
we kept a log of events that were recorded. Due
to inexperience with the equipment, the sound re-

cording, and the lighting, it was often necessary to
film a sequence several times in order to get the
desired results.
The final edited version of the first videotape
also contained a segment involving theoretical de-
velopment. The studios of Continuing Engineering
Education at Purdue, with mounted professional
cameras, were used to record diagrams and equation
developments. The result, a professional switching
of camera angles, gives the viewer the ability to
watch the speaker head-on or to view his handwrit-
ing from an overhead angle.
The videotape for the second week of the mod-
ule extended directly from the first videotape and
dealt mainly with mass balances and productivity of
biological reactors. No attempts were made to in-
clude laboratory sequences, but in keeping with the
self-paced format, the second videotape was included
in the module. The entire videotape was composed of
theoretical developments and examples and was re-
corded in the continuing education studios. Table 1
gives a complete breakdown of the topics covered on
each tape.
When planning the construction of the video-
tapes, a major concern was how students perceive
the medium. From the beginning the module was
designed and introduced as an active exercise since
the authors felt that only through active learning
would the students grasp the concepts. To aid in

Videotape Topics

Videotape 1: Cell Measurement
Plate Count, Hemacytometer,
Spectrophotometer, Volume Dry
Weight, Chemical Analysis
The Growth Curve
Monod's Equation

Videotape 2: Introduction to CSTR
Review of Macroscopic Mass Balance
Mass Balance on Cell Mass in CSTR
Mass Balance at Steady State
Maintenance Metabolism

Fall 1990

keeping the activity level high, example problem
were interspersed throughout the videotapes, an
the students were encouraged to pause during th
viewing sessions and to attempt the example prob
lems prior to watching the solutions provided on th
tape. The example problems also helped the stu
dents to identify the need for review of any section
which they felt they had not grasped.

Completing the module was a handout which
accompanied the videotapes. It contained suggest
reading, the weekly homework assignments, work
sheets for the example problems, and copies of item
presented on the videotapes for note-taking and late
reference. (Other educators have reported on th
need to have copies of the written materials pre
sented on screen in order to circumvent problems c
poor resolution of video screens and illegible hand
writing [8].) The booklet contained everything th
student needed for the two-week module.

Each of the final videotapes contained approxi
mately forty-five minutes of viewing material. W
estimated that if the student was actively learning
(by pausing to attempt the example problems an
reviewing poorly-understood material before continue
ing), each tape would require
approximately two hours to com-
plete. Six copies of each of the
Results of
two final videotapes were made
with the equipment in the Con- Q. # Question
tinuing Education studios. They
were deposited in the Engineer- 2-1 Did you use
ing Library, where they could be 2 Did yousto
2-3 Did you sto
signed out by the student for before wa
viewing within the library. 2-4 Would you
similar sel


Following the two-week
module, the students were asked
to fill out a short questionnaire 2-5 Thevideta
so that their opinions of the mod- 2-6 Material on
ule could be analyzed. The video- understand
tapes have been used for the past 2-7 The reading
packet con
two offerings of the course, and 2-8 xape pco
since each year's results are simi- reinforced
lar, the results have been com- 2-9 The videota
bined in Table 2. Of all the stu- instructor
2-10 Quality of in
dents, 94% said that they used assistant w
both the study guide and the 2-11 These video
videotapes, and 66% said that the materi
they stopped the videotape to 2-12 I would pref
So t e p lecture for:
work on the example problems

s before viewing the solution. These were two areas of
d concern: that the students would only use the study
e guide and that they would simply watch the problem
solutions without giving the problem a try. Other
e encouragement was generated by the students' feel-
I- ings that the overall quality of the tapes was accept-
n able and that the homework and example problems
were beneficial.

h On the negative side, only 44% of the class felt
d that they would like to see more sections of the
S course taught in the same way. Also, although most
S of the responses indicated that videotapes are an
r acceptable educational tool, the majority of students
e would have preferred that the material be taught by
the lecture method. These negative reactions, in part,
f may be the result of putting the onus of actively
I- learning the material onto the student.
e It should be noted that in a similar question-
naire which was administered before the module
(see Table 3), 73.5% of the students said that they
had used videotapes in a previous course, but only
e 17.2% said that the videotapes had taken the place
g of lectures.
*- The students' overall impression of the video-

Questionnaire Administered After Module (89 responses)

both the study guide and videotapes?
d from the supplied reading material?
p the videotape to thoroughly work example problems
thing the solution?
like to see more sections of this course presented in a
If-paced format?

(The following questions were posed with responses of
-2 for "strongly disagree" up to 2 for "strongly agree." )

pes were well-produced and of acceptable

the tapes was presented in an orderly and
able fashion
material in the accompanying information
iplemented videotapes well
blems on the videotapes provided good
ent of concepts presented
pes reduced the need for interaction with the
/ teaching assistant
Interaction with the instructor / teaching
ras enhanced by the module
tapes were a good medium for teaching
er that this material be presented in the


94.4% Yes
86.5% Yes

66.0% Yes

43.7% Yes

Responses -
-2 -1 0 1 2

2 12 21 47 7

1 3 17 47 21

5 13 21 37 12

1 4 15 50 19

11 22 17 30 9

6 15 32 24 12

6 14 23 36 10

6 19 20 25 19

Chemical Engineering Education

tapes and the module in general was, however, good.
They were free to make comments on the question-
naire, and many did. Of those who liked the module,
many commented that they liked both the change
of pace the module offered and the opportunity
of viewing the tapes at their convenience, freeing
them from the rigid lecture schedule. Positive com-
ments on specific aspects of the module included the
value of the example problems and the interest gen-
erated by the laboratory sequences. In general, the
students liked the first videotape the best, probably
due to the practical value of its laboratory demon-
strations and their counterbalancing effect on the-
ory. One student even commented that the course
should have a laboratory so more procedures could
be taught.
Those students who indicated a dislike for the
module can be separated into two groups: those who
did not like having to be active while viewing the
videotapes, and those who thought that the video-
tapes were too passive. In each case, the respondent
stated that he or she would prefer to have had the
material presented in a lecture format. Other nega-
tive comments mentioned the inability to ask ques-
tions when they arose and that the time for student/
instructor interaction was too far removed from the
learning environment.

We feel that this module, created to introduce
students to microbial kinetics and metabolism, sat-
isfied our main objectives. The students were ex-
posed to laboratory techniques and the concepts were
reinforced with theoretical development and prob-
lem solving. From the, feedback, it is apparent that
the students feel that videotape is a good medium in
which to introduce basic concepts of biochemical

Results of Questionnaire Administered Before Module

Q. # Question

3-1 Have you ever used videotapes in a course before?
3-2 Have you ever been in a course where videotapes took the pla
of lectures on occasion?
3-3 Do you think videotapes are a good medium for teaching?
3-4 Do you think that you will learn more in a self-paced format ov
the lecture format?
3-5 Do you expect to better utilize your time in the upcoming
self-paced module?
3-6 Have you ever had any experience in the biological sciences
(taken a biology course at a university or worked in a
biology-oriented lab)?

engineering. They like the advantage of advancing
at their own pace until the concepts are clear and of
being able to attempt example problems that will
indicate if there is a need for review.
Although the two-week module revolves around
the two videotapes, it is not complete without the
handout. Response from the students showed that
almost all of them used the study guide, demonstrat-
ing its importance as already claimed [8]. During
the viewing sessions, the activity level is kept high
by supplying example problems both on the video-
tape and in the handout. These example problems
contributed greatly to the module's success.
However, some students' negative reaction to
the module was due to its activity level. It is inter-
esting that one group of students disliked the en-
couraged activity when working with the videotapes,
while another group felt the videotapes were too
passive. One study [9] shows that a subject's expec-
tations of a learning experience based on an estab-
lished medium (such as television) can be affected by
his or her preconceived ideas of the medium. An-
other report [10] reveals that television is perceived
as an "easy" learning process and is often approached
with passive mental effort. It is possible that the
first of our two groups preferred the passive nature
of the lecture as a preconceived notion, while the
second group looked at the television experience as
an "easy" approach and preferred the lecture as a
more mentally-demanding process. It is not the pur-
pose of this report to speculate on why these indi-
viduals perceived the medium as they did, but it is
noteworthy that there are differences in individuals'
backgrounds and prior experiences and, hence, in
their acceptance.

Although we tried to prevent the module from
becoming a passive exercise, the video format is
generally viewed as a form of enter-
tainment. Videotapes are inherently
subject to a low level of viewer par-
;47 responses) ticipation, and an individual can
Response easily run straight through a vide-
otape at the lowest activity level
73.5% Yes (which, for some viewers, may be
ce Y sufficient to grasp the concept). In-
17.2% Yes
87.5% Yes cluding example problems, sugges-
er tions, and cues to review, are a step
73.5% Yes in the right direction for increasing
72.0 Yes student participation.
72.0b/o YeS
Another medium (also in the
48.3% Yes Continued on page 211.

Fall 1990





New Mexico State University
Las Cruces, NM 88003

Efficient and safe management of nuclear,
hazardous, and solid waste is an increasingly criti-
cal national issue [1-5]. Further, it is a broad mul-
tidisciplinary issue that cannot be effectively ad-
dressed by any one entity or organization. It re-
quires a collaborative effort between multiple or-
ganizations with diverse expertise and experience.
New Mexico has an infrastructure that will
support and provide benefits to the nation from
education and research activities related to nuclear,
hazardous, and solid waste management. This in-
frastructure includes the three major research uni-
versities, theWIPP site, the Sandia National Labo-
ratory, and the Los Alamos National Laboratory. A
designated "Center of Excellence" to educate and
research issues in managing nuclear, hazardous,
and solid waste is a natural extension of the pro-
grams and facilities that already exist in the State.

Ron Bhada is department head and professor in chemical engineering at New
Mexico State University, and is also director of the consortium described in this
paper. He received his PhD, Master's, and Bachelors degrees in chemical
engineering from the University of Michigan, and also holds an MBA. He has
published papers in the areas of thermodynamics, pollution control, manage-
ment, technology transfer, and education.
J. Derald Morgan is dean of the College of Engineering at New Mexico State
University. His degrees are in electrical engineering: a BS from Louisiana Tech
University, his MS from the University of Missouri-Rolla, and PhD from Arizona
State University.
Larryl Matthews is director of the Engineering Research centers at New
Mexico State University. He is a faculty member in the department of mechani-
cal engineering and has published papers in the areas of heat transfer, solar
energy, and engineering optics. He received his PhD from Purdue University.
Ricardo Jacquez is a professor of civil engineering. He received his BS and
MS degrees from New Mexico State University and his PhD from Virginia
Polytechnic Institute and State University. His specific field is environmental
engineering, and his publication areas include water pollution control and solid
and hazardous waste management.

The research scope of the Center of Excellence is
broad-based and is designed to include all
areas of radioactive, hazardous, and
solid waste management.


In July of 1989, the Secretary of Energy,
James Watkins, approved a waste (management)
education and research consortium program [6-8]
which had been proposed by New Mexico State Uni-
versity (NMSU) to the U.S. Department of Energy
(DOE). The program would be known by the acro-
nym "WERC."
The program is unique and innovative in many
aspects. It is the only program in the nation that
provides an integrated approach to this national
need, and it includes
Education in waste management by the three
Consortium universities which results in graduate,
undergraduate, and associate degrees.
Research programs on the leading edge, feeding
into the education programs.
Education and research at campuses, as well as
from three field sites:
at the WIPP site (for nuclear and mixed waste),
at Hobbs, near the WIPP site (for waste
management associated with oil and gas
recovery), and
at a Soil-Water-Air Laboratory on the NMSU
campus (for hazardous and solid waste).
Ties with other multidisciplinary university
Ties with two national labs located in New Mexico.
Copyright ChE Division ASEE 1990
Chemical Engineering Education

Technology transfer and education via an existing
fiber optic network, a proposed satellite link, and
an existing state-wide extension program.


The Center of Excellence offers several educa-
tion programs:
Master of Science degrees in chemical, civil,
geological, mechanical, mining, petroleum, or
nuclear engineering, with special emphasis on
the management of radioactive, hazardous, and
solid waste.

A two-year Technology Associate degree program
in fields relevant to nuclear and hazardous waste
Short courses presented through interactive
satellite video to laboratories, industry, and federal
agencies throughout the country.

An undergraduate option in Waste Management
Engineering, with a major in one of the engineering
fields noted in Table 1.

Undergraduate degrees accredited by ABET
are offered at the Consortium universities (New
Mexico State University [NMSU], University of New
Mexico [UNM], and New Mexico Institute of Mining
and Technology [NMIMT]) in the engineering fields
listed in Table 1. Each department offers options
specific to its discipline, leading to a minor in Waste
The core programs necessary to satisfy ABET
requirements in each of the disciplines are specified
in the catalogs of the respective universities. These
core requirements are supplemented by 18-30 hours
of courses relevant to waste management, covering

Undergraduate Degree Options
in Waste Management Engineering

Agricultural Engineering /
Chemical Engineering V V
Civil Engineering V V
Electrical Engineering V V
Geological Engineering V V
Mechanical Engineering V V
Nuclear Engineering
Petroleum Engineering V
Mining and Metallurg. Eng. V

not just technology but also other aspects such as
legal, public policy, economics, and risk evaluation.

The graduate program also requires the stu-
dents to take core courses in their chosen discipline,
but with approximately one-half of their credits in
the waste management concentration, including a
research thesis in waste management.
An associate degree program in radioactive and
hazardous materials technology is offered at the
Carlsbad Branch of New Mexico State University.
Graduates of this program are prepared for entry-
level employment as technicians in industries,
laboratories, and government agencies concerned
with the generation, mining, disposal, transporta-
tion, storage, or regulation of hazardous wastes and
The associate degree in hazardous materials
technology is closely patterned after the accredited
engineering technology programs offered on the main
campus of NMSU at Las Cruces. Thus, an important
feature of the new curriculum is the high degree of
transferability into existing, accredited four-year
engineering technology programs. The engineering
technology approach to program design and opera-
tion carries implications with respect to faculty cre-
dentials as well as course content, level, and rigor.
The technology program uses the WIPP facility in
conjunction with the NMSU Carlsbad Campus as
the training facilities.
The interactive satellite video component has
the objective of presenting overview economic, legal,
policy, management, and technical courses in the
problems of radioactive, hazardous, and solid waste
management to U.S. research, industry, and educa-
tional facilities.


The research scope of the Center of Excellence
is broad-based and is designed to include all areas
of radioactive, hazardous, and solid waste manage-
ment. Research under this scope can cover a multi-
tude of subjects. A critical analysis of the research
areas shows that research is vitally need in the
following subjects:
Novel Waste Disposal Systems
Waste Constituent Identification and Migration
Waste Storage Systems
Development of Instruments
Waste Reduction and Minimization

Fall 1990

Risk / Economics / Management
Public Policy / Community Negotiations
Petroleum Contamination
Topics Related Specifically to WIPP
Meteorological Systems and Methods
Air, Soil, and Water Monitoring

Individual research projects are funded in the
foregoing areas based on the following criteria:
Excellence of the proposed work in terms of
scientific, engineering, economic, social, legal, or
institutional factors

Relevance to Center of Excellence thrust areas
and subjects of emphasis
Importance of research to solution of problems in
areas of greatest need
Extent of cross-disciplinary interaction and
collaboration with industry and national
Technical expertise of the investigators.

Three facilities are utilized by the program to
assist with research and education. They are
1. The soil-water-air testing and research facil-
ity on the NMSU campus at Las Cruces, which has
the role of providing analytical services in the areas
of toxic and hazardous waste management to re-
searchers from the universities and other organiza-
tions. The laboratory cooperates with different re-
searchers in acquisition and operation of specialized
testing equipment related to toxic and hazardous
waste management projects.
2. The Radioactive Experimental Facility at
Carlsbad, which has the role of exploratory develop-
ment and research associated with transuranic waste
isolation. Furthermore, it provides support for moni-
toring WIPP activities and for instrumenting experi-
mental activities planned by other facilities. By
combining above-ground laboratories in proximity to
the underground repository, closely-monitored, long-
term evaluations of isolation strategies can be car-
ried out along with the required control experiments.
This facility provides the place to build experiments,
instrument experiments, calibrate instruments, and
monitor results from experiments that depend upon
exposure to chemical, thermal, and radiation envi-

ronments only available at the WIPP site.
3. The experimental facility at Hobbs, which
provides for educational, research, and development
programs related to environmental and waste dis-
posal concerns of the petroleum industry in the
United States.
It is particularly important to note that each of
the facilities has an educational component and a
technology transfer component. Each of the facilities
will provide short courses and instructional televi-
sion courses as part of their mission. Another educa-
tional mission of the facilities is to train people in all
aspects of handling, monitoring, and management of
all types of waste.
The facilities participate in technology transfer
via biannual conferences. Invitations will be extended
to industry personnel, academic experts, State offi-
cials, the federal government (legislators, Depart-
ment of Energy, Environmental Protection Agency,
Department of the Interior), and private environ-
mental groups. The purpose of the seminars will be
to provide a forum for opposing points of view, with
the goal of conflict resolution so that a mutually
acceptable environmental program can be developed.

The technology transfer function of the consor-
tium is emphasized throughout the program. Spe-
cific activities for technology/knowledge transfer
Use of NMSU's existing extension system to transfer
information to communities and individuals.

Continuous dialogue with industry and the
National Laboratories via an Industrial Liaison
An Advisory Board composed of representatives
from top management of governmental, industrial,
and environmental organizations.
The entire educational program is designed to
transfer knowledge from theory and research to
the hundreds of students in this program.
Research results transferred via seminars with
participants from industry and government.
Results from each funded project will be reported
at least once each year. The fiber optic
communication network and the satellite link
are used for wide communication of the results.
Research results will also be transferred via
technical reports. Every research project will issue
accomplishment reports at least once each year.
Chemical Engineering Education

Short courses will be presented on topics of interest
with participants from government and industrial

Highlights of operation for each laboratory facility
will be reported in an annual report. These reports
will be published and widely distributed.

Technical papers will be presented and published
on the various aspects of the program. They will
include progress in the education program, the
laboratory operations, and the research results.

The technology transfer is only meaningful
if the information is utilized by the outside world.
Therefore, the Consortium plans to hold meetings
and seminars where industrial and governmental
representatives will discuss implementation of
research results. These seminars, meetings, and
workshops will be held at various locations, includ-
ing the three Consortium university campuses and
the three laboratory sites. The meetings will also
provide opportunities to conduct tours to further
transfer technology.


The program is led by a director who reports to
the Dean of Engineering at NMSU. The Dean also
serves as chairman of an executive board that sets
the strategic direction of the Center. The executive
board is made up of top management representa-
tives from DOE, the national laboratories, and in-
dustry, and provides oversight of Center plans and
progress by reviewing overall program plans and
strategies, key resource allocations, and key hiring
decisions, as well as evaluating progress against
approved plans and budgets.
The operations are managed by a director. An
advisory board (made up of selected representatives
from the three Consortium universities, the two
national laboratories, selected environmental organ-
izations, and selected industrial organizations) works
with the director to provide advice, information,
and ambassadorship to identify key external link-
ages and to promote relationships. This board ad-
vises on agency and industry needs, on mechanisms
to build relationships, and on the status of key envi-
ronmental variables including technology state-of-
the-art and practice.
Each of the major functions (research, educa-
tion, facilities, interactive TV) are supervised by tech-
nical heads who report to the director.

Industrial participation is built into the pro-
gram as part of the advisory board. In addition,
industrial participation is included in the "Indus-
trial Affiliation Program." Sponsorship is sought for
specific programs that satisfy the criteria listed pre-
viously, i.e., technical excellence and relevance to
the Center's purpose.


Beneficial results from the program will in-
Professionals with degrees in engineering and
with expertise in economics, law, and science
for the management of nuclear, hazardous, and
solid waste.

Technicians who have been educated in the safe
handling of radioactive and hazardous waste,
long-term storage principles, robotics, health
procedures, environmental monitoring, materials
accounting, and public education.
Dissemination of research results that will advance
the state of waste management technology
throughout the United States.

Educational programs that will utilize research
results and thus maintain state-of-the-art
technology for all the students. Upon completion
of their education, these students will enter the
workforce with knowledge and experience at
the leading edge of the technology.
Interactive satellite video courses that present
overview economic, legal, policy, management,
and technical courses in the problems of
radioactive, hazardous, and solid waste
management to research, industry, and
educational facilities throughout the United

1. Wentz, C.A., Hazardous Waste Management, McGraw-
Hill, New York (1989)
2. Theodore, L., and J. Reynolds, Hazardous Waste Incinera-
tion, John Wiley & Sons, New York (1987)
3. Brunner, C.R., Handbook of Hazardous Waste Incinera-
tion, TAB Book, Inc. (1989)
4. "Admiral Watkins Toughest Command," U.S. News &
World Report, p 29-30, August 14 (1989)
5. "Buried Alive," Newsweek, p 66-76, November 27 (1989)
6. "DOE to Support Pilot Program for Waste Management
Research," DOE News, July 26 (1989)
7. Dickson, T.G., "NMSU to Head Federal Program," Las
Cruces Sun News, 109, No. 118, p. Al, July 27 (1989)
8. Weick,P.R., "NM Picked to Train N-Waste Managers,"
Albuquerque Journal, 109, No. 208, p. Al, A3, July 27
(1989) O

Fall 1990




Cleveland State University

The Education Projects Committee of the Ameri-
can Institute of Chemical Engineers has conducted
surveys of the chemical engineering undergraduate
curricula since 1957 [1-7]. The most recent survey
was initiated in the summer of 1989. The informa-
tion provided by the chemical engineering depart-
ments in the United States was to be based on the
curricula in effect as of the fall term of 1989.
The survey results are based on ninety-two depart-
mental responses to a mailing which was made to
all departments listed with AIChE in the summer
of 1989.

The data received were entered into a LOTUS
1-2-3 worksheet for ease of analysis and review. The
questionnaire was revised to closely correspond with
the ABET/AIChE categories in order to facilitate
completing the form.

The semester hours required for the bachelor's
degree appear to be stabilized in the low 130s, as
shown in Figure 1. It is interesting to observe from
the more detailed information on the spreadsheet
that the range is from 112 to 146.3 SH. It is difficult
to determine if this is an anomaly of the individual
school's credit system or a true reflection of the class-
room hours of the student. More than eighty percent
of the departments require 125 to 140 semester hours,
with only seven reporting fewer than 125 and seven
reporting more than 140.

George A. Coulman is the Dean of Fenn College of
Engineering and a professor of chemical engineer-
ing at Cleveland State University. He received his
BS in chemical engineering, his MS from the Univer-
sity of Michigan, and his PhD as a Ford Foundation
Fellow at Case Institute of Technology. After seven
years in industry, he moved to academia and has
taught at the University of Waterloo, Michigan State
University, and Cleveland State University. He
teaches courses in control, computation, and optimi-
zation, as well as introductory chemical engineering.



"'134 F
125 ---__.

1961 1966 1972 1976 1981 1985 1989


The average curricular area distribution con-
tinues to be very close to the ABET/EAC require-
ments, as shown in Table 1. However, it is interest-
ing to notice that the range of the categories is quite
wide. The mathematics category ranges from 12.0 to
22.0 hours, with an average of 16.4. The average is

Distribution of Course Work

AIChE 1981 1985 1989
Curricular Area % Avg Avg Avg
Mathematics beyond 12.5 13.6 12.7 12.4
Basic Sciences 25.0 24.3 25.4 24.8
(Incl. Advanced Chemistry) (12.5) (11.7) (12.8) (12.3)
Engineering Sciences/Design 37.5 37.3 37.2 39.7
Humanities/Social Sciences 12.5 16.1 15.1 13.5
Other 12.5 8.7 9.7 9.6

TOTAL PERCENT 100.0 100.0 100.0 100.0

TOTAL CREDIT HOURS 133.4 131.0 132.8

Copyright ChE Division ASEE 1990

Chemical Engineering Education

the specified 12.5%, but the range would result
in values from less than ten to more than sixteen
percent. Similar attributes exist in the other catego-
ries. No significant changes have occurred in the
program category averages.

Some changes have occurred within the catego-
ries. Although mathematics continues to be predomi-
nantly calculus and differential equations, a diver-
sity appears in the residual credits. Twenty-one de-
partments require linear algebra, nineteen require
advanced calculus, and thirteen require partial dif-
ferential equations. Many departments have a mathe-
matics elective.

The basic science category shows an initial move
to diversity. Introductory physics and chemistry have
traditionally satisfied this requirement and continue
to dominate the credit hours. However, twelve de-
partments report modern physics, six list biology,
and seven indicate other basic sciences.

The advanced chemistry requirement contin-
ues to average 12.5% (16.28 hours) of the program.
However, the range of 10.0 to 22.0 was surprising.
The total chemistry content is shown in Figure 2.
This value has stabilized, as might be expected.

The engineering science and design category
has increased slightly to 39.6%. Statics is taken by
nearly seventy percent of the departments, while
approximately one-quarter of the departments re-
port dynamics and/or mechanics of materials. Sixty-
seven departments indicate introduction to electri-
cal engineering and/or electronics, with an average
of approximately 3.0 hours. Material science is re-
quired by half of the departments. One-third of the

Elective Offerings

1. Biochemical
2. Polymers
3. Environmental
4 Transport Phei
5. Applied Math
6. Control
7. Biomedical
8. Design
9. Mass Transfer
10. Reactors
11. Electrochemisl

# De




Elective # Depts.
Petroleum 12
Catalysts 11
Paper 9
Nuclear 7
Coal 5
Energy 4
Equipment 3
Food 3
Fuel 2
Natural Gas 2
Other 45

Some changes have occurred
within the categories. Although mathematics
continues to be predominantly calculus and
differential equations, a diversity appears
in the residual credits.


1957 1961 1968 1972 1976 1961 1985 1989
SNo. hourn of curriculum

departments require engineering graphics.

The chemical engineering component is sev-
enty percent of the engineering category. Several
observations in this area suggest that some signifi-
cant differences may exist. Three course identifiers
overlap but suggest a difference in focus. Seventy-
five percent of the departments report transport
phenomena, eight-two percent report mass transfer,
and fifty-four percent report unit operation theory.
The process dynamics and process control courses
appear to offer little distinct information and will be
consolidated in the next survey. This appears to be
true of kinetics and reactor design as well. Also, it is
surprising that four departments do not report a
capstone design course.

The most significant differentiation between
departments was in the elective available. Twenty-
one specific electives were included in the category
questionnaire along with a broad "other." The re-
sults are presented in Table 2. The leading elective
is biochemical, with approximately half the depart-
ments offering it. Forty percent offered polymers
and environmental electives. At the lower end of the
offerings were the energy-related areas (coal, fuel,
natural gas, etc.).

The cultural category (humanities and social
science) continued a modest decline, as shown in

Fall 1990

Figure 3. The average program contains 13.5 per-
cent (17.95 hours), which is near the ABET mini-
mum. At the low end is a department with 6.0
hours, while the high end is 55.3 hours. This ex-
treme range is startling. The high extreme is 42
percent of the program.

The collection of subjects in the ABET "Other"
category is expectedly diverse. However, the area of
communication (Figure 4) appears to have stabilized
at 90% of the departments requiring either written
or oral communication courses. Prior to the 1970s, it
was near 95%. The 1970s saw a drop to approxi-
mately 78%, followed by a rise to the present level.
The only other course with a significant number of
departments (70%) requiring it is computer program-
ming. Still expanding is the availability of "free-
electives," with forty percent of the departments
reporting them.
An illustration of the average program is shown


1957 1961 1968 1972 1976 1981 1985 1989

ma No. hour M, X of cuiculum


(X hool. offering)


Average Program Abstract

Analytical Geometry
Differential Equations
General Physics
General Chemistry
Physical Chemistry
Organic Chemistry
Other Chemistry
Electrical Engineering
Material Science
Fluid Mechanics
Heat Transfer
Material and
Energy Balance

Hours Course
2.81 Thermodyna
8.66 Reaction Eng
3.09 Transport Ph
8.07 Mass Transfe
7.81 Unit Operati
6.43 Laboratory
7.25 Process Conti
3.68 Design
2.54 ChE Electives
3.13 Humanities
3.01 Social Scienc
2.83 Communicati
2.33 Computer Pr
3.38 Other

mics 4.00
ineering 3.00
enomena 4.28
r 3.24
ons 4.02
rol 3.00
s 5.94
;e 7.44
ions 5.19
ogramming 2.50
TOTAL 132.78

in Table 3. This composite is useful for comparison.
However, for detailed understanding of the program
variation among departments, a review of the spread-
sheet is necessary. I have distributed this to all de-
partments that participated in the survey. If others
are interested, the author would be pleased to send
copies while they last.

The staffing questionnaire had no surprises.
The ninety-two reporting departments indicated 69.5
openings. Total current staffing includes five hundred
twenty-two professors, two hundred forty-five asso-
ciate professors, and one hundred ninety-one assis-
tant professors.


1. Thatcher, C.M., "The Chemical Engineering Curriculum,
Chem. Eng. Ed., September (1962)
2. Schmidt, A.X., "What is the Current ChE Curriculum?" J.
of Eng. Ed., October (1958)
3. Balch, C.W., "Undergraduate Curricula in Chemical Engi-
neering, 1969-1970, Chem. Eng. Ed., 6[1] (1972)
4. Barker, D.H., "Undergraduate Curricula in Chemical
Engineering, 1970-71," Chem. Eng. Ed., 6[1] (1972)
5. Barker, D.H., "Undergraduate Curricula 1976," Chem. Eng.
Ed., 11[2] (1977)
6. Barker, D.H., "1981 AIChE-EPC Survey," Chem. Eng. Ed.,
15[4] (1982)
7. Coulman, G.A., "Chemical Engineering Curriculum -1985,"
Chem. Eng. Ed., 20[3] (1986) J

Chemical Engineering Education


The 1990 ASEE Chemical Engineering Divi-
sion Lecturer is Brice Carnahan of the University
of Michigan. The purpose of this award lecture is to
recognize and encourage outstanding achievement
in an important field of fundamental chemical engi-
neering theory or practice. The 3M Company pro-
vides the financial support for this annual award.
Bestowed annually upon a distinguished engi-
neering educator who delivers the annual lecture of
the Chemical Engineering Division, the award con-
sists of $1,000 and an engraved certificate. These
were presented to Dr. Carnahan at a banquet during
the ASEE annual meeting at the University of
Dr. Carnahan's lecture was entitled "Comput-
ers in Engineering Education: From There, to Here,
to Where?" and it will be published in a forthcoming
issue of CEE.
The award is made on an annual basis, with
nominations being received through February 1,
1991. Your nominations for the 1991 lectureship are

Raymond W. Fahien (University of Florida)
received the Distinguished Service Citation for his
outstanding service to the profession over the past
forty years and for his unselfish and longstanding
devotion to excellence in engineering education. In
addition to his teaching and research activities, he
has edited the journal Chemical Engineering Educa-
tion since 1967.

E. Dendy Sloan, Jr., (Colorado School of
Mines) was the recipient of the fifth annual Corco-
ran Award, presented in recognition of the most
outstanding paper published in Chemical Engineer-
ing Education in 1989. His paper, "Extrinsic Versus
Intrinsic Motivation in Faculty Development," ap-
peared in the summer 1989 issue of CEE.
The Joseph J. Martin Award was presented to
John W. Hoopes, Jr. (Widener University) for the
best paper presented at the annual ASEE meeting.

R. Neal Houze (Purdue University), recipient
of the Clement J. Freund Award, was recognized for
his outstanding contributions to cooperative educa-
tion programs through twenty years of innovative
and impressive leadership
Joint recipients of the Meriam/Wiley Distin-
guished Author Award were Dale E. Seborg (Uni-
versity of California, Santa Barbara), Thomas F.
Edgar (University of Texas), and Duncan A.
Mellichamp (University of California, Santa Bar-
bara) for their joint coauthorship of the outstanding
textbook Process Dynamics and Control.
Philip C. Wankat (Purdue University) received
the Chester F. Carlson Award in recognition of his
exceptional work in integrating educational peda-
gogy with technical applications, and the Curtis W.
McGraw Research Award winner, James M.
Caruthers (Purdue University), was singled out for
his fundamental and original contributions to the
theory and application of polymeric materials.
Y. A. Liu (Virginia Polytechnic Institute and
State University) was honored with the George
Westinghouse Award for his outstanding achieve-
ments as a teacher, counselor, scholar, researcher,
organizer, and consultant.
AT&T Foundation Awards, honoring outstand-
ing teachers, were presented to W. Nicholas Delgass
(Purdue University) and John W. Zondlo (West
Virginia University), while Dow Outstanding Young
Faculty Awards went to Andrew L. Zydney (Uni-
versity of Delaware), Richard Turton (West Vir-
ginia University), Ronald W. Larsen (Montana
State University), and Robert H. Davis (Univer-
sity of Colorado).


The Chemical Engineering Division officers for
the 1990-1991 term are:
Past Chairman: William Beckwith
Chairman: Tom Hanley
Chairman-Elect: Timothy J. Anderson
Secretary-Treasurer: William L. Conger
Directors: William L. Conger
Glenn Schrader
H. Connie Hollein

Fall 1990



North Carolina State University
Raleigh, NC 27695

Students who are about to take stoichiometry
fear it, and many who are currently taking it hate it.
The homework never ends, and you can spend hours
on a single problem without getting anywhere. It's
the weedout course-30%, or 50%, or 70% flunk it,
depending on the institution, the class size, and who
is teaching.
So what's in this killer stoichiometry course?
"What goes in either comes out or stays in," that's
what-and usually we never get to the part where it
stays in, leaving us with Input = Output. Not exactly
intellect-stretching stuff. Of course, there's more-
gas laws (PV = nRT: given three variable values,
solve for the fourth), simple vapor-liquid equilib-
rium relations (yAP = p,*(T): given a vapor pressure
correlation and two of the variables yA, P, and
T, solve for the third variable), and energy balances
(Q = AH: given feed and outlet conditions, calculate
AH by integrating heat capacities and adding latent
heats, and then solve for Q). That's about it.
The energy balances give the students their first
brief immersion in the alphabet soup of thermody-
namics, but only up to U and H-and most of those
who go down in the course are lost well before they
get there.
What defeats many of them, I believe, is the
simplicity of the subject matter. The course starts off
with deceptively easy material: units and dimen-
sions, definitions of process variables, and material
balance problems that can be solved with college
freshman or even high school methods. We give ser-
Richard M. Felder is professor of ChE at N.C. State,
where he has been since 1969. He received his
BChE at City College of C. U.N. Y. and his PhD from
Princeton. He has worked at the A.E.R.E., Harwell,
and Brookhaven National Laboratory, and has pre-
sented courses on chemical engineering principles,
reactor design, process optimization, and radioiso-
tope applications to various American and foreign
industries and institutions. He is coauthor of the text
Elementary Principles of Chemical Processes (Wiley,
Copyright ChE Division ASEE 1990

Educational psychologists tell us that you
never...teach anyone how to do anything by
telling them how to do it. Rather, you teach them
by showing them how, and then having them try it
themselves and giving them corrective feedback.
I believe in this principle ...

mons about carrying units, drawing and labeling
flow charts, doing the problem bookkeeping or de-
gree-of-freedom analysis before plunging into the
math, but they don't believe us-and sure enough,
they get the right answers doing it their way.
Then the game changes. The problems get
longer, and we keep throwing more information into
the pot. We give them multiple process units, recycle
and purge, single and multiple reactions, volumetric
flow rates instead of mass or molar flow rates, and
relative saturations or dew points instead of mole
fractions-and the problems that used to take them
thirty minutes start taking an hour, then two hours.
They write equation after equation, but never seem
to have quite enough information to solve for the
quantities they are trying to calculate. Some begin
to believe that there may be a point, after all, in
being systematic about setting up problem solutions,
and save themselves; others resist to the bitter end
and fail.
I don't recall ever failing a student in stoi-
chiometry who really understood how to draw and
label a flow chart and to use it systematically in
the course of a problem solution. Consequently, since
I began teaching the course twenty years ago I have
directed more and more of my efforts toward moti-
vating the students to do just that. It seems to work.
Only about ten percent of the students who take
the course from me these days fail it, and most of
those give up early in the semester. Also, the atti-
tudes of those who pass are neutral to positive; rela-
tively few of my students drop out of chemical engi-
neering as sophomores because they hated the stoi-
chiometry course.
I don't claim that the approach to be described
here is THE WAY to teach stoichiometry-there is

Chemical Engineering Education

no such thing. I only say that it works for me and
may also work for others.


The course is taken in the first semester of the
sophomore year. Enrollment has been as high as 180
students within the past decade, but prior to this
year it has been fairly steady in the range of 60-70.
There is only one lecture section, regardless of the
enrollment.* Chapters 1-9 of the course text [1] are
covered, which gets us through steady-state energy
balances on reactive systems.

On the first day of class I hand out an assign-
ment schedule identical or similar to the ones given
in the instructor's manual for the text. A number of
problems are marked as "bonus problems." They are
typically more difficult and/or longer than the regu-
larly assigned problems, or they require different
thinking skills (e.g., divergent thinking or problem
creation exercises), and many require computer so-
lution. The bonus problems serve both to stretch the
best students and to give me more flexibility in grad-
ing; they are optional unless the student wants to
get an A in the course, in which case some of them
are mandatory.

On the first day I also hand out and discuss a

written statement of policies and procedures (see
Table 1). The policy statement serves to establish
my ground rules, up front and in writing, thereby
forestalling endless explanations, arguments, and
bitter feelings at the end of the course. In my experi-
ence, students can deal with almost any rules, tough
or lenient, as long as they know what the rules are
and the instructor adheres strictly to them.

Let me make a few points about some of the
policies mentioned in the handout. Students do a
substantial part of their learning when they are
doing homework: only then do they discover that
they really didn't get what looked completely straight-
forward in a lecture. Consequently, if I want them to
get the material, I must do all I can to encourage
them to do the homework. Counting homework per-
formance toward the final course grade is one way to
do this, and accepting late homework with a penalty
is another.

Working together on homework in "study com-
munities" has been shown to have dramatic positive
effects on students' course performance [2], and so I
encourage cooperative efforts on homework in the
stoichiometry course (and in every other course I
teach). If I insist on individual efforts on all home-
work assignments, I deprive students of a powerful

Policies and Procedures

* There \ III be three quizzes and a final examination. All tests
will be open-book. The lowest quiz grade will be dropped.
Required homework will be assigned every week, and there
will also be a series of "bonus problems."
* No excuses for missed exams will be accepted other than
certified medical excuses. If your alarm fails to go off or your
car doesn't start on the day of a quiz, the zero you get will be
the grade that is dropped. If it happens on the day of the final,
see you next semester.
* Homework should be handed in at the beginning of the
period in which it is due. Late homework will be accepted up
to the Friday before the last week of class and will receive a
maximum grade of 60%. However, if you abuse this privilege
by routinely handing homework in late or coming in with 20
problem sets on the last day, the privilege will be withdrawn.
* A weighted average grade will be calculated as follows:


2 units
1 unit
2.5 units

Letter grades will be assigned on a curve. However,
* There will be a "gray area" between each two letter grades in
the final distribution, so that two people getting the same

weighted average grade could get different letter grades. If
you are in one of these gray areas, whether you get the higher
or lower grade depends on two factors: (a) your performance
on the bonus problems (how many attempted, grades
achieved), and (b) whether your test and homework perform-
ance has been improving (you go up) or declining (you go
* To get an A in the course, you must attempt and do satisfac-
tory work on at least eight bonus problems in addition to
getting the necessary weighted average grade on homework
and tests.
* You may work in groups on the required non-computer
homework-in fact, you are encouraged to do so. Individual
solutions must be handed in, however. You may not collabo-
rate on the computer homework, except to get help with
debugging; programs that are too nearly identical will be
regarded with grave suspicion. You may do the bonus prob-
lems individually or in pairs; in the latter case, only one
solution need be handed in.
* Homework solutions will not be posted. The burden is on
you to make sure you find out how to solve the problems by
getting help before they are due and/or asking about them in
class after they have been handed in.

* I do not recommend this feature of the course.

Fall 1990

learning tool. There is no good reason to do so. If
they simply copy the work of others without under-
standing it, they will go down on the tests. On the
other hand, if they are copying and learning enough
to do well on the tests, then the homework has
served its function-so why should I care?
I strongly recommend not posting homework
solutions. When I post solutions, the students sim-
ply copy them without thinking about them, and
thereafter I see my solutions coming back at me
again and again in subsequent semesters.
Some of my colleagues are uncomfortable with
the grading flexibility I grant myself by using such
subjective (i.e., non-numerical) criteria as "satisfac-
tory" performance on bonus problems and rising or
falling patterns in test grades. I understand their
feeling. However, I am much more uncomfortable
with the intrinsic unfairness of strictly objective
grading, which is based on the illusion that there is
a qualitative difference between a student who gets
a 69 and one who gets a 70. Again, as long as I
clearly state my criteria, objective or subjective
though they may be, I do not get complaints from
students about my unfairness in assigning grades.
Educational psychologists tell us that you never
(well, hardly ever) teach anyone how to do anything
by telling them how to do it. Rather, you teach them
by showing them how, and then having them try it
themselves and giving them corrective feedback. I
believe in this principle and so do very little formal
lecturing in the stoichiometry course. Instead, I an-
swer questions and outline (or get the students to
outline) problem solutions, modeling for them the
techniques I want them to learn. After repeatedly
seeing me work problems in twenty minutes that
took them two hours, they start to believe that my
way works better than theirs.
I begin each period by asking if anyone has any
questions about anything. Since I don't post solu-
tions, there are almost always questions of the type
"How do you do Problem 34?" My preferred proce-
dure is to have the students form groups of three at
their seats and work on the problems in these
groups-one person writing, three talking. I first
ask them to draw and label the process flow chart. I
generally don't give them enough time to complete
it, but stop them after two or three minutes and do it
myself on the board, calling on specific groups to tell
me what to write next. I then lead them through the
solution in steps, giving them tasks, stopping them

before most of them can finish, and outlining the
solutions on the board with their assistance. We
don't do any algebra or arithmetic-that's their re-
sponsibility to do on their own time if they want the
If I don't want to spend too much time on a
given problem, I give the students less to do and go
through most of the solution myself. I lecture some-
times when we get to concepts that they tradition-
ally have trouble with (multicomponent vapor-liquid
equilibrium calculations, for example, or the intro-
ductory material on the first law), but these lectures
probably account for no more than twenty percent of
the total class time.
In the next section I present a problem and
then outline how I would go through the solution in
class. The problem (a modified version of an example
problem in the text) involves material balances on a
process with recycle and a gas law calculation. The
solution procedures to be shown are explicitly pre-
sented in the text, but like most formal problem-
solving strategies in textbooks, they are universally
ignored. Only through repeated illustration in class
do they become part of the working tools of most of
the students in the course.
Crystalline potassium chromate (KCrO,, which we
will abbreviate as PC) is to be recovered from an
aqueous solution of this salt containing one-third
PC by mass. Forty-five hundred kg/h of this solu-
tion is mixed with a recycle stream containing 36.4
wt%PC, and the combined solution is fed to an
evaporator, which operates at 75 UC and -450 mm
Hg. Two streams leave the evaporator: water vapor
at the evaporator temperature and pressure, and an
aqueous solution containing 49.4%PC. The latter
stream is fed to a crystallizer in which it is cooled to
0 C, causing solid crystals of PC to precipitate out
of solution, and the resulting slurry is then filtered
at the crystallizer temperature. The filter cake con-
sists of all the PC crystals and a solution containing
36.4 wt%PC. The crystals account for 95% of the
total mass of the filter cake. The filtrate (the solu-
tion that passes through the filter), which also con-
tains 36.4 wt%PC, is the recycle stream.

Calculate the fraction of potassium chromate in the
feed recovered as solid crystals, the ratio (kg recycle
/kg fresh feed), the volumetric flow rate (m3/h) of
the vapor effluent from the evaporator, and the
mass flow rates (kg/h) of the feed streams to the
evaporator and crystallizer.

I outline below in excruciating detail how

Chemical Engineering Education

I might work through this problem in class. I hasten
to say that I rarely do anything this elaborate for
any individual problem. However, each question/re-
sponse pair to be given illustrates an important as-
pect of the approach to process analysis that I am
trying to teach, and so if a particular type of ques-
tion does not come up in a given solution, it will
come up in others. I suggest that readers who
are not specifically involved in teaching stoi-
chiometry might skim the balance of this sec-
tion to get an idea of what I am doing, and that
readers who are teaching the course might pay
a bit more attention to the details.
My lines are in italics, and possible answers to
my questions are in parentheses.
OK, get in groups of three, read the problem
statement, and draw and completely label a flow
chart of the process. You've got three minutes-go!
I am presuming that we've done group exer-
cises in class before so I don't have to explain the
procedure to them. The first time I do it, some stu-
dents may be uncomfortable or think it's a game, but
after two or three such exercises they start taking it
seriously. As they get to work, the noise level in-
creases and the classroom loses the usual wax mu-
seum atmosphere that characterizes typical lecture
(Three minutes later.)
Stop-everyone with me.

Most groups will not have time to complete the

task, which is fine. My objectives are to get them all
to think about the problem, to figure out how to get
started, and to take the first few steps. Two or three
minutes are more than enough time to achieve these
I then draw the flowchart on the board and call
on different groups to tell me how to label the streams.
We end up with something like the illustration in
Figure 1.
Next, I go through a series of questions de-
signed to make sure the students understand the
flowchart and the process it symbolizes and know
what they are being asked to determine. I ask the
groups to discuss some of the questions for a few
seconds and decide on answers among themselves,
and I call on the class as a whole for responses to
other questions.
What's the basis of calculation here?
(4500 kg/h of fresh feed)
Is the filter cake stream labeled completely?
How do you know?
(Because you can express the flow rates of
both stream components-PC and W-in
terms of what's written on the chart.)
What's the flow rate of potassium chromate in
that stream?
(n, + 0.364 ns)
How about water?
(0.646 ns)
What if I asked you for the mass fraction of water
in the total filter cake and not just the solution?

PC = K2CrO4
W= H20

4500 kg/h n, (kg/h)
1500 kg PC/h x, (kg P
3000 kg W/h t (1-xi)(kg V

V (m /h)
n,(kg W(v)/h)
750C, -450 mm Hg

Filter cake (95X crystals)
nc(kg PC(s)/h) (crystals)
ns(kg soln/h)
0.364 kg PC/kg soln
0.636 kg W/kg soln


Filtrate (recycle)
0.364 kg PC/kg
0.636 kg W/kg

Figure 1

Fall 1990

(0.646 ns / [n, + ns])
Is the whole chart labeled completely?
How do you know?
(Because every stream is labeled completely.)
In terms of the labeled variables on the chart,
what does the problem call on us to calculate?
(ne/1500, n/4500, Vw, n1, and n2)
Why is liquid in the filter cake, and why does that
liquid have the same composition as the filtrate?
See if you can put it in terms of a filtration
process many of us encounter every morning?
(It's like brewing coffee in a drip pot. You don't
get dry powder left on the filter-it's a soggy
mass containing solid grounds and coffee, the
same liquid that goes through the filter.)
What might be the physical significance of the
36.4 wt%PC composition of the filtrate?
(It's the solubility or saturation concentration
of PC in water at 0C, the most potassium
chromate that can be dissolved in water at
that temperature.)
What do you think would happen if we cooled the
solution in the crystallizer to a lower temperature
than 0 "C?
(PC would have a lower solubility and more
crystals would precipitate.)
So why don't we do it?
(It might cost more for the additional cooling
than the additional crystals are worth.)
What's the function of the evaporator?
(It concentrates the solution, so that when you
cool it to the crystallizer temperature more
solid precipitates.)
What if it weren't there?
(You would recover less salt for the same
crystallizer temperature or you would have to
cool to a much lower temperature to recover
the same amount of salt.)
How could you recover pure solid potassium
chromate, which is what you really want? In other
words, where might the filter cake go next in the
(To a dryer, in which the residual water is
vaporized. It's like letting the coffee filter
stand in the sink for a few hours so the water
in the wet grounds evaporates, leaving a dry
In practice, this process might not be truly
continuous, so that the calculated flow rates
would be averages over time. Can you think of
which operation would probably not be
(Filtration-the filter would have to be taken

out periodically, the filter cake dumped, and a
clean filter put in.)
Can you invent a way to get around this, so that
the process is truly continuous?
(Use a moving belt or screen as the filter,
scraping the filter cake off at the end.)
OK, back to the problem. What next?
(Identify possible process subsystems and do
the problem bookkeeping to find a starting
point for the calculation.)
Which system would you try first?
(The overall process.)
Good-do it. Three minutes.

Possible subsystems include the overall proc-
ess, the fresh feed/recycle mixing point, the three
individual process units, and combinations of the
units. Problem bookkeeping is an informal version of
degree-of-freedom analysis; unknown variables as-
sociated with the streams entering and leaving the
chosen system and sources of independent equations
relating them are counted. If the number of vari-
ables equals the number of independent equations,
the calculation can proceed. If there are more vari-
ables than equations, see if any information has
been overlooked, and if none is found, try another
system. The overall system is shown in Figure 2.
Bookkeeping! How many unknowns?
What are they?
(Vw, nw, nc, and ns.)
What equations can we come up with?
(Two material balances, the 95% figure for the
filter cake, and the ideal gas law for the water
Why two balances?
(Because there are two independent species
and no reactions.)
What possible balances could I write?

VW (m /h)
nw (kg W(v)/h)
75 C, -450 mm Hg

OVERALL n. (kg PC(s)/h) (crystals)
1500 kg PC/h SYSTEM n, (kg soln/h)
3000 kg W/h 0.364 kg PC/kg soln
0.636 kg W/kg soln
95X crystals, 5X soln
Figure 2
Chemical Engineering Education

We have to play with the hand we are dealt: the
next generation of engineers will come from this
group of students... .If the teaching method used
for the past nine hundred years is ineffective,...
we need to find better methods.

(Total mass, potassium chromate, water,
atomic potassium, atomic hydrogen,...)
So what's the significance of 2?
(That's the number that are independent-
once you satisfy any two of the balances, the
others are automatically satisfied.)
OK, so we can work out this system, at least in
principle-four equations in four unknowns,
including two that are asked for in the problem
statement. What's our next decision?
(Which equation do we write first?)
What determines the answer?
(Which one involves the fewest unknowns.)
Fine-let's check the possibilities, balances first.
What form do all the balances take?
(Input = output)
(No generation and consumption because
there are no reactions, no accumulation
because we're at steady-state.)
Which unknowns are involved in an overall mass
(nw, n., ns)
What is that balance?
(4500 = nw + n. + ns)
Which unknowns are involved in a chromate
(ne, n )
A water balance?
(nw, n )
The gas law?
(nw, V )
The filter cake composition relation?
(nc, ns)
How do you translate the statement "The crystals
in the filter cake comprise 95% of the total mass of
the filter cake" into an equation?
(n. = 0.95[n. + n])
So the worst has happened-we can't come up
with one equation in one unknown! What do we
do now?
(Write the filter cake composition equation
and the potassium chromate balance.)
Why those two?
(Because they involve the same two unknowns
and you can solve them simultaneously.)
Good, let's do it, circling the variables we're

solving for.
(Write on board.)
Filter cake composition: nc = 0.95(nc +ns)
Overall PC balance: 1500 = n, +0.3636n J

What do I do once I've done the algebra and found
n and n ?
(Write the values on the flow chart.)
Then what?
(Write the water balance or the total mass
Why not the gas law?
(Because the gas law still involves two
unknowns, but the balances each involve only
OK-we'll write the water balance.

Overall water balance: (4500)(0.6667) = n + 0.6364n,

(Write nw on the chart.)
How can we find out if we've made an algebra
(Write the total mass balance and make sure
it closes.)
OK, let's say it works. Now what?
(Now write the gas law.)

Gas law:
PV = nRT = (760- 450)( ) = n (kg) (R)(75 + 273.2)
18 kg / kmol
(Write the value of V on the chart.)
What have we assumed here?
(Barometric pressure is 1 atmosphere and the
ideal gas law works.)
How about the assumption of ideal gas
behavior-think we might have a problem?
(Not likely-at temperatures above ambient
and pressures less than one atmosphere the
ideal gas law should work fine. To be on the
safe side, we can always calculate the
compressibility factor and correct V if Z is
much different than 1.)
And now?
(Choose and analyze the next subsystem.)
Which one should we consider first?
(How about the recycle mixing point.)
The mixing point is where most students would
start writing balance equations, since it looks like

Fall 1990

the simplest of the possible subsystems. If isolated,
this system appears as shown in Figure 3.
How many unknowns?
(Three--nr, nl, and x,.)
How many equations?
(Two-two independent material balances.)
Any more information about these streams buried
in the problem statement?
So what do we do?
(Try a different system-this one won't work.)

We could, of course, just write equations for all
the systems and sooner or later come up with a set
that could be solved if the process is well-defined.
However, most students will give up before they
reach that point; moreover, if the process is not well-
defined, the students will discover it in a few min-
utes this way rather than spending hours trying to
solve an unsolvable problem.
We would go on to do the bookkeeping on the
evaporator next (left to right seeming like a logical
way to search) and would find that this system also
would not work-it involves two equations in three
unknowns (n1, x,, and n2). We implicitly wrote bal-
ances on the crystallizer when we labeled the flow
chart so there is noting more we can do with that
system. The filter is left as our last hope (see Figure
Bookkeeping. Unknowns?
(Two-n2 and nr.)
(Two balances.)
Bingo! Which balance first?
(It doesn't matter. Balances on PC, W, and
total mass each involve both unknowns. Write
any two and solve simultaneously.)
OK-here we go.

Mass balance on filter: n2 n + n, + n
PC balance on filter:
0.494n2 =n. +0.3636ns +0.3636nr

(Write the values on the chart.)
Then what?
(Now we can attack either the mixing point or
the evaporator-both involve two unknowns,
n1 and x,, and two equations.)
Fine. Let's do the mixing point. Which balance
(Total mass first-it only involves one unknown.

Then either PC or W.)
Right. Here they are.

Mass balance on mixing point: 4500 + nr =
PC balance on mixing point: 1500 + 0.364nr = ni
(Write them on the chart, and then calculate
the remaining quantities the problem
statement asked us to determine--n/1500
and n/4500.)
Good. Now before we leave this process, let's think
about that recycle. What does it do for us?
(It lets us recover some of the potassium
chromate that didn't precipitate the first time
What if we didn't recycle?
(We'd lose a lot of PC in the filtrate.)

This is the kind of explanation that many stu-
dents simply won't get, and many who think they
got it really didn't. If I want my students to under-
stand arguments like this, I must either show them
the numbers or have them work them out them-
selves. In the case at hand, I might redraw the flow
chart without recycle, quickly step through the solu-
tion, and observe that with recycle we recover 98% of
the potassium chromate in the feed as solid crystals

1500 kg PC/h
3000 kg W/h

n, (kg/h)
x, (kg PC/kg)
(1-x, )(kg W/kg)

nr (kg/h)
0.494 kg PC/kg
0.506 kg W/kg
Figure 3

nz(kg/h) FILTER I n(kg PC(s)/h)
0.494 kg PC/kg ns (kg soln/h)
0.506 kg W/kg 0.364 kg PC/kg soln
I 0.636 kg W/kg soln
n, (kg/h)
0.364 kg PC/kg
0.636 kg W/kg
Figure 4

Chemical Engineering Education

(and 100% of it if we include the subsequent drying
step), while in an a cyclic process only 41% of the
solute in the feed precipitates, and 58% of it is lost
with the filtrate. I could also get the class to specu-
late on why we might have chosen to use a complex
evaporation-crystallization-filtration-drying sequence
with recycle rather than simply running the feed
solution through a single evaporator and driving off
all the water in one operation.
One more question. What if we build this process,
run it according to our design specifications,
measure the yield of crystals, and find that it is
less than our design value? What could be
(Errors in temperature, pressure, and flow
rate measurements; not enough residence
time in the crystallizer to achieve complete
precipitation; more residual liquid in the filter
cake than we figured on; the solubility of
potassium chromate at 0C is greater than we
thought; the solute is not pure potassium
chromate; operator errors; etc.)


And that's that. Does it take more time than
simply laying out the solution myself in class and
much more time than posting the solution outside
my office? Yes, it does. Is there a more productive
use I could make of the class time? I don't think so,
and even if there is I know it isn't reciting the text
material and doing algebra on the board. Besides, it
isn't necessary to go through the whole elaborate
dialogue for every problem; after I've done it a few
times I can move through the solutions much more
rapidly as the class becomes familiar with the drill.
I use this group-based Socratic approach be-
cause it feels comfortable to me, students respond
well to it in terms of both their class performance
and their attitude, and it is consistent with certain
educational psychology principles and research find-
ings [3.4]:
SStudents do not learn anything nontrivial in one
shot; for a skill to be learned and mastered, it
must be taught and exercised repeatedly. If I
want my students to develop a systematic
approach to material and energy balance
calculations, I have to model the approach for
them and get them to follow it over and over
again. Providing in-class exercises that step them
through the procedure is an effective way to do

People learn best either when they are acting
(doing something, talking to someone) or
reflecting (thinking about the information they
are trying to understand or the problem they are
trying to solve) [3]. They retain little of what
they get when they are simply being passive-
listening to a lecture, for example. This being the
case, in a problem-solving course like
stoichiometry I might as well use most class time
for what instructs (solving problems) and spend
little time on what does not (lecturing).
Group problem-solving exercises in class are an
effective way to teach material: they give active
learners something to do and reflective learners
a chance to think. They also involve all
students-it's easy to hide in a class of 30 or 60
or 150, letting your mind wander, but you can't
readily hide in a group of three. Moreover, once
students become involved they tend to stay that
way, even after the exercise is over; as little as
five minutes of this type of activity spread over
the course of an hour can be enough to keep the
whole class engaged for the entire period.

A final point concerns the technique of outlin-
ing a problem solution by writing down equations
and circling the variables to be solved for but not
doing the algebra and arithmetic. This technique
does two things for me. First, it allows me to go
through complex solutions in class in a reasonable
period of time. Second, it allows me to put any prob-
lem I want to on a test.
A difficulty with the stoichiometry course is
that problems involving combined material and en-
ergy balances and phase equilibrium calculations
take a long time to solve, even when done efficiently.
In particular, they simply do not fit on fifty-minute
quizzes. Many instructors deal with this difficulty
by giving fragmentary problems on quizzes (calcu-
late a dew point, integrate a heat capacity formula)
that do not test the student's ability to integrate the
material. Alternatively, tests are given that are far
too long to be completed in the allotted time, leading
to terrible grades and student frustration and re-
What I do is announce to my class that some of
their test problems will call on them to draw and
label a flow chart, write the necessary equations,
and circle the variables they would solve for. If they
follow this procedure, they will have enough time to
show me that they know (or don't know) how to solve
comprehensive problems. However, it is essential to
illustrate the procedure in class several times before
putting it on a test; if I didn't, many of the students

Fall 1990

would not understand what I was asking for and
would go back to the conventional method of grind-
ing out all the calculations, probably running out of
time with less than half of the test completed.

When large numbers of students fail the stoi-
chiometry course, our unstated presumption is that
none of them are qualified to be chemical engineers
and we are serving society by weeding them out. I
question this presumption. Since the course is con-
ceptually not all that difficult, we should at least
entertain the possibility that many are not learning
the material because we are not teaching it well.
We can stoutly assert (as some will when they
read this article) that by the time our students get to
us they "are supposed to be adults," that we should
not have to "hold their hands" or "spoon-feed them"-
and when their test averages are in the 40s and
many of them fail and/or drop out, we can grumble
about how they are unmotivated, apathetic, incom-
petent in mathematics, and so on. All of that may or
may not be true, but it misses the point. We have to
play with the hand we are dealt: the next generation
of engineers will have to come from this group of

students, whether we like it (and them) or not. If the
teaching method used at universities for the past
nine hundred years (wherein the professor speaks
and the students sit at his feet and absorb wisdom)
is ineffective, then we need to find better methods.
This paper suggests an approach that has been found
effective in the context of one chemical engineering
course. It may not solve the problem, but it could be
a start.
Many thanks to the faculty of the School of
Chemical Engineering at Georgia Tech, where this
article was written while I was on sabbatical leave,
for their hospitality, and to Dick Bailie and Paul
Kohl for helpful critiques of a preliminary draft.
1. Felder, R.M., and R.W. Rousseau, Elementary Principles
of Chemical Processes, Second Edn., John Wiley & Sons,
Inc., NY (1986)
2. Conciatore, J., "From Flunking to Mastering Calculus,"
Black Issues in Higher Education, p 5, Feb. 1 (1990)
3. Felder, R.M., and L.K. Silverman, "Learning and Teach-
ing Styles in Engineering Education," Eng. Ed., 78(7), p.
4. Gagne', R.M., The Conditions of Learning and Theory of
Instruction, CBS College Publishing, New York (1985) J

and AC the concentration driving force.

So that

It was with some interest that I read the article
"A Laboratory Experiment on Combined Mass Trans-
fer and Kinetics," by S. A. Sanders and J. Sommer-
feld. I would like to offer the following comments:
1. I searched for a mass transfer link, like kL or DA for
example and it was in vain. Does not a "film"
transfer disguise the overall kinetics? If it did not,
where else does mass transfer interfere to justify
the title?

2. For the aspect ratio to remain constant, (h/r)t should
equal (H/R). This condition holds for a very special
initial geometry where H = R and approximate
spherical symmetry for later times would ensure
that (h/r) equals unity. If H R, a rough analysis
would show that

ah 2

and --o h.r

at at
The proportionality constant is 4 = ( (k1, kL; AC)
where k1 is the intrinsic heterogeneous rate
constant, k, the external mass transfer coefficient,

dh r
dr t h

Therefore it is the function

f(r,h) 1-(r/H)2
1 -(h/H H)2
that equals H/R, when R = H, a remains constant
at unity.
3. Experiments could have been interrupted and
aspect ratio shown to be constant or variable at
various t. A tumbling soft pellet like the antacid
tablet is hardly expected to maintain sharp corners.
It might even disintegrate like "disprin," probably
it does in the stomach.

4. Tablets are often porous and the rate equation
proposed (Eq. 3) may not be valid even in the
absence of external diffusion resistance.

Professor G. Narasimhan
Monash University
Clayton, Melbourne, Victoria,
Australia 3168

Chemical Engineering Education

@B letter to the editor

In Memoriam...


Lee C. Eagleton died abruptly on May 15,
1990, of heart failure after an inspiring five-year
battle with multiple myoloma. He was born on
July 27, 1923, in Vallejo, California, to a naval
officer and his travel-lov-
ing spouse. Lee is survived
by his wife of thirty-seven
years, Mary, and by his
three children, William,
James and Elizabeth, and
one grandchild.
Lee was educated in
chemical engineering at
MIT (BS and MS) and at
Yale University (DEng).
His professional career en-
compassed one year as Re-
search Associate at Colum-
bia, five years as Develop-
ment Engineer with Rohm
& Haas, fourteen years on
the faculty of the Univer-
sity of Pennsylvania, and
fifteen years on the faculty
of Penn State University
(thirteen of them as De-
partment Head). Lee's re-
search activity during the first part of his career
left its mark on the profession. In the second part,
his leadership brought growth and recognition to
chemical engineering at Penn State.
He was at his best, however, in the human
interactions that comprise extra-curricular profes-
sional activities, almost all of which were related
to the focus of his dedication, chemical engineer-
ing. He had held all of the offices in the Chemical
Engineering Division of ASEE at one time or an-
other and was completing his fifth year as Chair of
the Publications Board when his cancer was diag-
nosed. Lee was active as well at all levels of AIChE,
especially in Education and Accreditation, and from
1980 to 1983 he served as an elected Director to

the national organization. The local section recog-
nized him with the Diamond Jubilee Award. At
the national level he was an AIChE Fellow and re-
ceived the Founder's Award. For his extraordi-
nary service to the Chemical
Engineering Division, he was
named ASEE Fellow.
Lee's candor and wit,
which served him and his
S colleagues so well through-
out his professional career,
continued during his ex-
tended illness. All who came
into contact with him were
immediately set at ease in
the resulting conversations.
He would observe casually
that the familiar greeting,
"How are you?" took on new
meaning in his situation,
and then he would go on to
answer the question liter-
ally. Thus his friends and
acquaintances understood
clearly what he was experi-
encing, as well as the deter-
mination and humor that he
was bringing to this ultimate physical and intel-
lectual challenge.
During the years of his illness, Lee and Mary
traveled extensively to ASEE and AIChE meet-
ings as well as overseas. With his indomitable
spirit he was looking ahead, from his wheelchair,
to trips to a family reunion in Illinois and to his
vacation home on St. John. In fact, a few days
after Lee's death, Mary received a call from a local
photography store. The camera that Lee had or-
dered had come in.
It is little wonder that his colleagues and
friends were inspired by his attitude during the
last five years of his life and delighted and stimu-
lated by his presence for a lifetime.

Fall 1990


MX -classroom


Opportunities for Chemical Engineers

Purdue University
West Lafayette, IN 47907

IN ALL THE furor over new technologies and the
wealth of opportunities they hold for chemical en-
gineers, the biggest change in mathematics as a
source of opportunity is probably the development of
new applications. The remarkable computing poten-
tial of current hardware and software presents new
alternatives for the use of mathematics. A belief that
the reputation of analysis has suffered in recent years
(at least in expression, if not in practice) is the main
reason for this article. More specifically, the objective
of this article is to deliberate on certain areas of
applied mathematics that may be old but which are
most useful, and others that are new but which hold
great promise.
In meeting this objective, we are faced with two
dilemmas. First, mathematics is so diverse and frag-
mented that even mathematicians find communica-
tion between themselves hampered by specialized
machinery. This makes writing a coherent article on
the application of mathematics difficult because of
constraints on one's familiarity and because of the
discomfiture that comes from the limited rationale of
one's selection. Yet, a compromise possibly lies in the
selection of an area of mathematics which has wide
applications in chemical engineering and the exami-
nation of how that area fulfills various requirements
of the discipline.
This brings up the second dilemma. Engineer-
ing applications, too, are diverse and difficult to
categorize. How can one devise a coherent scheme for

Doraiswami Ramkrishna is professor of chemical
engineering at Purdue University. He received his BS
from Bombay University and his PhD from the Univer-
sity of Minnesota. This article was compiled while he
was the George T Piercy Distinguished Visiting Pro-
fessor at the University of Minnesota during the fall of
1988. His research interests cover applied mathemat-
ics, dispersed phase systems, and biochemical engi-

covering such disparate applications? Figure 1 pres-
ents an attempt in this direction which, with suitable
interpretation, could embrace the newer areas. It
views chemical engineering analysis as being broadly
concerned with the application of two physical
theories-continuum and statistical, the latter of
molecular and particulate states of matter (which
purport to include heterogeneous media, etc.) to chemi-
cal process systems (or other systems in which matter
undergoes similar experiences). Methods of averag-
ing used in the treatment of heterogeneous media
may be absorbed in continuum analysis. Commen-
tary on Figure 1 also presents the opportunity to
briefly (and superficially) cover general areas of
mathematics which are useful to chemical engineer-
ing whether or not they are in current use.


Figure 1 depicts the methodology of chemical
engineering in a sequence through which a mathe-
matical model of a system matures to the stage at
which it serves to guide the design and control of the
operating system. Formulation represents the stage
of its birth in which constitutive equations are pro-
posed based on material behavior observed experimen-
tally and on certain principles. In this regard, the
framework of rational thermodynamics by Truesdell
and coworkers [1-3], in spite of being germane, has
received little attention from chemical engineers.
(This is particularly true with respect to guidelines
for constitutive equations in multicomponent sys-
tems which contain results at variance from irrevers-
ible thermodynamics and which could possibly be of
significance.) Caruthers and coworkers [4,5] have
recently exploited the framework to formulate consti-
tutive equations for viscoelastic polymers. This for-
mulational stage employs vector and tensor calculus,
algebra, and topology.
The next stage is model validation, which must
interact mutually with formulation. Validation could
@ Copyright ChE Division ASEE 1990
Chemical Engineering Education

A belief that the reputation of analysis has suffered in recent years (at least in expression,
if not in practice) is the main reason for this article. More specifically, the objective of this article is to
deliberate on certain areas of applied mathematics that may be old but which are most useful,
and others that are new but which hold great promise.

be a long drawn-out process exceeding the bounds
indicated in which the investigation of solution struc-
ture (a favorite term ofAmundson) could be a partici-
pant. Here the implements do, or could, originate
from statistics, stochastic filtering theory, inverse
scattering theory, functional analysis, etc.
A model which emerges from the validation
state (but not necessarily weathered to that of accep-
tance) is ready to be probed for its mathematical
solution structure. This stage is preliminary to de-
tailed computation and is one in which several ana-
lytical and semi-analytical tools of functional analy-
sis (including nonlinear bifurcation and stability
theories, catastrophe, and singularity theories), to-
pology, differential, and algebraic geometry (rela-
tively unfamiliar to chemical engineers), etc., are, and
have been shown to be, very useful. Indeed, this stage
may substantially overlap with the validation stage
because of its capacity to create subtle situations for
discriminating between models. Particular attention


is called to recent successes of differential geometry in
the solution of partial differential equations [6]. Since
the resolution of singularities is an integral aspect of
algebraic geometry, it has many potential applica-
tions in the analysis of chemical reaction systems.
Engineering analysis consists of obtaining de-
tailed solutions of model equations by examining
system behavior under various circumstances.
Numerical methods form the backbone of this effort,
even in implementing analytical solutions. The method
of finite elements has established itself as a tool
of central importance in the analysis of complex
models. In view of the many free boundary problems
in chemical engineering, and the facility of algebraic
geometry to describe geometric shapes, attention is
called to the use of rational basis functions in finite
element methodology [7].
Finally, the synthesis stage represents the ulti-
mate accomplishment of mathematical models in
realizing engineering objectives. Here, control theory
and the methods of operations
research form the bulwark of
process systems engineering.
Ical mechanics of Of special interest in opera-
ar and particulate tions research are recent de-
mol.cul.r dynamic velopments in the application
of projective geometric meth-
ods to linear programming [8].
The above is a general
overview of the development
Analysis Synthesi$
and application of mathemati-
&" ow I~ o'5 "o, cal models in chemical engi-
iiwmngl a np.U, neering in which areas of
p"M.y'M mathematics are identified
(D...n) with significant roles in the
different stages shown in Fig-
T ure 1. We now return to the
,a i [u main objective of this article,
,is stochastlc Control
i-,NuMl Therm which is to present opportuni-
C'aO"n* a i d ties in an area with broad
applications. The subject of
linear operator theory fits this
requirement for a number of
reasons. Chiefly, it not only
serves the cause of the many
linear problems that occur
naturally in applications, but

Fall 1990

also forms the basis of several aspects of nonlinear
analysis. There are even more reasons which will be
left for subsequent discussions.

There are several linear problems of interest to
chemical engineers which we will briefly cover. While
their selection was based on their engineering impor-
tance, they also have mathematical traits which are
generally unfamiliar. In the discussion that follows, it
will become clear that modeling engineering systems
usually calls for a blend of different mathematical
implements. This feature does make modeling some-
what difficult.

Solid-Fluid Contacting
Many operations in chemical engineering in-
volve solid-fluid contacting, which is normally accom-
plished by passing a fluid through a bed of particles.
The packed bed, catalytic reactor is a very important
example. It is well-known that when modeling a
packed bed reactor, one must take account of diffu-
sional resistance within particles. A consequence of

... a compromise possibly lies in the
selection of an area of mathematics which has
wide applications in chemical engineering and
the examination of how that area fulfills
various requirements of the discipline

this awareness is the concept of the effectiveness
factor. However, much reactor analysis has depended
on the pseudo-homogeneous reactor model which
neglects particles.
Let us briefly consider the reactor in which the
fluid phase undergoes some form of convective mixing
(possibly axial dispersion), and there is diffusion in
every particle in the bed. The equations are easily
written down. The reaction-free linear operator can
be readily identified [9] and written in terms of the
isolated "fluid" operator F, the isolated "particle"
operator S, and an interaction operator A accounting
for transport across the particle surface to the fluid as
shown below.

(F A)

The above operator L has a discrete spectrum
containing an infinite set of sequences ofeigenvalues,
each converging to an eigenvalue of the particle op-
erator. The eigenvalues can be characterized in terms

of the eigenvalues of the isolated fluid and particle
operators. Limiting cases representing various sim-
plifications of a physical nature can be studied from
the behavior of the spectrum. Thus, conditions under
which the fluid phase controls the dynamics can
be determined.
From this analysis [10] it emerges that the
quasi-static assumption for the particle phase can be
made only when the effectiveness factor is too small to
permit significant production. In other words, the
"empty" tubular reactor does not exist from the tran-
sient viewpoint. It would appear then that much of
the reactor analysis with pseudo-homogeneous mod-
els concerning steady state multiplicity, stability, and
other transient features would be more appropriately
performed with heterogeneous (two-phase) models.
It is here that the linear operator above becomes
a very important tool. Furthermore, it has been cus-
tomary to stipulate the extent to which particle steady
states can vary in the reactor. A heterogeneous model
of the foregoing type which includes only "indirect"
interaction between particles because of mixing in the
fluid phase can allow discontinuous changes in par-
ticle states. Modeling direct interaction between
particles by some form of heat conduction and/or
diffusion could eliminate such discontinuities but not
prevent very fine variations presenting a reactor
exploding with patterns [11]!

Singular Spectral Theory
Sturm-Liouville operators (representing trans-
port and reaction) on infinite domains have behaviors
quite different from those on bounded domains. The
theory, not covered in most engineering courses on
applied mathematics, is extremely useful in dealing
with transport in media of infinite (indefinite) extent.
For a treatment of this material, see J6rgens [12] or
Naimark [13]. While some applications have been
made [14,15], there are several other interesting
Consider, for example, the concept of surface
renewal for mass transfer in turbulent gas-liquid
systems. It would seem that a similar approach would
be of interest in liquid-liquid systems. The applica-
tion of this concept to liquid-liquid systems is compli-
cated by two problems.* One is if renewal occurs
on either side of the interface, it is not clear what
an "eddy" on arrival at the interface from one side
would "see" on the other side. The other is that the
*Stewart, Angelo, and Lightfoot [32] present an application of
surface renewal concepts to such a situation in which the surface
elements are not renewed but are merely stretched because of
deformation of the interface.

Chemical Engineering Education

methodology for solving diffusion equations in infi-
nite contiguous media (for arbitrary initial condi-
tions) is not available from standard treatments of
boundary value problems.
On either count, a solution is made possible as
follows. In regard to the first, assume an "expected"
concentration profile on each side of the interface to
which a freshly arriving eddy from the opposite side
would be exposed. During its life at the interface, a
random number of renewals may occur on the other
side (with specifiable probabilities). Transport during
this time can be described by using continuous spec-
tral transforms. Averaging over all possible renewal
combinations, the expected concentration profile
of the eddy is computed on either side of the interface
in terms ofthe concentration profile in the other. Two
coupled integral equations result for the expected
concentration profiles, the solution of which will
lead to the calculation of mass transfer rates between
the two phases. This particular example should give
the right flavor of the nature of applications under
this category.

Inverse Scattering Theory
Avery interesting problem, which was addressed
as early as 1951 by Gelfand and Levitan [16], is the
inverse Sturm-Liouville problem [13] which poses the
question of how to determine a linear operator when
given its spectral information. The spectral informa-
tion, broadly stated, consists of the eigenvalues and
the spectral distribution function of the operator.
(The problem arose in quantum mechanics when the
potential function was of interest given spectral infor-
mation of the Schrodinger operator.) The spectral
distribution function arises as the coefficient of the
eigenfunction written at large distance (essentially
normalization constants) and must be determined
experimentally. The strategy for determining the
potential function (i.e., the operator), as developed by
Gelfand and Levitan [16], involves the solution of a
certain integral equation derived from the spectral
data {17 When the potential function is a constant,
this step is greatly simplified.
The elegant treatment of first order reaction
systems by Wei and Prater [18] may be considered as
a rudimentary example of the methodology of inverse
scattering theory. Except for the work ofKravaris and
Seinfeld [19], the author is unaware of instances of
the application of scattering theory in the chemical
engineering literature. There are many applications
possible in the validation-identification area, particu-
larly in determining transport coefficients in multi-
component systems. Besides the effort of Krishna, et

al. [20], who were more concerned with transfer
coefficients than diffusivities, few instances can be
cited in the literature where multicomponent sys-
tems have been subjected to identification experi-
ments. An experiment which appears attractive is to
allow the diffusion of species from a well-mixed sec-
tion across a rigid membrane of known transport
properties into a long quiescent medium. Concentra-
tion measurements in the well-mixed section could be
made as a function of time from which the spectral
distribution of the operator, and thence the diffusion
coefficients, could be calculated. The convenient fea-
ture of this setup is that the concentration range can
be controlled to use "constant" diffusion coefficients.
There have also been alternative inverse prob-
lem formulations without involving the spectral trans-
form. Rundell [21] has investigated the solution of the
parabolic equation
au a u
= 2 -q(x)u 0 at ax
in a bounded domain. Given measurements of u(0,t),
u(1,t), u(x,0), and u(x,to), to>0, the problem of deter-
mining q(x) becomes a well-posed problem, and one
can constructively march to the solution. However,
note that this well-posed problem has been obtained
by measuring an entire concentration profile at one
fixed time during the diffusion process.
The subject of inverse problems is also impor-
tant in other formulations in chemical engineering.
Thus, population balance models of dispersed phase
systems are often based on rate functions (such as
those of break-up and agglomeration of individual
particles, or of particle "growth," etc.) that must be
determined by inverse problem formulation. For
example, the determination of the coalescence rate of
liquid droplets as a function of drop sizes in a stirred
liquid-liquid dispersion, denoted by q(v,v'), may be
determined by transient measurements of the cumu-
lative drop size distribution, F(v,r), through the solu-
tion of the inverse problem

aF(v,T) r ,,V ,,,
=_'- aF(v',T) f F(v",T)q(v,v")/v"
0 v-v'
The problem above is ill-posed, and a regulariza-
tion method due to Tikhonov and Arsenin [22] is
required to solve the problem. Muralidhar and
Ramkrishna [23,24] have solved this problem by
using similarity theory to convert the integro-differ-
ential equation to a Volterra integral equation and
applying regularization techniques to the latter.
Regularization techniques have been used by others

Fall 1990

(e.g.,[25]), but generally they are not common knowl-
edge among chemical engineers.

Inverse Scattering Transform and Nonlinear
A most interesting development of the inverse
scattering theory referred to earlier is its connection
to the solution of certain families of nonlinear partial
differential equations. This development has occurred
over the last decade. Briefly, the method works like
any linear integral transform used to solve linear
differential equations. The remarkable aspect of the
technique is that while the dependent variable evolves
in time through a nonlinear equation, its transform
evolves through a linear equation! Shelving, for the
present, the nature of the association of the linear
problem which defines the transform and the nonlin-
ear equation, let us denote the linear operator as

x2 +q(x,t)

oo< X < o

where t is to be regarded as a parameter, and q is in
fact the dependent variable in the nonlinear evolution
equation. The self-adjoint operator above defines a
spectral transform depending obviously on parame-
ter t. What we are interested in is solving a certain
nonlinear partial differential equation in q(x,t) sub-
ject to some initial condition q(x,0) = q,(x). The trans-
form is well-defined at time t = 0 since q is known then.
This transform may have a continuous and discrete
part (if there are discrete eigenvalues). We denote the
partial differential equation satisfied by q(x,t) by
aq(x,t) 2 q(x,t)
3t 3x
where L is the linear operator
32 aq(x,t)i
L= 4q(x,t)+2 dy(
ax2 ax f
in which specific attention is called to the presence of
the dependent variable q(x,t) here also. The function
p(z,t) appearing in the nonlinear operator can be any
entire function of z, and it determines the linear
evolution equation in the spectral (inverse scattering)
transform. Inverting the spectral transform for the
solution requires the solution of a linear integral
equation, which is not always easy. On inversion, the
continuous transform provides for dispersivee" waves,
while the discrete part gives rise to solitary waves or
"solitons." The solitons survive at large times and can
be calculated analytically because when there is only
a discrete transform the integral equation to be solved
for inversion contains a degenerate kernel. Thus the

most interesting attribute of this technique seems to
be the calculation of soliton solutions of nonlinear
evolution equations. For an interesting account, see
Degasperis [26] and Drazin [27]. Some of the equa-
tions that have been analytically solved for solitons
are the KdV equation in the production of shallow
water waves given by
ut -6uu +u, =0
and Fischer's equation in nonlinear diffusion
Ut = Uxx +a2U(1-u)
and Burger's equation
Ut +uux = vux
etc. All of the foregoing examples could be obtained
by specific choices of the function 3 in the general
Lax [28] has provided an operator formulation of
the above in which the association between the non-
linear and the linear problem is less mysterious.
Consider the nonlinear operator N:H --H where H is
a Hilbert space, and the nonlinear evolution equation

Ut =N(u) (1)

The problem is to find a linear operator L which
generates a transform applicable to the solution of the
nonlinear problem (Eq. 1) in the sense described
above. (In linear problems, this step was immediately
obvious.) Lax requires that one must determine two
linear operators, L and B, on H-both depending on u
such that L is symmetric and of the type considered
earlier in the inverse scattering transform above with
u in place of q, and such that Eq. (1) somehow implies
Lt BL-LB (2)

The eigenvalues of L will obviously depend on
the parameter t. It turns out that the necessary and
sufficient condition for the eigenvalues of L to be
independent of t is that the nonlinear Eq. (1) be
satisfied. In other words, the interesting conclusion
emerges that the eigenvalues of L (which depend on
u(x,t)) will be independent of t if and only if u(x,t)
satisfies a suitable nonlinear evolution equation.
In applications, one is of course confronted with
a given nonlinear equation and the utility of the
foregoing methods is clearly not straightforward. On
the other hand, the above methods can generate a
dictionary of solvable equations through a tool that
can admit some "tuning" to accommodate a given prob-
lem. For example, it is not inconceivable that the
combination of chemical reaction and diffusion could
produce solitary waves in flowing systems.

Chemical Engineering Education

Direct Methods for Nonlinear Evolution
The nonlinear equations which can be solved for
the solitons by using the inverse scattering transform
appear to be also solvable by more direct methods
[29]. In this approach, where the main advantage is
that it also becomes available for those not conversant
with inverse scattering theory, a traveling frame of
reference is introduced in terms of a wave velocity to
be subsequently determined. The solution is expressed
in terms of a convergent power series of decaying
exponentials (of the transformed variable) and the
entire form of the solution is obtained by direct substi-
tution into the equation. Soliton solutions emerge as
exactly summable expansions in this direct approach.

Other Methods Differential Geometry
It appears that exactly solvable nonlinear sys-
tems are amenable to seemingly different approaches.
One such approach is provided by the methods of
differential geometry in which a second order partial
differential equation is converted by appropriate
transformation into a linear system of first order
partial differential equations. The first order system
is, in turn, associated with what are known as exterior
differential forms in a manner that provides for either
analytical solutions or computationally efficient solu-
tions {4,30,31].


This article has attempted a brief survey of the
offshoots of linear operator theory and their potential
to various aspects of chemical engineering analysis,
including the solution of nonlinear problems.


This article was prepared by the author while at
the University of Minnesota as the George T. Piercy
Distinguished Professor, during the fall of 1988. He is
also grateful to the Institute for Mathematical Appli-
cations, University of Minnesota, for collaborative
interaction with several members of the institute
during this period. The material here was presented
in the Alpha Chi Sigma Award Symposium at the
AIChE annual meeting in November, 1988, in Wash-
ington, DC.

The author also acknowledges and thanks Jeff
Kantor of the University of Notre Dame for many
useful references.

1. Truesdell, C., and Toupin, "The Classical Field Theories,"

in Handbuch der Physik, Ed. S. Fliigge, III, Springer-
Verlag, Berlin (1960)
2. Coleman, B.D., and W. Noll,Arch. Rational Mech. & Anal.,
13,167 (1963)
3. Mueller, I., Arch. Rational Mech. & Anal., 28, 1 (1968)
4. Lustig, S.R., and J.M. Caruthers, Sixth International Con-
gress of Rheology, Sydney, 1, 100 (1988)
5. Shay, R.M., Jr., and J.M. Caruthers, Sixth International
Congress of Rheology, Sydney, 1, 266 (1988)
6. Edelen, D.G.B., IsovectorMethodsforEquations ofBalance,
Sijthopff& Noordhoff, Maryland (1980)
7. Wachspress, E.L., A Rational Finite Element Basis, Aca-
demic Press, New York (1975)
8. Karmarkar, N., Combinatorica, 4, 373 (1984)
9. Ramkrishna, D., and P. Arce., Chem. Eng. Sci., 43, 933
10. Ramkrishna, D., and P. Arce, Chem. Eng. Sci., 44, 1949
11. Arce, P., and D. Ramkrishna, Chem. Eng. Reviews, submit-
ted (1989)
12. J6rgens, K., Spectral Theory of Second-Order Differential
Operators, Lecture Notes Series No. 2, Aarhus University
Press (1964)
13. Naimark, M.A., Linear Differential Operators, Parts I and
II, Frederick Ungar, New York (1968)
14. Parulekar, S.J., and D. Ramkrishna, Chem. Eng. Sci., 39,
15. Parulekar, S.J., D. Ramkrishna, N.R. Amundson, and R.
Flummerfeld, Chem. Eng. Sci., 42, 2447 (1987)
16. Gel'fand, I.M., and B.M. Levitan, "On the Determination of
a Differential Equation from Its Spectral Function," Izv.
Akad. Nauk. SSSR Ser. Mat., 15, 309 (in Russian) (1951);
Amer. Math. Soc. Transl., (2), 1, 253 (in English)(1955)
17. Agranovich, Z.S., and V.A. Marchenko, The Inverse Prob-
lem of Scattering Theory, Gordon & Breach, New York
18. Wei, J., and C.D. Prater, in Chap. 5 ofAdvances in Catalysis,
13, Academic Press, New York (1962)
19. Kravaris, C., and J.H. Seinfeld, SIAMJ. Control & Optimi-
zation, 23, 217 (1985)
20. Krishna, R., C.Y. Low, D.M.T. Newsham, C.G. Olivera-
Fuentes, and G.L. Standart, Chem. Eng. Sci., 40,893(1985)
21. Rundell, W., Proc. of the American Math. Soc. #99, Sec. 4,
22. Tikhonov, A.N., and V.Y. Arsenin, Solutions of Ill-Posed
Problems, V.H. Winston and Sons, Washington, DC (1977)
23. Muralidhar, R., and D. Ramkrishna, J. Coll. & Interface
Sci., 112, 348 (1986)
24. Muralidhar, R., and D. Ramkrishna, J. Coll. & Interface
Sci., 131, 503 (1989)
25. Kravaris, C., and J.H. Seinfeld, Proceedings 22nd IEEE
CDC, San Antonio, TX, 50, December (1983)
26. Degasperis, A., "Solitons, Boomerons, Trappons," in Non-
linear Evolution Equations Solvable by the Spectral Trans-
form, ed., F. Calogero, Pittman, London (1977)
27. Drazin, P., Solitons, Cambridge University Press, London
28. Lax, P.D., "Integrals of Nonlinear Equations of Evolution
and Solitary Waves," Comm. Pure Appl. Math., 21 467
29. Hereman, W., A. Korpel, and P.P. Banerjee, "A General
Physical Approach to Solitary Wave Construction from
Linear Solutions," Wave Motion, 7, 283 (1985)
30. Kantor, J., Chem. Eng. Sci., 44, 1503 (1989)
31. Kravaris, C., AIChE J., 34, 1803 (1988)
32. Stewart, W.E., J.B. Angelo, and E.N. Lightfoot, AIChE J.,
16, 771 (1970)0

Fall 1990

class and home problems

The object of this column is to enhance our readers'collection of interesting and novel problems
in chemical engineering. Problems of the type that can be used to motivate the student by present-
ing a particular principle in class, or in a new light, or that can be assigned as a novel home
problem, are requested as well as those that are more traditional in nature, which elucidate
difficult concepts. Please submit them toProfessor James 0. Wilkes and Professor T. C. Papanasta-
siou, ChE Department, University of Michigan, Ann Arbor, MI 48109.




Yale University
New Haven, CT 06520

Large-scale chromatography is widely used
as a purification process in the biotechnology and
pharmaceutical industries [1,2]. It is therefore
important to include discussions of this process in
separations courses taught in the chemical engi-
neering curriculum.
This paper illustrates the use of spreadsheet
programs for implementing finite difference numeri-
cal simulations of chromatography as an instruc-
tional tool in a separations course. This approach
is motivated by the fact that numerical solutions
are needed to investigate realistic chromatographic
processes (e.g., those involving nonlinear equilib-
rium), but the use of traditional programming lan-
guages such as FORTRAN for this purpose involves
excessive demands on students' time. In contrast,
an equivalent spreadsheet program can be con-
structed with little effort. Although the computation
time is larger for a spreadsheet program than for

Douglas Frey received his chemical engineering
degrees from Stanford University (BS) and the Uni-
versity of California, Berkeley (PhD). He is currently
an associate professor at Yale University. His re-
search interests are in the areas of separation and
transport processes.

Copyright ChE Division ASEE 1990

a comparable FORTRAN program, the fact that
spreadsheet programs require very little time to
develop outweighs this disadvantage if only a few
simulations are performed. It should be noted that
several authors have previously recognized the con-
venience of spreadsheet programs for engineering
calculations [3-5].


The equations describing chromatography can
be written as follows [6]:
C ac a2C a,
SL Vfluid axial- 2+Pb (1)
dt dz az at

Ri-Pb i =-_bkias qi -q) (2)
Equation 1 describes a differential material
balance in the column, while Equation 2 describes
interphase mass transfer using a linear driving force
approximation. If diffusion in the particle is the
dominant mass transfer resistance, the transport
coefficients in Equation 2 can be approximated by
kias = 60D (3)

In most cases, the following form of the Langmuir
isotherm gives an adequate description of equilib-
rium behavior:
q aiCi (4)
i 1+=I bi Ci

Chemical Engineering Education

This paper illustrates the use of spreadsheet programs for implementing finite difference numerical
simulations of chromatography as an instructional tool in a separations course.

Although Equation 1 includes a term for axial dis-
persion, for simplicity's sake this term will be ex-
cluded in the following discussion.


Equations 1 and 2 are readily solved using
finite difference methods. For this purpose, the fol-
lowing three-point backward difference formula for
the spatial first derivative usually gives excellent re-
sults [8,91:

(3Ci 3(Ci)zt -4(Ci)z-Az,t +Ci)z-2Az,t (
Sz t 2Az

Provided that the number of theoretical equi-
librium stages is not excessively large, Equations 1
0 Z--. L
0 x5 x -x--x---x --
A B C E F ,

and 2 in finite difference form can be integrated in
time using a modified Euler predictor-corrector
method. Starting from time, t, this method involves
making an explicit forward Euler step in time to
obtain estimates of quantities at t+dt. This is fol-
lowed by a second explicit forward Euler step from t
to t+dt in which the rates of mass transfer and the
spatial derivatives are evaluated at the average con-
ditions of the time step.


Figure 1 shows the basic strategy of the spread-
sheet program. At any time, two adjacent time points
are stored in the cells of the spreadsheet. One recal-
culation of the spreadsheet corresponds to advanc-
ing one time step down the computational grid. If
the concentration history at the column outlet is
desired, rather than a spatial composition profile at
x x x spcfltm,tfec,1 ,aTz= 1an "wftteto

2X x x7Rc x x x\ a specific time, tne cells at z = L can be written to a
separate file as the computation proceeds.
27 X X X X X X X X
St Figure 2 shows cell contents from a spread-
X X X X X X X X Spreadsheet
t Xsheet program constructed using 1-2-3TM (Lotus
x x x x x x x x Development Corporation). This spreadsheet imple-

S x x x x x x ments the computation strategy shown in Figure 1
oGrd Point for isocratic conditions. The cell contents in Figure 2
x x x x x x x x were printed using the 1-2-3 PRINT command. The

FIGURE 1. Location of spreadsheet on computation entry F5 in each cell is the format, which in the
grid. present case indicates that 5
Al: (s) .sco.p decimal places are to be dis-
2 (,5, SCOP.. played. Each column in the
A19: (F5) +$COMP1
A2; (F5) .S CO2 spreadsheet corresponds to
A21: (75) 03COeP3
B1: (75) +s .COM one spatial grid point and two
B2: (75) +$COMP2
a: (E > adjacent time points, as shown
21: (75) 00C003
Bl19 (F5) +$COIP1
.21: M() +$SC..3 in Figure 1. The composition
c 7 ( c9) of the feed, which is composed
C2: (FS) (C20)
C: (5) (C2 of three solutes in this ex-
C4: (F5) (C232)
c6 (7S) (2 ) ample, is entered into cells Al
C7 (F5) (C25)
0 (75) (C2 ) to A3, B1 to B3, A19 to A21,
C9: (F5) (C27)
,1: 5) ()(-$VLUID $DELTA T/(2*$DELTA Z))*(3 C1-4 1+Al ))+C -(C7 $D.LTA T/$ALPHA) and B19 to B21 to provide two
C11: (F5) ((-$VFLUID*$DELTA T/(2*$DELTA Z))*(3*C2-4*B2+A2))+C2-(CB*$DELTA T/$ALPHA)
012; (F) ((-$VFLUID*$DELTA T/(2*SDELTA Z))*(3*C3-4*B3+A3))+C3-(C9*$DELTA T/$ALPHA) *
C13 7, c4.C sELA T/.... upwind points for the spatial
14 (F5) (C5+C8*$DELTA T/$RHOB)
lI ( ) s.C6C. D.LTA .nRHOB.) difference formulas for both
C16: (75) (-$K(1)*$A*$RHO, B (C13-( $A(1)C10/(+$B(1)*C10+$B(2)*C11+$B(3)*C12)))
C 17 (F5) (-$K2).A^.$.o.(C-$4.A C B C 0$ o+ ^$C. the predictor and corrector
0C8E (75) (-SK(3)*$A*$RHOB*(C154-(S A(3)*C12/(1+$(1)0+2)11(3)C2) the predictor and corrector
C19: (F5) (-$VFLUID*$DELTA T/(2*$DELTA Z))*(3*((C1+C10)/)2))-4*(( 81+1 9)/2+ (A+A19)/21)+C1-(((C16+C7)/2)*$DELTA T/$ALPHA)
C20: (F5) (-$VFLUID*$DELTA T/(2*SDELTA Z))*(3*((C2+C11)/2)-4*((B2+B20)/2)+((A2+A20)/2))+C2-(((C17+C8)/2)*$DELTA T/ALPHA) steps in column n C.
C21: (F5 )(-$VFLUID*$DELTA T/(2*$DELTA Z))*(3*((C3+C12)/2)-4*((B3+B21)/2)+((A3+A21)/2))+C3-(((CI8+C9)/2)*$DELTA T/$ALPHA)
C22: (F5) (C4+((C16+C7)/2)*$DELTA T/$RHOB)
C24: (F5) (C6+((C18+C9)/2)*$DELTA T/$RHOB) The purpose of each cell
C25: (F5) (-$K(1)*$A*$RHOB*(C22-( A(1)*C19/(1+$B(1)*C19$B(2)*C20+$B(3)*C21))))
C26: (F5 )(-$K(2)*$A.$RHOB*(C23-($A(2).C20/(1$+SB(1)*C19+$B(2)*C2.0+(3)*C21)) in column C is described in
C27: (F5) (-SK(3)*$A*$RHOB*(C24-($A(3)*C21/(1+$B(1)C9+$B(2)*C20+$B(3)*C21)))

FIGURE 2. Cell contents for a 1-2-3 spreadsheet program

Fall 1990

Figure 3. The 1-2-3 COPY
command can be used to copy

column C into as many cells to the right of this
column as desired to produce a grid of the appropri-
ate size. After construction of the grid, the numeri-
cal simulation is advanced one time step by recalcu-
lating the entire spreadsheet column by column. The
feed composition can be changed at any time by
stopping the recalculation iterations, changing the
entries in the feed composition cells, and then re-
starting the recalculation iterations. Note that in-
stead of having the feed compositions in column B,
column C can also be copied into column B. How-
ever, the spatial derivatives in column B must then
be changed to Euler formulas since there is only one
upstream point relative to column B.
Variables in Figure 2 incorporating the symbol
$ refer to named absolute cell references containing
the indicated variables, e.g., $COMP1 indicates an
absolute reference to a cell containing the composi-
tion of component 1 in the feed to the column. For
simplicity, these cells are not shown in Figure 2, but
can be located beneath those corresponding to the
feed composition.

Simulations using the 1-2-3 spreadsheet pro-
gram shown in Figure 2 can be performed conven-
iently on an IBM AT personal computer operating at
8MHz clock speed. With such a computer, a spread-
sheet program involving three solutes and two
hundred spatial grid points requires approximately
400 kB of RAM and 5 s for each recalculation, i.e., for
each time step. Since 5,000 to 10,000 time steps are
often required to ensure stability and accuracy, the
time needed for a complete simulation is usually
about ten hours for the case where three solutes are
present and about three hours for the case where
only one solute is present. Faster simulations can be
performed by writing spreadsheet subroutines which
add downstream grid points only as needed and
which delete upstream grid points if that portion of
the column has come to equilibrium with the feed.

Figure 4 illustrates an effluent concentration
profile calculated using the spreadsheet program in
Figure 2 for the isocratic elution of three solutes
having Langmuir isotherms. The physical parame-
ters used were as follows:
D. = 10-6cm2/s
fluid = 0.1 cm/s
d = 0.005 cm
Pp 1 g/cm3
a =0.4

L = 5 cm
a = 1.6 a2 = 0.6 a3 = 2.08 cm3/g
b, = 2.3 b2 = 0.6 b3 = 0.025 cm3/n-mole

The feed was injected as a square-wave pulse of
87.5 s duration. The concentration of all three sol-
utes in the feed slug was 10 n-mole/cm3 (i.e., 1 mg/
cm3 of an average-sized protein). Under these condi-
tions, the chromatographic column had an efficiency
of approximately 200 theoretical plates based on
linear isotherms. Note that Figure 4 employs a di-
mensionless concentration and time, the latter being
defined as

T =avluidCl,feed (t L / Vfluid) / (Lpbq,feed) (6)

Over the last several years, spreadsheet pro-
grams which simulate multicomponent chromatog-
raphy using finite difference methods have been used
in the undergraduate separations course at Yale
University. These programs permit students to study
complex phenomena which would otherwise be diffi-
cult to investigate, such as the compression of the
Cell Description
Cl Copy C(1) from cell C19 to advance one time step
C2 C(2) C20 "
C3 C(3) C21 "0
C4 q (1) C22 "
C5 q(2) C23 "
C6 q(3) C24 "
C7 e R(1) C25 "
C8 R(2) C26 "
C9 R(3) C27 "
CI0 Euler predictor step for C(l) at t+dt
Cll C(2) "
C12 C )
C13 q(i)
C14 (2) "
C15 (3)
C Calculate R(1) attt t using results from predictor step
C17 R(2) "
C18 R(3) "
C19 Recalculate C(1) at t+dt using average values of R(1) and spatial derivative
C20 0 C(2) R(2) "
C22 q(1) R(1)
C23 C q(2) >R(2)
C24 q(3) u R(3)
C25 Rcalculate () at tidt using quantities recalculated in cell C19-C24
C26 R(2) "
C27 R(3) "

FIGURE 3 Description of cell contents from
column C of Figure 2.


FIGURE 4. Numerical simulation of isocratic elution
chromatography of solutes having Langmuir isotherms.

Chemical Engineering Education

upstream band shown in Figure 4. Students can also
gain insights into numerical calculations, such as
the effects of numerical instability, since they are
able to observe the calculation proceed in time. Many
types of spreadsheet programs also incorporate
graphics capabilities, which further enhances their
educational value. In particular, when using version
2.x of 1-2-3, we recommend also using the program
SeeMORETM (Personics Corporation), which can be
employed to produce multiple live graphs as the
simulation proceeds.

a. = interfacial area per unit volume in bed-(cm-')
a, = Langmuir isotherm parameter (cm"g-')
b, = Langmuir isotherm parameter (cm3 mole1)
C, = concentration of component i (mole cm-3)
Cid = feed concentration (mole cm-3)
Daxial = axial dispersion coefficient (cm2s-1)
D. = diffusivity of component i in particle (cm2s-1)
d = particle diameter (cm)
L = length of bed (cm)
k, = coefficient in linear driving force approximation,
(cm s-1)
qi = amount adsorbed per mass of sorbent averaged
over particle (mole (g of sorbent)-1)
qi* = value of q, in equilibrium with interparticle
fluid (mole (g of sorbent)-1)
q feed = value of qi in equilibrium with C,feed (mole (g of
R. = rate of solute uptake per bed volume
(mole cm-3s-1)
t = time (s)
T = dimensionless time
Vfuid = interstitial fluid velocity (cm s-1)
z = distance in column (cm)

Greek Symbols
a = bed void volume
Pb = bulk density of bed (g cm-3)
p = particle density (g cm-3)

1. Guiochon, G., and A. Katti, "Preparative Liquid Chroma-
tography," Chromatographia, 24, 165 (1987)
2. Antia, F.D., and Cs. Horvath, "Operational Modes of Chro-
matographic Separation Processes," Ber. Bunsenges. Phys.
Chem., 93, 961 (1989)
3. Grulke, E.A., "Using Spreadsheets for Teaching Design,"
Chem Eng. Ed., 20, 28 (1986)

4. Julian, F.M., "Process Modelling on Spreadsheets," Chem.
Eng. Prog., 85(10), 33 (1989)
5. Orvis, W., 1-2-3 for Scientists and Engineers, Sybex Inc.,
Alameda, CA (1987)
6. Vermeulen, T., M.D. LeVan, N.K. Hiester, and G. Klein,
"Adsorption and Ion Exchange," in Perry's Chemical Engi-
neers' Handbook, R.H. Perry, D.W. Green, J.O. Maloney
(editors), McGraw-Hill, New York (1984)
7. Wong, T., and D.D. Frey, "Matrix Calculation of Multi-
component Transient Diffusion in Porous Sorbents," Int.
J. Heat Mass Transfer, 2(11), 2179 (1989)
8. Brian, B.F., and I. Zwiebel, "Numerical Simulation of Fixed-
Bed Adsorption Using the Method of Lines," AIChE Symp.
Ser., No 259, 83, 80 (1988)
9. Morgan, M.H., and S. Srinavasan, "Explicit Finite Differ-
ence Scheme for Nonlinear Convective Problems," Com-
put. Chem. Eng., 1(1), 69 (1977)0

book review

Gianni Astarita
Plenum Press, 233 Spring St., New York 10013
444 pages, $69.50 (1989)

Reviewed by
Athanassios Panagiotopoulos
Cornell University

Thermodynamics, as the subtitle implies, is
primarily a textbook intended for an advanced
thermodynamics course for chemical engineers. Such
a course is typically part of the graduate core cur-
riculum, and the graduate and advanced un-
dergraduate students taking it would have completed
beginner's courses in thermodynamics, physical
chemistry, and transport phenomena. The book has
two parts, the first emphasizing macroscopic theory
and the second engineering applications. The sub-
ject coverage is unusually broad, including chapters
on the thermodynamics of relaxation, surface thermo-
dynamics, and dissipative phenomena in the first
part, and electrochemistry, polymers (written by G.
Marrucci) and the thermodynamics of electro-
magnetism (by R.E. Rosenweig) in the second part.
The point of view of the authors is almost entirely
There are a number of strong points to this
book. It is perhaps the most comprehensive in cover-
age of the current graduate thermodynamics text-
books for chemical engineers. With research activi-
ties shifting away from "traditional" chemical engi-
neering areas into new intellectual territories, the
need for a fresh look at what is included in a thermo-
dynamics course is clear. By discussing topics such
Continued on page 232.

Fall 1990

A Program in ...


at the University of Cincinnati

University of Cincinnati
Cincinnati, OH 45221-0171

Chemical engineering at the University of Cin-
cinnati is the sixth oldest program in the United
States and one of the first thirteen programs accred-
ited by the AIChE in 1925. Since that time the
program has been accredited continuously by both
In the early 1930s, a graduate program in
chemical engineering was established, and the first
PhD degree was awarded in 1938; the 100th doctoral
degree was awarded in 1988. Today, more than fifty
students from nine countries are studying towards
graduate degrees in chemical engineering, and the
majority of them are working towards PhD degrees.
Fifteen new students are expected to join the depart-
ment at the start of the 1990-91 academic year.
Areas of graduate research represent all tradi-
tional areas of chemical engineering, with principal
emphasis focusing on the research areas of four uni-
versity centers which have their homes within the
chemical engineering department. They are the Poly-
mer Research Center, the Center-of-Excellence in
Membrane Technology, the Clean Coal Center, and
the Center for Aerosol Processes.
The purpose of this article is to focus on poly-
mer education and research in the chemical engi-
neering department, which involves the activities of
the university-wide Polymer Research Center and
includes strong interaction and collaboration with
the Membrane Center.

Joel R. Fried received B.S. degrees in biology (1968)
and chemical engineering (1971) from Rensselaer
Polytechnic Institute and graduate degrees in chemi-
Scal engineering (RPI, M.E., 1972) and polymer sci-
ence and engineering (University of Massachusetts,
M.S., 1975; Ph.D., 1976). He is presently professor
of chemical engineering and Director of the Polymer
S.Research Center at the University of Cincinnati. He
is the author of over sixty journal articles and book
chapters and is presently finishing a textbook in poly-
mer science and technology.
Copyright ChE Division ASEE 1990

The origins of polymer research at the Univer-
sity of Cincinnati go back a long way. In the 1920s,
the Tanners Council Research Laboratory was lo-
cated on campus to study leather and its products.
This facility is still active and interacts with chemi-
cal engineering, notably through the undergraduate
professional practice program (the first such pro-
gram in North America). In the 1930s, a Basic Sci-
ence Research Laboratory was established in the
College of Engineering, and Paul Flory (1974 Nobel
laureate in Chemistry) accomplished much of his
pioneering work in the area of polyesterification while
working in this laboratory. Then in the mid-1950s
the chemical engineering department had the dis-
tinction of offering the first polymer chemistry course
at Cincinnati.
Formal coordination of polymer research and
educational activities within the university was es-
tablished in 1977 by the formation of the Polymer
Research Center. Then in 1989 the Center was re-
organized to reflect the growth of polymer research
within the university, particularly within the Col-
lege of Engineering. An Executive Board, consisting
of the Director and a Co-Director, guides the educa-
tional and research activities of the Center, includ-
ing its seminar program. Eight faculty members
of the Center, thirty-five graduate students, and
fifteen postdoctoral students and visiting scholars
are engaged in a wide variety of research activities.
Total annual external funding for this research ex-
ceeds $1 million in individual grants and contracts.
Another six faculty, who have polymer-related re-
search activities within the departments of aero-
space engineering, physics, and chemistry, are affili-
ated with the Center.


The University of Cincinnati operates on an
academic quarter system. A minimum of thirty-six

Chemical Engineering Education

course credits are required for the MS degree and
ninety credits are required for the PhD degree. The
majority of these graduate credits may be taken
from a large list of technical electives offered as
graduate- and dual-level courses (available for credit
for undergraduate or graduate students). Of these,
seventeen polymer courses are offered by the three
participating departments of chemistry, chemical
engineering, and materials science and engineering
(see Table 1).

Undergraduate students in chemical engineer-

Polymer Course Offerings

Polymer Configurations and Rubberlike Elasticity
Chemistry; dual-level
Preparation and Reactions of Polymers
Chemistry; dual-level
Polymer Properties Laboratory
Chemistry; dual-level
Solution Properties of Polymers
Chemistry; dual-level
Readings in Polymer Chemistry
Chemistry; graduate
Polymer Technology
Chemical Engineering; undergraduate
Properties and Applications of Hydrogels
Chemical Engineering; dual-level
Polymer Engineering
Chemical Engineering; graduate
Polymer Engineering Laboratory
Chemical Engineering; dual-level
Polymer Viscoelasticity
Chemical Engineering; graduate
Introduction to Polymers
Materials Science and Engineering; undergraduate
Polymer Characterization
Materials Science and Engineering; dual-level
Properties of Polymers
Materials Science and Engineering; graduate
Polymer Spectroscopy
Materials Science and Engineering; graduate
Solid-State Polymer Systems
Materials Science and Engineering; graduate
Polymerization, Degradation, and Characterization Tech-
Materials Science and Engineering; graduate
Introduction to Polymer Science
Materials Science and Engineering; graduate

Fall 1990

The purpose of this article is to focus on polymer
education and research in the ChE department,which
involves the activities of the university-wide Polymer
Research Center and includes strong interaction and
collaboration with the Membrane Center.

ing may enroll in either Polymer Technology (offered
in chemical engineering) or Introduction to Poly-
mers (offered in materials science and engineering)
for their first polymer course, while graduate stu-
dents would typically take Introduction to Polymer
Science (offered in materials science and engineer-
ing). A total of fifteen polymer courses (listed in
Table 1) are available to satisfy graduate elective re-
quirements in chemical engineering.
The Polymer Engineering and Polymer Visco-
elasticity courses are given once every two years,
with the lecture course on polymer engineering
rotated every Spring quarter on an alternate-year
basis with the laboratory course described below.
Coverage includes an introduction to polymer rheol-
ogy, dynamic equations, constitutive relationships,
and the modeling of simple processing operations
such as extrusion. Middleman's textbook Funda-
mentals of Polymer Processing is normally used as
the text for Polymer Engineering. The book for
the viscoelasticity course is Introduction to Polymer
Viscoelasticity by Aklonis and MacKnight. Coverage
in this course includes the principles of linear visco-
elasticity and rubber elasticity with applications to
dynamic mechanical and dielectric spectroscopy.
The dual-level laboratory course in polymer
engineering contains experiments in capillary extru-
sion, rheology, gas permeation, impact testing, crys-
tallization kinetics, solution viscosity, and polymeri-
zation. Experiments utilize both commercial and
custom fabricated instrumentation, often with com-
puter acquisition and analysis of data. Theoretical
background, experimental procedures, and questions
related to each experiment are provided in a labora-
tory manual.
A dual-level course on polymer gels is offered
which focuses on the properties of polymeric hydro-
gels including synthesis, swelling, solute transport,
phase transitions, and network structures and their
use for chemical separations and biomedical/phar-
maceutical applications. Both a written and an oral
report on a research project involving theoretical,
computational, or laboratory work in the area of
hydrogels are required.
In addition to these courses, several other
courses with strong polymer content are routinely


available within the university. For example, the
Department of Materials Science and Engineering
offers a dual-level course (Advanced X-Ray Diffrac-
tion) with strong emphasis on polymeric systems.
In the Department of Chemical Engineering a
novel course (Scaling Phenomena in Chemical Engi-
neering-Applications of Fractal Concepts and
Nonlinear Dynamics) was introduced during the
1989-90 academic year. It included scaling phenom-
ena, renormalization group theory, and percola-
tion as applied to polymer systems. The Department
of Chemical Engineering also offers a dual-level
course (Membrane Technology) which includes ma-
terial on polymer membrane preparation and trans-
port phenomena.


Research areas within the Polymer Research
Center include studies of composites, block copoly-
mers, polymer blends, rubber elasticity, polymer gels,
and polymeric controlled drug release, to name only
a few. Within the Department of Chemical
Engineering, seven (out of a total of twelve) faculty
members have one or more projects involving basic
or applied polymer research. A brief summation of
these follows:
a Research interests of Joel Fried include the study of
polymer blends and composites and the transport of
organic liquids and permanent gasses through
polymeric membranes. Specific research projects
development of a polymeric membrane system for
the pervaporation of methanol from an organic catalyst
development of a molecular sieve membrane from
the partial pyrolysis of ceramic precursor polymer
*investigation of the sorption and permeability
behavior of plasticized PVC films to carbon dioxide
and methane
*development of a model for the flow of biopolymers
through affinity membranes (macroporous polymer
membranes to which biospecific organic ligands can
be attached at the surface and which may represent an
important new technique for industrial bioseparations)
using laser scattering techniques to study phase
separation in binary and ternary blends of different
polycarbonates for which experimental data is
compared with theoretically obtained phase diagrams
using semi-empirical quantum mechanical and
molecular mechanics methods to correlate polyimide
structures with thermal properties such as the glass
transition temperature and thermal stability.

a Stevin H. Gehrke joined the department in 1986 and his
interests have focused primarily on the synthesis,
properties, and applications of polymeric hydrogels.
(Steve also directs a successful program of Research

Graduate student Hsieng-Cheng Liu examines the mor-
phology of a polymeric membrane in an ISI Scanning
Electron Microscope.

Experience for Undergraduates in which
undergraduates from different colleges pursue
supervised research projects.) His ongoing graduate
research projects include
phase behavior of novel cellulose ether hydrogels
(thermally responsive hydrogels produced by
crosslinking of various cellulose ethers, providing a
material with pharmaceutical value and a model system
enabling critical analysis of thermodynamic theories
for the swelling of such gels)
investigation of the permeability of a synthetic,
thermally responsive hydrogel, crosslinked poly(N-
isopropylacrylamide), to different drugs (requires
separation of the complex dependencies of the diffusion
and partition coefficients of solutes)
pursuing the control of the microstructure of
responsive polymer gels and the relation of this
structure to the response rate of the gel
exploration of the novel use of recyclable absorbent
gels as a means of dewatering the fine and ultrafine
coal slurries generated by precombustion coal cleaning
a Rakesh Govind is extremely active in a large number of
research areas including process synthesis, clean coal
technology, and membrane systems. One project is
developing the technology to use polymeric hollow
fibers with attached microorganisms as bioreactors for
the anaerobic treatment of organic in wastewater.

a Sun-Tak Hwang joined the department in 1982 as its
Department Head. Under his leadership the department
received a five-year $2 million grant from Sohio in
1983 to establish a Center-of-Excellence in Membrane
Technology. Since then, the Center has grown and
currently has an active Industrial Partnership program.
Many of the research areas within the Center are
concerned with gas and liquid transport through
polymeric material.
a Glenn Lipscomb joined the department in 1989 and has
research interests in the thermodynamic analysis of
gas sorption in glassy polymeric materials, the design
of hollow fiber polymeric membrane separation devices,
boundary layer analysis of various polymer processing
operations, and the study of structure formation in

Chemical Engineering Education

slow flows of concentrated suspensions.
a Neville Pinto joined the department in 1985. His recent
interests have focused on ion-exchange separations and
chemical sensors. One project seeks to develop polymer-
based chromatographic supports with novel cylindrical
geometries for the downstream processing of
biomolecules. The focus of another polymer-related
project is the use of low molecular weight ionic and
nonionic polymers as displacers for the large-scale
chromatographic separation of biomolecules.

Excellent instrumentation for polymer research
is available within the department of chemical engi-
neering. Facilities include several Digilab Infrared
Spectrophotometers, ISI Scanning Electron Micro-
scope, Perkin-Elmer System 7 Differential Scanning
Calorimeter and Thermogravimetric Analyzer, Wa-
ters Gel Permeation Chromatograph, Instron model
1122 Mechanical Tester, Cahn C-1100 High-Pres-
sure Balance, Rheovibron, Rheometrics Mechanical
Spectrometers, and Weissenberg Rheogoniometer.
In addition, fine facilities are also available in the
departments of chemistry and materials science and
engineering. They include transmission electron
microscopy, cryogenic microtome, X-ray diffraction,
ESCA, and infrared and Raman spectrometers. 1

Continued from page 179.

video format) exists which can be used to promote
higher levels of student activity during video-based
learning processes: videodiscs. The technology, al-
though still expensive, has been shown to be effec-
tive in learning environments [11]. The most desir-
able aspect of videodiscs is their interactive capabil-
ity; any number of video sequences (limited only by
the disc's storage capacity) can be accessed under
the correct recall conditions. For example, under
computer control from an interactive program run
by the student, any sequence of video segments can
be combined to take the student through a lesson.
Not only can videodiscs store anything from labora-
tory demonstrations to example problems and solu-
tions, but they can also be recalled in any sequence
determined by the student. The use of videodiscs
will certainly become more widespread on all educa-
tional levels as their price decreases.

Our experience with the videotaped module was
rewarding in spite of the great amounts of time and

effort it required. To produce the two forty-five min-
ute videotapes, we invested approximately twenty
hours of script preparation, taping, and editing time.
The result, though, is a complete module of instruc-
tional material which can be dispensed with mini-
mum effort of copying and distribution. The facts
that the students felt the videotapes were a good
medium for teaching and that the quality of student-
teacher interaction was improved should be peda-
gogical driving forces for investigating the use of
videotapes an an alternative approach to biochemi-
cal engineering education. Additionally, the students
experienced another teaching medium and were
exposed to a biochemical engineering laboratory with-
out the expense of equipping the lab.

The authors would like to thank Phillip Wankat
and Frank Oreovicz, the instructors of the grad-
uate course on educational methods in chemical
engineering, for their support and encouragement
in bringing these ideas to reality. We would also like
to acknowledge the assistance of Continuing
En-gineering Education at Purdue, and especially
the aid of Ivan Spencer. The assistance of Beth
Breidenbach in the construction of the questionnaires
is also appreciated.

1. Bungay, H.R., "Biochemical Engineering with Extensive
Use of Personal Computers," Chem. Eng. Ed., 20, 122
2. Ng., T.K.-L, J.F. Gonzalez, and W.-S. Hu, "Biochemical
Engineering," Chem. Eng. Ed., 22, 202 (1988)
3. Squires, R.G., and D.V. Frank, "Supplemental TV Taped
Problems," Chem. Eng. Ed., 17, 117 (1983)
4. Newell, R.B., P.L. Lee, and L.S. Leung, "A Resource-Based
Approach to ChE Education," Chem. Eng. Ed., 19, 36
5. Baasel, W. D., "Why PSI? How to Stop Demotivating Stu-
dents," Chem. Eng. Ed., 12, 78 (1978)
6. Bailey, J.E., and D.F. Ollis, Biochemical Engineering
Fundamentals, second edition, McGraw-Hill Book Co., New
York (1986)
7. Pirt, S.J., Principles of Microbe and Cell Cultivation, John
Wiley and Sons, New York (1975)
8. Dutton, J.C., "A Comparison of Live and Videotaped Pres-
entations of a Graduate ME Course," Eng. Ed., January,
243 (1988)
9. Salomon, G., and H. Gardner, "The Computer as Edu-
cator: Lessons from Television Research," Ed. Researcher,
15(1), 13 (1986)
10. Salomon, G, "Television is 'Easy' and Print is 'Tough': The
Differential Investment of Mental Effort in Learning as a
Function of Perceptions and Attributes," J. of Ed. Psychol-
ogy, 76(4), 647 (1984)
11. Clark, D.J., "How do Interactive Videodiscs Rate Against
Other Media," Instructional Innovator, 29(6), 12 (1984) 0

Fall 1990





University of California
Los Angeles, CA 90024

The chemical engineering profession is un-
dergoing an era of self-reflection (and evaluation)
during which it has become apparent that chemical
engineers must strive to design processes geared
toward waste minimization (or pollution prevention).
It is a long-range goal that must begin with the
education of students in the fundamental and emerg-
ing concepts of pollution prevention.
In order to appreciate the need for pollution
prevention, students must first be educated to un-
derstand the potential problems that can occur due
to emission of pollutants into the environment. This
awareness can, in principle, be introduced through
regular course work. Recently, Lane [1] reviewed
chemical engineering programs that incorporate
health, safety, environmental, and ethical (HSE&E)
issues into the curriculum. He concluded that most
schools focus on the incorporation of HSE&E into
existing courses, with the most popular course being
the capstone design course. Such an approach, while
attractive, is difficult to implement given the broad
nature of environmental issues. As a result, often
only a few lectures are devoted to environmental
issues, and obviously a fundamental background deal-
ing with environmental issues is not realized. Thus,
although the optimal approach is to introduce en-
vironmental issues throughout the curriculum, there
is still a need to teach fundamental environmental

Yoram Cohem received his B.A.Sc. (1975) and his
M.A.Sc. (1977), both in chemical engineering, from
the University of Toronto. He received his PhD from
the University of Delaware in 1981 and has been on
the faculty at the University of California, Los Ange-
les, since that time. He is also the Director of the
UCLA/EPA National Center for Intermedia Transport
Research. He has an active research program in the
areas of multimedia pollutant transport, hazardous
substances control, and macromolecular interfaces. I

courses that clearly demonstrate that environmental
issues are an integral part of the chemical engineer's
responsibilities. Moreover, such courses should ex-
pose the student to the basics of pollution abate-
The UCLA chemical engineering department
has incorporated environmental issues throughout
the undergraduate curriculum with special problems,
assignments, and examples. In addition, an elective
undergraduate course in the area of "Pollution Pre-
vention" has been established. This course, which is
one quarter in length (i.e., ten weeks), is offered to
students at the junior and senior level, but it is also
suitable as a first-year level graduate course.

General Guidelines
The course begins with a general discussion of
the problems (see Table 1) that are associated with
environmental pollution and the need for pollution
abatement. The student is then introduced to vari-
ous major environmental acts (such as the Clean Air
Act, Clean Water Act, Resource Conservation Recov-
ery Act, Comprehensive Environmental Response,

Wangteng Tsai is a postdoctoral researcher in the
chemical engineering department at the University
of California, Los Angeles. He obtained his BS from
the National Taipei Institute of Technology in 1978
and his MS and PhD from Rensselaer Polytechnic
Institute in 1984 and 1987. His research interests
are in multimedia and intermedia transport, expo-
sure and risk assessment, rain scavenging, andpho-
tochemical modeling.

Steven Chetty has been in the United States Army
since 1982 and holds the rank of Captain. He re-
ceived his BS in chemical engineering from Widener
University in 1982 and is currently a graduate stu-
dent at the University of California, Los Angeles. His
research interests include multimedia modeling, and
exposure and risk analyses.

Copyright ChE Division 1990

Chemical Engineering Education

Compensation, and Liability Act, etc.). Examples of
health effects due to chronic and acute exposure to
toxic chemicals, as well as ecological effects, are stud-
ied. This material covers about three lecture hours.

In the second part of the course, examples of
emissions are given from various references, in-
cluding the Toxic Release Inventory [2]. Subse-
quently, examples that pertain to the prevention of
toxic chemical emission to the air, water, and soil
media are discussed.

The third part of the course focuses on pollu-
tion prevention. The student learns to differentiate
between source reduction (or waste minimization)
strategies that are designed to prevent the genera-
tion of waste as part of the manufacturing process
and treatment methods that are often referred to as
"end-of-the-pipe" control methods. At least two case
studies are reviewed through classroom discussion
and homework assignments. The students go through

Course Outline
# of
Lecture Hours
1. Introduction
A. Environmental pollution and its impact on our environment 1
B. Major environmental regulations 1
C. Exposure and risk 1

2. Sources
A. Nature of emissions: gases, liquids, solids, aerosols 2
B. Emission inventories: engineering mass balances at 2
trace concentrations

3. Pollution Control
A. Source reduction 3
B. Treatment technologies 1
C. Disposal of chemical wastes 2
D. Remediation: The penalty for past environmental "crimes" 2

4. Transport of Chemicals Across Environmental Phase Boundaries
A. Review of major intermedia transport processes (e.g., dry and
wet deposition; volatilization from soils and water bodies) 5
B.Dynamic partitioning of chemicals in the multimedia
environment: compartmental and spatial models 2

5. Multimedia Exposure
A. Identification and review of the various exposure pathways 1
B. Estimation of exposure parameters 1
C. Determination of exposure based on multimedia transport
information 2
D. Uncertainties in transport and exposure analyses 2

6. Multimedia Risk Analysis
A. Health risks: chronic versus acute health risks 2
B. Toxicology and risk assessment: laboratory vs. epidemiological
studies 1
C. Ecological risks (i.e., non-human health risks) 1
D. Societal risks discussion 1
E. Uncertainties in risk analysis 1

7. Group Projects
A. Group project: A multimedia exposure and risk assessment for
a given chemical in a specific geographical region 4
B.Project presentations 2

Fall 1990

a simple process analysis to discover the areas where
simple process modification might be feasible in or-
der to eliminate (or minimize) unnecessary waste
streams [3,4]. Although the subject of remediation
technologies (e.g., the clean-up of existing disposal
and storage sites) is of importance, only two lecture
hours are devoted to this subject area. It is impor-
tant to emphasize that disposal is not an acceptable
pollution prevention strategy.

In the fourth part of the course the focus is on
the transport of pollutants in the environment, with
particular emphasis on the intermedia (or cross-
media) transport of contaminants. The objective is
to ensure that the student realizes that environ-
mental pollution is a multimedia problem. Various
intermedia transport processes that occur in the
environment are described (shown in Table 2) in
order to emphasize the idea that pollutants which
are emitted into one environmental media (e.g., air,
water, or soil) will migrate and partition into most
other environmental media with which we come
in contact. The potential hazards of various pollut-
ants released into the environment will then depend
upon the degree of multimedia exposure of human
and ecological receptors to the chemicals and their
associated risks. Therefore, in order to evaluate po-
tential risks due to the release of various chemicals
into the environment, one must be able to describe
their probable concentrations in the environment,
the exposure of human and ecological receptors to
the chemicals, and the associated health and ecol-
ogical risks.

Summary of Major Intermedia Transport Processes

1. Transportfrom atmosphere to soil and water
a. Dry deposition of gaseous and particulate pollutants
b. Adsorption onto particle matter and subsequent dry and
wet deposition
c. Rain scavenging of gases and particles
d. Infiltration
e. Runoff
2. Transportfrom waterto atmosphere, sediment, suspended solids, and
a. Evaporation
b. Aerosol formation at the air/water interface
c. Sorption by sediment and suspended solids
d. Sedimentation and resuspension of solids
e. Uptake and release by biota
3. Transport from soil to atmosphere, water, sediment, and biota
a. Volatilization from soil and vegetation
b. Dissolution in rain water which is associated with infiltration
c. Leaching to groundwater
d. Adsorption on soil particles and transport by runoff or wind
e. Resuspension of contaminated soil particles by wind
f. Uptake by biomass such as microorganisms, plants, and animals

The task of predicting
the multimedia parti-
tioning of pollutants in the
environment is obviously
very complex. The distri-
bution of pollutants that
are released into the envi-
ronment is the result of
complex physical, chemical,
and biological processes.
Nonetheless, it is possible
to construct relatively
simple, yet practical, mod-
els [5-7] that will allow the
chemical engineering stu-
dent to explore ideas that
encompass the subject area
of pollutant partitioning in
the multimedia envi-
ronment. For example, the
concept of pollutant trans-
port in the multimedia
environment can be illus-

Intermedia Traspon Proca Environmmental System InitialConditions
Rain Scavenging. Infltration, Transport Equations for Media Dimmenionm
Runoff, Soil Drying etc. Individual Compartments Sources
(Uikage of Media through Polhilant Initial and
Boundary Conditions) Background Concentrations MULTIMEDIA
Phi.hrrical rmea Meteorological Data TRANSPORT
Diffusion Coefficients
Mas Transfer Coefficients
Reaction Rate Constants Concentration vs Time
in Various Media
------_^ ---------------------

Pathway Exposure Factors Exposure Assessment Total Daily Exposure for
All Pathways (mg/g-day)
Exposure for Individual
Pathways (mg/kg-day)
,----------------------------------------------- ,-------- -------------------------------------.
I-------------------------- --- I-------* ------------ -------------------------

FRisk Fanor for All Pathwpys
L ------------- ------- -----------------------------------------------------------

FIGURE 1. Schematic of risk analysis from a multimedia transport modeling approach.

treated via a simple example such as an oil spill on
water with pollutant exchange between the oil, air,
and water phases. Subsequently, as described later,
a group project is assigned where use is made of
more sophisticated models which mimic the complex
environmental system. Through such a study, for
example, the student can gain an appreciation for
the applications of transport phenomena and thermo-
dynamics in the "real world."
In the fifth part of the course the student is in-
troduced to the concept of exposure assessment due
to chronic and acute exposure to chemical contam-
inants and the connection of risk analysis with the
multimedia transport modeling, as illustrated in
Figure 1. This part of the course focuses on the
integrated multimedia approach to assessing the
individual intake of contaminant via a variety of
pathways (see Table 3). Given simple exposure sce-
narios, the students are asked to go through the
exercise of calculating human exposure to different
chemicals due to chronic exposure [8-10].
Topics four through six of the course, including
the group project (Table 1), comprise about seventy
percent of the course. This latter material, which is
the core of the course, is discussed in the following

Multimedia Exposure and Health Risk
The assessment of risks due to exposure of a
receptor (usually a biological receptor) to pollutants

is generally determined from appropriate dose-re-
sponse relations. In order to utilize dose-response
relations to predict the expected response of a target
receptor, the dose must be determined. The dose, in
turn, can be related to the exposure of the receptor
to the given agent. The exposure, as discussed be-
low, is a function (among other factors) of the pollut-
ant concentration in various environmental media
that affect the receptor either directly or indirectly
The measure of exposure is the average amount
of agent (i.e., chemical contaminant) available per
unit time at the exchange boundaries (i.e., lungs,
skin, intestinal tract) during a specified period of

Potential Exposure Pathways to Humans

1. Inhalation
a. Gases in outdoor and indoor air
b. Particulates in outdoor and indoor air

2. Ingestion
a. Drinking water (surface and ground waters)
b. Fruits, vegetables, and grain
c. Meat, milk, and dairy products
d. Fish
e. Soil
3. Dermal absorption
a. Immersion in contaminated water such as swimming
and showering
b. Accumulation of contaminated soil and dust on skin

Chemical Engineering Education

Suggested References

* "Are We Cleaning Up? 10 Superfund Case Studies," A Special Report of
OTA's Assessment on Superfund Implementation, Congress of the U.S., Off.
of Technology Assessment, Washington, DC, OTA-ITE-362, June (1988)
* "From Pollution to Prevention: A Progress Report on Waste Reduction,"
Congress of the U.S., Office of Technology Assessment, Washington, DC,
OTA-ITE-347, June (1987)
* "New Perspectives on Pollution Control," The Conservation Foundation,
Washington, DC (1984)
* "Wastes in the Marine Environment," Congress of the U.S., Office of Tech-
nology Assessment, Washington, DC, OTA-O-334 (1987)

* Macias, E.S., and P.K. Hopke (eds), Atmospheric Aerosol: Source/Air
Quality Relationships, ACS Symp. Series 167, Am. Chem. Soc., Washing-
ton, DC (1981)
* Rogozen, M.B., R.D. Rapoport, and A. Sochet, "Development and Improve-
ment of Organic Compound Emission Inventories for California," prepared
under Contract AO-101-32, State of California Air Resource Board, Sacra-
mento, CA (1985)
* Tate, R., P. Ayala, J. Curaan, H. Linnard, C. Nguyen, R. Bradley, and T.
McGuire, "Preliminary Inventory: Substances of Special Interest," Technical
Support Div., Emission Inventory Branch, Cal. Air Resources Board (1984)
* TRI, the Toxic Release Inventory, US Dept. of Health and Human Services,
National Board of Health, Bethesda, MD (1989)
* Weiner, A.M., D.R. Fritz, P.R. Miller, R. Atkinson, D.E. Brown, W.P.L.
Carter, M.C. Dodd, C.W. Johnson, M.A. Myers, K.R. Neises, M.P. Poe, and
E.R. Stephens, "Investigation of the Role of Natural Hydrocarbons in Photo-
chemical Smog Formation in California," Final Report, prepared under Con-
tract No. AO-056-32 to the California Air Resources Board (1983)

Pollution Control
* Dawson, G.W., and B.W. Mercer, Hazardous Waste Management, John
Wiley and Sons, New York (1986)
* Handbook of Industrial Water Conditioning, BETZ Laboratories, INBC, Tre-
vose, PA 19047 (1980)
* Fawcett, H.H., Hazardous and Toxic Materials: Safe Handling and Dis-
posal, John Wiley and Sons, New York (1984)
* Multimedia Approaches to Pollution Control, National Academy Press,
Washington, DC (1987)
* Novotny, V., and G. Chesters, Handbook of Nonpoint Pollution: Sources
and Management, Van Nostrand Reinhold, New York (1981)
* Purcell, R.Y., and G.S. Shareef, Handbook of Control Technologies for
Hazardous Air Pollutants, Hemisphere Publishing Corp., New York (1988)
* Viessman, Jr., W., and M.J. Hammer, Water Supply and Pollution Control,
Harper & Row Publishers, New York (1985)
* Wentz, C.A., Hazardous Waste Management, McGraw-Hill Book Co., New
York (1989)

Pollutant Transport
* Cohen, Y., "Intermedia Transport Modeling in Multimedia Systems," in
Pollutants in a Multimedia Environment, Cohen, Y.(ed), Plenum Press (1986)
* Cohen, Yoram, "Modeling of Pollutant Transport and Accumulation in a
Multimedia Environment," in Geochemical and Hydrologic Processes and
Their Protection: The Agenda for Long Term Research and Development, S.
Draggan, J.J. Cohrssen, and R.E. Morrison (eds), Praeger Publishing Co.,
New York (1987)
* Cohen,Yoram, "Organic Pollutant Transport," Environ. Sci. Tech., 20, 538
* Cohen, Yoram (ed), Pollutants in a Multimedia Environment, Plenum Press
* Cohen, Yoram, D. Mackay, and W.Y. Shiu, "Mass Transfer Rates Between
Oil Slicks and Water," Can. J. Chem. Eng., 58, 569 (1980)
* Cohen, Yoram, H. Taghavi, and P.A. Ryan, "Contaminant Diffusion Under
Non-Isothermal Conditions in Nearly Dry Soils," J. Environ. Quality, 17, 198
* Draggan, S., J.J. Cohrssen, and R.E. Morrison (eds), Geochemical and
Hydrologic Processes and Their Protection: The Agenda for Long Term
Research and Development, Praeger Publishing Co., New York (1987)
* Friedlander, S.K., Smoke, Dust and Haze: Fundamentals of Aerosol Be-
havior, John Wiley and Sons, New York (1977)

* Mackay, D., and S. Paterson, "Calculating Fugacity," Environ. Sci. Tech.,
15, 106(1981)
* Mackay, D., and S. Paterson, "The Fugacity Approach to Multimedia Envi-
ronmental Modeling," in Pollutants in a Multimedia Environment, Cohen, Y.
(ed), Plenum Press, New York (1986)
* Mackay, D., S. Paterson, B. Cheung, and W.B. Neely, "Evaluating the Envi-
ronmental Behavior of Chemicals with a Level III Fugacity Model," Che-
mosphere, 14, 335 (1985)
* Ryan, P.A., and Yoram Cohen, "Multiphase Chemical Transport in Soils," in
Intermedia Pollutant Transport: Modeling and Field Measurements, D.T.
Allen, I.R. Kaplan, and Y. Cohen (eds), Plenum Press, in press (1989)
* Swann, R.L., and A. Eschenroeder, "Fate of Chemicals in the Environ-
ment," ACS Symp. Series 225, Am. Chem. Soc., Washington, DC (1983)
* Thibodeaux, L.J., Chemodynamics: Environmental Movement of Chemi-
cals in Air, Water, and Soil, John Wiley and Sons, New York (1970)
* Travis, C.C., J.W. Dennison, and A.D. Arms, "The Nature and Extent of
Multimedia Partitioning of Chemicals," unpublished report, Health and Safety
Research Div., Oak Ridge Nat. Lab., Oak Ridge, TN (1987)

Multimedia Exposure
* Kenaga, G.E., and C.A.I. Goring, "Relationship Between Water Solubility,
Soil Sorption, Octanol-Water Partitioning and Concentration of Chemicals in
Biota," Aquatic Toxicology, ASTM Stp 707, 78 (1980)
* McKone, T.E., and P.B. Ryan, "Human Exposure to Chemical Through
Food Chains: An Uncertainty Analysis," Environ. Sci. Tech., 23, 1154 (1989)
*Ott, W.R., "Total Human Exposure," Environ. Sci. Tech., 19, 880 (1985)
* Travis, C.C., and A.D. Arms, "The Food Chain as a Source of Toxic Chemi-
cal Exposure," in Toxic Chemicals, Health and the Environment, L.B. Lave,
A.C. Upton (eds), The John Hopkins U. Press, Baltimore, MD, 5, 95 (1987)
* United States Environmental Protection Agency, "Guidelines for Estimating
Exposures," Fed. Register, 51, 34092 (1988)
* Vaughan, B.E., "State of Research: Environmental Pathways and Food
Chain Transfer," Environ. Health Perspect., 54, 353 (1984)
* Wallace, L.A., The Total Exposure Assessment Methodology (TEAM) Study:
Project Summary, U.S. Environmental Protection Agency., Washington, DC,
EPA/600/S6-87/002 (1987)
* Wallace, L., E. Pellizari, L. Sheldon, T. Harwell, C. Sparacino, and H. Zelon,
"The Total Exposure Assessment Methodology (TEAM) Study: Direct Meas-
urements of Personal Exposure Through Air and Water for 600 Residents of
Several U.S. Cities," in Pollution in a Multimedia Environment, Y. Cohen (ed),
Plenum Press, New York (1986)

Multimedia Risk Analysis
* Bolten, J.G., P.F. Morrison, K.A. Solomon, and K. Wolf, "Alternative Models
for Risk Assessment of Toxic Emissions," Report N-2261-EPRI, The Rand
Publication Series, Rand, Santa Monica, CA, April (1983)
* Bolten, J.G., P.F. Morrison, and K.A. Solomon, "Risk-Cost Assessment
Methodology for Toxic Pollutants from Fossil Fuel Power Plants," Report R-
2993-EPRI, The Rand Pub. Ser., Rand, Santa Monica, CA, June (1983)
* Conway, R.A. (ed), Environmental Risk Analysis for Chemicals, Van Nor-
strand Reinhold Co., New York (1982)
* Cothern, R., W.A. Coniglio, and W.L. Marcus, "Estimating Risk to Human
Health," Environ. Sci. Tech., 20, 111 (1986)
* Dydek, T., "Comparison of Health Risk Assessment Approach for Carcino-
genic Air Pollutants," paper no. 89-56.10, presented at 82nd Annual Meeting
and Exhibition, Anaheim, CA, June (1989)
* McKone, T.E., and D.W. Layton, "Screening the Potential Risks of Toxic
Substances Using a Multimedia Compartment Model, Estimation of Human
Exposure," Regulatory Toxicology and Pharmacology, 6, 359 (1986)
* McKone, T.E., and W.E. Kastenberg, "Applications of Multimedia Pollutant
Transport Models to Risk Analysis," in Pollutants in a Multimedia Environ-
ment, Y. Cohen (ed), Plenum Press, New York (1986)
* Travis, C.C., and A.D. Arms, "Bioconcentration of Organics in Beef, Milk,
and Vegetation," Environ. Sci. Tech., 22, 271 (1988)
* U.S. Environmental Protection Agency, "Guidelines for Carcinogen Risk
Assessment," 51 Federal Register 33992, September 24 (1986)

Group Projects
* Cohen, Yoram, W. Tsai, and S. Chetty, The SMCM Software (3.0) User's
Manual, the Regents of the University of California, Los Angeles, CA (1989)

Fall 1990


time. The exposure via a specific pathway, during a
time interval t, can be defined by the following


to+ At
Ei= J I(t)dt

in which Ii is the intake rate (or intensity of contact)
of the given agent by the receptor. The intake rate Ii
is expressed by
Ii =LiCi (2)

Features of the SMCM Model

1. The SMCM is a user-friendly software package that..
a. Can be used to answer "what if' type questions
b. Allows for rapid scenario changes
c. Minimizes data input
d. Provides a graphical output display for quick scenario analysis
e. Provides specific online help for input data fields
f. Provides a menu system for user selection of data input, simula-
tion execution, plotting, and printing a summary report of the
calculated results
g. Allows the software to be run on IBM-PC/XT/AT compatible
h. Allows an inexperienced user to run the SMCM software with
virtually no background in transport phenomena.
2. The SMCM model applies a new modeling approach that...
a. Makes use of both uniform (air, water, biota, suspended solid)
and non-uniform compartments (soil and sediment)
b. Allows for mass exchange of pollutant between the air compart-
ment and its surrounding atmospheric environment. The water
compartment is also treated in a similar way.
c. Treats non-uniform compartments as an unsteady state, one-
dimensional diffusion type equation with convection and
chemical reaction
d. Incorporates the simulation of a chemical buried in the soil
e. Considers a variety of source types and allows the user to select
and input source data through the data input screens
f. Applies flux boundary conditions for non-uniform compart-
ments. Although groundwater is not treated as a compartment in
the SMCM model, flux condition at the bottom boundary of the
soil compartment can be incorporated to account for the
chemical transport to groundwater.
3. The SMCM model accounts for the effects of rainfall and tempera-
ture on the environmental transport of pollutants.
a. The SMCM has a rain generation module which can generate
rainfall in the form of a single event of specified intensity and
duration, or randomly distribute rainfall within specified levels
of rainfall intensity, duration, and total rainfall.
b. The transport processes associated with rainfall, such as rain sca-
venging, infiltration, runoff, and soil drying, are simulated by a
water balance method which uses theoretically based correla-
c. User-supplied average monthly temperatures are used to
construct average daily temperatures.

4. Provides accurate and reliable parameter estimation methods
a. Physicochemical parameters such as mass transfer coefficient,
diffusion coefficient, and partition coefficient are estimated
using theoretical methods and empirical correlations. The user
can input partition coefficients and diffusion coefficients if
known. These will override any model-estimated values.
b. Temperature variations of diffusivities, partition coefficients,
mass transfer coefficients, and reaction rate constants are
included by either internal predictions or via user-input data.
c. Production or degradation rates are treated as first order

in which C. is the concentration of the agent in en-
vironmental compartment i in contact with the re-
ceptor, and Li is the extent of contact (e.g., inhalation
rate is given as volume of air/unit time/body weight).
The extent of contact, L,, is obviously characteristic
of the behavior of the receptor (i.e., its dynamics in
the environment). For example, exposure that oc-
curs through inhalation is a function of the time that
the individual spends at various locations (indoors
and outdoors) and the rate of inhalation, L, at each
location. Such information can be obtained, for ex-
ample, from population activity pattern studies
[11,12]. The concentration C, in compartment i can
be determined from either monitoring studies or from
appropriate transport and fate models. In the sim-
plest approximation, once the exposure is known,
the dose can be related to exposure by the following
Di =Ei Fi (3)

in which F, is an absorption factor associated with
the absorption of the contaminant by the receptor

Physicochemical Properties of TCE

Molecular weights
Henry's law constant
Boiling temperature
Molal volume
Reaction rate constants
Suspended solids
Diffusion coefficients
Partition coefficients
Octanol/water, Kw
Water/suspended solids
Mass transfer coefficients
Water/suspended solids

1179 Pa-m3/mol
1103.8 mg/L
360.25 K
89.9 cm3/mol

0.01 hr-1
1.24 x 10-4 hr-

2.89 x 102 m2/hr
3.43 x 10- m2/hr
9.07 x 10-4 m2/hr
3.59 x 10-7 m2/hr


0.14 m/hr
0.07 m/hr
7.0 x 104 m/hr
0.10 hr-1
0.73 m/hr

* Calculated by the SMCM model (at the first step of model integration)
using theoretical methods and empirical correlations. The temperature
variations of diffusivities, partition, and mass transfer coefficients are
taken into account.

Chemical Engineering Education

attributed to exposure pathway i. Detailed evalua-
tion of the absorption factor requires either exper-
imental data or prediction using appropriate phar-
macokinetic models.
The exposure of the population to various pollu-
tants can occur via three major exposure routes:
inhalation, dermal absorption, and ingestion. The
ingestion pathway refers to the consumption of both
food and drinking water and other liquids. The in-
take of contaminants via food consumption is par-
ticularly significant since contaminants may accu-
mulate in the food chain [10,13,14]. Thus, exposure
can be strongly affected by multimedia transfers.
Multimedia health risk analysis is covered in
the sixth part of the course. For example, the risk as-
sociated with chronic exposure to chemical car-
cinogens can be estimated using cancer potency fac-
tors [15] which relate the average daily intake per
unit body mass to the risk of developing cancer as
defined below:
Rij = 1.0-exp(-Dijqi) (4)
where R. is the health risk for exposure to chemical
carcinogen i for exposure pathway j (dimension-
less), Dj is the average daily intake (or dose) rate of
chemical carcinogen i [mg/kg-day] and qi is the corre-
sponding cancer potency factor [(mg/ ']. In
contrast to carcinogens, the risk associated with non-
carcinogens is difficult to quantify. However, the
regulatory approach to establishing guidelines such
as with the reference dose (Rfd) method are dis-
cussed in the sixth part of the course (see Table 1).
The concepts of multimedia pollutant transport,
exposure, and risk analyses are covered through the
lectures and a group project as described below.
Materials from pertinent literature sources are util-
ized as listed in the sample of suggested references
(Table 4). I I

FIGURE 2. Configuration of the SMCM model.

The group project is designed to illustrate
the concepts of pollutant partitioning in the
environment, the subsequent chronic exposure of
human receptors, and the potential risk as
well as the uncertainties associated with
such estimates of health risks.

Group Project
The group project is designed to illustrate the
concepts of pollutant partitioning in the environ-
ment, the subsequent chronic exposure of human
receptors, and the potential risk as well as the un-
certainties associated with such estimates of health
risks. Groups of two or three students (depending
on the size of the class) are assigned a particular
chemical and must estimate exposure and risk to
an individual within a given environmental region
(a particular geographical location or a fictitious
region). The group projects are assigned once the
topic of multimedia transport has been covered (see
Table 1).
In order to determine the multimedia distri-
bution of the chemical given estimated emissions,
the students utilize the Spatial-Multimedia-Com-
partmental (SMCM) pollutant transport and fate
model. The SMCM model [16] was developed at
UCLA through the sponsorship of the UCLA/EPA
National Center for Intermedia Transport Research.
The SMCM software is user-friendly and runs on
IBM PC/XT/AT compatible computers. The SMCM
model was designed to allow the student to get a
better understanding of pollutant distribution in
the environment without the need to develop spe-
cial computer-related skills or even knowledge in
transport phenomena or thermodynamics. The stu-
dent is required, however, to obtain some basic phys-
icochemical and thermodynamic information for the
chemical that is assigned, as well as information
regarding the climate, size, and simple meteorologi-
cal information for the region of interest.
The various environmental compartments in-
cluded in the SMCM model are shown in Figure 2.
The student can simulate various scenarios for
source emissions, rain events, and temperature
variations in the region as described in Table 5.
This introduces the student to the concept of pollu-
tant movement across environmental phase bounda-
ries and, thus, the role of mass transfer in the
natural environment. Also, the concept of equilib-
rium partitioning and local equilibrium calculation
assumptions are introduced. Once pollutant con-

Fall 1990

centrations are obtained, the students utilize a simple
procedure to determine the average daily exposure
of an average adult to the given chemical for a pre-
scribed period (usually a lifetime period of about
seventy years). The latter part of the analysis relies
on recommended EPA values for human intake of
beef, milk, vegetables, etc., inhalation, water con-
sumption, and other activities such as swimming
that may lead to exposure to chemical contaminants.

Example of a Group Case Study
An example of a potential group project is the
analysis of the steady state partitioning of trichlo-
roethylene (TCE) in the Los Angeles area and the
determination of the resulting exposure and health
risks. The pertinent physicochemical properties for
TCE and the appropriate compartmental data for
Los Angeles are shown in Tables 6 and 7, respec-
tively. The results of an analysis for the multimedia
partitioning of TCE in Los Angeles are shown in
Table 8. Given the predicted TCE concentrations in
different media, and with the estimates of various
partition coefficients and pathway exposure factors
[10] between beef, milk, vegetables, etc., the average
daily exposure for all pathways over a seventy-year
lifetime was calculated to be 1.00 x 10-4 mg/
(Table 9). Moreover, using the appropriate cancer
potency factors for TCE (0.011 lmg/kg-day}-1 for oral
intake, and 0.0046 {mg/kg-day- 1 for inhalation in-
take) [15], the associated lifetime cancer health risk
for chronic exposure was found to be 7.47 x 10-7. The
health risk is interpreted as the probability of cancer
occurring over the lifetime of the individual due to
exposure to TCE. Alternatively, one can view this
health risk as implying that 7.47 cancer cases are to
be expected for a population of 1.0 x 107. Thus, by
comparing results for different chemicals, the stu-
dents can determine the difference in the potential
exposures and health risks associated with the re-
lease of toxic chemicals to the environment.


Chemical engineering students must be made
aware of their responsibilities as engineers to design
processes that will operate safely and with minimal
environmental impact. The course described in this
article should allow the student to gain a scientific
appreciation for the magnitude and source of poten-
tial environmental health risks. Through such a
course, the student also learns that the various chemi-
cal engineering fundamentals provide a solid foun-
dation for covering topics such as environmental
transport and exposure and risk analysis, as well as

pollution control.


The preparation of this manuscript was par-
tially funded by the U.S. Environmental Protection
Agency under assistance agreement CR-812771-03
to the National Center for Intermedia Transport Re-
search at UCLA, and the University of California
Toxic Substances Research and Teaching program.

Compartmental Data for Los Angeles*

1. Air
Air viscosity
Wind velocity
Mixing height
Source strength of pollutantt
2. Water
Air/water interfacial area
Flow rate
Source strength
3. Soil
Air/soil interfacial area
Organic carbon fraction
Source strength
Type of soil

4. Sediment
Sediment/water interfacial area
Organic carbon fraction
Source strength
5. Suspended solids
Organic carbon fraction
Average diameter
Suspended solids/water interfacial area
Suspended solids vol/water volume %

6. Biota
Biota volume/water volume %


1.78 x 10" Pa-s
270 cm
400 m
1 atm
92.4 mol/hr

4.9 m
5.27 x 107 m2
12.60 C
0 mt/hr
0.9 mol/hr

1.5 x 106 g/m3
1.04 x 101' m2
0 mol/hr
Nickel gravelly
sand loam*

1 m
1.5 x 106 g/m3
4.94 x 107 m2
0 mol/hr

1.5 x 106 g/m3
0.001 cm
7.75 x 106 m'
5 x 104

5 x 10-5

* Without rainfall
* In this simulation, the source strengths of pollutant in air,
water, soil and sediment compartments are assumed to be non-
repetitious constant sources. However, other types of source
such as non-repetitious sinusoidal, constant repetitious, and
sinusoidal repetitious sources are also provided for the air and
water compartments in the SMCM model.
* This type of soil corresponds to average conditions in the soil
of 34% aircontent, 8% water content, and 58% occupied bysoil

Chemical Engineering Education

The authors have also benefitted from discussions 3.
with V. Vilker, S.K. Friedlander, and D.T. Allen,
who participated in the early design and teaching of
this course.


1. Lane, A.M., "Incorporating Health, Safety, Environmental,
and Ethical Issues into the Curriculum," Chem. Eng. Ed., 6.
2. TRI, the Toxic Release Inventory, U.S. Dept. of Health 7.
and Human Services, National Inst. of Health., Bethesda,
MD (1989) 8.

Results of Multimedia Partitioning of TCE in Los Angeles

Compartment Predicted Concentrations % Chemical in Monitorec
[gmol/m'](x10") inOtherUnits Compartment* Concentrati

Air 0.2 0.2 (pg/m3) 97.10 0.1 (pg/m
Water 21.2 0.03 (pg/L) 0.73 0.08 (gg/I
Soil 0.8 0.72 (ng/kg) 2.16
Sediment 18.0 15.8 (ng/kg) 9.03 x 10- --
Biota 218.0 287.0 (ng/kg) 3.74 x 10-6 -
Suspended Solids 116.0 102.0 (ng/kg) 1.99 x 10- -

Predicted total amount of trichloroethylene (gmols) in the multimedia system is 7.5 x 1
at the simulation time 1000 hrs: the simulation started from February 1, 1984.
The reported environmental concentrations are average values [12].

Predicted Average Daily Exposure and Cancer Health Risk for
Chronic Exposure to Trichloroethylene in Los Angeles

Exposure Pathway

Drinking water
Ingestion of meat
Ingestion of milk
Ingestion of vegetable
Ingestion of root vegetable
Ingestion of fish
Ingestion of soil
Inhalation of air
Dermal adsorption of water via showering
Dermal adsorption of water via swimming
Dermal absorption of soil

Dose Rate*

6.15 x 107


6.76 x 10-"

1.04 x 10-5 1.15 x 10-7
6.34 x 10 6.97 x 10"
2.26 x 10-1' 2.49 x 1012
2.72 x 10-' 2.99 x 10.7
2.06 x 10-8 2.26 x 10-'0
4.59 x 10 5.05 x 10s'
5.57 x 10-5 2.56 x 10-'
1.43 x 10' 1.58 x 10"

2.92 x 10 -'

3.21 x 10-12

4.01 x 10-4 4.42 x 10-"

* Total avg. daily intake for all pathways over 70 years is 1.00 x 101 mg/
f Lifetime risk for adult (all pathways combined) is 7.47 x 107 Also note that the aboi
calculations for cancer health risk is based on carcinogenic potency factors of 0.011 [(im'] for oral intake, and 0.0046 [(mg/'] for inhalation intake [15].

Purcell, R.Y., and G.S. Shareef, Handbook of Control Tech-
nologies for Hazardous Air Pollutants, Hemisphere Pub-
lishing Corp., New York (1988)
Wentz, C.A., Hazardous Waste Management, McGraw-
Hill Book Co., New York (1989)
Cohen, Yoram, "Intermedia Transport Modeling in Multi-
media Systems," in Pollutants in a Multimedia Environ-
ment, Cohen, Y. (editor), Plenum Press (1986)
Cohen, Yoram (editor), Pollutants in a Multimedia En-
vironment," Plenum Press (1986)
Cohen, Yoram, "Organic Pollutant Transport," Environ.
Sci. Tech., 20 538 (1986)
McKone, T.E., and D.W. Layton, "Screening the Potential
Risks of Toxic Substances Using a Multimedia Compart-
ment Model: Estimation of Human Exposure,"
Regulatory Toxicology and Pharmacology, 6,
359 (1986)
9. McKone, T.E., and W.E. Kasteriberg, "Applica-
tions of Multimedia Pollutant Transport Mod-
Sels to Risk Analysis," in Pollutants in a Multi-
on, media Environment, Cohen, Y. (editor), Ple-
num Press, New York (1986)
3) 10. McKone, T.E., and P.B. Ryan, "Human Expo-
L) sure to Chemical Through Food Chains: An
Uncertainty Analysis," UCRL-99290, preprint,
Lawrence Livermore Nat. Lab., submitted to
Environ. Sci. Tech. (1989)
11. Ott, W.R., "Total Human Exposure," Environ.
Sci. Tech., 19, 880 (1985)
12. Wallace, L., E. Pellizari, L. Sheldon, T. Harwell,
oa' C. Sparacino, and H. Zelon, "The Total Expo-
sure Assessment Methodology (TEAM) Study:
Direct Measurements of Personal Exposures
Through Air and Water for 600 Residents of
Several U.S. Cities," in Pollution in a Mul-
timedia Environment," Cohen, Y. (editor), Ple-
num Press, New York (1986)
13. Travis, C.C., and A.D. Arms, "Bioconcentra-
tion of Organics in Beef, Milk, and Vegetation"
Environ. Sci. Tech., 22, 271 (1988)
14. Vaughan, B.E., "State of Research: Environ-
mental Pathways and Food Chain Transfer,"
Environ. Health Perspect., 54, 353 (1984)
15. EPA, Superfund Public Health Evaluation
Manual, U.S. Environ. Protection Agency,
Washington, DC, EPA/540/1-86-060 (1986)
16. Cohen, Yoram, W. Tsai, and S. Chetty, The
SMCM Software (3.q) User's Manual, the Re-
gents of the Univ. of California, Los Angeles,
CA (1989)
17. Perry, R.H., D.W. Green, and J.O. Maloney,
Perry's Chemical Engineers' Handbook, 6th ed.,
McGraw-Hill Book Co., New York (1984)
18. Dilling,, W.L., N.B. Tefertiller, and G.J. Kal-
los, "Evaporation Rates and Reactivities of
Methylene Chloride, Chloroform, 1,1,1-Trichlo-
roethane, Trichloroethylene, Tetrachloroeth-
ylene, and Other Chlorinated Compounds in
Dilute Aqueous Solutions," Environ. Sci. Tech.,
ve 19. Cohen, Yoram, and P.A. Ryan, "Multimedia
g/ Modeling of Environmental Transport: Trichlo-
roethylene Test Case," Environ. Sci. Tech., 19,
412 (1985)0

Fall 1990




at Virginia Polytechnic Institute and State University

Virginia Polytechnic Institute and State University
Blacksburg, VA 24061

Preparing chemical engineering undergradu-
ates to make effective technical presentations is a
topic of current interest to chemical engineering
educators, a fact attested to by recent articles in
Chemical Engineering Education by Felder [1] and
by Brewster and Hecker [2]. An equally important
issue is the promotion of good communication skills
among graduate students. This topic was recently
addressed in an article by Modi and Bowman [3]
which described a symposium developed at Carnegie
Mellon University.
At Virginia Polytechnic Institute and State Uni-
versity (VPI&SU), graduate students have several
avenues available to them for the development of
both oral and written communication skills. Two
programs are offered by the Graduate Student As-
sembly [4]. In the first of these programs (the Gradu-
ate Research Development Project), graduate stu-
dents compete for supplemental research funding
via written research proposals. The second program
(the Graduate Research Symposium) is conducted
every fall semester and provides a forum for gradu-
ate students to present their research in the form of
poster sessions. Finally, the VPI&SU chemical engi-
neering department offers a one-hour graduate semi-
nar class where students are instructed on the ba-
sics of oral communication. Each student gives black-

Kirk H. Schulz is a PhD candidate at VPI&SU. He
obtained his BS degree in chemical engineering at
VPI&SU in 1986. He is interested in an academic
career of teaching and performing research in chemi-
cal engineering. His research interests include sur-
face science/catalysis and applied process control.
He served as coordinator of the CES3 for 1988 and
1989 and as co-coordinator in 1987

board, overhead, and slide talks on both technical
and non-technical material, and he or she is cri-
tiqued by fellow students and the course professor.
In addition to these opportunities, the Chemi-
cal Engineering Graduate Society in our department
felt that a forum for organizing and presenting tech-
nical oral presentations of the nature of professional
society meetings would be beneficial. We also felt
that such a forum would supplement the
department's academic-year seminar program by
enhancing our understanding in areas of depart-
mental research outside of our particular thesis and
dissertation areas. Consequently, the Chemical
Engineering Summer Seminar Series (CES3) was
conceived in the spring of 1987 by several graduate
students in our department, and it has been success-
fully administered solely by graduate students since
its inception. The purpose of this article is to de-
scribe this unique seminar program.


The overall purpose of the CES3 program is to
give students practice in making oral presentations,
to provide helpful suggestions concerning graduate
students' research, and to broaden the horizons of
those attending the seminars. By providing an op-
portunity to present research in a structured semi-
nar format to an audience of peers, this seminar

-' B'^G. Gregory Benge is a PhD candidate at VPI&SU.
He received his BS from North Carolina State Univer-
sity and his MS from VPI&SU. His primary research
interests are in mathematical modeling, numerical
methods, and reaction engineering. He is Chief Jus-
tice of the VPI&SU Graduate Honor System and has
also served as a delegate to the VPI&SU Graduate
Student Assembly. He was co-coordinator of the
1987 CES3.

Copyright ChE Division ASEE 1990

Chemical Engineering Education

... the chemical engineering students
at VPI&SU formed the Chemical Engineering
Graduate Society for the purpose of helping
coordinate graduate student activities in
the department and addressing
graduate student concerns.

program encourages the development of oral com-
munication skills. Also, since we do not require that
all topics be research-related, we do not limit speaker
participation to graduate students who have made
significant progress in their research.
As a second goal, this forum allows for critique
of a student's research without the accompanying
pressure of a professional presentation. Therefore,
for students who are well into their thesis or disser-
tation research, the CES3 affords an opportunity to
practice presentations that will later be given at a
professional meeting.
A third objective of the CES3 program is to
broaden the horizons of the participants. As Profes-
sor Gerry Beyer said in a recent CES3 seminar,
"...graduate students should venture down the hall
to see what research their fellow graduate students
are doing." This program provides such an opportu-
nity. Consequently, the program serves as an excel-
lent supplement to the department's academic-year
seminar program, which generally entails more spe-
cific topics.


In the fall of 1986, the chemical engineering
students at VPI&SU formed the Chemical Engineer-
ing Graduate Society for the purpose of helping coor-
dinate graduate student activities in the depart-
ment and addressing graduate student concerns.
Several graduate students were interested in work-
ing with the departmental academic-year seminar
program, and so the Seminars Committee was
formed. Through discussions in the Seminars Com-
mittee, the idea of CES3 was conceived. The program
was originally organized during the spring of 1987
and was administered for the first time during the
summer of 1987.
During the initial planning and organization
of the CES3 program, departmental faculty and
graduate students were surveyed to determine their
interest in such a program. Approximately half
of the graduate students and more than a half-

dozen faculty responded. All of the responses
were very positive, with a large majority of them ex-
pressing an interest in giving a presentation. The
faculty have supported the concept of CES3 from the
very beginning.


The CES3 program is attractive from an opera-
tional standpoint in that it does not require a great
deal of planning and organization. The program is
run exclusively by graduate students, with mone-
tary support from the department for food and bev-
erages. The work is divided among several graduate
students so that no one person is overburdened with
responsibility. One student serves as the seminar
coordinator and is responsible for seminar schedul-
ing and publicity, and a committee of three to four
students is responsible for purchasing the food and
drinks and ensuring that the room is set up for the
seminar presentation.
The program runs the entire length of the sum-
mer session, generally from mid-May to mid-August,
with one seminar given each week. Speaker partici-
pation is solicited a couple of months prior to the
first seminar. An information bulletin is sent to all
graduate students, faculty, and staff in the chemical
engineering department. It has a detachable portion
(to be returned to the coordinator) which allows the
speakers to specify their topic area and to choose the
date of their presentation. About three weeks before
the seminar series is to start, a specific title is re-
quested from the speakers, and a final schedule is
then completed and distributed to all faculty, staff,
and graduate students.


Speakers are encouraged to prepare seminars
as though they were making a presentation at a na-
tional technical meeting. The format of the seminars
is structured, yet flexible enough to allow for differ-
ent styles of presentation. Speakers generally use
slides or overhead transparancies; however, video
tapes and computers are occasionally incorporated
into the talks. Seminars are generally 40- to 45-
minute presentations, followed by a 10- to 15-min-
ute question-and-answer period. Quite often, stu-
dents and professors alike remain for a short time
following the talk to continue discussions generated
by the seminar. Speakers are encouraged to give a
fairly detailed introduction since their audience is

Fall 1990

quite diverse in its technical background.


One of the unique features of the CES3 pro-
gram is the requirement that the seminar topic be
related to chemical engineering only in a distant
way, and that it does not necessarily have to be
research-related. The 1988 CES3 featured talks rang-
ing from "Some Thoughts on Chemical Engineering
Education, or On Being Beaten at Your Own Busi-
ness," by Henry McGee, to "Use of Colloidal Gas
Aphrons in the Chemical Engineering Department
at VPI&SU," by former graduate student Alan Foss.
Table 1 is a representative sample of the seminars
given during the first three years of CES3 and shows
the diversity of subjects covered.


Although our seminar program is aimed pri-
marily at the graduate student population, several
faculty are encouraged each year to give talks on
their research or interest areas. We feel that this
gives the graduate students a chance to get better
acquainted with the faculty and their research and
extracurricular activities. This is particularly im-
portant with faculty who do not teach graduate

Selected Titles from the VPI&SU CES3

Year Speaker

1987 Arthur Squires

Benku Thomas
Cal Moreland
Kim Hunter

1988 Henry McGee

Daan Feng
Alan Foss

Randy Moynihan

1989 Nancy Rauschenberg

Jeff Kaster
Tom Quantrille
Gerry Beyer


Maestros or Duffers: What an Engineer
Should Look For in His or Her First Bosses
Polyurethane Foams
Process Dynamics

Some Thoughts on Chemical Engineering
Education, or On Being Beaten at Your
Own Business
Polymer Materials
Use of Colloidal Gas Aphrons in the Chemi-
cal Engineering Department at VPI&SU
Polymer Processing

Natural and Biodegradable Polymer
Biochemical Engineering
Innovative Process Design
SEX: Surface Enhanced eXtraction

courses, faculty with smaller research groups, and
new departmental faculty. Our department has three
recent additions to the faculty, and each of them has
been asked to present a seminar during the summer
after his first year, to give graduate students an idea
of his research interests. Out of a total of ten to
eleven seminar slots each summer, typically two to
three seminars are given by faculty.


The summer seminars are attended primarily
by graduate students, with approximately fifty per-
cent of the graduate students in residence attending
on a regular basis. Additionally, several post-doc-
toral research assistants and undergraduates fre-
quently attend. At VPI&SU, the unit operations labo-
ratory is held in the summer, and on occasion the
entire class attends a seminar that is applicable to
one of the unit operations experiments. Faculty at-
tendance varies widely, with ten to twenty-five per-
cent of the faculty attending on a regular basis.
Since many of the seminar topics are interdiscipli-
nary, they have attracted audiences from other de-
partments such as forest products, materials science
and engineering, and chemistry.


The program is not without flaws. For
example, the number of seminar presenta-
tions given each summer depends upon the
number of graduate students who are in-
terested in giving presentations. This prob-
lem is aggravated by the transient nature
of the graduate student population, which
affects the number of students available.
Any program (such as CES3) that is initi-
ated and administered solely by graduate
students tends to vary yearly due to the
aforementioned problem. If such a program
can be maintained, however, it can be a
valuable part of the graduate student ex-


In summary, we have initiated and
successfully run a summer seminar pro-
gram for the past three summers. The bene-
fits of the program include enhancing oral

Chemical Engineering Education

communication skills among graduate students, af-
fording graduate students the opportunity to pres-
ent their research to an audience of peers, and in-
creasing the breadth of knowledge of the partici-
pants through a diversity of topics. In addition, the
benefits exceedingly outweigh the time investment
of the program administrators.

The largest problem in the organization and
operation of such a program is generating sufficient
interest to fill the available seminar slots. Over-
all, however, the program has been very beneficial
to our department and to the graduate students
involved in planning the program and present-
ing seminars. A summer seminar program similar to
the one described here may be applicable at other

stirred pots

(Tune: Battle Hymn of the Republic)

Free energy and entropy were whirling in his brain
With partial differentials and Greek letters in their
For delta, sigma, gamma, theta, epsilon, and pi
Were driving him distracted as they danced before his

Glory, glory, dear old thermo.
Glory, glory, dear old thermo.
Glory, glory, dear old thermo.
I'll learn you by and by

Heat content and fugacity revolved within his mind
Like molecules and atoms that you never have to wind.
With logarithmic functions doing cake walks in his
And partial molal quantities devouring chocolate


They asked him on the final if a mole of any gas
In a vessel with a membrane through which hydrogen
could pass
Were compressed to half its volume, what the entropy
would be,
If two-thirds delta sigma equalled half of delta P?


The authors wish to thank Noel Schulz for her
helpful comments on the manuscript and Bill Con-
ger for moral and financial support. Also, Tim Longe,
Alma Rodarte, and Jeff Smith were involved in the
conception of the program.

1. Felder, R.M., "A Course on Presenting Technical Talks,"
Chem. Eng. Ed., 22, 84 (1988)
2. Brewster, B.S., and W.C. Hecker, "A Course on Making
Oral Technical Presentations," Chem. Eng. Ed., 22, 48
3. Modi, A.K., and P.T. Bowman, "The ChEGSA Symposium:
A Continuing Tradition at Carnegie Mellon University,"
Chem. Eng. Ed., 23, 100 (1989)
4. The VPI&SU Graduate Assembly is a graduate student-
run governance organization for the entire graduate com-
munity. It is administered under the auspices of the Gradu-
ate School. 1

He said he guessed the entropy would have to equal
Unless the Second Law would bring it up a couple
But then it might be seven if the thermostat were good,
Or it might be almost zero if once rightly understood.


The professor read his paper with a corrugated brow,
For he knew he'd have to grade it, but he didn't know
quite how.
Till a sudden inspiration in his cerebellum smote,
And he seized his trusty fountain pen and this is what
he wrote:


"Just as you guessed the entropy, I'll have to guess your
But the Second Law won't raise it to the mark you
might have made;
For it might have been a hundred if your guess had
been quite good,
But I think it must be zero till you've rightly under-


Author Unknown
Edited and Submitted by
KennethR. Jolls
Iowa State University
Ames, IA 50011-2230

Fall 1990

----- --I I




Is It Really So Simple?

Villanova University
Villanova, PA 19085

In teaching an introductory, graduate-level
course in diffusional operations over the past several
years, I have been struck by the lack of a derivation
of the complete differential equation describing dis-
persion effects in beds and other multiple-phase sys-
tems. Most authors simply give a simplified equa-
tion applicable to some special case, with no deriva-
tion and with only a briefly-stated mention of the
equation following from a material balance on a
component in the fluid phase in question, or with a
statement referring to the comparable equation for a
single-phase fluid.
For example, Sherwood, Pigford, and Wilke [1]
CA Er r( CA )+Ea 2CA Ui CA ()
at r ar a r a z2 z
(The symbols are defined after Equation 3.)
As expected, this equation is correct for the
simplified case to which it applies, but unless care is
exercised, there is great danger of error when addi-
tional terms are added to include the effects of chemi-
cal reaction or a source (such as the introduction of a
tracer material). In addition, two standard forms of
the dispersion-model equation are commonly found
in the literature where the terms from one of these
equations are frequently used inconsistently in the
other standard form. Finally, there has been consid-
erable confusion in applying the solutions from mass-
and heat-transfer cases in unpacked conduits to
similar cases in packed beds.
For these reasons, in my classes I have found it
necessary to present a simple derivation of the ap-
plicable differential equation. The derivation will be
given in this paper, and then the two standard forms
of the differential equation will be stated, the rela-
tionship between them will be developed, and some
of the potential errors in writing the equations will
Copyright ChE Division, ASEE 1990

be discussed. Finally, an example of using a solution
of the comparable differential equation from heat
conduction to provide a solution to a dispersion prob-
lem in a packed bed will be presented to illustrate
the need for care in using such solutions.


Deriving the applicable differential equation
for describing the concentration of some component
A in fluid phase i as a function of location and time
for a packed or fluidized bed, in both phases for a
gas-sparged liquid, and for all phases in other simi-
lar systems, may be done simply by considering a
material balance on a differential volume of the sys-
tem using the well-known, shell-balance technique
[2] referring to an element of fluid phase i. In such a
treatment, each fluid phase may be considered sepa-
rately. The equation for fluid phase i is, in word
(Rate of A in by dispersion) + (Rate of A in by convection)
= (Rate of A out by dispersion) + (Rate of A out by convection)
+ (Rate of accumulation of A within the volume element)
(Rate of production of A within the volume element)
(Rate of mass transfer of A into fluid phase from another
phase within the volume element)
(Rate of introduction of A into fluid phase from a
source within the volume element) (2)

where each term has units of (moles of A)/(time).
The dispersion terms in Equation 2 represent
the combined effects of diffusion and dispersion due
to convective stirring caused by the relative flows of
fluid phase i and the packing or other phase or by

William J. Rice is a professor of chemical engineer-
ing at Villanova University, where he has been since
1957. He received his BS and MS from Worcester
Polytechnic Institute and his PhD from Princeton
University, all degrees being in chemical engineer-
ing. He teaches thermodynamics, separation proc-
esses, diffusional operations, and laboratory. His
published research has been on fluidized beds, solar
energy, and fluid mechanics.

Chemical Engineering Education

velocity gradients. For convenience, these combined
effects are accounted for mathematically using
a dispersion coefficient which relates a mass flux to
a concentration gradient in the same form in one
dimension as the well-known Fick's first law:
Flux = (D)x (concentration gradient). In this use,
the dispersion coefficients are used in place of the
diffusion coefficient, D, giving: Flux = (E)x (concen-
tration gradient). The dispersion coefficient, E, is
frequently different in different directions, whereas
diffusion coefficients are the same in all directions.
To simplify the remainder of the derivation, let
us assume that the system consists of a cylindrical
conduit with the concentration of component A in
fluid phase i symmetric about the z-axis and with
the net flow only in the axial direction. Then, for
very small r and z, the various terms in Equation
2 expressed for a chosen ring element of volume =
2irArAz are

-Er(2rEAz) aa
ar ir

Ea(27reAr)- z +(EUiCA) (27irAr)
n7az z

=-Er(2n{r+Ar}eAz)aCA -Ea(2TrEAr) CA
a riAr a z z+Az
+(EU CA) (2trAr)+ -(2eitrArAz)

-RA(2 ErArAz)-SA(2 ErArAz)-MA(2 rAr Az) (3)
S= local fraction of the total volume occupied by fluid
phase i, taken as a continuous function of space
and time (i.e., fluid phase i is treated as a con-
tinuum fluid with smoothly varying properties in
space and time).
CA = local concentration of A in fluid phase i
Ea, Er =local effective axial and radial dispersion coeffi-
cients, respectively
U. = actual local velocity in the z-direction of fluid phase
i (e.g., if fluid phase i is the fluid phase in a packed
bed, then U. is the local velocity in the z-direction
of fluid phase i in the interstices between the bed
RA = local net rate of production of A by chemical reac-
tion in fluid phase i per unit volume of that phase
SA = local rate of introduction of A into fluid phase i
from a point, line, or area source within fluid phase
i per unit volume of that phase
MA = local net rate of introduction of A into fluid phase i
from another phase or region outside fluid phase i
per unit volume of fluid phase i (e.g., this term al-
lows for mass transfer being considered from an-
other phase into fluid phase i)
r, z = radial and axial distances, respectively
t = time

Each term in Equation 3 also has the units of
(moles ofA)/(time). Equation 3 can now be simplified
by dividing all terms by 27xArAz to obtain
ErE(r+Ar) CA r ErEr EEr 'z
dar riAr r l r + a z IZ+Az
Ar Ar Az

Eaer aCAz z (eUiCA) z+Az-(EUiCA) z 0CA
Z r [(UC Er CA
Az Az at
+erRA + erSA + rMA = 0 (4)
where each term has the units of (moles of A)(length)/
[(volume of entire system)(time)].
Now, Ar and Az in Equation 4 are allowed to
approach zero as a limit, and Equation 4 becomes

SEr arCA]+ Ea E acA a(EUi CA)
ar ar az [ az J az
-er A+erRA+ErSA+rMA=0 (5)
where each term still has the units of (moles of
A)(length)/[(volume of entire system)(time)].
As additional simplifications, which are nearly
always made, Er, Ea, and e are considered constant
in space and time, and Ui is replaced by Ui, the
average axial velocity of fluid in fluid phase i. This
allows Equation 5 to be written for a fluid phase i of
constant density as
EE, a ~ CAEE, aCA -a CA aC,
r- r I +EEa E-- -eA
r ar ar az az at
+eRA +eSA +EMA =0 (6)

where each term now has the units of (moles of A)/
[(volume of entire system)(time)]. The above deriva-
tion is an independently derived extension of the
equation for an adsorption column given by Holland
and Liapis [3].
Clearly, an equivalent form of Equation 6 can
be obtained by dividing by e to obtain
E, a r CA,] +E a2A -_ 'CA AC,
[-r-j +Ea-2-U aCA-aCA-
r ar ar az 2 z at
+RA+SA+MA =0 (7)
where each term has the units of (moles of A)/[(vol-
ume of phase i)(time)].
Equations 6 and 7 represent two different forms
of the complete differential equation for the speci-
fied simplifying conditions. They are the basis for
the two standard forms of these equations found in
the literature. Various forms of these with certain
terms omitted are the usual starting differential

Fall 1990

equations (often presented with no derivation and
with confusion as to the meaning of some of the
symbols such as E., Er, andUi) which are used in
most books and journal articles attempting to de-
scribe the concentration changes in time and/or space
in a multiple-phase system such as a packed bed. A
clear understanding of the relationship between
Equations 6 and 7 and the meaning of the various
terms contained in them is crucial to using these
equations without error.


As has been shown, all terms in Equation 6
must be expressed in the units of (amount of A)/
[(volume of entire system)(time)], whereas all terms
in Equation 7 must be expressed in the units of
(amount of A)/[(volume of fluid phase i)(time)]. This
seems so simple that it should cause no difficulty.
However, when attempting to write the differential
equation without going through the derivation, the
units of each term are frequently not recognized as
far as the distinction between the volume of fluid
phase i alone and the entire volume of the system.
Thus, many text- and reference-book writers have
inadvertently given equations with inconsistent units
in the various terms.
Another source of difficulty is the definition of
E and E the effective dispersion coefficients in
the radial and axial directions, respectively. As
used here, E and E are consistent with DM/T in
the limit when Uigoes to zero and only molecular dif-
fusivity (DM) remains, and where T is the tortuosity.
Also, this gives E and Ea in the form of most of the
reported data on radial and axial diffusivities, such
as the excellent papers of Wilhelm and his coauthors
[4-7]. Some authors [8,9], however, define E as con-
sistent with EDM/T in the limit when Ui goes to zero.
Since the standard sources of experimental data use
the other definition of E, this definition greatly in-
creases the chance of making an error since there is
no clear warning that a different definition is being
used, and sometimes authors using this second defi-
nition misuse the experimental E correlations.


An attractive way of getting solutions to the
differential equations for dispersion is by using pre-
existing solutions to heat-transfer problems that have

the same differential equation and boundary values.
A case in point is the use of the solution sometimes
known as the Wilson [10] equation from heat trans-
fer (one form of which is given on page 218 of Carslaw
and Jaeger [11]), to the problem of radial dispersion
of a tracer added continuously at a point on the axis
of a cylindrical packed bed in which the fluid phase i
is flowing in the axial direction.
The applicable differential equation for heat
conduction in the radial direction only in an infinite,
cylindrical, isotropic solid is
F a2T 1 T] a r aT1 T -
r" r r t r Lr d ar (8)

where a = thermal diffusivity and T = temperature
increase from initial, uniform temperature of solid.
The solution to this equation for the case of an in-
stantaneous line source at the z-axis of strength Q is
given in Carlslaw and Jaeger. After simplification, it
T= Qexpt (9)
41cat [ 4atJ
In this equation, Q represents the amount of heat
per unit length of instantaneous line source divided
by c p, where p = density of solid and cp = heat
capacity of solid per unit mass. Thus, Q also repre-
sents the temperature increase to which this amount
of heat per unit length of the line source would
provide unit volume of the solid.
To apply this solution to a continuous point
source of some tracer at the axis of a conduit in
which a single-phase fluid is flowing in plug flow in
the z-direction is straightforward. The differential
equation for the case of axial dispersion considered
negligible may be written by reference to either
Equations 6 or 7, since e = 1, as

Er [ + d CA

Ui- a = 0

If z is replaced by Uit, effectively replacing the
instantaneous line heat source by a continuous point
matter source, then Equation 10 becomes

E [CA1 dCA
Dr 2 r dr

CA =0

This equation is seen to be analogous to Equation 8,
with Er replacing a and t = z/ Ui .
By analogy to Equation 9, the solution to Equa-
tion 11 for concentration of A as a function of radial
position and z (= Uit) in the absence of wall effect is

Chemical Engineering Education

CA -- exp -(12)
47Erz 4E_ (z-)
,L U) U,
In this case, Q'represents the moles of A supplied
per unit length of the equivalent instantaneous line
source. The experimentally measured quantity in
the tracer experiment is the rate of addition of tracer.
Thus, let us introduce the quantity N defined as
(moles of A from point source/time). Q'can now be
replaced by its equal, N/ U and Equation 12 be-

CA = Nexp r2 (13)
4nErz 4E z)

Equation 13 is for a single-phase system and
thus makes no allowance for the presence of a pack-
ing material; rather, it is the applicable equation for
dispersion from an axial, continuous, point source in
fluid phase i flowing in plug flow at velocity Ui in the
z (axial) direction
To find an equation similar to Equation 13 but
applicable to a packed bed, it is necessary to take the
differences between Equation 6 and Equation 7 into
proper account. Starting with Equation 6 as applied
to a packed bed with only radial dispersion and plug
flow of fluid phase i gives
Er a r [ (eCA) i .(ECA) 0 (14)
r ar ar ] az
r I [r C IU (15)
r ar L r J z
where C'A = eCA = moles of A/(total volume including
packing). This equation is mathematically analo-
gous to Equation 8, has the same boundary (initial)
conditions, and has the same spacial significance
since all terms in Equations 8 and 15 are per unit
volume of the entire system. Thus, a solution to
Equation 14 or 15 for the axial, continuous, point
tracer can be obtained by direct analogy to Equa-
tions 8 and 9. The result is

Q e r2
C'A -- exp -- = ECA (16)
4lEr e 4Er_ -
4 ui E Ui z

Q'/e r 2 N r2
CA Q -exp -- =-----exp --
4x^r 4Er z 4neErz 4Ez
Ui Ui Ui

since Q'still equals N/U,.
The significant difference between the solution
for the no packing case (Equation 13) and this solu-
tion for a packed bed (Equation 17) is the presence of
e in the denominator of the coefficient in the right
side of Equation 17. This result shows that in a
packed bed or similar system, the source term, N,
must be divided by E in the final solution of the
Wilson equation. Physically, this makes sense since
CA must be increased when part of the volume is
blocked by solid bed particles or the like.
This is only one example of the need for great
caution in taking over solutions from heat conduc-
tion or diffusion in open systems and applying them
to packed beds or similar multiphase systems.

A derivation of the complete differential equa-
tion for the dispersion model in a packed bed or
similar system shows the physical meaning and units
of each term in the two standard forms of the result-
ing equation. These two standard forms differ by a
factor of the void fraction in the bed so that terms
from one form may not be interchanged with terms
from the other form.
Two different definitions of E, the effective dis-
persion coefficient, in packed beds require care to
distinguish between them and avoid misuse. Simi-
larly, in using pre-existing solutions from heat con-
duction, source terms must be interpreted properly
when applying such solutions to packed beds.

1. Sherwood, T.K., R.L. Pigford, and C.R. Wilke, Mass Trans-
fer, McGraw-Hill Book Company, New York (1975)
2. Bird, R.B., W.E. Stewart, and E.N. Lightfoot, Transport
Phenomena, John Wiley & Sons, New York (1960)
3. Holland, C.D., and A.I. Liapis, Computer Methods for Solv-
ing Dynamic Separation Problems, McGraw-Hill Book
Company, New York (1983)
4. Bernard, R.A., and R.H. Wilhelm, Chem. Eng. Prog., 46,
5. Hanratty, T.J., G. Latinen, and R.H. Wilhelm, AIChE J.,
6. McHenry, Jr., K.J., and R.H. Wilhelm, AIChE J., 3, 83
7. Deisler, Jr., P.F., and R.H. Wilhelm, Ind. Eng. Chem., 45,
8. Rase, H.F., Chemical Reactor Design for Process Plants:
Vol. 1, Principles and Techniques, John Wiley and Sons,
New York (1977)
9. Smith, J.M., Chemical Engineering Kinetics, 2nd edition,
McGraw-Hill Book Company, New York (1970)
10. Wilson, H.A., Proc. Cambridge Phil. Soc., 12,406 (1904)
11. Carslaw, H.S., and J.C. Jaeger, Conduction of Heat in
Solids, Oxford University Press, London (1947) O

Fall 1990



A Parallel Between Teaching Chemical Engineering and

Developing Expert Systems

Royal Military College of Canada
Kingston, Ontario, Canada K7L 5LO

Since the coining of the phrase "artificial intel-
ligence" (AI), in 1955, to describe codes imitating
various aspects of the human intelligence, numer-
ous books, reviews, and research papers have been
published which deal with the socio-economic as-
pects of introducing such technology into the human
environment. According to John McCarthy [1] (in-
ventor of the AI phrase), too few people are working,
a quarter of a century later, in AI research and too
many on its applications. This imbalance in the pres-
ent effort is mainly due to the considerable market
developed during the last ten years for one of the
most visible and successful applications of Al, i.e.,
expert systems (ES) tools and services. The latest
Ovum report [2], for example, estimated that sales
of ES products and development services in the US
and Europe were over $400 million in 1988, with an
annual increase of approximately thirty percent.
While it is true that better tools originating
from computer science laboratories will make AI
products more closely mimic the best of human in-
telligence and will eventually render machines more
flexible in their learning process, the real debates
around widespread implementation of AI products
are still to come.
From a philosophical point of view, the advent
of AI is a true sign of an imminent grand inter-disci-
plinary marriage. According to Haugeland [3], AI
has little to do with computer technology and much
more to do with abstract principles of mental organi-

While it is true that better tools originating
from computer science laboratories will make AI
products more closely mimic the best of human
intelligence and will eventually render
machines more flexible...the real
debates are still to come.

Pierre R.Roberge is an associate professor of mate-
rials engineering at the Royal Military College of
Canada, where he has been teaching for the past
eight years. He received his BScCh, MChA, and PhD
degrees from the University of Sherbrooke. His re-
search interests have been in the field of applied
electrochemistry and, more recently, in applications
of artificial intelligence in engineering.

zation. From the same philosophical point of view,
the successful ES technology belongs to a micro-
world strategy that is really not made for exploring
the underlying principles of general intelligence and
common sense.

Two Information Processing Disciplines

For a specialist or a real expert, developing an
expert system prototype is a challenge in knowledge
engineering and information processing which is both
difficult to define and fascinating because of its
inter-disciplinary nature. On the other hand, the de-
velopment of professional competence in teaching
can be seen as an increased ability to play various
assigned roles more effectively, even if such a state-
ment may not seem obvious to someone starting a
teaching career.
Different roles require different teaching strate-
gies which can be based on defendable theories about
how people learn, grow, and develop. Some of these
theory-based models of teaching are more appropri-
ate to some objectives than to others. At the higher
education level, the most relevant models pertain to
the mastery of subject matter and deal mainly with
information processing goals, although not neces-
sarily excluding other social and personal develop-
ment goals.
The information processing models of teaching

Copyright ChE Divstion ASEE 1990
Chemical Engineering Education

In a general article on the influence ES technology will have on how chemical engineers do their
job in the future, Barnwell, et al., predicted that it could have a major impact and dramatically change
the role practising chemical engineers play in their respective industries. Major chemical processing
companies have already established groups to explore and exploit ES technology

focus mostly on the development of the information
processing capability of students and on the systems
that can improve their information processing capa-
bility [4]. In general terms, information processing
refers to the ways people handle stimuli from the
environment, organize data, sense problems, and
generate concepts and solutions to problems. Some
information processing models are concerned with
the ability of the learner to solve problems and with
the productive thinking process, while others are
more concerned with general intellectual ability and/
or strategies derived from research and development

A broad overview of the entire expert system
development and implementation process is war-
ranted in order to define the specific skills required
to develop expert systems. According to Harmon,

et al. [5], there are seven phases which can summa-
rize the effort of many people who have fielded com-
mercial expert system applications. This division
into seven phases would apply mainly to mid-size
or large efforts since the phases of a smaller effort
tend to blur together. These seven phases are
briefly described in Table 1 in relation to the various
skills required to perform the goals characteristic of
each phase.

The skill analysis presented in Table 1 indi-
cates that in order to develop expert systems, one
needs primarily to be proficient in the art or science
of information processing. Although not all teachers
and professors excel at information processing, by
the very nature of their profession all have to work
regularly at transferring information from notes, text-
books, and personal expertise to students avid for
useful knowledge.

Seven Phases of Expert System Development as a
Function of Their Goals and the Skills Required


Front End Analysis

Task Analysis


* Identify problem
* Evaluate cost/effectiveness
* Find management support

* Circumscribe task
* Set development schedule
* Identify knowledge required

Prototype Development Set information gathering strategy
(3) Develop proof of concept prototype

System Development

Field Testing



* Arrange overall structure
* Build knowledge system

* Test system with users
* Iterative validation

* Prototype system
* Train users

* Arrange means to update
* Update system

Skills Required*



x x

x x

x x

x x
X x


TOTAL 5 12 7 7

* M Skills required in management
IP Information processing
PR Public relations
C Computing


The branch of psychology that
studies human cognition is called
cognitive psychology. Cognitive in
this broad sense refers to the ac-
quisition, processing, and utiliza-
tion of knowledge [6]. While be-
havioural psychology provided the
initial research base for the devel-
opment of instructional technology,
the emergence of cognitive ap-
proaches to the analysis of behavi-
our has led to a new emphasis on
the nature, development, and rep-
resentation of knowledge.

A central design issue per-
taining to the instructional plan-
ning of learning experiences is how
much and what kinds of knowl-
edge transfer can be expected from
the specific content of textbooks,
lectures, or homework problems to
the tasks that students will be
expected to handle in subsequent
courses or in professional life [7].

Fall 1990

There are many possible changes that can take place
in students as a result of learning experiences, but
since the time and resources are fundamentally lim-
ited, only a few of the possibilities can be realized.
In an attempt to develop a taxonomy of educa-
tional objectives, a committee of college and univer-
sity examiners concluded that the most common
educational objective in American education is the
acquisition of knowledge or information [8]. Knowl-
edge or information may be justified as an important
objective or outcome of learning in many ways. Per-
haps the most common justification is that with
increase in knowledge or information there is a de-
velopment of one's acquaintance with reality. Such
reality may represent what is known by convention
or definition, what are known as the findings or
outcome of inquiry in the various fields, what are
known as the more fruitful ways of attacking prob-
lems in the field, or what are known as the more
useful ways of organizing a field [8]. This list of
goals, which was made to characterize the develop-
ment of knowledge by education, is almost identical
to the central tenet of most methodologies for build-
ing ES. In fact, the explication of knowledge domain
strategies and knowledge structure has to be accom-
plished much more meticulously if the knowledge is
to be transferred into an unforgivingly logical com-
puterized format.

The need to formalize and quantify knowledge
structures for AI products has created new trends in
knowledge representation that will transform not
only how things are perceived but also how engi-
neers think about them. These trends have also
started to be visible in recent literature dealing with
applications of AI in chemical engineering.
Qualitative reasoning, for example, is a well-
defined method for dealing with qualitative models.
Some of the proposed process engineering applica-
tions include fault simulation [9,10], generation and
testing of failure modes [11], and explanation of
process behaviour [12]. The shortcomings of qualita-
tive reasoning have stimulated researchers into look-
ing for a more quantitative approach to knowledge
representation such as the order-of-magnitude rea-
soning approach [13]. Reasoning with order-of-mag-
nitude approximate relations makes possible the
quantification of some engineering common sense
and offers a vocabulary for formalizing concepts and
handling diverse forms of knowledge.
A novel approach that exploits symbolic proc-

essing and knowledge representation to mimic the
adaptive distributed architecture in the human brain
was also recently applied to chemical engineering
problems. Artificial neural networks are claimed to
be particularly suitable for chemical process engi-
neering tasks requiring pattern recognition or con-
tinuous input-output control in process with uncer-
tain models or data [14].
Knowledge-based approaches for handling ex-
perimental knowledge as well as quantitative and
model-based knowledge have emerged as the most
appropriate approach for automated process diag-
nosis. But in order to overcome some of the draw-
backs associated with the use of KBES in this con-
text (such as poor efficiency and lack of generality),
the focus was put on creating architectures which
could explicitly recognize the structured nature of
problem-solving activities [15,16]. Integrating
compiled knowledge with deep-knowledge is a
methodology that is at the same time more efficient
at problem solving and also a more accurate repre-
sentation of the mental models of process operators
and engineers [17].
For design activities, KBES will also require
hybrid approaches combining the symbolic and
numerical domains. The inherent dualism present
in such coupled architectures is very much in corre-
spondence with reality. Various approaches have
been proposed to incorporate the different types of
knowledge and problem-solving strategies which are
applied during the design process [18,20]. When the
notions necessary to link the knowledge segments
are amalgamated into the database design, the spirit
of knowledge engineering is also infused into the
database. The resultant DBS!preserves not only the
data but also the knowledge of a certain domain. It
is then more ready to interact intelligently with a
process designer.
Several review papers on ES or KBS applica-
tions in process engineering have been published
during the past five years [21-24]. Most of these
publications outline the opportunities offered by the
evolving AI technology in terms of new conceptual
developments and new facilities provided by flexible
and friendly computing environments.
In a general article on the influence ES tech-
nology will have on how chemical engineers do their
job in the future, Barnwell, et al. [25], predicted that
it could have a major impact and drastically change
the role practising chemical engineers play in their
respective industries. Major chemical processing com-
Chemical Engineering Education

panies have already established groups to explore
and exploit ES technology. A survey [26] reporting
ES applications activities in the industrial sector
showed that most of the companies which had dem-
onstrated some interest in the technology had also
formed some kind of AI group or task force to foster
the successful development of ES within the operat-
ing units of the company. Most respondents of this
survey predicted that eventually ES technology would
become part of computing's mainstream, following a
similar pattern established during the recent im-
plementation of the database technology. It was also
felt that by reaching a mainstream status the tech-
nology would have a significant impact on the chemi-
cal engineering profession and could become a pri-
mary vehicle for technology and expertise transfer
and accumulation.
Universities have also begun to respond to the
new needs created by the introduction of ES technol-
ogy in industry by creating centers such as the Labo-
ratory for Intelligent Systems for Process Engineer-
ing (LISPE) established at MIT in 1986 [27]. The
original focus of LISPE was to move the use of com-
puting into the earlier stages of the chemical prod-
uct life cycles and expand it in real-time operations
as well as in all other aspects of process operations.
Courses in AI, once the sole domain of com-
puter science and research-oriented projects, are now
being made available in chemical engineering cur-
ricula as technical electives to graduate and under-
graduate students. The re-emergence of artificial
intelligence in the early part of the 80s was a suffi-
cient stimulus for the Computer Aids for Chemical
Engineering Committee (CACHE) to create a special
task force with the mission of addressing the role of
AI and its derivative environments in the education
of chemical engineers [28]. An initial objective of the
task force was to generate a compilation of current
AI research projects in chemical engineering. Fif-
teen papers representing the breadth of then-
current research and development in progress col-
lected by the task force committee were published as
a special issue of an international journal [29].
In the first of two articles on instructional com-
puting in the chemical engineering curriculum, Sei-
der [30] notes that although there is some evidence
of computer-oriented problems in courses other than
design and control, the level of utilization of comput-
ers lags far behind that in the design and control
courses. On the topic of expert systems, Seider con-
cluded his paper by stating that in spite of the flurry
of activity to develop logic-based systems principally
in the fields of design and control, there was, at the
Fall 1990

time (1988), no evidence of the use of expert systems
in chemical engineering coursework.
In a slightly more recent article, Douglas and
Kirkwood [31] described an approach to teaching the
conceptual design of chemical processes to under-
graduates which is based on a very structured ap-
proach to inventing petrochemical processes and
which would be used as the basis for a hybrid expert
system. In another article, Venkatasubramanian [32]
described the experiences at Columbia University a
few years ago in incorporating a graduate course,
specifically designed for chemical engineers, on the
applications of knowledge-based ES (KBES) meth-
odology in process engineering. One of the conclu-
sions of these experiences in teaching the inter-
disciplinary area of AI and process engineering was
that student understanding was significantly facili-
tated through teaching with the aid of examples
from chemical engineering and of exercises involv-
ing typical process engineering problems. Such a
treatment was felt to be missing from courses previ-
ously provided by the computer science department.
From domain experts and accumulated exper-
tise through a computing machine and back to train
and support domain experts, the development of ES
requires many of the skills common to those re-
quired to teach engineering courses. Trying to make
machines simulate the human thought process has
forced psychologists and programmers to sit together
and develop better models to explain some of the
human thinking process. Similarly, the development
of KBES for the transfer of expertise and deep knowl-
edge will require that professional communicators of
knowledge sit with programmers to draft out ade-
quate strategies and elaborate operational models.
The lessons learned today by organizing do-
main knowledge and optimizing the generality and
efficiency of its transfer into KBES will show the
way to new means of knowledge representation.
The results of such efforts will then surely benefit
educators who are themselves in the business of
transferring concepts and knowledge. The articula-
tion of some aspects of tacit knowledge as well as
the creation of adequate interfaces between qualita-
tive and quantitative reasoning are two specific ex-
amples of grey areas where progress could drasti-
cally change how chemical engineering courses are
taught in the future.
1. Owen, K., "Interview with John McCarthy," Expert Sys-
tems, 6, 278 (1989)

2. Expert Systems Markets and Suppliers, Ovum Ltd., (1989)
3. Haugeland, J., Artificial Intelligence: The Very Idea, MIT
Press, Cambridge, MA (1985)
4. Weil, M., and B. Joyce, Information Processing Models of
Teaching, Prentice-Hall, Englewood Cliffs, NJ (1978)
5. Harmon, P., R. Maus, and W. Morrissey, Expert Systems:
Tools and Applications, John Wiley & Sons, New York,
Chap. 10 (1988)
6. Mussen, P., et al., Psychology:An Introduction, D.C. Heath
and Company, Lexington, KY (1973)
7. Simon, H.A., in Problem Solving and Education, ed. D.T.
Tuma and F. Reif, Lawrence Erlbaum Assoc., Hillsdale,
NK, Chap. 6 (1980)
8. Bloom, B.S., M.D. Engelhart, E.J. Furst, W.H. Hill, and
D.R. Krathwohl, Taxonomy of Educational Objectives,
Longman, New York (1956)
9. Oyeleye, O.O., and M.A. Kramer, "Qualitative Simulation
of Process Plants," Proc. 10th IFAC World Cong. Autom.
Control, 6, 324 (1987)
10. Venkatasubramanian, V., and S.H. Rich, "Integrating
Heuristic and Deep-Level Knowledge in Expert Systems
for Process Fault Diagnosis," AAAI Workshop Artificial
Intell. Process Eng., Columbia University (1987)
11. Dvorak, D.L., "Expert Operations Systems," technical re-
port, Dept. of Computer Sci., University of Texas at Austin
12. Dalle Molle, D.T., T.F. Edgar, and B.J. Kuipers, "Qualita-
tive Modeling and Simulation of Dynamic Systems," Com-
put. Chem. Eng., 12, 853 (1988)
13. Mavrovouniotis, M.L., and G. Stephanopoulos, "Formal
Order-of-Magnitude Reasoning in Process Engineering,"
Comput. Chem. Eng., 12, 867 (1988)
14. Hoskins, J.C., and D.M. Himmelblau, "Artificial Neural
Network Models of Knowledge Representation in Chemi-
cal Engineering, Comput. Chem. Eng., 12, 881 (1988)
15. Finch, F.E., and M.A. Kramer, "Narrowing Diagnostic
Focus by Control Systems," AIChE 1987 Spring Meeting,
Houston (1987)
16. Ramesh, T.S., S.K. Shum, and J.F. Davis, "A Structural
Framework for Efficient Problem Solving in Diagnostic
Expert Systems," Comput. Chem. Eng., 12, 891 (1988)
17. Venkatasubramanian, V., and S.H. Rich, "An Opject-Ori-
ented Two-Tier Architecture for Integrating Compiled and
Deep-Level Knowledge for Process Diagnosis," Comput.
Chem. Eng., 12, 903 (1988)
18. Beltramini, L., and R.L. Motard, "KNOD-A Knowledge-
Based Approach for Process Design," Comput. Chem. Eng.,
12, 939 (1988)
19. Myers, D.R., J.F. Davis, and D.J. Herman, "A Task-Ori-
ented Approach to Knowledge-Based Systems for Process
Engineering Design," Comput. Chem. Eng., 12, 959 (1988)
20. Huang, Y.W., and L.T. Fan, "Designing an Object-Rela-
tion Hybrid Database for Chemical Process Engineering,"
Comput. Chem. Eng., 12, 973 (1988)
21. Banares-Alcantara, R., D. Sriram, V. Venkatasubrama-
nian, A. Westerberg, and M. Rychener, "Knowledge-Based
Expert Systems for CAD," Chem. Eng. Prog., 81, 25 (1985)
22. Stephanopoulos, G., "Expert Systems and Computing En-
vironments for Process Systems Engineering," CAST News-
letter, Spring (1986)
23. Lieberam, A., Chem.-Ing.-Tech., 58, 9 (1986)
24. Umeda, T., "Expert Systems in Process Engineering," Proc.
World Pet. Congr., 12, 103 (1987)
25. Barnwell, J., and B. Ertl, "Expert systems and the Chemi-
cal Engineer," Chem. Eng. (London), 41, September (1987)
26. San Giovanni, J.P., and H.C. Romans, "Expert Systems in

Industry: A Survey," Chem. Eng. Prog., 83, 52 (1987)
27. Stephanopoulos, G., "The Future of Expert Systems in
Chemical Engineering," Chem. Eng. Prog., 83, 44 (1987)
28. Davis, J.F., and G. Stephanopoulos, "CACHE Artificial
Intelligence in Process Engineering Task Force," CACHE
News, 29, 4 (1989)
29. "Artificial Intelligence in Chemical Engineering Research
and Development," Comput. Chem. Eng., 12, 9 (1988)
30. Seider, W.D., "Chemical Engineering and Instructional
Computing," Chem. Eng. Ed., 22, 134 (1988)
31. Douglas, J.M., and R.L. Kirkwood, "Design Education in
Chemical Engineering," Chem. Eng. Ed., 23, 120 (1989)
32. Venkatasubramanian, "A Course in Artificial Intelligence
in Process Engineering," Chem. Eng. Ed., 20 (1986) 0

Continued from page 207.
as liquid crystals, rubbers, biological systems, and
non-equilibrium thermodynamics, Professor Astar-
ita makes it easier for the student to appreciate the
relevance of thermodynamics to diverse systems that
he or she will encounter later as a researcher.

The author consistently adheres to a high stan-
dard of logical and mathematical rigor. A number of
intellectually challenging examples and problems
are included at the end of each chapter. Extensive
literature for further study is also provided. Even
small details, such as the usually interesting (but
not always obviously relevant) quotations at many
points in the text and the attractive typographical
layout of the book, help retain the attention of the

It is clear that the intention of this book is to
give a broad, somewhat philosophical treatment of
classical thermodynamics. Because of this, the book
is sometimes limited in the depth of coverage of
some of its many topics. I found the omission of
certain key concepts, such as Legendre transforms
or stability in general thermodynamic systems, to be
the most significant potential weakness of the book.
Also, no attempt is made to provide the student with
the computational skills required to handle complex
real-life problems. A minor complaint that I have is
that a different notation is used in each chapter; this
might lead to some confusion.

Overall, this book is a welcome addition to the
thermodynamics literature and is worthy of con-
sideration as a textbook for all or part of an ad-
vanced thermodynamics course. The last chapters of
the book might provide a useful starting point to
researchers interested in applications of classical
thermodynamic theory to polymers, electrochemical,
and electromagnetic systems. 0

Chemical Engineering Education







G. A. ATWOOD Digital Control, Mass Transfer, Multicomponent Adsorption
G. G. CHASE Multiphase Processes, Heat Transfer, Interfacial Phenomena
H. M. CHEUNG Colloids, Light Scattering Techniques
S. C. CHUANG Catalysis, Reaction Engineering, Combustion
J.R. ELLIOTT Thermodynamics, Material Properties
L. G. FOCHT Fixed Bed Adsorption, Process Design
K. L. FULLERTON Fuel Technology, Process Engineering, Environmental Engineering
M. A. GENCER2 Biochemical Engineering, Environmental Biotechnology
H. L. GREENE1 Oxidative Catalysis, Reactor Design, Mixing
H. C. KILLORY Hazardous Waste Treatment, Nonlinear Dynamics
S. LEE Fuel and Chemical Process Engineering, Reactive Polymers, Waste Clean-Up
D. MAHAJAN2 Homogeneous Catalysis, Reaction Kinetics
J. W. MILLER2 Polymerization Reaction Engineering
R. W. ROBERTS' Plastics Processing, Polymer Films, System Design
M. S. WILLIS Multiphase Transport Theory, Filtration, Interfacial Phenomena
'Professor Emeritus
Adjunct Faculty Member

Graduate assistant stipends for teaching and research start at $7,800.
Industrially sponsored fellowships available up to $17,000.
In addition to stipends, tuition and fees are waived.
Ph.D. students may get some incentive scholarships.
Cooperative Graduate Education Program is also available.
The deadline for assistantship applications is March 1st.
For Additional Information, Write *
Chairman, Graduate Committee
Department of Chemical Engineering
The University of Akron
Akron, OH 44325-3906

Fall 1990






The University of Alabama, located in the
sunny South, offers excellent programs lead-
ing to M.S. and Ph.D. degrees in Chemical
Our research emphasis areas are concentrated
in environmental studies, reaction kinetics
and catalysis, alternate fuels, and related
processes. The faculty has extensive indus-
trial experience, which gives a distinctive
engineering flavor to our programs.
For further information, contact the Director
of Graduate Studies, Department of Chemi-
cal Engineering, Box 870203, Tuscaloosa, AL
35487-0203; (205-348-6450).

g G. C. April, Ph.D. (Louisiana State)
D. W. Arnold, Ph.D. (Purdue)
W. C. Clements, Jr., Ph.D. (Vanderbilt)
R. A. Griffin, Ph.D. (Utah State)
W. I. Hatcher, Jr., Ph.D. (Louisiana State)
I. A. Jefcoat, Ph.D. (Clemson)
A. M. Lane, Ph.D. (Massachusetts)
M. D. McKinley, Ph.D. (Florida)
L. Y. Sadler III, Ph.D. (Alabama)
V. N. Schrodt, Ph.D. (Pennsylvania State)

Biomass Conversion, Modeling Transport Processes, Thermodynamics, Coal-Water Fuel Development,
Process Dynamics and Control, Microcomputer Hardware, Catalysis,
Chemical Reactor Design, Reaction Kinetics, Environmental,
Synfuels, Alternate Chemical Feedstocks, Mass Transfer,
Energy Conversion Processes, Ceramics, Rheology, Mineral Processing,
Separations, Computer Applications, and Bioprocessing.
An equal employment/equal educational
opportunity institution.

Chemical Engineering Education

4IL University of Alberta

Degrees: M.Sc., Ph.D. in Chemical Engineering

and in Process Control


K.T. CHUANG, Ph.D. (Alberta):
Mass Transfer, Catalysis, Separation Processes,
Pollution Control.
P.J. CRICKMORE, Ph.D. (Queen's):
Fractal Analysis, Cellular Automata, Utilization
of Oil Sand and Coal.
I.G. DALLA LANA, Ph.D. (Minnesota):
Chemical Reaction Engineering,
Heterogeneous Catalysis, Hydroprocessing.
D.G. FISHER, Ph.D. (Michigan):
Process Dynamics and Control, Real-Time
Computer Applications.
M.R. GRAY, Ph.D. (Caltech), CHAIRMAN:
Bioreactors, Chemical Kinetics,
Characterization of Complex Organic Mixtures.
R.E. HAYES, Ph.D. (Bath):
Numerical Analysis, Reactor Modelling,
Computational Fluid Dynamics.
D.T. LYNCH, Ph.D. (Alberta):
Catalysis, Kinetic Modelling, Numerical Methods,
Reactor Modelling and Design.
J.H. MASLIYAH, Ph.D. (British Columbia):
Transport Phenomena, Numerical Analysis,
Particle-Fluid Dynamics.
A.E. MATHER, Ph.D. (Michigan):
Phase Equilibria, Fluid Properties at High
Pressures, Thermodynamics.
W.K. NADER, Dr. Phil. (Vienna):
Heat Transfer, Transport Phenomena in
Porous Media, Applied Mathematics.
K. NANDAKUMAR, Ph.D. (Princeton):
Transport Phenomena, Multicomponent Distillation,
Computational Fluid Dynamics.

F.D. OTTO, Ph.D. (Michigan),
Mass Transfer, Gas-Liquid
Reactions, Separation Processes.
M. RAO, Ph.D. (Rutgers):
AI, Intelligent Control, Process Control.
D.B. ROBINSON, Ph.D. (Michigan),
Thermal and Volumetric Properties of
Fluids, Phase Equilibria, Thermodynamics.
J.T. RYAN, Ph.D. (Missouri):
Energy Economics and Supply,
Porous Media.
S.L. SHAH, Ph.D. (Alberta):
Computer Process Control, System Identification,
Adaptive Control.
S.E. WANKE, Ph.D. (California-Davis):
Heterogeneous Catalysis, Kinetics.
M.C. WILLIAMS, Ph.D. (Wisconsin):
Rheology, Polymer Characterization, Polymer
R.K. WOOD, Ph.D. (Northwestern):
Process Modelling and Dynamic Simulation,
Distillation Column Control,
Dynamics and Control of Grinding Circuits.

For further information contact:
Graduate Program Officer,
Department of Chemical Engineering,
University of Alberta,
Edmonton, Canada T6G 2G6


The Chemical Engineering Department at the University of Arizona is young and dynamic, with a fully accredited
undergraduate degree program and M.S. and Ph.D. graduate programs. Financial support is available through
fellowships, government grants and contracts, teaching and research assistantships, traineeships and industrial
grants. The faculty assures full opportunity to study in all major areas of chemical engineering. Graduate courses are
offered in most of the research areas listed below.


MILAN BIER, Professor, Director of Center for Separation Science*:
Ph.D., Fordham University, 1950
Protein Separation, Electrophoresis, Membrane Transport

Ph.D., University of Florida, 1985
Statistical Thermodynamics, Aqueous Two-Phase Extraction,
Protein Separation

WILLIAM P. COSART, Assoc. Professor, Assoc. Dean
Ph.D., Oregon State University, 1973
Heat transfer in Biological Systems, Blood Processing

EDWARD J. FREEH, Adjunct Research Professor
Ph.D., Ohio State University, 1958
Process Control, Computer Applications

JOSEPH F. GROSS, Professor
Ph.D., Purdue University, 1956
Boundary Layer Theory, Pharmacokinetics. Fluid Mechanics and
Mass Transfer in the Microcirculation, Biorheology

ROBERTO GUZMAN, Asst. Professor
Ph.D., North Carolina State University, 1988
Protein Separation, Affinity Methods

THOMAS W. PETERSON, Professor and Acting Head
Ph.D., California Institute of Technology, 1977
Atmospheric Modeling of Aerosol Pollutants, Particulate Growth
Kinetics, Combustion Aerosols, Microcontamination

Tucson has an excellent climate and many
recreational opportunities. It is a growing
modern city of 450,000 that retains much
of the old Southwestern atmosphere.

For further information, write to

Graduate Study Committee
Department of Chemical Engineering
University of Arizona
Tucson, Arizona 85721

The University of Arizona is an equal opportunity
educational institution/equal opportunity employer.
Women and minorities are encouraged
to apply.

Ph.D., Iowa State University, 1962
Simulation and Design of Crystallization Processes, Nucleation
Phenomena, Particulate Processes
THOMAS R. REHM, Professor
Ph.D., University of Washington, 1960
Mass Transfer, Process Instrumentation, Packed Column Distillation.
Computer Aided Design
Ph.D., University of California-Berkeley, 1972
Reaction Engineering, Kinetics, Catalysis, Coal Conversion, Advanced
Materials Processing

JOST 0. L. WENDT, Professor
Ph.D., Johns Hopkins University, 1968
Combustion Generated Air Pollution, Nitrogen and Sulfur Oxide Abate-
ment, Chemical Kinetics, Thermodynamics, Incineration, Waste

DON H. WHITE, Professor
Ph.D., Iowa State University, 1949
Polymers Fundamentals and Processes, Solar Energy, Microbial and
Enzymatic Processes

DAVID WOLF, Visiting Professor
D.Sc., Technion, 1962
Energy, Fermentation. Mixing

SCenter for Separation Science is staffed by four research professors, several technicians, and several
postdocs and graduate students. Other research involves 2-0 electrophoresis, cell culture, electro cell
fusion, and electro fluid dynamic modelling.

Chemical Engineering Education




I i

0lo S
&: 0


Chemical Engineering
Beckman, James R., Ph.D., U. of
Arizona. Crystallization and
Solar Cooling.
Bellamy, Lynn, Ph.D., Tulane.
Process Simulation.
Berman, Neil S.,Ph.D.,U. of
Texas, Austin. Fluid Dynamics
and Air Pollution.
Burrows, Veronica A., Ph.D.,
Princeton. Surface Science,
Semiconductor Processing.
Cale, Timothy S., Ph.D., U. of
Houston. Catalysis, Semiconduc-
tor Processing.
Garcia, Antonio A., Ph.D.,U.C.,
Berkeley. Acid-Base
Interactions, Biochemical
Separation, Colloid Chemistry.
Henry, Joseph D.,Jr., Ph.D.,
U. of Michigan. Biochemical,
Molecular Recognition, Surface
and Colloid Phenomena.
Kuester, James L., Ph.D., Texas
A&M. Thermochemical
Conversion, Complex Reaction

Raupp, Gregory B., Ph.D., U. of
Wisconsin. Semiconductor
Materials Processing, Surface
Science, Catalysis.
Rivera, Daniel, Ph.D., Cal Tech.
Process Control and Design.
Sater, Vernon E., Ph.D., Illinois
Institute of Tech. Heavy Metal
Removal from Waste Water,
Process Control.
Torrest, Robert S., Ph.D.,
U. of Minnesota. Multiphase
Flow, Filtration, Flow in Porous
Media, Pollution Control.
Zwlebel, Imre, Ph.D., Yale.
Adsorption of Macromolecules,
Biochemical Separations.

Dorson, William J., Ph.D., U. of
Cincinnati. Physicochemical
Phenomena, Transport Processes.
Guilbeau, Eric J., Ph.D.,
Louisiana Tech. Biosensors,
Physiological Systems,
Pizziconi, Vincent B., Ph.D.,
Arizona State. Artificial Organs,
Biomaterials, Bioseparations.
Sweeney, James D., Ph.D.,
Case-Western Reserve. Rehab
Engineering, Applied Neural
Towe, Bruce C, Ph.D.,Penn
State. Bioelectric Phenomena,
Biosensors, Biomedical Imaging.
Winters, Jack M., Ph.D., U.C.,
Berkeley. Biomechanics, Rehab
Engineering, Neuromuscular
Yamaguchi, Gary T., Ph.D.,
Stanford. Biomechanics,
Rehab Engineering, Computer-
Aided Surgery.

Materials Science&Engineering
Dey, Sandwip K.,Ph.D., NYSC of
Ceramics, Alfred U. Ceramics,
Sol-Gel Processing.
Hendrickson, Lester E., Ph.D.,
U. of Illinois. Fracture and
Failure Analysis, Physical and
Chemical Metallurgy.
Jacobson, Dean L., Ph.D.,UCLA.
Thermionic Energy Conversion,
High Temperature Materials.
Jindal, Bal K., Ph.D., Stanford.
Crystal Growth, Electronic
Krause, Stephen L., Ph.D., U. of
Michigan. Ordered Polymers,
Electronic Materials, Electron X-
ray Diffraction, Electron
Shin, Kwang S., Ph.D.,
Northwestern. Mechanical Prop-
erties, High Temperature
Stanley, James T., Ph.D., U. of
Illinois. Phase Transformations,

For more details regarding the graduate degree programs in the Department of Chemical, Bio, and Materials Engineering, please call (602)965-3313 or
(602)965-3676 or write to: Dr. Eric Guilbeau, Chair of the Graduate Committee, Department of Chemical, Bio and Materials Engineering, Arizona
State University, Tempe, Arizona 85287-6006.

University of Arkansas

Department of Chemical Engineering

Graduate Study and Research Leading to MS and PhD Degrees


Michael D. Ackerson (Ph.D., U. of Arkansas)
Biochemical Engineering, Thermodynamics
Robert E. Babcock (Ph.D., U. of Oklahoma)
Water Resources, Fluid Mechanics, Thermodynamics,
Enhanced Oil Recovery
Edgar C. Clausen (Ph.D., U. of Missouri-Rolla)
Biochemical Engineering, Process Kinetics
James L. Gaddy (Ph.D., U. of Tennessee)
Biochemical Engineering, Process Optimization
Jerry A. Havens (Ph.D., U. of Oklahoma)
Irreversible Thermodynamics, Fire and Explosion Hazards
Assessment, Dense Gas Dispersion
William A. Myers (M.S., U. of Arkansas)
Natural and Artifical Radioactivity, Nuclear Engineering
W. Roy Penney (Ph.D., Oklahoma State)
Process Engineering, Process Development
Thomas O. Spicer (Ph.D., U. of Arkansas)
Computer Simulation, Dense Gas Dispersion
Charles Springer (Ph.D., U. of Iowa)
Mass Transfer, Diffusional Processes
Charles M. Thatcher (Ph.D., U. of Michigan)
Mathematical Modeling, Computer Simulation
Jim L. Turpin (Ph.D., U. of Oklahoma)
Fluid Mechanics, Biomass Conversion, Process Design
Richard K. Ulrich (Ph.D., U. of Texas)
Microelectronics Materials and Processing
J. Reed Welker (Ph.D., U. of Oklahoma)
Risk Analysis, Fire and Explosion Behavior and Control

Graduate students are supported by fellowships and
research or teaching assistantships.


Graduate Program Advisor
Department of Chemical Engineering
3202 Bell Engineering Center
University of Arkansas
Fayetteville, AR 72701

The University of Arkansas at Fayetteville, the flagship
campus in the six-campus system, is situated in the heart
of the Ozark Mountains and offers students a unique
blend of urban and rural environments. Fayetteville is
literally surrounded by some of the most outstanding
outdoor recreation facilities in the nation, but it is also a
dynamic city and serves as the center of trade, government,
and finance for the region. The city and University offer a
wealth of cultural and intellectual events.

The Department of Chemical Engineering occupies more
than 40,000 sq. ft. in the new Bell Engineering Center, a
$30-million state-of-the-art facility, and an additional
20,000 sq. ft. of laboratories at the Engineering Research

Chemical Engineering Education



Graduate Studies

Auburn University



R. T. K. BAKER (University of Wales, 1966) Advanced Polymer Science
R. P. CHAMBERS (University of California, 1965) BomedicalBiochemical Engineering
C. W. CURTIS (Florida State University, 1976) Carbon Fibers and Composites
J. A. GUIN (University of Texas, 1970) Coal Conversion
A. KRISHNAGOPALAN (University of Maine, 1976) Computer-Aided AtmosProcess Control
Y. Y. LEE (Iowa State University, 1972) Electron Microscopy
G. MAPLES (Oklahoma State University, 1967) Environmental Engineering
R. D. NEUMAN (Institute of Paper Chemistry, 1973) Heterogeneous Catalysis
T. D. PLACEK (University of Kentucky, 1978)
C. W. ROOS (Washington University, 1951)
A. R. TARRER (Purdue University, 1973) THE PROGRAM
B. J. TATARCHUK (University of Wisconsin, 1981)
The Department is one of the fas
offers degrees at the M.S. and P
For Information andApplication, Write both experimental and theoretical
Dr. R. P. Chambers, Head with modern research equipme
Chemical Engineering studies. Generous financial as
Auburn University, AL 36849-5127 students.
Auburn University is an Equal Opportunity Educational Institution

Interfacial Phenomena
Process Design
Process Simulation
Pulp and Paper Engineering
Reaction Engineering
Surface Science
Transport Phenomena

test growing in the Southeast and
h.D. levels. Research emphasizes
il work in areas of national interest,
nt available for most all types of
distance is available to qualified

Fall 1990



Bradford, West Yorkshire, Great Britain

The Department of Chemical Engineering at the University of Bradford is
engaged in a wide range of research programmes which cross many scientific
and engineering disciplines. These offer opportunities for researchers to widen
their scientific background and to gain experience in new and expanding areas
of technology. Some of these areas are listed below:

Applied Organic Chemistry a Medical Engineering
Biochemical Engineering a Non-Newtonian Fluids
Catalysis a Polymer Processing
Computer-Aided Design a Powder Technology
Control Engineering a Solid-State Chemistry
Heat and Mass Transfer a Solvent Extraction

The department, which has 28 academic staff, has strong links with indus-
trial companies in the U.K. and other European countries. Many of the re-
search projects are sponsored by industry/government jointly, or by in-
dustry alone. The department also runs two post graduate taught courses
leading to M.Sc. (Control Engineering) and M.Sc. (Chemical Engineering).

SEnquiries should be addressed to *
Director of Postgraduate Studies
Department of Chemical Engineering
University of Bradford,
Richmond Road
Bradford, West Yorkshire BD7 1DP U.K.
Tel: 0274-733466 Ext. 380

Chemical Engineering Education

f I-s

^ ^



TE The Department offers graduate programs leading to the M.Sc. and Ph.D. degrees
ITHE in Chemical Engineering (full-time) and the M.Eng. degree in Chemical Engineer-
UNIVERSITY ing or Petroleum Reservoir Engineering (part-time) in the following areas:
SThermodynamics Phase Equilibria
FACULTY Heat Transfer and Cryogenics
R. A. Heidemann, Head, (Washington U.) Catalysis, Reaction Kinetics and Combustion
A. Badakhshan (Birmingham, U.K.) Multiphase Flow in Pipelines
L. A. Behie (Western Ontario) Fluid Bed Reaction Systems
J. D. M. Belgrave (Calgary) Environmental Engineering
F. Berruti (Waterloo)
F. Berruti (Waterloo) Petroleum Engineering and Reservoir Simulation
P. R. Bishnoi (Alberta)
R. M. Butler (Imperial College, U.K.) Enhanced OilRecovery
A. Chakma (UBC) In-Situ Recovery of Bitumen and Heavy Oils
M. A. Hastaoglu (SUNY) Natural Gas Processing and Gas Hydrates
A. A. Jeje (MIT) Computer Simulation of Separation Processes
N. Kalogerakis (Toronto) Computer Control and Optimization of Bio/Engineering
A. K. Mehrotra (Calgary) Processes
R. G. Moore (Alberta) Biotechnology and Biorheology
E. Rhodes (Manchester, U.K.)
P. M. Sigmund (Texas)
P. M. Signed (Txas) Fellowships and Research Assistantships are available
J. Stanislav (Prague)
W. Y. Svrcek (Alberta) to qualified applicants.

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 with the
Olympic Oval and the student residences in the foreground. The Engineering complex is on the left of the picture.

Chemical Engineering Education





... offers graduate programs leading to the
Master of Science and Doctor of Philosophy.
Both programs involve joint faculty-student
research as well as courses and seminars
within and outside the department. Students
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.




Fall 1990

University of California, Davis
Department of Chemical Engineering

BELL, Richard L.
University of Washington, Seattle Mass
transfer phenomena on non-ideal trays,
environmental transport, biochemical
University of Melbourne Chemical en-
gineering aspects of fermentation and
wine processing, fermentation kinetics,
computer simulation and control of enol-
ogical operations.
University of Minnesota Wetting hy-
drodynamics, fluid mechanics of thin
films, coating flows, Langmuir-Blodgett
Films, Sol-Gel processes.
University of Minnesota Biological ki-
netics and reactor design, kinetics of ion
exchange, environmental solute trans-
port, heat and mass transport at air-water
interface, hemodynamics and fluid ex-
KATZ, David F.
University of California, Berkeley Bio-
logical fluid mechanics, biorheology,
cell biology, image analysis.
McCOY, Benjamin J.
University of Minnesota Chemical re-
action engineering adsorption, cataly-
sis, multiphase reactors; separation proc-
esses chromatography, ion exchange,
supercritical fluid extraction.
University of Maryland, College Park -
Distillation control, control of multivari-
able, nonlinear processes, control of bio-
chemical processes, adaptive control,
parameter and state estimation.

Rensselaer Polytechnic Institute Proc-
ess control, process design and synthesis.
POWELL, Robert L.
The Johns Hopkins University Rheol-
ogy, fluid mechanics, properties of sus-
pensions and physiological fluids.
RYU, Dewey D.Y.
Massachusetts Institute of Technology -
Kinetics and reaction engineering of
biochemical and enzyme systems, opti-
mization of continuous bioreactor, bio-
conversion of biologically active com-
pounds, biochemical and genetic engi-
neering, and renewable resources devel-
Massachusetts Institute of Technology -
Transport rates and chemical kinetics for
catalytic reactors, studies by dynamic
and steady-state methods in slurry,
trickle-bed, single pellet, and fixed-bed
Massachusetts Institute of Technology -
Transport with chemical reaction, bio-
technology, rheology of heterogeneous
media, thin film technology, interfacial
phenomena, image analysis.
University of Delaware Drying porous
media, transport processes in heteroge-
neous reactors, multiphase transport
phenomena in heterogeneous systems.

Davis and Vicinity
The campus is a 20-minute drive from
Sacramento and just an hour away from
the San Francisco Bay Area. Outdoor
enthusiasts may enjoy water sports at
nearby Lake Berryessa, skiing and other
alpine activities in the Lake Tahoe Bowl
(2 hours away). These recreational op-

portunities combine with the friendly
informal spirit of the Davis campus and
town to make it a pleasant place in which
to live and study.
The city of Davis is adjacent to the
campus and within easy walking or cy-
cling distance. Both furnished and unfur-
nished one- and two-bedroom apart-
ments are available. Married student
housing, at reasonable cost, is located on-

Course Areas
Applied Kinetics & Reactor Design
Applied Mathematics
Biomedical/Biochemical Engineering
Environmental Transport
Fluid Mechanics
Heat Transfer
Mass Transfer
Process Design & Control
Process Dynamics
Separation Processes
Transport Phenomena in Multiphase

More Information
The Graduate Group in Biomedical
Engineering is now housed within the
Department of Chemical Engineering.
Further information and application ma-
terials for either program (Chemical En-
gineering or Biomedical Engineering)
and financial aid may be obtained by
Graduate Admissions
Department of Chemical Engineering
University of California, Davis
Davis, CA 95616

Chemical Engineering Education



D. T. Allen K. Nobe

Y. Cohen L. B. Robinson
(Prof. Emeritus)

T. H. K. Frederking
S. K. Friedlander
R. F. Hicks

S. N. Senkan
0. I. Smith

W. D. Van Vorst
E. L. Knuth (Prof. Emeritus)

V. Manousiouthakis
H. G. Monbouquette

UCLA's Chemical Engineering Department
offers a program of teaching and research linking
fundamental engineering science and industrial
needs. The department's national leadership is
demonstrated by the newly established Engineer-
ing Research Center for Hazardous Substance
Control. This center of advanced technology is
complemented by existing programs in Environ-
mental Transport Research and Biotechnology
Research and Education.

Fellowships are available for outstanding ap-
plicants. A fellowship includes a waiver of tuition
and fees plus a stipend.

Located five miles from the Pacific Coast,
UCLA's expansive 417-acre campus extends from
Bel Air to Westwood Village. Students have ac-
cess to the highly regarded science programs
and to a variety of experiences in theatre, music,
art, and sports on campus.

V. L. Vilker
A. R. Wazzan

Thermodynamics and Cryogenics
Process Design and Process Control
Polymer Processing and Rheology
Mass Transfer and Fluid Mechanics
Kinetics, Combustion, and Catalysis
Semiconductor Device Chemistry and Surface
Electrochemistry and Corrosion
Biochemical and Biomedical Engineering
Particle Technology
Environmental Engineering

Admissions Officer
Chemical Engineering Department
5531 Boelter Hall
Los Angeles, CA 90024-1592
(213) 825-9063

Fall 1990



L. GARY LEAL Ph.D. (Stanford) (Chairman) Fluid Mechanics; Transport Phenomena; Polymer Physics.
SANJOY BANERJEE Ph.D. (Waterloo) Two-Phase Flow, Chemical & Nuclear Safety, Computational Fluid Dynamics,
BRADLEY F. CHMELKA Ph.D. (U.C. Berkeley) Guest/Host Interactions in Molecular Sieves, Dispersal of Metals in
Oxide Catalysts, Molecular Structure and Dynamics in Polymeric Solids, Properties of Partially Ordered Materials,
Solid-State NMR Spectroscopy.
HENRI FENECH Ph.D. (M.I.T.) Nuclear Systems Design and Safety, Nuclear Fuel Cycles, Two-Phase Flow, Heat
GLENN H. FREDRICKSON Ph.D. (Stanford) Electronic Transport, Glasses, Polymers. Composites, Phase Separation.
OWEN T. HANNA Ph.D. (Purdue) Theoretical Methods, Chemical Reactor Analysis, Transport Phenomena.
JACOB ISRAELACHVILI Ph.D. (Cambridge) Surface and Interfacial Phenomena, Adhesion, Colloidal Systems,
Surface Forces.
FRED F. LANGE Ph.D. (Penn State) Powder Processing of Composite Ceramics; Liquid Precursors for Ceramics;
Superconducting Oxides.
GLENN E. LUCAS Ph.D. (M.I.T.) Radiation Damage, Mechanics of Materials.
DUNCAN A. MELLICHAMP Ph.D. (Purdue) Computer Control, Process Dynamics, Real-Time Computing.
JOHN E. MYERS Ph.D. (Michigan) (Professor Emeritus) Boiling Heat Transfer.
G. ROBERT ODETTE Ph.D. (M.I.T.) Radiation Effects in Solids, Energy Related Materials Development
DALE S. PEARSON Ph.D. (Northwestern) Rheological and Optical Properties of Polymer Liquids and Colloidal
PHILIP ALAN PINCUS Ph.D. (U.C. Berkeley) Theory of Surfactant Aggregates, Colloid Systems.
A. EDWARD PROFIO Ph.D. (M.I.T.) Biomedical Engineering, Reactor Physics, Radiation Transport Analysis.
ROBERT G. RINKER Ph.D. (Caltech) Chemical Reactor Design, Catalysis, Energy Conversion, Air Pollution.
ORVILLE C. SANDALL Ph.D. (U.C. Berkeley) Transport Phenomena, Separation Processes.
DALE E. SEBORG Ph.D. (Princeton) Process Control, Computer Control, Process Identification.
PAUL SMITH Ph.D. (State University of Groningen, Netherlands) High Performance Fibers; Processing of Conducting
Polymers; Polymer Processing.
T. G. THEOFANOUS Ph.D. (Minnesota) Nuclear and Chemical Plant Safety, Multiphase Flow, Thermalhydraulics.
W. HENRY WEINBERG Ph.D. (U.C. Berkeley) Surface Chemistry; Heterogeneous Catalysis; Electronic Materials
JOSEPH A. N. ZASADZINSKI Ph.D. (Minnesota) Surface and Interfacial Phenomen, Structure of Microemulsions.


The Department offers M.S. and
Ph.D. degree programs Financial
aid, including fellowships, teach-
ing assistantships, and research
assistantships, is available.


One of the world's few seashore
campuses, UCSB is located on the
Pacific Coast 100 miles south of
San Francisco. The student enroll-
ment is over 18,000. The metro-
politan Santa Barbara area has over
150,000 residents and is famous for
its mild, even climate.

For additional information
and applications,
write to

Professor Dale Pearson
Department of Chemical and
Nuclear Engineering
University of California
Santa Barbara, CA 93106

Chemical Engineering Education

at the


"At the Leading Edge"

Frances H. Arnold
James E. Bailey
John F Brady
Mark E. Davis
Richard C. Flagan
George R. Gavalas
Konstantinos P. Giapis
Julia A. Kornfield
Manfred Morari
C. Dwight Prater (Visiting)
John H. Seinfeld
Fred H. Shair
Nicholas W. Tschoegl (Emeritus)

Aerosol Science
Applied Mathematics
Atmospheric Chemistry and Physics
Biocatalysis and Bioreactor Engineering
Chemical Vapor Deposition
Colloid Physics
Computational Hydrodynamics
Fluid Mechanics
Materials Processing
Microelectronics Processing
Polymer Science
Process Control and Synthesis
Protein Engineering
Statistical Mechanics of Heterogeneous

* for further information, write *
Professor John F. Brady
Department of Chemical Engineering
California Institute of Technology
Pasadena, California 91125

Fall 1990

I. A m r yi
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Become a part of the best-balanced
equation in the profession -
chemical engineering at Case
Western Reserve University.
Work with top-ranked instructors
and researchers in one of the best
research environments in the U.S.

Opportunities in:
*Advanced sensors
*Intelligent control strategies
*Laser applications
*Micro- and nano-engineered materials
*Novel separation and processing concepts

For more information contact:
The Graduate Coordinator
Department of Chemical Engineering
Case Western Reserve University
Cleveland, Ohio 44106




Faculty and specializations:
ROBERT J. ADLER, Ph.D. 1959, Lehigh University -
Particle separations, mixing, acid gas recovery
JOHN C. ANGUS, Ph.D. 1960, University of Michigan
Redox equilibria, diamond and diamond-like
films, modulated electroplating
COLEMAN B. BROSILOW, Ph.D. 1962, Polytechnic
Institute of Brooklyn-Adaptive inferential
control, multi-variable control, coordination
ROBERT V. EDWARDS, Ph.D. 1968, Johns Hopkins
University-Laser anemometry, mathematical
modelling, data acquisition
DONALD L. FEKE, Ph.D. 1981, Princeton
University-Colloidal phenomena, ceramic
dispersions, fine-particle processing
NELSON C. GARDNER, Ph.D. 1966, Iowa State
University-High-gravity separations, sulfur
removal processes
UZIEL LANDAU, Ph.D. 1975, University of California
(Berkeley)-Electrochemical engineering, current
distributions, electrodeposition
CHUNG-CHIUN Liu, Ph.D. 1968, Case Western
Reserve University-Electrochemical sensors,
electrochemical synthesis, electrochemistry
related to electronic materials
J. ADIN MANN, JR., Ph.D. 1962, Iowa State
University-Interfacial structure and dymanics,
light scattering, Langmuir-Blodgett films,
stochastic processes
SYED QUTUBUDDIN, Ph.D. 1983, Carnegie-Mellon
University-Surfactant and polymer solutions,
metal extraction, enhanced oil recovery
ROBERT F. SAVINELL, Ph.D. 1977, University of
Pittsburgh-Electrochemical engineering, reactor
design and simulation, electrode processes

Th Opportunities for


O F in Chemical Engineering

CIN C I N N A T I M.S. andPhD Degrees
in Chemical Engineering

SFinancial Aid Available *

Location_ Faculty
The city of Cincinnati is the 23rd largest city in the United States, with a greater Amy Ciric Sun-Tak Hwang
metropolitan population of 1.7 million. The city offers numerous sites of architec- Joel Fried Robert Jenkins
tural and historical interest, as well as a full range of cultural attractions, such as Stevin Gehrke Yuen-Koh Kao
an outstanding art museum, botanical gardens, a world-famous zoo, theaters, sym- Rakesh Govind Soon-ai Khang
phony, and opera. The city is also home to the Cincinnati Bengals and the Cincin-
nati Reds. The business and industrial base of the city includes pharmaceutics, David Greenberg Glenn Lipscomb
chemicals, jet engines, autoworks, electronics, printing and publishing, insurance, Daniel Hershey Neville Pinto
investment banking and health care. A number of Fortune 500 companies are Sotiris Pratsinis
located in the city.

a Air Pollution
Modeling and design of gas cleaning devices and systems, source apportionment of air pollutants.

a Biotechnology (Bioseparations)
Novel bioseparation techniques, chromatography, affinity separations, biodegradation of toxic wastes, controlled drug
delivery, two-phase flow, suspension rheology.
a Chemical Reaction Engineering and Heterogeneous Catalysis
Modeling and design of chemical reactors, deactivation of catalysts, flow pattern and mixing in chemical equipment, laser
induced effects.
a Coal Research
New technology for coal combustion power plant, desulfuriza-
tion and denitritication.

a Material Synthesis
Manufacture of advanced ceramics, optical fibers and pigments
by aerosol processes.
a Membrane Separations
Membrane gas separations, continuous membrane reactor col-
umns, equilibrium shift, pervaporation, dynamic simulation of
membrane separators, membrane preparation and characteri-

a Polymers
Thermodynamics, thermal analysis and morphology of polymer blends, high-temperature polymers, hydrogels, polymer

a Process Synthesis
Computer-aided design, modeling and simulation of coal gasifiers, activated carbon columns, process unit operations, pre-
diction of reaction by-products.
For Admission Information *
Director, Graduate Studies
Department of Chemical Engineering, #171
University of Cincinnati
Cincinnati, Ohio 45221

Chemical Engineering Education

-. .I
I ,^




Graduate Study at

Clemson University

In Chemical Engineering

Coming Up for Air
No matter where you do your graduate work,
your nose will be in your books and your mind on
your research. But at Clemson University, there's
something for you when you can stretch out for a
SLike breathing good air. Or swimming, fishing,
sailing and water skiing in the clean lakes. Or hiking
in the nearby Blue Ridge Mountains. Or driving to
South Carolina's famous beaches for a weekend.
Something that can really relax you.
All this and a top-notch Chemical Engineering
Department, too.
With active research and teaching in polymer
processing, composite materials, process
automation, thermodynamics, catalysis, and
membrane applications what more do you

The University
Clemson, the land-grant university of South Carolina, offers 62 undergraduate and 61 graduate
fields of study in its nine academic colleges. Present on-campus enrollment is about 14,000 students,
one-third of whom are in the College of Engineering. There are about 2,600 graduate students. The
1,400-acre campus is located on the shores of Lake Hartwell in South Carolina's Piedmont, and is
midway between Charlotte, N.C., and Atlanta, Ga.
The Faculty
Charles H. Barron, Jr. James M. Haile Amod A. Ogale
John N. Beard, Jr. Douglas E. Hirt Richard W. Rice
Dan D. Edie Stephen S. Melsheimer Mark C. Thies
Charles H. Gooding Joseph C. Mullins

Programs lead to the M.S. and Ph.D. degrees.
Financial aid, including fellowships and assistantships, is available.
For Further Information
For further information and a descriptive brochure, write:

Graduate Coordinator
Department of Chemical Engineering
Earle Hall
Clemson University U -VHRSTrY
Clemson, South Carolina 29634-0909 College of Engineering


Alternate Energy Sources
Biotechnology and Bioengineering
Heterogeneous Catalysis
Coal Gasification and Combustion
Enhanced Oil Recovery
Fluid Dynamics and Fluidization

Interfacial and Surface Phenomena
Low Gravity Fluid Mechanics
Materials Processing
Mass Transfer
Membrane Transport and Separations
Numerical and Analytical Modeling

Process Control and Identification
Semiconductor Processing
Surface Chemistry and Surface Science
Thermodynamics and Cryogenics
Thin Film Science
Transport Processes

Graduate students in the Department of chemical Engineering may also participate in the popular, interdisciplinary
Biotechnology Training Program at the University of Colorado.


DAVID E. CLOUGH, Professor, Associate Dean WILLIAM B. KRANTZ, Professor
for Academic Affairs Ph.D., University of California, Berkeley, 1968
Ph.D., University of Colorado, 1975
RICHARD D. NOBLE, Research Professor
ROBERT H. DAVIS, Associate Professor Ph.D., University of California, Davis, 1976
Ph.D., Stanford University, 1983
W. FRED RAMIREZ, Professor and Chairman
JOHN L. FALCONER, Professor Ph.D. Tulane University, 1965
Ph.D., Stanford University, 1974
ROBERT L. SANI, Professor
ZOHREH FATHI, Assistant Res. Professor Director of Center for Low Gravity
Ph.D., University of Colorado, 1986 Ph.D., University of Minnesota, 1963
YURIS O. FUENTES, Assistant Professor KLAUS D. TIMMERHAUS, Professor
Ph.D., University of Wisconsin-Madison, 1990 Ph.D., University of Illinois, 1951

R. IGOR GAMOW, Associate Professor PAUL W. TODD, Professor Adjoint
Ph.D., University of Colorado, 1967 Ph.D. University of California, Berkeley, 1964

HOWARD J. M. HANLEY, Professor Adjoint RONALD E. WEST, Professor
Ph.D., University of London, 1963 Ph.D., University of Michigan, 1958

DHINAKAR S. KOMPALA, Assistant Professor
Ph.D., Purdue University, 1984
FOR INFORMATION AND APPLICATION, WRITE TO Director, Graduate Admissions Committee Department of Chemical Engineering
University of Colorado, Boulder Boulder, Colorado 80309-0424

Fall 1990





A. J. KIDNAY, Professor and Graduate Dean: D.Sc., Col-
orado School of Mines. Thermodvynamic properties
of gases and liquids, vapor-liquid equilibria, crvo-
genic engineering.
J. H. GARY, Professor Emeritus; Ph.D., Florida. Petroleum
refinery processing operations, heavv oil processing,
thermal cracking. visbreaking and solvent extraction.
V. F. YESAVAGE, Professor; Ph.D., Michigan. Vapor liquid
equilibrium and enthalpy of polar associating fluids,
equations of state for highly non-ideal systems, flow
E. D. SLOAN, JR., Professor: Ph.D. Clemson. Phase
equilibrium measurements of natural gas fluids and
hydrates. thermal conductivity of coal derived fluids,
adsorption equilibria, education methods research.
R. M. BALDWIN, Professor and Head; Ph.D.. Colorado
School of Mines. Mechanisms and kinetics of coal
liquefaction, catalysis. oil shale processing,
supercritical extraction.
M. S. SELIM, Professor: Ph.D., Iowa State. Heat and mass
transfer with a moving boundary, sedimentation and
diffusion of colloidal suspensions, heat effects in gas
absorption with chemical reaction, entrance region
flow and heat transfer, gas hydrate dissociation
A. L. BUNGE, Associate Professor: Ph.D., Berkeley.
Membrane transport and separations, mass transfer
in porous media, ion exchange and adsorption
chromatography. in place remediation of
contaminated soils, percutaneous absorption.
R. L. MILLER, Associate Professor; Ph.D., Colorado School
of Mines. Liquefaction co-processing of coal and
heavy oil, lowm severity coal liquefaction, oil shale
processing, particulate removal with venturi
scrubbers, supercritical extraction.
J. F. ELY, Adjunct Professor; Ph.D., Indiana. Molecular
thermodynamics and transport properties of fluids.

For Applications and Further Information
on M.S. and Ph.D. Programs, Write

Chemical Engineering and Petroleum Refining
Colorado School of Mines
Golden, CO 80401

Chemical Engineering Education

Graduate Study in Chemical Engineering
M.S. and Ph.D. Programs for Scientists and Engineers

Faculty and Research Areas
statistical thermodynamics, polymer science, polymer morphology
phase equilibria, separations composite materials and properties
structure and electrochemical engineering, polymer processing,
properties of polymers enrivonmental engineering rheology
expert systems, process dynamics, environmental engineering,
process control, energy technology biochemical engineering
flphase equilibriation separations composite materials and properties

ROBERT W. COUGHLIN biochemical engineering, polymer science
catalysis, biotechnology, environmental engineering
surface science
chemical reaction engineering,

We's gladly supply the Answers!

STH E Graduate Admissions
UNIVERSITY OF Dept. of Chemical Engineering
Box U-139
-CONNIECTICUT The University of Connecticut
Storrs, CT 06268
(203) 486-4019

Graduate Study in Chemical Engineering

at Cornell University

World-class research in ...
biochemical engineering
applied mathematics
computer simulation
environmental engineering
kinetics and catalysis
surface science
heat and mass transfer
polymer science and engineering
fluid dynamics
rheology and biorheology
process control
molecular thermodynamics
statistical mechanics
computer-aided design

A diverse A distinguished faculty
intellectual climate

Graduate students arrange indi-
vidual programs with a core of
chemical engineering courses
supplemented by work in other
outstanding Cornell depart-
ments, including chemistry,
biological sciences, physics,
computer science, food science,
materials science, mechanical
engineering, and business

A scenic location
Situated in the scenic Finger
Lakes region of upstate New
York, the Cornell campus is one
of the most beautiful in the

A stimulating university com-
munity offers excellent recrea-
tional and cultural opportunities
in an attractive environment

Brad Anton
Paulette Clancy
Peter A. Clark
Claude Cohen
T. Michael Duncan
James R, Engstrom
Robert K. Finn (Emeritus)
Keith E. Gubbins
Daniel A. Hammer
Peter Harriott
Donald L. Koch
Robert P. Merrill
William L. Olbricht
Athanassios Z. Panagiotopoulos
Ferdinand Rodriguez
George F. Scheele
Michael L. Shuler
Julian C. Smith (Emeritus)
Paul H. Steen
William B. Street
Raymond G. Thorpe (Emeritus)
Robert L. Von Berg (Emeritus)
Herbert F. Wiegandt (Emeritus)
John A. Zollweg

Graduate programs lead to the
degrees of master of engineering,
master of science, and doctor of
philosophy. Financial aid, including
attractive fellowships, is available.

For further information, write
Professor William L. Olbricht
Cornell University
Olin Hall of Chemical Engineering
Ithaca, NY 14853-520

Chemical Engineering Education

Chemical En ineerin at

The Faculty

Giovanni Astarita D ere
Mark A. Barteau
Antony N. Beris
Kenneth B. Bischoff
Douglas J. Buttrey
Costel D. Denson
Prasad S. Dhurjati
Henry C. Foley
Bruce C. Gates
Eric W. Kaler
Michael T. Klein
Abraham M. Lenhoff
Roy L. McCullough
Arthur B. Metzner
Jon H. Olson
Michael E. Paulaitis
T. W. Fraser Russell
Stanley I. Sandler
Jerold M. Schultz
Annette D. Shine
Norman J. Wagner
Andrew L. Zydney he University of Delaware offers M.ChE and Ph.D.

degrees in Chemical Engineering. Both degrees involve research and course work
in engineering and related sciences. The Delaware tradition is one of strong
interdisciplinary research on both fundamental and applied problems. Current
fields include Thermodynamics, Separation Processes, Polymer Science
and Engineering, Fluid Mechanics and Rheology, Transport Phenomena,
Materials Science and Metallurgy, Catalysis and Surface Science, Reaction
Kinetics, Reactor Engineering, Process Control, Semiconductor and Photo-
voltaic Processing, Biomedical Engineering and Biochemical Engineering.

New York


For more information and application materials, write:
Graduate Advisor
Department of Chemical Engineering
University of Delaware
Newark, Delaware 19716

The University of

Modern Applications of

Chemical Engineering

at the

University of Florida

Graduate Study Leading to the MS and PhD

TIM ANDERSON Semiconductor Processing, Thermodynamics
IOANNIS BITSANIS Molecular Modeling of Interfaces
SEYMOUR S. BLOCK Biotechnology
OSCAR D. CRISALLE Electronic Materials, Process Control
RAY W. FAHIEN Transport Phenomena, Reactor Design
ARTHUR L. FRICKE Polymers, Pulp & Paper Characterization
GAR HOFLUND Catalysis, Surface Science
LEW JOHNS Applied Design, Process Control, Energy Systems
DALE KIRMSE Computer Aided Design, Process Control
HONG H. LEE Semiconductor Processing, Reaction Engineering
GERASIMOS LYBERATOS Biochemical Engineering, Chemical Reaction Engineering
FRANK MAY Computer-Aided Learning
RANGA NARAYANAN Transport Phenomena, Semiconductor Processing
MARK E. ORAZEM Electrochemical Engineering, Semiconductor Processing
CHANG-WON PARK Fluid Mechanics, Polymer Processing
DINESH 0. SHAH Surface Sciences, Biomedical Engineering
SPYROS SVORONOS Process Control, Biochemical Engineering
GERALD WESTERMANN-CLARK Electrochemical Engineering, Bioseparations

For more information, please write:

Graduate Admissions Coordinator
Department of Chemical Engineering
University of Florida
Gainesville, Florida 32611
or call (904) 392-0881

Chemical Engineering Education


The Faculty and Their Research

ics, polymer
Sue Ann Bidstrup

ics. chemical
Charles A. Eckert


William R. Ernst

catalysis, sur-
face chemistry,
S reaction kinetics
Pradeep K. Agrawal

Mechanics of
aerosols, buoy-
ant plumes and
LarryJ. Forney

Heat transport
4 nfluidization
Charles W. Gorton


Pulp and paper

Jeffrey S. Hsieh

Paul A. Kohl

fc ... a Aerocolloidal
6 systems, inter-
A facial phe-
nomenea, fine-
S -, technology
Michael J. Matteson

W Biomechanics,
cell cultures
Robert M. Nerem

tion, latex
Gary W. Poehlein

Reactor engi-
neermnng, prc-
ess control,
Polymer sci- polymerization
ence and reactor
engineering dynamics
Robert J. Samuels F. Joseph Schork

mass transfer,
reactor design
Ronnie S. Roberts

Mass transfer,
mixing, non-
A. H. Peter Skelland

S crystallization
Ronald W. Rousseau

P Process design
'Jt and simulation
Jude T. Sommerfeld

microbial and
animal cell
-i cultures
Athanassios Sambanis

Process synthe-
sis and simula-
tion, chemical
waste manage-
ment, resource
D. William Tedder

B biochemical
cell-cell inter-
S dynamics
Timothy M. Wick

cal engineer-
ing, thermo-
dynamics, air

Jack Winnick

SBiofluid dynam-
ics, rheology,
Ajit P. Yoganathan

science and

design and

Polymer engi-
neering, energy

John D. Muzzy

namic and
transport prop-
erties, phase
gas extraction

Amyn S. Teja

Catalysis, ki-
netics, reactor

Mark G. White

Georgia Tec

What do graduate students say about

the University of Houston

Department of Chemical Engineering?
"Houston is a university on the move. The chemical engineering department is ranked
among the top ten schools, and you can work in the specialty o your choice: semiconductor
processing, biochemical engineering, the traditional areas. The choice of advisor is yours, too,
and you're given enough time to make the right decision. You can see your advisor almost any
time you want to because the student-to-teacher ratio is low.
Houston is the center of the petrochemical industry, which puts the 'real world' of
research within reach. And Houston is one of the few schools with a major research program
in superconductivity.
The UH campus is really nice, and city life is just 15 minutes away for concerts, plays.
nightclubs professional sports-everything. Galveston beach is just 40 minutes away.
"The faculty are dedicated and always friendly. People work hard here, but there is time
for intramural sports and Friday night get togethers"
If you'd like to be part of this team, let us hear from you.

"It's great!"

j Y dN OP\
( ) R- fl~

. i1
"' ^ "'I

6NL- k I

Biochemical Engineering Chemical Reaction Engineering
Superconducting, Ceramic and Applied Transport Phenomena
Electronic Materials Thermodynamics
Enhanced Oil Recovery

Neal Amundson
Vemuri Balakotaiah
Elmond Claridge
Abe Dukler

Demetre Economou
Ernest Henley
John Killough
Dan Luss

Richard Pollard
William Prengle
Raj Rajagopalan
Jim Richardson

For an application, write: Dept. of Chemical Engineering, University of Houston, 4800 Calhoun, Houston, TX 77004, or call collect 713/749-4407
The University is in conmpance with Title IX

Cynthia Stokes
Frank Tiller
Richard Willson
Frank Worley

-- --

---- -L -


U IC The University of Illinois at Chicago

Department of Chemical Engineering

MS and PhD Graduate Program *


Joachim Floess
Ph.D., Massachusetts Inst. of Tech., 1985
Assistant Professor

John H. Kiefer
Ph.D., Cornell University, 1961
Professor and Acting Head

G. Ali Mansoori
Ph.D., University of Oklahoma, 1969

Irving F. Miller
Ph.D., University of Michigan, 1960

Sohail Murad
Ph.D., Cornell University, 1979
Associate Professor

John Regalbuto
Ph.D., University of Notre Dame, 1986
Assistant Professor

Satish C. Saxena
Ph.D., Calcutta University, 1956

Stephen Szepe
Ph.D., Illinois Institute of Technology, 1966
Associate Professor

Raffi M. Turian
Ph.D., University of Wisconsin, 1964

David Willcox
Ph.D., Northwestern University, 1985
Assistant Professor


Transport Phenomena: Slurry transport, multiphase fluid flow
and heat transfer, fixed and fluidized bed combustion, indirect
coal liquefaction, porous media, membrane transport, pulmonary
deposition and clearance, biorheology.
Thermodynamics: Transport properties of fluids, statistical
mechanics of liquid mixtures, supercritical fluid extraction/
retrograde condensation, asphaltene characterization,
Kinetics and Reaction Engineering: Gas-solid reaction kinetics,
diffusion and adsorption phenomena, energy transfer processes,
laser diagnostics, combustion chemistry, environmental
Heterogeneous Catalysis: Surface chemistry, catalyst preparation
and characterization, structure sensitivity, supported metals, clay
chemistry, artificial intelligence applications, modeling and

For more information, write to
Director of Graduate Studies Department of Chemical Engineering
University of Illinois at Chicago Box 4348 Chicago, IL 60680 (312) 996-3424

Fall 1990

Chemical Engineering at the

University of Illinois

at Urbana-Champaign





The combination of distinguished faculty, out-
standing facilities and a diversity of research
interests results in exceptional opportunities for
graduate education.

The chemical engineering department offers
graduate programs leading to the M.S. and Ph.D.

Richard C. Alkire
Thomas J. Hanratty
Jonathan J. L. Higdon
Douglas A. Lauffenburger
Richard I. Masel
Anthony J. McHugh
William R. Schowalter
Edmund G. Seebauer
Mark A. Stadtherr
Frank B. van Swol
K. Dane Wittrup
Charles F. Zukoski IV

Electrochemical and Plasma Processing
Fluid Dynamics, Convective Heat and Mass Transfer
Fluid Mechanics, Applied Mathematics
Cellular Bioengineering
Surface Science Studies of Catalysts and Semiconductor Growt]
Polymer Engineering and Science
Mechanics of Colloids and Rheologically Complex Fluids
Laser Studies of Semiconductor Growth
Process Flowsheeting and Optimization
Wetting and Capillary Condensation
Biochemical Engineering, Molecular Biology
Colloid and Interfacial Science

For information and application forms write:

Department of Chemical Engineering
University of Illinois at Urbana-Champaign
Box C-3 Roger Adams Lab
1209 West California Street
Urbana, Illinois 61801


Illinois Institute of Technology


* Private, coeducational and research university
* 3000 undergraduate students
* 2400 graduate students
* 3 miles from downtown Chicago and 1 mile west of
Lake Michigan
* Campus recognized as an architectural landmark


* One of the largest cities in the world
* National and international center of business and
* Enormous variety of cultural resources
* Excellent recreational facilities
* Industrial collaboration and job opportunities


* One of the oldest in the nation
* Approximately 60 full-time and 40 part-time
graduate students
* M.Ch.E., M.S., and Ph.D. degrees
* Financially attractive fellowships and assistant-
ships available to outstanding students


Multiphase flow and fluidization, flow in porous media,
gas technology

Transport processes in chemical and biological
systems, rheology of polymeric and biological fluids

* ALl CINAR (Ph.D., Texas A & M)
Chemical process control, distributed parameter
systems, expert systems

Hydrodynamics of fluidization, multiphase flow,
separations processes

Energy policy, planning, and forecasting

Biochemical engineering, chemical reaction engineering

* J. ROBERT SELMAN (Ph.D., California-Berkeley)
Electrochemical engineering and electrochemical
energy storage

Combustion, high-temperature chemical reaction

* DAVID C. VENERUS (Ph.D., Pennsylvania State U)
Polymer rheology and processing, and transport

* DARSH T. WASAN (Ph.D., California-Berkeley)
Interfacial phenomena, separation processes,
enhanced oil recovery

Dr. J. R. Selman
Chairman, Graduate Admissions Committee
Department of Chemical Engineering
Illinois Institute of Technology
I. .T. Center
SChicago, IL 60616

Fall 1990

Puzzled About Your Career?

One Move Could

Make a Difference.

Institute of Paper Science and TecFnologyis an independent, fully accredited
graduate school offering an interdisciplinary degree program designed for B.S. chemical
engineering graduates. The Institute has an excellent record of preparing graduates for
challenging and highly rewarding careers in the paper industry. The Institute is located
next to the Georgia Institute of Technology and shares many educational resources with
Georgia Tech.

Students eligible to accept employment in the U.S. or Canada are generally awarded full
tuition scholarships, as well as stipends of $15,000 to $17,000 per calendar year.

Graduates select thesis research projects from a variety of topics, including:

* Process Engineering
* Simulation and Control
* Heat and Mass Transfer
* Separation Science
* Reaction Engineering
* Fluid Mechanics
* Materials Science
* Surface and Colloid Science
* Combustion Technology
* Chemical Kinetics

For further information,
please contact:
Director of Admissions
Institute of Paper Science
and Technology
575 14th St., N.W.
Atlanta, GA 30318
(404) 853-9500
FAX: (404) 853-9510
Toll Free Number: 1-800-558-6611



William H. Abraham
Thermodynamics, heat and mass transport, process modeling
George Burnet
Coal technology, separation processes, high temperature ceramics
John M. Eggebrecht
Statistical thermodynamics of fluids and fluid surfaces
Charles E. Glatz
Biochemical engineering, processing of biological materials
Kurt R. Hebert
Applied electrochemistry, corrosion
James C. Hill
Fluid mechanics, turbulent, convective transport phenomena, aerosols
Kenneth R. Jolls
Thermodynamics, simulation, computer graphics
Terry S. King
Catalysis, surface science, catalyst applications
Maurice A. Larson
Crystallization, process dynamics
Peter J. Reilly
Biochemical engineering, enzyme technology, carbohydrate
Derrick K. Rollins
Gross error detection for chemical processes, minimum variance
process control
Glenn L. Schrader
Catalysis, kinetics, solid state electronics processing, sensors
Richard C. Seagrave
Biological transport phenomena, biothermodynamics,
reactor analysis
Dean L. Ulrichson
Process modeling, simulation
Thomas D. Wheelock
Chemical reactor design, coal technology, fluidization
Gordon R. Youngquist
Crystallization, chemical reactor design, polymerization

For additional information, please write
Graduate Office
Department of Chemical Engineering
Iowa State University
Ames, Iowa 50011

p^-?^^ --

"2' "Z ,... -- -'. -

- '---- -ti- -..

t Tz



Chair; U. of Kentucky,
1979, Global Change/

UCSB, 1981
Reaction Engineering/
Catalyst Design

U. of Houston, 1989
Animal Cell Culture

U. of Cambridge, 1959
Particle Morphological

MIT, 1986,
Biocatalysis and

U. of Wisconsin, 1984
Membrane Science/
Catalysis and Cluster

U. of Iowa, 1989
Chemical Precipita-
tion Processes

U. of Iowa, 1980
Fine Particle Science

Washington U., 1989
Transport Phenomena
in Bioseparations

For information and application write to:
Chemical and Biochemical Engineering
The University of Iowa
Iowa City, Iowa 52242


Graduate Study and Research in


Ph.D., University of Texas, Austin
Membrane Science
Sorption and Diffusion in Polymers
Polymeric Thin Films
Ph.D., University of Delaware
Biochemical Kinetics
Insect Cell Culture
Recombinant DNA Technology
Ph.D., University of California, Berkeley
Equations of State
Statistical Thermodynamics
Phase Equilibria
Ph.D., University of Chicago
Flame Generation of Ceramic Powders
Ph.D., North Carolina State University
Process Simulation
Biochemical Engineering
Separations Processes


Ph.D., University of Delaware
High-Pressure Thermodynamics
Polymer Solution Thermodynamics
Supercritical Solvent Extraction
Ph.D., University of California, Berkeley
Electrochemical Engineering
Ph.D., Massachusetts Institute of Technology
Transport in Biological Systems
Polymeric Controlled Release
Cell-Surface Interactions
Dr. Engr., The Johns Hopkins University
Non-Newtonian Fluid Dynamics
Physical Acoustics and Fluids
Ph.D., The City University of New York
Interfacial Phenomena
Electropermeability of Biological Membranes
Surface Effects at Fluid-Droplet Interfaces

For further information contact:
The Johns Hopkins University
G.W.C. Whiting School of Engineering
Department of Chemical Engineering
34th and Charles Streets
Baltimore, MD 21218




* M.S. degree with a thesis requirement in both
chemical and petroleum engineering
* M.S. degree with a major in petroleum man-
agement offered jointly with the School of
* Ph.D. degree with emphasis in either chemi-
cal or petroleum engineering, characterized by
moderate and flexible course requirements
and a strong research emphasis
* Typical completion times are 16-18 months
for a M.S. degree and 4 1/2 years for a Ph.D.
degree (from B.S.).

Catalytic Kinetics and Reaction Engineering
Chemical Vapor Deposition Kinetics and
Reactor Modeling
Controlled Drug Delivery
Enhanced Oil Recovery Processes
Fluid Phase Equilibria and Process Design
Nucleate Boiling
Numerical Modeling of Pore Structure
Plasma Modeling and Plasma Reactor Design
Process Control
Supercomputer Applications
Supercritical Fluid Applications

Financial aid is available in the form of fellow-
ships and research and teaching assistantships
($13,000 to $15,000 a year).

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 members. KU offers more
than 100 bachelors', nearly ninety masters',
and more than fifty doctoral programs. The main
campus is in Lawrence, Kansas, with other
campuses in Kansas City, Wichita, Topeka, and
Overland Park, Kansas.

Kenneth A. Bishop (Ph.D., Oklahoma)
John C. Davis (Ph.D., Wyoming)
Don W. Green (Ph.D., Oklahoma)
Colin S. Howat (Ph.D., Kansas)
Carl E. Locke, Jr., Dean (Ph.D., Texas)
James 0. Maloney, Emeritus (Ph.D., Penn State)
Russell B. Mesler (Ph.D., Michigan)
Floyd W. Preston (Ph.D., Penn State)
Harold F. Rosson, Associate Dean (Ph.D., Rice)
Marylee Z. Southard (Ph.D., Kansas)
Bala Subramaniam (Ph.D., Notre Dame)
George W. Swift (Ph.D., Kansas)
Brian E. Thompson (Ph.D., MIT)
Shapour Vossoughi (Ph.D., Alberta, Canada)
Stanley M. Walas, Emeritus (Ph.D., Michigan)
G. Paul Willhite, Chairman (Ph.D., Northwestern)

Excellent facilities are available for research
and instruction. Extensive equipment and shop
facilities are available for research in such
areas as enhanced oil recovery processes, fluid
phase equilibria, nucleate boiling, catalytic
kinetics, plasma processing, and supercritical
fluid applications. The VAX 9000, along with a
network of Macintosh personal computers and
IBM, Apollo, and Sun workstations, support
computational and graphical needs.

For more information and application
material, write or call
The University of Kansas
The Graduate Adviser
Department of Chemical and Petroleum
4006 Learned Hall
Lawrence, KS 66045-2223
(913) 864-4965


WHEREAS, Mark E. Davis has won
what is perhaps the Federal government's
most prestigious scientific award, the
$500,000, 3-year research National
Science Foundation Alan T. Waterman
prize. WHEREAS, Dr. Davis is the first
engineer ever to receive this award, and
WHEREAS, he earned his bachelor's,
master's and doctoral degrees from the
Department of Chemical Engineering,
University of Kentucky.
We, the undersigned faculty, staff and
students salute, congratulate and thank
Dr. Davis for underscoring the Depart-
ment of Chemical Engineering's ongoing
commitment to educational excellence.
The University of Kentucky-
A Tradition of Value.

A 14 Al


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Me~6 \jl,71
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i i / iv
^~ve \'\'L9~N
^yCy S^, ^1^-^
^^^W ^^~ue~ P~

Zr~-Z/ S~~^Lif'yl\

Dr. Davis holds 3 degrees in Chemical Engineering from UK.
He has been recognized for his work in synthesizing "molecular
sieves" with 12 angstrom pores.

Department of Chemical Engineering
A Tradition of Value
For detailed information, contact: Dept. of Chemical Engineering,
University of Kentucky, Lexington, KY 40506-0046 1-800-63UKCHE

M.S. and Ph.D. programs
*Chemical Engineering
*Interdisciplinary Areas of Systems Engineering
*Food Science
*Environmental Engineering

Financial Aid Available
Up to $15,000 Per Year

For More Information Write to
Professor B.G. Kyle
Durland Hall
Kansas State University
Manhattan, KS 66506

Areas of Study and Research
Transport Phenomena
Energy Engineering
Coal and Biomass Conversion
Thermodynamics and Phase Equilibrium
Biochemical Engineering
Process Dynamics and Control
Chemical Reaction Engineering
Materials Science
Catalysis and Fuel Synthesis
Process System Engineering
and Artificial Intelligence
Environmental Pollution Control
Fluidization and Solid Mixing
Hazardous Waste Treatment





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    PAGE 27

    I n Memoriam. LEE C. EAGLETON 1,,.c.~tond>NlbtupUyonM~l 5 :,.~~ !:;';;;-::;;!~ :~.;"i'f:" ;:, r;:,;:,: ~~:,.:t~:3: ;~:~::: C&lffomio t<> a novol in ~o-. J,,.,. u,,..ived byhiowifeof1h,,ty-oeven ~~~ff:iL~: i !:; oneUniver ,ityofP.,.noyh,.nia,and fifleonyeartootl>eforully t.i.:=/;;~i!:i:rs~ ........ ,11...ii.i...,~ ..,..,, h...,_i,ityduri"tfl"-.,,,.lntho-.!po,t hiol,~hiporoogh1gro,,,1hondn:.-rognitionto t.ho.,.,..,,;ntheh u man tlo,,alai,,hiptri :7~;;-:.:1~::,:;.:;;: ;::,,.~;~;;::.:;.hioultimo1hU< v oco1H)Ohomofh;,H,.,nddeli ... tedo n d.,imu l_,edhyhiopruo.,, a !if,t;,no_

    PAGE 28

    M c/8ssroom APPLIED MATHEMATICS Opportunities for Chemical Engineers no ................ u .. ,,,,. ""'"'"'i.r ... .. ;,.,. .-,.,,,.,.,,,,,.1,v,_, ......... ,. ,. ...... -,., <1i-:,:~ r;,. . ..i r,,,o ....... ... ; ON _,..n. ........................ ,..1c1 ~;;t~~\;i:~ ...................... oNn . ........... ....... ..... _,.,.11,,-..., .. .. ........ ,,. .. -,. -t,, ::~:~:::.::i:,;.;;:~.=~"i:';~:'.:.:.::~.:-;:; ;nto,pn!tolion.rouldomh...,.he,,.,..,. ,. ... u vw-...,h,mi {o,oth,,,.y,..,,.,.nwhoroedin,;ontinuumonaly,,io.Con,men toryoot;gu,.lol .. p,._lalhopp,:,nuntyto hrieflyi ndu.,.rl"o<; n,1,,,.,,.!l',..,.,....or ........ . who<""'-lhy,en,,,.,..,_, t"igu,.JdepiMtotUw .. .. - .. ,,,-... ,-,<1....,.;onmot,,iolh,~,io,-n-l,.peri""'n ~~:!."'or::7.:." .. t~~17i and-k.,..11-31,in ?iu,ofhr.nd"""""'" ;.,..;".:;.';:,,~;::=~.~~:::~id:~:;:.,";'~

    PAGE 29

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    PAGE 31

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    PAGE 32

    l.lf.J~l,01up .. rall,O"'f"'-'-""""'"koowl. """"'cllo .. .,. 1 ..., ...... -~:"'-A.-1rn1< ............. 1opm,,,..or,i..;,., ..... .,""""'"ll"-,..r......i1.o.._, 1 ,.,,.,.,_..,.'" .,,,.... .... ,_.,,..,..~r-d-ofnonl,-,.n,.I 4,_.., __ ,,,..........,_ __ _,....laot_l!nol\y.U.0-"""'-obU 1,n._.,I .. -.,, .....i 10 ... .., h,-, dlre,.ntooltqoo<,.,....Tho"'""'"'"ble-ol.w,,.todn ,1 ._,,..,., nonli..,a,porta l dlfe,.n1oo l jttlto-inil l-.do1-qt,.O 'l.''lThotn,.._ -;,. .. ,11.ii....i ... -,.0 .... .. .,,,.., .......... ....... _,. ___ portl.Cti--._d_...,....i.-,,1/e-,._ "'""'ld,IJe""''"l""l.,.. ..., ... ..lle,r,oloo.Th<1111,-ool....i lo.-NI,,..,. ~:..:::;::o~"l<,.m~""lLa,,,o,i ~[::.-olhofl,nt1 .... ~;tho ..... ,.1 ,....,:.1:~":".::..--=:::-:.":: 1 ._ ......... 1,,,,,,,...-., .. _..,. __ c,,.,,,.,.,.,.."""1 ..... ,.,.,..,.,.. 1, 11-u .. i,,.,,,11;,. l l t.on,_..,ndho"""lin1mm< ob, ..... 11.-,,equ,,..,11.o, ...... .,..,...,,.,,, ... ,..,., 1;,__._ l. OM R ..,ll__,,,,.h.,,,..10,:011 u ......,,hat l. ia-noOMof ..... typo.........d ..,,1..,...,,i,....,,.__...,,.,..-. ...... ..,,h ;: 1 ,i.-o/q,and-lMlt:q.Ol>-;,npl_ ,,,...,.,-..1-o1 1 ... ,11....-..,c1o,...1 ... .,..,....__,., ... ..... _""" ..... __ ... 111rwno-1w, ... _..i-.r 1. 1.obo """"'ncit"' ot,;, ""' t.o ....,1,,_, 1:q n, i.. ,01o,n..,lloth<,~1hei""''"''l"'""I""""' ......_.ko.,the.,;,i.,nvolu,,o( L owhhO<'O"ndoo u<.IH..,IJbe~ot1lland011l>ifu<,.11 ----------lno,,pl------"h ,s;....,_,1,_,..,...,...,and1M"11h17of ..... r.,_.'11,...hocl, .. d,ar!J,not",aiJlhl-nl On thoootl\erhand.ho ..... method,<;.n11<..,..1.0a d,n"""")
    PAGE 33

    Dllwc1Morhod s to,Nan!!nHrE>'Oi<,t/on Th;-/alGl<>mo"1 h a pp0a,.1h.otexoctlyoolvat,k,..,.line.o,oyo """"",.""'""blow ... minslyd,IT....,.,approae""" OnoouttP" ..... bJlho a ulhot"hilo ot theUniv,,.lly.CM,n-.. .. thoGrorpT.Pi<,cy ll,,t;ngu ; ,h,,J Prof.....-,durin~U>tfallotl!/118. l!o;, :~:::1~; .~~::1~~-==s~~:s,r: duri...-1h,.period.Ther,wMp,_,nll in1hoAlpho.Ch;S'l<'" A"a,dSym..,.iumo1tho AJChF.aoouolm..,,...-;nNov,m\,er,l9&l,in\\'..h ington ,OC ~~~~.1,:.:,~-:;~~ t ._. ll, PA,..,O,,,,.""a, ., '" \ 0 .... ,D ... PM ... ,,.,.,,E,w& tl ... -"........... ~-,, -. ... ,,_,., ...... ~-""" '""""""' '"' ...,_. ._.~...... -. ,a .,-.M.A.l.-~_,_,0,,,,-..Pa"'< ... --~ .... .. ,, ... .. .......,.,....,, .... .. ,, ... ,,.,.,_

    PAGE 34

    :classandholnl!prob/ems NUMERICAL SIMULATION OF MULTICOMPONENT CHROMATOGRAPHY USING SPREADSHEETS Ooom.<$D. For, Yol ,Unn,.rnfy Newllo,~o,CTO&l20 l.orv, olhect ~m":i!:"..!,:~,~~:~:-.:~m,=':~:,=: a.,p0nu..,,..rou....,.ThiPl"""" h i o motivalttlbythmaWO'flph'< ]>t00! .... (,.,,.,i-.inv.,l,ingnonhn,r,quilib tium ),bulthe u .. ol'1raJ, t ""'lprognmmi1111lon::~:1:~~=~p=::i:~ .. : otrurt.All....,..,,.htheK>'lputabon limei,lorg,rforapr-ead,hee1-mth onfc,, ac,;,mporohleFORTI!ANp"'l'am,thefocttho< opn,ad.,heet_,.._ms-i ui,..,'(ff"!httl e ti""'IQ .iov.1opou,.,,i,t,,1iu,dioadn10,;,eifonly Few limulohonsareperfonnen ;:~:,-:.:.if~-_,.,.,. for IO....,~-0 Ill "'"'~'"q ,o ;) bal,::~= !.i::'1:,: t~:7!'1 =~:: in"',ph&M.,...,,..,feru, ; n~lneordti,i,._ii>r, app,..,.,m,1ion,lfdiffu,.,,,m1hop&<,,.n,port ~,c;.n .. inF,qua10002tatibe o ppr,;,ximolttlby l nmoot,.,...., .... foli,w;"ll'.Rnmoflhel..ongmuor ::::-.:;:;:,~;::nod,quU!d
    PAGE 35

    11,;,,.,,,.,,,mu,lral~ < lh< uf,p,..,,d,,J, ,,.,,1""8 ,am ,Jor; mpk...,nUn sfl nUediffere""'!numen flOl H li l .'-"<12;nfimtedHfv,.,.,Kln>'l<0nt.e;nt,gn1ted in timeo.,ng mod1fiedt;ulerp,..d;<10,--<0rrttt-0r mtl>od.Sn t~n,l oOOW, t hebo,ih<=..,< ingooe1;me,t,pllttntrotioohilumnooti.tio dtt;!"N ,nitl1ttthon o,p,,.11ol<0mpoo;tioopn>fila oep,,ra1efile .. t he""""" '"'""'Pron J. Th; ,, p..,..i,i-,;mplei::~!~::.,:;:::;: ;;::17.,!,'7.,:;.;,: ~-:::: ,... ,. printodu i ngthoJ 2-:Jl'fllNTcommor>d.The ,n1ryn ;n., abed,, pla)'<:d E11dlw,J ~,;,,..,.,. .... .. ...,.. . inFi(u,.-.l.Therompooil;oo :::::::";;:;::;;~";:;~ ::,mx~~-;1 :,"'~ ;,~:,11;;{ ondB19wB21wpro,i,;l,t.,.. upw;ndpd
    PAGE 36

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    PAGE 37

    . .... --...... ... ..................... ....................... ,._ .. ..,,..,, .,., ....... ., .... ,-.. ... ,., ...... c, """""''"'"""',_...,.., .. ....,..,.., ,; __ -0, ..... ,.,,, ""' d..,. ,.--, I>, d,,.-..,,,.,...,oom...,.n. -.KA .. "U __ ... T_,_ D'. bookrvlew THERMOO~MAMICS : AM AD~ANCED TEXTBOOK FOR<::MEMICALENGINEERS l'l,n .. ,,,__=s,,,,~SJ .. N,,,. r.,.,oo,a ,.,_,.,W,,t,Of/9"'! i
    PAGE 38

    A Program in .. POLYMER SCIENCE AND ENGINEERING at the University of Cincinnati cinno~;':m~l:;:fh"';1:";.:.~;:"7Jt.f::.; Statooand.,.,.of!ho6ratth,,...n?""fr""m>;1<-<1 bylhoA Ch~ ;n 1925. s;...,,h., t,n>< II>< ~'Z~~.:t:.l';r'_,;=<1;m;n che m ;,a1,nio,-nn1w .... 1abli>hed.andl11;,,;nthdi ~Efi;:~f~~i~l~ ::,:7::-;;::.-::r~C..l<' ~ ~-nd "'" ~:,::"n.tor:":.~~,.;~ ;:,."' !::,::; :,: ~u~:!:':.::~;!;~:::7~::~.-:::::1=::.':8~"n:':.";on and 00HaootatK>n w;th .. -~_,,_ ,.,., __ Tht,..;,,;n o ofpol;m,,'"""'hatlht o u gnm;nt<'"1hAmdl'ault"lo,y(197 .'lobe l :.:.:i~E~E:~:?~:.:;.~~ thod filleli'""nlOndron..-.CU A.,,.h<, i,foelty,wOOhav,polymer-re l atI~ :=:i;~;~:.t:nd"::::;.~ :!~';; TtieUn i ,..<> i tyolCincinn&,i.,,.... ... on o n """ "' "qu ,..,,,,..,m.Amiimumofthi,ty, ;,

    PAGE 39

    coo...,,,... ; ,..,. ....,u,Nd for the ~ ts~ o nd nir.e1y,N
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    PAGE 40

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      PAGE 41

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      PAGE 42

      cunkulum A COURSE ON MULTIMEDIA ENVIRONMENTAL TRANSPORT EXPOSURE AND RISK ASSESSMENT Y oaAll Cotboin>e--IMtoinl-th,_.. ...,.i.,_,,..wwt,.Rtatitly.l.aMI I I .......... ,:ho,n,i<,,l.,.i ... ri,..-_,,_ .... ,l_to ::-.:.~,.,~: ; ;;:;:;~:~ :.:~::1: ~~ :.:: :\:'!:.-..:~~~::.t., :!!!\.:.~ [~.:=~~=;; oo,lyoStw-..,.,..,... .., .. ...... _..,......._.,..,.,,..,, _._,.. __ .. ..;t1,.,..;,-ia1 ___ ......... ,,,..., ~=-==-=i=~ ..:u ... -c.. "E _...._-.-.,,_ .. ....,..,,;__. ~~~:-;~:: TlooUCl.,\..-i,ng;_,,,,.,...,...._ tu.i_ ....... .;,.,......,, .. 1_ ... .......,.,, :.~~ .. ::.::;'!_";:.'!i=.~ ~i.:~.::;.~:t~ .. "',::~ :.::..": .,.,."'"'"
      PAGE 43

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      PAGE 44

      ,~.J::~;.::; ~mm pl n.Thexplott.i.a.tho< """"-'""'"i,;.,~ 1:::~::2~::": oonttplofpollulonlt,.,... po': in lh~ mul~"' :;"'" n,;~ R ~t.,;,.._ ,;, -,,; ,, 000 1,-.;,,,_ 0 ,..1,;....i1a,,..,,....,-,; --~ ,,.....,.,;, ,,i mpl'"mpke,uhong,bet~een lheoil, o,r, ,..,._ ..,IOlioo&, In onkr t,) util i z, doo,-reopon>< ndw .. ph,.,,oo.Su._,,..,1y,o,cle.cril,ed l ow. '"'"'"""'"'o-1ithe<>pe<1ed,..p,,ru1Jwlw,,.u .. i,m,r 1<>U>r<)ofthepollu1 th,appl=f "'''""'po,tph,nom,noaodtl>ermc,. o ntronc,,nt,.t,;nnv, ron....,nto lmfontam nant ,-;a a variol~ or poftinghumanpo,rewlduew,h..,.>po,,urelS-101 u,,~~~~1:.~::;,:":=;.\"!'7~~: ::.";;.'!.':":.':,~-~;:;~~~~:~i:1-~~:~~:

      PAGE 45

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      PAGE 46

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      PAGE 47

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      PAGE 48

      ""'''"'"""'""'"""''nl lhootoden.,util;,.. .,; moi< pt,'.lttdu,.todet,rm;ooth,.-.,..!ldy A11e>Ontpl,o h Jl(>lent; a J ,...,..ppt"qlttl;o1ho naly., ol',ho o teady ta to part i loomr,gol'trii.. reo ndt ho dlern'lortat""'ol'h<,.,uil,"1!<<-,. ndho,lth ~t -:,1; .~";:-~~~-:~:.=~::: l. oo Agele,, ,. ho o nmTolM6 a ndl,=pe,:1;..,1y Th<.....,ltaohnan o ly o ,.lo,1homul~me<:h o .. ,.,,..., i n1olTCE;ni..Ang,eln,.l>own;n !,~:.!, a.::7 '.~::1 ; ~e;th~: .. :::;:~: .. ,.; ...,..,.,rr,c;en., nd,,.,h., oy e>poou,.r""'" ~/,'7.-;:::::;:1 :' ~~.!":~-:~~:.;.;,-: 1, r.i ; .,.,. .. ,. J rulat.Mo..,,.,.,,.u i"lll>e-rite<""' pot,n<)'f""'"fo,TC!:10 0 l l l m,otl.c eprobot,;lit)"ol' """""'"ll""Mhr<1,mtolll ,,nd.-idu o ld .. to <>pooureto'l'CKAll,mativ,<>n> le w1h; o ,.._llhriok .. ,mplyi ng tha t H7t u U <0nd.ttomti, >< ll 1 ,d,m rc,,,.;n1l>eJl(>lenh l f:.:"::r~,:MpO; ., _.,.,,,.,,.,.,,. .. .,,, ...,.,., ____ ........ ,.,, _, ...... ,, ,,...,_ _.., ____ ___ _, ~==E~-==.:::

      PAGE 49

      n.. .......... .,. ... -...,i,._-,._ -.a.ov.-ocS __ .,,__ """'V\lilUl',S. K.Yn ,, 11 .-.,...i11 T,1.1 i.,.,. _.__,.. __ :::::=-..iio,th,Mtiy._,. ..... .. "' ,. =~.:::::=!.:'!":.--. I 1-A.11.---.... .....,, __ .. C_"C... M 1TIU, ... ..__,_,u .. ...... ...... ... ,, __ s_,.,._.,,__ ,c_,, ____ ., ,. ...._ -------~-,-..... ,,_,_,...,_ .. .,. -.--..._,, .. , .,__,, _____ ._ II. -TI .... D--.... .,.,.__.,_,,._'"r-------~ ==-~=; = ~~ ~~ ~ ..... [b=~ .. IH 1101UhW mo ,.,.,-.,-.i ,,.,, . .. ... ..... ,..,... '"" ,o 11r11. .... ... --=~~~%=: ,,o,,.wo_.,._,._.,_ ..,_ ____ ,.g_,.._, __ I =:.,--~-~~ r-~----~ ~=~=::'.::"~ TA9lf t --Ooifl'~----... .. ~"'!:!.=:-.:=: ~i: : ~:: !~i~i =~=:~:= :: .. =:.:.:::==.: -._;,,;,...,, .. =-1.:::~:E-E

      PAGE 50

      D'. curriculum THE CHEMICAL ENGINEERING SUMMER SEMINAR SERIES at Virginia Polytechnic Institute and State University !'rpom>1r .... J>'n101h,,._..uniti<,.theChemi u lf; g;-,;ngG.-..Juo1<:Sx,etyin<"dei>art"""'l ;~?:;;~ft:~:-:t?.E;i lht uch o forum would "PPlnnattoonoud ; ,...,.ot,,... ,ru '""'"ina,

      PAGE 51

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      PAGE 52

      Oc.tofU,euniq.,.r .. ,u-ol'thoCES'pn> ,n.mintng i n,f.,,.,,Som.Thougt,,>IEngu,,,,,;ng Ed,xotion.o,Onll,,"11ll<""' Y "",Ownflu,i ,__"bylle n ')" M lH. IO-U..,ol'ColloidIG"' Aph.,,,,,.;n tll,partrnenl atVJ'l lSU;byfm,rKt">'-ntoti .. .. mp l oftho.,m i nor, g; .. ndun,..,i..r,,.,,i,,..yu .. otCF.S'aodho 1hediv,,.ityol'~,. .. ...i A lt i.o...t,o,., .. m i no,p..,....mioo n>Nlpri marilyottho,n.dua10otudeol""1'Ulation ....... 1 :::::~:::::~,..';",h,:.:' 11 ~ ~';' ;-~~~h': ~-,th,,in,duot,owd, n "''ha"""toptb& ularly ""antwithfocultywhodonott<0Onmtn,.. t ..,..,11yot t,r.dao,oriffodoly,withllwonty-fi> o p<,.. oonl of111< fwo l ty ottootflow, t., ompl<.thenumb,,-ofoem;no,,,,_,.1a '""'IJ'=oalun! trr~~::,:,:,~;:t::;~::: ; ~:t Any....,,.mloock .. CK~'Jthotio;niti atodond o dmm"tvo,yy,orlyd""tothe '.:F.:i:~}~,~:~~ E:F: ln,umma,y.hv> n"l"atod o r.d ,...,., Ul,runum.,.,.o,r,un.,pn,.. ..,..mfot"1heput1h,...,umme.,_n,,1;,,ne fi"ofthep..,....min
      PAGE 53

      _,,.,.,,.,.,_ ... dlto_r,od.,.to-nuo"''t1hoi ,_,.tth10onoud ; ,"""ofpttl'l',ondlo "'"'oC rudlh of knowlodr of tl>oponi&tl"lh._t,od,.......,.of_lnodd01_,,lhe .. -;,.i,.w1,...t, lhe .. ,.,_....,, <6tloo--n....._,..,.,.;,,u .. o,pni .. ,1Mano1 :-.:.7" .. ';.;"U::.:.=~:...~ o ll,how,v,,,lhoprocn,mh .. 1-nVfff- I .... ,d,,po.......,t ondlOlhe.,...iuoieot""""" io-inpi,,onin111>o_,....,..,..,.._,... ;,. ......... ,. _____ ,Jo, .. =._-----...... s tlrt9d-t ~-""----~.,., ... ;., ..... ,. o.,, ,.,,.., d,.,.,...,,ol ,oo,/U,..,,l, t.,,.,o,._,, ~s"'!:-_""::,::::...,~.:~ ... ..,.., a-,,i-7,_ ... a-, .i,,,. ..... ,.u ... .__ ,;,.,,, .i,,,. ......... ,..,_ ,11 __ .,.,../., ,,_ ____ ,./_4,,_ -------.. ..... ___ ,_ __ 4,, ...... ,,.,...,...., __ ,,_..., ___ ,, n.,,.-,-, ...... ,,_.,,_.,_,_ -:::?..."::.:..,'7;;::::;n Tt..o utt.o<.,.;,h10thonkN.,.IS
      PAGE 54

      tlanraom THE DISPERSION MODEL DIFFERENTIAL EQUATION FOR PACKED BEDS I s ft Really So Simple? Wu.u,.,.J.HocE ~=:.i:.:t~= .. ..... ,..........,._..,.,. __ _,.....,d;_..,..... __ ..._ __ _... .... 1two ... -ndll)'thelod.,/adon .. ,_ ., .... _, ..... d,tr.,..ntool""''"Nril,;oSdotpo,.io.,,,r .... ;nbed,oondoth,,..,"l1,plo-p/luolJ't=::~~$~~3:~'"-3~~::~;~ "'l""''"iloli.,,.-;Rlr,,_,--lbolo....,ooo ....,_rot,ntheno.:lplluoin-ioo, .... ,riltoo =-~"'""'_...... .... ,_ .... l'or"""-,,,,l.oowl"'"ilkII I .. ~ t;l : ?, ._ ~ u,~ ,, 1n...,. .. oo1o .... -....i.-1:.,,..,...,,.) Aoo,p,,ct.,,Plkob l od m,,..n, lo leqotion l..-doocribo"1,,-ondumo 1or ~ ... n..i.i.-1bod.i,,bouiJOMMOlor a ___ ....,. l"'!uiol. and lwoll ...,_i,,..-....,;. w.__,...,....,..,,.,.,...,..-....,.. ---dllefttotlolYOl-ottloo.,._ .......... -.11.-...----121-. ....... -...,lhudpt,uel.l,,___,,,_.,n .:1,i,.-...,.1,,.~-,,,.""""'""'1wnoldp1,uo;;,,,i,,,_ ,f ,< M>,1/ -"f A ;.>,-/ : :~Ji:-~~ :::.:=:.- . !!:::=-........,_.,,_...,.,..;u,1 ( -,IA,,,, ,,,...,.__ifti:,q_t_ tloe-no<1.n..u,1,l,tr.-on<1d...,..-...._ ..,_...,, .... ,m .. -1o,-,t.o....., .. now.., n .:1phM01an<1,hopod
      PAGE 55

      ,.1.,;,ygnd;enUl t" orron n ienu .111< .. oomt,;<> :~-:;;,:.::,:=;.,~:-: :roc:::1~=-::~~ n"::':! dimen,,on~,~--ll-k:..!'::'rkk' a 7,;';,'"l w t"l"-' Dl1(ronn1tatHIO'lfl"odi<,nt).lnlhio...,. t hedioperoionrooi'fowonly mt heoxi,l<1,,.....;,,n,n., . r.,. ""'7"'"lrond1.1hoeariouot,rmomF,quo1>0 ~:= r..o ,hooe ~i "'"""''" K,,lO<~~ '"'L~~-~ . ftl' .C,L:.lU.C.tJ.,~ """""-""""'h.,heunii,ol,moi..-Oi:AXlo-OlAY l("""""'""" 'i .. ,yateuit,of("'""of..,_,,,.... u.,.of,,.,,...i XlimoJI i;q ... --.~.oo,..,,.,_ .,,...,o;w......,11,nn, -Ol th&"""p \ot,d iff re nto ol
      PAGE 56

      --'----'""" ...... .... w>l.l, ___ .. ,..._ .. .,_., .... ~--r. .. ..: .. .....iu,1 .. ~""--"' --. ... __. ....... .. _,.. ...... otnll,,l.ho--"'"'-"' __ 1,ioll.,i..,i.._.,....,...d, .. a-l,dl,o,d.A Nlio"",.,.-,heN PIIOIIL IEMSIN I/SIOtG TWE TWOSTAND AROl'ORMS -":.':..::.i~-:~(:.!':.":",.: l(.-olu-ol .. "'-~-i~ .. ,n i:..,...11.,_ 1,o .,..-.,1;., t1,o ...,.,..,r la,,.,..nLolA-,1...iu-<,f fl".:l"" l~od ffol<....,.bown,11.,.3, dhl:.,p1.,.;"ll"ndt .JU; ....,1':"r:."".!:.,':,,.~~,.9;.":=:~ __ ..,.,,.u.,,wo,....-.c.-.11-

      PAGE 57

      ,, .,,J L '"' .... r .. ,c. lnd"""11>oqu.nrnyN.itfloodu '"''""'"r,_,poi,11-.-"t,_,Q,.n-bo :::..-1>1u.,...a1.N10,.MEq .. ,-121>et... b-. .:'r. Eq .... _,3 ............. ,i.-.,...-...i 11, .. ...uo .... 1i....... ... the_..,.,-11 ,.,._a1,,.,t.o..rtd1Mappha,bl<...,..,_fo, ;~!~E:':.."7:'pi:;'0:.":."~=.~:~1~:.: Toftndon.,.ua1-,.;m,1.,1or.q ... ,...,1)bd1l11ooolo ...... ""',.. .... ,u.:.. ........ 11Jio111e_,.r rinthe-"""""''""-"""',... ''"1.h,..,.t,( .,,loo( f.qo otNNll7Thi,,_,h.-,INltino ,-klb)'tintho ftnol oolutioooftl>o Wil100,quotioo l'liyo""'IIJ",lhiomok,....,..,;..., c.m ... beiocr,,-.l,.hHponolthe"'1umo;,, blOt1No,1l,olik<, Tlw,,....,._ .... ...,i..,11,o_,.,_ ....._.,....., .. __._, ___ ___ ,Ai_., ___ ...... pp1,;..-.10pod,l...... ;i., ..... ,111>-Adori,.,.ohho<0n>p!N,d,l!".,.nt>oloq ... ,.,.fo,tl>ed,.,,.,..,..modolinai-ke, .... ..,_,U_i,Eqw,-8oa416.,.,.,...,;, ........ ot ............ ,....._n.. . -... ,,...._14'"'"""""ial-"'-''"' .,_,..1,o....__.,,. __ ...,. .... __ ~:~.:.;1:,,; " ,. 1 I 1 I c..... ~ ~.,;--.. ~~1

      PAGE 58

      ffl'. curric u l u m TRANSFERRING KNOWLEDGE A Parallel Between Teaching Chemical Engineering and Developing Expert Systems P .k .,ENE -1N;i;,..,.c.,..,,<(e,,, ..,,. .... ,o.,.,-.(..,,..,,1 .u1,.1.1:, ~:,=:-r~~~.:~~E2:1:; ""' l>oo:ou. ~""" aod n,s,ah poptff h>'e '-" pubh ot...t .,hi l i<>,;nth,P""'I ~:::i ~u:"~;~i.!7.!: ::;:::;:;:. m;~:.: :,t:!::..:.~-="~:f~::: ;::~~; Ovum121.1..- mpi., .. ,,mtlthalMIN oit:Sprodu""'"""'"'"i:ointh,US =~~::.~=.:.':i-7,..!:~.:;~ 1 1;;~::;,.9:;:~~h n ,,,., .. ;,;,,_,1,., ..... ..... .-;.,.., .. r_.., ....... _I_,_ .. rn -k Al ,.... ___ 1 .. .... ......... 1,.,,,.., . .. .. rn ... ... ,.11, _,.,,.,.,1,,_, ::-;~I::::~ ol: Al ...,._ :.~~f ~;::::7~~:.:::11;~; : hulBUu,dow,c1w1ooJ,o,;g;na1;n ~ from,ompu,.,,.,-;i,,n, n loborororie.KU!mal o AI produd mon,d ...,/ymimKlloo,-lafhu mun /nleW ~ en.u,../,.,m,:,-,nruol/y,.,nder ;,.";:,1::',,;:,:r:ir::::::/1," "'"I .. ,...,.f,....,i.. .. ,..p1,;.,..,..,,,.1po;n1of,.;,,. U1u<>Nfulf~<;1tthooJotyl;,elonpWam;,,..,. "orld,t,.."-il)lthatiore.llyl'>Otmodelre,plorinR 1hOrloyotompn>Onim-,ing,..1, .,l thouhoo
      PAGE 59

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      PAGE 60

      n., .. a.-.m1111y-ibkperie,.,..,bu, o,nlt-nd....,.mo,a,.fondon"'"'llyhm ;to<1.Mlyofowof1hflfOM acq.,. .. ...,,..;u,,.,._11wsoch ,.,hlym&yn!,,.._n,,..hatloknownby""'vention 0< findin p or ""'"'"><<>finqu;,yin1ho,..riou,field,,,wh>1an, ~::7::~ .. "i':." ::~~~ 1 :;:,:!;~~;;:: = u..,.ulw.,..ofo;gnl>lna' f,.kl l !I.Th; 1 ;.,,,t ,.._ 1,.whl-ntifyknowledge """"",uforA!,,,.,..uin.....,ntli1ffo,lu,......i.., 1 11]. o nd.,pl N,q@ntit>-ll"" PP"""'htoknowledp ,.,,,.._n,.,;,,,,,u,hulheo,,;le,4-mqnitudo,. 100;ngopp,w,<>foomeenr;;...,;n l "'"''""""""oe o ndolf.,.,,...,.1,u1 .,.ro.-r.,.,...1 ; .,ng,,,,.,.p<., o nd h a ndling div,..,. form,,,t~,_,,.1..i,,. Anov,l o wrooth1h a< eoloi1<,ymb0Hc,,.,,. eo,.jn1 o ndk..,..ledgerep.--nta1ioo1omim;,U.. odopll-w i lhuno,,K..,,...llgo.t.u.>da-h H fo,handling< p,,timcnt>-1 k"""'ledg,, H ~ell ._. quanlit>-t;..., o nd moulde.plltilly_; .. u ,. .. ru< ;l ,ompilcdknowledgew;thdeeo kno,.lod,,,. me1hodology1t ot1ho .. ,....,,.."""" ,+,t :S!!if:1:'.:i:1 ":'~ ~:; 1,dt-oign Oi""""""'telhodirfe,.ntlYPN<>f ',nowled,oeondpr,,hlem401,0ng""'.._;.."'hio,npubllohod duoingthepoot a,-.ytt,. 1 21-2 4 1 Mootofthooo p
      PAGE 61

      "'" __ .,._, __ ......... anc1 .. p1o,,F.S-no&oa.A......,.l:MI ES""'""""""...,.,,_,olhoifld_,.;ol .-..i,11o1-oltho-p,1"-"h,rt,1,o,1-. """'"ted-in__,;ntbeltth....i.aho,I .... --k;ndotAlrrwp...... k_to_ the,-r.1,:1o~ .. ,otESM1hrnlhoopt,ol inJun,toolH..,....,p,1ny.Moot,,,.pon<1e""'ot1hi, "'rv<)l~-""'-u.tlly F.S tedonolocr,..,.lo ...,.;na111>o-1;..-otlhocbeffntol,,...i ... bloey,clooondppond ~io.-lh-- -ioallothe,_rCl>tmiaol En,;inrin1C.,.,m i, ... !C ACH~ J .. .. .. )>f!<"iI ta>k-MlhlbeffliN"'ofadd_l,..ll>troloof Alnd;iodonvau ..... ,;....,.....,,.;,.u,ood..,.,_ .,,_1.,..; ...... 1:i&LMinituJ ...... ; .. .,w ....................................... ., ... .. Al __ __ ..., __ tV LMn,apo,. .. P_""J'"'""'"d1hol,_ ......--r ,n,onl1n~ .,.,ro""'tlh.-;,...,,,h,t..oidol...-.ploo r.-,1,.,.;,,.1.,..;....,.;,..ondot....-ri-invol> 1,..,,.,,.,.1pn>ho m,,.;n~ f,...,. "'"'"" ,,._i. ouolyprovidodh7thoH1tputorocion...,..rt"""'t _,_ t .... -.. ... ,,..... .... """' .. ..i.""' .. ....... ....... .-p,_,,,,,._.. ......... ._.. ..... ...i ... -,.._,...,._.._.,..,ES __ ., ........ ~i.-.. -..................... _____ fl)>n(f .. _.,,,_.,..., .... ""'i..-il,oupt.,.-t.oo lorot,lpoyd,oloJiotoand_.. .. ...,.. ..... ,__ nd~bottffn>Odolotoo,pl.Un-otlho hum,.nth,nki"l...,._.s;milotly.U..-kol)menl ofKBESfur11>ttro"'forofo,pen, .. nd.....,koowl edgeMll-u,,..,lholprof_...,,I'"""""''"""' k..,. llp ... wlch_..,.,_,.,.dtol' """'""".._;.,oMeloi-. .. .......,,ioowMOdelo ,,,._loo,n,ed"'4oyti,-o,p,.;, ....... ... ..,~ ....... --"""'"'the_,.ln1and ~.,,...,......,_KJll,;!j,riU-tho .,., .. .,..._.,k_lcdtp..._.,_ ~"-::0":-: ::.i:: ~""'--===~ ,,..-.,.k,--i....11>oanintla ,...,.,_...,..._.ot1Kttk..,..ll(,,u...!lu lhoc'ffl,o,,ol""'""'"inle0<1flco o mp l,aolfr07'"""h
      PAGE 62

      .. ----0.--u.l .. [l._ "'"''''''"""-'""v ..,. _., ,., ...._,,_ ..... ,, ... .. ,.. .... ,. ..... ........ _,_-...., ,,_, ., .. """... """"" _.. .. ,...,.,_.-c.,ott,: T-.,_ .........._ H d .-Clllf<.>, ....... u. ,n ... ... II-" .. ........ .. u .. .. ... ..-., .. ... .. ...,_ .,,..., ........ ., c-""".,,-,. -uM,, ..... ~ ---R E VIEW : THERMODYNAMICS c""""",.;r,..,,,,_,207. &0l i qoital1 .... -bir ltudy UI al,o provided.~ moll de1a;1, ... 1th H lh< osu a l!y int,,.,,U"1 ( bt,t oot a lw ayaoh vK>uolytti<>'anl)q...._lHHl&atmony pointainth,t,xtondtl>tann,ctiv,tyl'05'0phKO I :: of11>tbook,he i pr,1a i nth,au,n1ionoftJ>e n1,d .. r t hollheint,ntionofth i oboo1ebook Uloomdioworthyo(.,,., oitbookfo, al lorp ,,. tofonl'ermodynomiOdynam;dlo
      PAGE 63

      The. of vers1ty on DEPARTMENT O F 91''~1F CHEMICA L ENGINEERIN G 11.M. tF.lJNG S.C.CIIIJA ..G l,R !:LWITT 11.J..CHls..-t : 11. C. KI U ,OK Y s.,,r. r, l) .M,\11,I.IA/a., t e,i"!ITodJ nmieo. M atori IPro...,.,i oo fo odlledA,h0<:etvironmenta l EngiDNring B i.,.,b.,mi,;.o l f,n8i"""ri"8,Envi,onmo n 10IBio1 i ,o('.o1olp i 1 .'"''""'"'ign. Mi ,ing 11a,.ordou,w.,. o fffi,tmen1.Nooli<>NrD)'nunia tUol o ndChem ico l l ,_Kngin..,ing.ROKllv.Pol)'m"" ,\ \' o SloCt...n-Up ltomogell9001C.ulysi .Rooction K i""'ico l'olyn..,riu11ooRooc p,_.;n& P,;,lym.,. film ,. Sy01om O..ign M u il iph .. T,-n,po,1Ti.-y.t11t ,. fa>n l no orl>Oo1 P henomeno c..,,,.,..,,;,-oG"' d"al o t :d ucolionl .,,,g,am4a/,,_,a, a;/abl-. r,,,,i,,,,w,.,j,,,a-,.,,;papplko"o"'i<"-"'~'" >'o,Md""""'''"-'" "'",_ Ch o nn ~.':-~ u a 1 0 C' ,mu.., U.,parl....., lofChem ic o l t : nginoerin& 1;!;,'.;;;'.~-;:!1,;~~l;;.,

      PAGE 64

      CHEMICAL ENGINEERING PROGRAMS AT THE UNIVERSITY OF ALABAMA R ES EAR C H I N TERE S T S ll> M.S. o<>d l'h.D.dtc1U"'eind-,, <ot>c o loo.a,AL 35487-0103;(105-Jot8'150) FACU L T Y ~: fv_"f,~~:hi!;;t;~;~-:::t") w.c.a .... n ... 1, Ph.D.(V.,,d ,bm) R.A.Gri[fin,Ph.D.!llllll5lal<) W,/.Ho1chor,/r,.Ph.D.(l.oui,i a naS t .,e) I.A./fcoo,Ph.D.(Clem,onJ ,1 M.1.on o Ph.D.IM ossach.,.. ttsJ 7-' r::.ii;:~r:h~: .. C~l~~=~l V, N. S,: /,,00/, Ph.D. (Ponn,~l.,,i o Stuol &oma,,C,,.,,mit,n,Modl'O!""Pro<""",Them,o.l,,-n;,m,a,O,. l ,Wa,,rfoe l lkVnl-..,, Ca<.IY>~, O..m,c,lll<><1orO..;p,,R...,, .,.K,,,,.1<~En,itonrt>toc!,. M.,_,Tran,ln En<'lll"Coo"'"""'l'roc<<>.C.m;,,,.Rll l l'T<"""->...JIJ ,opru<.,. i ..

      PAGE 65

      University of Alberta Degrees: M.Sc., P h .D. i n C h emical Eng in eering and in Proce ss Con tr ol FACU LTY AN D RESEARC H I N TERE S T S

      PAGE 66

      THE UNIVERSITY OF ARIZONA ""-'"""' .. D--,,_ ____ "''"' """" "'" "'-' S. __ .. 0 ___ _____ ___ "'IIJJUtP LPH ,_ ... ___ ------1'110\IA~-u~... ___ --~---,., ... ,__ ... ____ ,m -"t. __ ,_,._ _, l{>
      PAGE 67


      PAGE 68

      University of Arkansa s D e partm ent o f C h e mic a l Engin ee ring Gradu u /e Study mrd H e scurch Lc u din 11 lo M S ,md l'hO V c groc ., ..., .., ,,,_._.,,.... ,Ph.D.U ... .,._, ,_,_-,g ... ... ...._ ... ..,.,.,,L,.._. .. D U.ol.,.._, ._,_,,_.,......_~,...._.... ~o.,-.., ,PhP,U Y .,.,.,_, ___ ..,,,,_ K '""' Jo-LG-, l'h .1> .,U ..-- ---.---~.. ..,. .... .. .... o,.u.o1,._, ,,..,.....,,_....._,.,,,,,.,_,._ ..__,.,.., __ w, .,..,.,.,...,~,.;.,_,,.,.,.,, ......,,.,..._., W f~o .. J>.Uol,..,._, ,,..., _,.,_,, __ S,M.,.,_ Jl L .._.,,.,,_u_u_.,,,...,,_, ,,..,_..__,____ __ ~"'""'""-~, ..... ... o .. u.,n, ... ,. ____ .,_ . ...., .. . ..... o u_.,.,._, ,......_,.,,. .,, ___ ...,< __ G ......... ....., ..... ,._,.,.,..,.~.,,..i,;.,,nd .,._., .. _,.,.,,.,,.,,. t'ORn : R rneR Dt :-I" Al l.l! C O,.TACT G,....,,_........,,,.,wv;_ u.,. ...... ,..-0,,., ... ....... JM~ lt :....,nMn..,C...... ~"""""",.,..""" t o,,tt,,illo,AH1il7(ll ..... u. ,.,.. ,, .. ,.,, ...,.,1-.,... ... m,.,1,on.,.h r ""'-'"'""~'"'"'..,..''""'"' \ :;d' "''-" .,,,..0,., ... .. ,,. ................... ..... ..... """".twt>onond,, ., ,1 .... ,,.,.. .... F ,,,..~; '""'''-''"""""""'"'-o1u .. -,,...,.,.;., .. .--... loriM. n1honor ,...,, ..... "-'"'m<01,,od_,_,.,......,..,, ...... ........,,_., odf,.,,...1o,,.,......,.,,,.,,.,,,..u .. ,...,,,....,. .,.. t,h of,.h ,alandm1, ....,ua1....., .. lbol>,po~-mofC .... ...,,_,., __ _.. ..., .0,000,..~. ,., .. ,, .. ,Ilda eno;,,..n.,c.. .. ,., ... .,,_ ................ ,,,.,, .. ,, ........... ,. ...... , ,._11.,ra,bo<-011M,,_,.,.-.,,.h

      PAGE 69

      CHEMICAL ENGINEERING Graduate Studies --'""""'""-~ ..... .... _,_ .. .., ,....._ .... o.-.-~----------_____ ..,_.,_ .. .,. --.. .. ......,,.__....,c- -. ,__,. .. .,._, __ ._ _ __

      PAGE 70

      UNIVERSITY OF BRADFORD Applied Ol'l/unic Chemistry Mcc/ica/ E11si11ccring Biuchemicul l i' ngimmring Ncm-Ncw/oJlicut l'luid s Cfllulysis l'ul y mcr l 'ruc cssing Compulcr-Aillec/ 1Jc sig11 l'Dwc/cr Technolog y Control t'ngi n ccring Solid-Stole Chem i stry flcut um/ Mas s 'f'ronsfcr Sulvcnl Exfractiun Thu deparlmcnl whid, has 2a academic s!aff. h as S!rong links wilh i nchis trial com1~,nio< in llu: U.K. and olher EuroiMt,m ooun1,;e, Mat>y of tho,..,.. search pruj,oclsarusponsored by industrylgooernmen l joinlly,orl,y in dustryalone.Thodopar1mcnlalsoninstwol)OStgraduatclaughlcourses l cad i ,,gtoM.Sc.(ControlEnginooringJandM .. '>c (ChomkalEngi 1 weri1,g). Oirec1orofPostgradt1aleS1 u cl i es Ocl)artmcmofChomicalEngineering Uni,ersityofBradford. RichmondRn,,d IJradford.WoslYurkshirel!D?lDl'U.K Td: 0274-7334&6 fat.380

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      ii'c ==: ,.. '"' UNMRStlY Of(Ai.GARY DEPARTMENT OF CHEMICAL AND PETROLEUM ENGINEERING ~~,ff,,,...,_..,..,,_,,_,.,,.,"'.s,"""'w-ui.,,,, ;,, C-...1 &,;_;,., f/,11--J W .. /,I Lo, '-t p;,, ,., __, >of'""' ..... ,-~_.,_,,,,1,.,,.,;...J .. ,.,~--, T11
      PAGE 73

      THE UNIVERSITY OF CALIFORNIA AT BERKELEY .. RNVIH(lNMENTA!.!'RO'IBCTKlN KINt:11! :SANIJCATAI.YSIS POI.YM>:RnX:HNUl,UGY E l .ll."fROCJlEMICAI.L"l(;INOl,Jllt,;G l'R(X:FSS l)f~~IGN AND m:VEUJl'MENT SURFACF.ANIJ,l [ CAl.>;NJP(ll:F,SSES fl.UlU~ I ECllA~'ICSANDRIUX.ll.OCY El.ECTHON!CMA11iRIAISf'll(JO:ss1NG nff,,.,. g,a du a 1ep msn m,l .,. dOngto!ho .11 a ;l.,o fS,,;,, n, .<1 u n~yro1ak o partinthoman y : 1 0 ~ff:~~.:~:~;,:::, F : :~~;:,B~; C. l ffo,n l .. no,.,hUOlin fCll/llSONKIN<; SCOTTl.YNN n.-vms.S<>ANE IJUROSN.T!IWIXJROU DEl'ARTMl;NTOf'C:l l l,;l,llCALE:1'Glt,;HRING lJN l\ "ERSlrYOYf:Al,lfl)RNIA BERHl.f:Y,C.AI.IF()RNIA!>,72{1

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      UCD Univcrsity of California, Davis ~partml'TltofChemicalEngineering

      PAGE 75

      CHEMICAL ENGINEERING AT PROGRAMS --uc1.A c~ E~ Dai>l,tmen1 ol!OQP10Q1amo!teact,,ngandrtSH11'""'"'9 sao-nca and H'l(lu&t,ial .-Thedtl)a~moorsna!ionallea,:l&r1llipit -~-t,yllMtMWtyeslaC,lisl,eOE~ "'11-C.-forHuatllOye<..ungJ)IGr-inEnwon =:::r~ 8-hrology F--.,re-to,outslandonglP" plicantl.A~iruJde$w-olluilCWI andlte1pl,Jlao1'1"'f'd l.ocale<:11 ... milolsfromlhoPaclficCca&l UClA'1eo<:1VillaQ8S1--..: -I01hlfloglllyr~....,,C,O~ ard1D&nt1yol--"'-""""' aOl1lon.,...,... UCLA WO vanVOO'SI ~ f?ESEARc_H_AREAS Thorm<>Or--c,_...,. p,_..Dtt,g,,...iPJOCMaCotology ...... ,, ..... ,.,_~...., KftoOQ eomo..-,....icatalyM -o..;oo-c-y.-.:1--~ ---~ CONTACT ~m, __ l.oo,.,__CA_..,,_ P' JJ

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      PAGE 77

      CHEMICAL ENGINEERING at the CALIFORNIA INSTITUTE OF TECHNOLOGY At th e L ead ing Ed ge" f ACUI TI FrancesH AmoJd James E. Bailey JohnF.Brady MarkE: Davis RichardC.Flagan GeorgeR.Gavalas Kons1antmos P. Giapis JulsaA.KomfiekJ Manfred Morari C. Dwigl!/Prater(V",s,t,ng ) Jol'lnH.Seinfeld Fred H Shair HESEAIIC/1 / NT/iH /i lffS AerosolScience AppJiedMa/hema/lCS A/mQspherie Chemistry and Physics BiocatalysisandBioreac/orE:ngineering Bioseparations Caralysis Chemieal Vapor Deposirion """"""""' Colloid Physics Computational Hydroct;namics Fluid Mechanics Nicholas w Tschoegl {Emt"11us/ Materials Processing MicfoelectroniesProcessing Polymer5cience Process Control and Synthesis Protein E:ngineen~ Statistical Mechan ics ol Heterogeneous Sysrems f<,,/urt,-lnf,,;,001,0,,,~.,.. o --&..,. .. ~-a1r_,,...

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      PAGE 79

      BETTER BETTER CHEMISTRY ENGINEERING B cco m ea part of th ebes t -bal; u 1 ced equation inth epro f essio n c hcmica l e n gincednga1Casc \Vestern R escrveUni,crsity. \V or k with top-ranked in st ru c tors an d r es ear c h ers in o n e of the be st research e nviro n m e nt s in the U.S. in: l n td h !"'11t M,cl'(l-andn.i1~>-..,\>1 F or mor e info rmati on contac t: T)..,(),.Jua,eCoordmator IJ< Wc-so...n Re;,,,,,< Un"mity Cie.<1, Oh,o +1106 ft CASE. WESTERN RESERVE UNIVE.RSITY F aculty and spec i ali:atio n s: R "'u j. Aouo,Ph 1).1959,Lehijd,Uni,er,,t!' l'a,n,ck,"l"rao,n,.mm"-", a< .J..,=,-,r, l lotoT V, ,,,. ,.,,,_Pl,_[)_J'l68,jo<,n,Ho('I,,.,. Un;,-,"', y1.a .. .. .....,,..,.,m:,,hmo< J""'"'"""f,"".'"'"''"=~ J. "' '"~ M ~~. J ... l'l'd). 1962, S.. Un,-,N, yln,"fa,: .. l"""'""anJJ1nni<>, l~'' "'"'""'~"""llloJp:,ufolm~ xhao
      PAGE 80

      Tho UNIVERSITY OF CINCINNATI GRADUATE STUDY in C h cmic,.IF:ngi n ccring M.S. and P hD D cJ;roes in Chemical Engineer i ng Fi,iancia/AidAuai/ablc ~m,~l"' ""' "I 1 -q .. .. ......... K o hr.o,Ood l}o,;dc,.. "''" ''l,nnLp D,n;.111,._ho rS"' ill,l'inlo Mod<-!m 11Mk,fJ o/1Pclo""""'"""''of'''"'""'""" ..... 1 .... .. ...... --_..,. ... _b_,, __ d_ ,,. y.t, r.,r --....-'f"";,---J,J ""' ,1,,,1,..., __ ,,_.,,__,.,_ .... ....... a.... ,_,. .-, ... ... .... ___ ,,,, ~ . -,...... ., ... _____ _,,, __ ,._,,,_ .... _,,_,,.,,_ ..... .. .. ;., ..... ,.,.,_.,_ ... ___ ,__ .. ...... --,., .. ... -,,... ,..... ... ,,,,, __ .... .. .. .. ... ,.,,~, ........... ,,,,.~,...~>.. -..... __ .,..,_ ......... 11 .......... IJI.----~,--'"'""'" --...... --.... ,_ .. 1--'""-' .... f""__...._.",,,. ---- .... .. ,,,. __ ._,..._. ,,,._,_ c-,.._,_.., __ ,,,, ..,.,, ..... .... "_1-,.,.,a
      PAGE 82

      Graduate Study at Clemson University I n Chemical Engin eer in g Coming Up for A ir .,:,.:,att:;.~~'v~~~':;'1~"';; VOg ,alrogand wa!&!S lg 10 SovlhCorollna'sfamausoeact>eken<1 Sam&ti.,gt"'cG"l/eofyrelaxyo,., M tr..andotoP-natcncr.em1ca1Er,giri$e ri"'lg Oeparfrn9n!.TOQ. W~n acffve ,e..,,,cn and teaching ;., pafymer proces,lng. compo>ite materials. proceu outomotlan. thermodvnomlco. cotolysls, Ond ;:1..;:rorie OppliCotlQns wnat mo,e dQ you The Univ e rsit y Cl8mlan.thelCrid-gru,turMtrSl!ya1Sou!nC<>ra5na.offen62Ul"lderg""2uateand61g,a,j,._.,(rt9 tlel::liafs T....:,Y ;.,n,nneacemk:c<>Mges .~<>n-<:ampu1 ftlYC.frnenllso~ l4.0:::0STU(l&rll$ ane-ltwd Of""'<>m c,e ;., 1ne College a1 Eno"""""" Tn&re 01e o~ 2H:IJ graduale "'-"8nT>. 1fle 1 AOO-ac,ecor'l'IPe!Mles<>ll oefiartwe11i,Sou!nCoroin0lPl&Omont .and~ l"l'IIOwa\'t>elwe9nCl'-.aMl!e.N.C . andAtlcrnta.Ga T h F ac uhy ChotlesH.Ba rr on.J, JohnN.Bea r d.Jr DonD.Edie Charle$ H. Gooding JomesM. Haile DouglosE. Hirt Step>,enS.Melsl1eime r JosephC.Mullins l'r<>s"m' led to t h e M.S d Ph D. deg r ett F in ocil a id, i ndud i ngfellowsh i ?Sn d "i"ntship<,i< vail,ble F o r Fur t her l nform~t i on f orfunhe,inlo,mati o n nd dn< ripliv eb oc hur e, wri te: Gro d u o teCoordino!or ~,Fe~ 1 ent of Chemical Engheer i1 g Clemson Univers i ty Clemson. South Coromo 29634-0909

      PAGE 83

      ----"""""""'"'""-'.,__ ..._.,, o, ,-..,. .,,,..,,,.._... ... ......_ 1,;,_....:.,c_ ,.,. ,...o ,..;.,,., ~ ....-. :;;,,J "s ~";;,u~?"' .. \;. ,. :,. ......_ ..., L .... o~!"' ~:::tt:' ":.::'.t ~J,M IIA, CM /.\:'~ r,.,.A<, 1 c..,.;., ,_ :,.-_,_.., ... ,_,...._ ...,_,_,,, ... ,,_,, __ E:::E::ac._ --::::--r--1 "R U' "'::"! '~ "::'.':::::'~ ~ ~ L\N~ ~m ' O"'M~ ~_,..; ,. ,;, .. ~c,,;;,,";,_"-':,..., ,,,,_ ,: u.......,..,.r~--' ... {;,,_.,_.,:..:...,. .... ..._.,.,. ____ __,, __ ,..,., --------_., _____ _

      PAGE 84

      COLORADO SCHOOL OF MINES ... ..... ... ,><.( .. E:!~~--=-= -n .._...__,,_ ==::::-.=::..=:::.-::..."": .,-:..-=~ .... ........ ... __ .,__,,.. _, .. ...... ...... ...... ,.,.__..,,_,.,_ -~-'""""' .... ,.... ... ,., .... ,..., ._.,_,.., __ ........... =-~z=-= ,.._ ...,,,.. _>_, .. ..... ....,, .. _,.. __ _.:!, .. ~-.....---" , ... ,_, __ _____ .,_ ..... .. "g~.::'" .,,_., ___

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      Y.2!'Co~letes Th.e Eqwdion.. l'l, .O. (Reseru-cJt + F~+ )dt f Dunfius Life+ BS =UCONN Graduate Study in Chemical Engineering M.S. and Ph.D Programs for Scientists and Enginee rs Faculty and Research Areas -~,.. ..... eonll'OI, _,,.,,,, Aotl:AIW COOGHI.IN ~-~IIICIIAELI CU!l lf =,~ing MTIIOlflf.OIIENEOITTO -compc,sittm,loriall JAMHII.HNTON Oie
      PAGE 86

      Graduate Study in Chemical Engineering Ad;v e rse lnte ll&e!uolcl ima!e GrOOJO t es"e<11>0fJor,gen.:i -p>gondCioll'>&ologv P>CGS>Conll'OI '"'""' "'Adl$lingulshedfoculty -~-"-.Cb'\< JomooR!:ngurom K .FIM(E""""'u0 --c~ .......,..._,.2~ ~-;;L """"'""G.lhO,po([..-uoJ -l-Von~(EmO,rituo) -f~([...-....i JoM"-l~

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      Chemical ~ri!~t~E:a ~:~~:rtn ~i~hoff &:::! 1 1i 1 i!~=y P....,.dS.Dhurjati ~it?it~7~nnhoff ~~h:;; ~1-~:;1:~~rh Stanloyl.Sandlo, ~~i1~\,Scs~:::: NormanJ.W~nr A"drew L. Zydnoy T he U ni',crsity of Delaware offers M ChE and Ph.I) degrees in Chemical Engineering. Both degrees i mulre l'eiC"Jrch and cour.;e work in engineering and related sc ien ces The Delawaretr.tdilion is one of strong imcrdisciplinar y research o nbothfundam entalan dappliedproblem s. CUrrent fields inclu de Thermodynamics Separation Proc:esses Polymer Science and Engineering, }111id Mechanics and Rheology Transport Phenomena Malerials Science and Metallt1rg) ', Cataly s is and Surface Sdence Reaction Kinetics Reactor Engineering Process Contro l Semiconductor and Photo. \ Ohaic Proc:essing Biomedical Engint--ering and Biochemical Engineering. ~ -= -~ ,_=-;_ ---, I ---~.: ~ ':':: ::"' _!/ ~ o..,.nmtn oof Cli
      PAGE 88

      Modern Applications of Chemical Engineering at the University of Florida Grodual e Study L,,ad;,,g 10 th t: M S Md PhD ... ..._. __ ---..... .. __ ___ ._ .. ,., __ ___ -L- ... -..., __ _____ ----IOIO ~ -----fOI --.-..--------~---------0.--------------

      PAGE 89

      Georgia Tech C HEMICAL ENGINEERING The Faculty and Their Research ......... -~

      PAGE 90

      What do graduate students say about the University of Houston Departmen t of Chemical Engineering? It s greatl" ;::."dlt~'-:::"rll~:~ __,,.,.......,,""""""" =o:~===~= f!= g~ ..... __ o.,,,., __ ,._..,. .. ........_...., __ T)(~,=: :i:: ,!!!'.:=-::>i

      PAGE 91

      U IC The U ni ve r sity of Illinoi s at Chicago Department of Chemical Engineering MS and P hD Graduate Progr am _,, ........ 1'1>.D.,,...,,_,,,,,_,,_ln~otfrtk.,1_ ... ....... r,,IJ.,C-u--,, .. .-..- .. Aot, .. .... .,r "' l'l,.l> .,U,.; "..,..,ot'"~'"""' '"" ,,__,..u ... .,.,,..,. ""'""""'"""""' ""'""'"" l,,.,o,, 1'1, 1) .. U., ......,,J.~, nl).o ,.., ,_ .......... ... -"-"""'-"'"''"'.,1 ........... __ ...,_ ... __ ,, __ ,.,.,~---..... ,, ___ ..... ... ...... ... ,. ,..,.. ....... """"'., .. _,. _____ .. .,.,_,.,. __ ._,..., '"'" -' . -..... ~"""',.,_, ___ ,,,, .. ,._.,c,.._,,. _,.,,_ . ~-""-""""""'<"8 C1o--ll

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      Chemica l Enginccr i n g a11he Un i vers i t y of Ill i n ois at U rbana -Cha mp aig n ;:=::::: .. -~ .... ~for ~ A Th:chrmoc,l,.,.,..,.,n'II-"""'""' TRADITIO N ::;:;;::~~~'""'-"" ~!!c_ __ _, OF ""'" " --~"'" EXCELLENCE =:ff:filf,_ ~~l::::~ :::M~U AntbonyJ MMd, P.,.,... Plo w ,_,.., M 0pu .. 1ueo,lco l E,ql.-,l0&Molo, po,1""'"'"'".-.1~,_,.,1 u.,.,,..,o<111,..,,, ,.u._."""'I""'' eo,.c .J R -Mom,l..>b 1m w, ~c i;1u .,,,.s,,.., u __ 111;..,,,6 1 S01

      PAGE 93

      Pr,/a10 .~ iona1am,_,<"..-....sily 3000~adua .. .,_ 2ffllg,radual851Udonts 3-lrom-ChicagOOrdl-Wfll"' Campusrea,g,-N,O' .. .,..,,_.,....,_..,._ AL=:::!:::.~r,,, 0/MITRIGICMSPOW (Ph D .. ffT) ,_ .. _____ --~:;,,:;.:=:!i ::1SA~A=:==) -J R06ERTSELMAN/Ph.D .. ~-Y/ E-----11'1'-~ St"HYM SENKAN(Sc D .. W1) ~"9' --"'"""""'D,\=-.,..~~~~...t=...Sla!<>U) OA=::: .!.Z!-:"~eloy) C,,0,-.G, __ .__ _., __ __ .,,_ ------.. ------

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      Puzzled About Your Career? One Move Could Make a Difference. :.a~~~~~~iltof/e~~!.cn~:~~:.!p~~':f~~~';;;=~:c~,f!~~:s~~':!it;~ engineertnggraduates.The lnstitulehas a nexc,,llen1rt!Ctlrrlofpropatlnggradua!esfor challengingandhighlyrowardingcareersinthepaper indu stry.ThelnsH!uteislocaled next!otheGeorgialnstituteofTechnologyandsharesrnanyoducationalresourceswith GoorgiaToch Studentseligible1oac,:eptemploymentintheU S.orCanadalff1generallyawardedfull tuitionscholar$hips ... wellassUpendsofS 1 5.0001oSt7,000percelendary...... Graduatesselectthesisresean:hprojoctsfromavarietyoftopics,includlng: For fonho,i,of,,...,,.,;.,.,, ,>lo1ta,GA 3031 8 (404)853 9500 Toll Fm: Nu,:~: t:;rnt~:~

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      IOWA STATE UNIVERSITY Tl~m;.,,.hoolond"""''"'"'""--i; ~ G~'f..!~~ ..,.,,.,1<>n,-,,..-,hW,....,.....,,u,..,.,,,.,.,_ l;.: .; ;: ;...'#.e..~ .. .,.,, of fluld,ondflud 0$ F..(;Jat, Bfoomlot7,..,.,.,.;.,, l ~C~~nK>, lu.t>uJ.ol, """"""''"'"""'po,t ,,,..___, __,i, KonnOlh R [oll, T~"""''"'~"'Km.eom,,.,,,,,,,.ph,.. T-;;.:r,; ;, ~i~ .,,,,...,,.__.,.,.(y, 11 .. n L.Ul1 lchson --""'""'""''mo a.,,,,,Jo,,c10,,,,,1p.<<>0l--i.,o,./Md;wn ~~~~~:;~m~inform,Hon, ple a>
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      PAGE 97

      Graduate Study and Research in CHEMICAL ENGINEERING T "' T Hr A B R H.RI Pn~~=M ICHAE< J. B ErvieAUCH Pn.D ~o<""'""'" --OOATOCl'lnlllogj M RC D. Doioot1o.<,n,,a, ==~ G EDF A A P A D fTICE Pn,D .. ~QIC-,.,.l)f,J; ... ~E~"II W M....._S LnuA N Pn D.,............_-..o1r~y T ,-.,~~ Polj'menc~ c.o-s.,.,..,..,..,_ W.H.Sci, w N 0,> .. T .. ..,,.,.,..,,,._,.L_ ~.. fo.tutffiMk ,! orma l loncontaet : n,.Jorins_,,,.,...._.,, G~=~E Johns ()0 1 1338-"3' """ Hopkins

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      THE UNIVERSITY OF KANSAS GRADUATE STUDY IN CHEMICAL AND PETROLEUM ENGINEERING r_.,,. __ ..,.,,.tom,.,,,. _____ .....,... __ ($!).0001011~.000-~ .,..,..,v,:gm ... ... ...... ......, ... ___ .......... ____ .. __ 28.000_ ::l==-~~= ~----___ c__ ----.. Olal ___ .. ___ =.::===..~.=.,.. ==:::.:;.: --.. fo, __ ..., __ .., .. .tt ...... ... _,..,,.....,.. ...,c;. __ -"'t>wNOOl-::.7~~2m

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      CONGRATULATIONS DR MARK E DAVIS Wf!UEAS M.,( E.lh,,. h., ...,., ...... ~thI ... rll C REAS.he 0q,on ...... o1a...-aa&w, ........ U,rufin1U1<,lJo
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      KANSAS ST ATE UNIVERSITY M.S.tnCIPll.D ~ --.. '-~ --~ ForMorltn!OITnatiooWrilll!o -u ..... ---~--~ :=-a= -...... ,_ --~ -----.:----

      PAGE 101


      PAGE 102

      U UNIVERSITE lefBIAVAL Quebec, Canada Ph D. and M Sc in Chemical Engineering R esea r c h Areas CATALYSIS (S. Kaliugui,w / BIOCHEMICJ\L f:NGINEE/l/NG (L. ChopUn. A l.cDuy J.-H.More<>u.J.Thibault/ f:NVIRONMENT/1.L l!NCINH' WNG (//, S 1/nmalho C.1/oy) C0.111'/JTEI/ 11/Dl!D 1,WGINEl,'/1/NG (P.A Tanguy/ TECHNOI.OCY MANAGf:.\ft:,vr(P, -fl. Roy) MODELLJNG ANDCON1 1/0l (J. 1"11ibau/1) 1/1/EO/.IXY AND f'OLYMHI/ ENGINEER/NG (,U,l.Chop/in,P.A.Tanguy/ Tf/ER,\IODYNAM/CS (// S. 1/umnlho, S. Koliaguine) CHl,;\11('.,ll AND IJI OCl/t~ \I/CAL Ul'GRAD/NG OF BIOMASS (S Knlin g11ine, J\. l.cDuy, C. Roy) FLUID/SAT/ON AND Sl:PAI/AT/ONS /)\' MEM/Jlu\Nf:S(B.Grondjean/ ,.,._..,~ ... .. ,,. ~""g;,,.."""' ,_,,.._ ., .,. ~ ..-...i.... $oiw-Foy,a:.iboc;CMIMUG1K7P ~zUOSIJ.U!OPLI~ IJ GIANlllf ,,i 1'1, ,D.&ol.l'oly.--, -0 ,Mf, / .G C.T.....,_ ,..,,_,,, _,, .. 1 -a..,11,o ,1:1110T .....__ A .,, ..... JEA" Mou: ... u ...,._. ,, RUat:.,sS.llA.\IAUK) -PAl L-U RO~ ,., .,, __ ...,_
      PAGE 103

      Synefldb<,in tndi tcipliowy l'Csatdl ia =~:',;~~ l'n:>cn 1 modelin 1&contro1 M"l1ipt, ...,pr,:nssin1 ludin1 "'~ LS. and Ph .D. dc,=s mmcmica1 ... ,;-..,an,;1po1yme, .,,;.,u&cnJinotrin1 Superb facili ties Oneol 1 Mlar1c<1docLc:m,PA1801$ W e promi se the challenge ~~~=.=..a H" goS.Corom(llo,..,.;, ----liqoid--1'"'"-' -M lMna...ta ~-d-~ _..,...,,.., ___ J""'1C.O,..(Uoo..._,.dMicllpo) :::--'-Pi
      PAGE 104

      l9ws1ana Stare Un1wrs1ry CHEMICAL ENGINEERING GRADUATE SCHOOL THE CITY ... .. .,, .,., ......... ,, .. .. _, ..... )', otm ~ o1,.,i .. ., ~,,., .. + LSU. '' ""' ......... .. ... . .. ... ..... ........ """" .. C. )ooc.tlo m. r., .. .......... 11,0/ ...... ,,, _,... ,, .. .. ,,,,. ....... ..... .. ,. , ,. .... ......... ,,k~ t w o l-. t, h o. T 1"''" "' ..... ,., .. .. ...... ...... hlt lH .. ,, .. ... ... .. ...... ,,., ..... .. ... .. .. .. ., ... . ........ ...... .. ........ . THE DEPARTMENT ,.,. ,., ,,. ,, ... ,o,..,..,,,... ,, .,.., ., ~ -~cc '.~ Ro. '."'GC I MS, "'" fl-N M~. ,,. ,. ..,. .... _, ... ., .. .. ... ........ .... ,.,.._. ......... .,.,iOO,. Y( .. 0 .,Do .. rn) "" "'"" '" .... .. Glllf''"''""-D .. ..... .. .. M0< ....... -C o1>11 '" llwlm M,t -~ - J Govn, .. o ....... .... C,,,,J. M 04 ... S'lu,tloo ......,,.., o. -OSOt<< ... o .. .... , .... .... ..... ,.-., .. ,w .. .. U.JOHHSCNC .. D .... ,> 1>1o .. .. c,,,,0 .... .... M. "'"TN< .. O .. ...... . ..... .., ... .. _, _, .... .... .. "-' .............. ...... ..... .. .... .... uuo.._ .. ,o.s. .. ..... ,, c _, .. ... .. .. ,.,. .... .. ... .. ........ .. ,,, o .w. ,.< ... o . -..,. .... , ,... o, .. ''" .. ~. ._,.,.. ,., ;,,, G,L,l'lt!O<( .. O . lti ... .. .,_, c.,,.,,h llw fom o.o .. .. ........... ... ,. ....... .. FINANCIAL AID ,n,o": ... .... ,,e~o, .... ~ "'"t 10 .. .... ., .,5,00<>,.,, .. ........ ,. ......... .. . ... ., ... ,,. .... ,. .. . .. :: .... .. .--:. :: :~'",:~ ...

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      ==----~ '~~ . ....:: ~.;,.. ~-~--~ ____ ._.._ _,...._,.N._. ... ................... __ .,,. ... .....

      PAGE 106

      University of Maryland A.erOOOISclnc. MillC_,.ln T &llgenee ~''",:::t'"~ Nelro!Con-c,ulalion Pot,,merProceSP>g =~:,.,.ll<>ocfl<>'>Eng~ ~=.:.:~:cMOIOQY sv.,em,eno1n&e11ng Turt>IM>r>eeondMbc!ng For~inclF\rlher~ion,Wl'l9' Ct>&mlca Eng,-ng Gmc>..iatesn.odi/lvo1Mo-ylond Colego?ol<.Mcl:10742-2111

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      UMBC : m1 huoi, Th, l, lll!C (:l,e., i,al t : n ~ n.,r i n ~ p,..,. m .,ff, .-, ,.,1., ,.. l"" ~ no, ~ lo \l, S. rnl l'h.l) I, ~ .....,,;,, m I t : ~ ;,.,~,i" J ~ ;,1, pcitn a r i rd, r, . ,., i n l,i,. 1,.,mi,ol,,., ~ in,,ri" ~ F n c ull y G F.Poyn,, Plt.V.' Mido~n s.J.Ct>ppllo,l'll.l).' ""'" "" .. .. ~-femw,<1off-U .. ,,,..,,,.,. /!.-po "" loN,-_, ,,,,.. ,1n..:1-r,,S. < __ /.tl.Li,mpt;n,l'h.D. l'wno,y ..,I .,, ,., ,,.. ,,,, .,,, .,, ,,.,, ,,, ..,m, _,,._, c; _,.,.of A d,p,;::::;,:,. : ::;,.~/Jicp,oa, M.11.S!Ma,Plt D. -S.. .. "'- .... -"&;S >o-dl_...,.,.., ,._,. ,,,,,, ,,, ., ... G.R,,o,Plt.O.' DNoc I A n/.., J .,., .t,. _. ~10,,ldty;ll!o#,,,Jn1 /.llo.nb/ort,Ph.D. Bnh lo:, ::::::-.:.. "W-"&'Vl'v&d
      PAGE 108

      University of Massachusetts ____ at A mher s t M.S H11tll'h.D.l'rogramsi11 Chemical En g ine er in g fl~,,ollJi,0;1 1 ao;-..Aol-10;.,, (ho, o l liiun '. ;"':"""' A i ~~----0 ... l noiliun lJ -'-isna nd Con oroJ Cenw, ____ n .. ,,.,,.~menl h.,.,,,,.,,.nhcon"~in,l .. i>(fl on d ,;ont'". wh ch "I""''' '>: n,h'> tf al n.A,,.,.,.,.,r .. 11 1 11 Now 1,.1 0 0<11-o l ow.,, ... M-~n .,,.,_ ... 0 ,,. ;,1 r ,,1,.,1 .. 1 .. 11i ~111,. ,~. ""'.'-'" 1:loo":'~:i_i, i~,..,O"i too .,. ...... ,.&..__, ....... ,...._. ,....,.,.,., ...... ,.._,, ....... _. ,__. _,,....,...__._.,;,. C'U[X'ATI,_._, ... ., ,. fPo\"lT>IIXTOl'Cllll l-1 !HCX.. A~>,U.--rcY rncwwA-ClH'I-.TTI

      PAGE 109

      CHEMICAL ENGINEERING AT MIT .. ,,_ G..'.. _ u., :. "--<: ____ ,,_ C_,A_I_ --,<--n----~"'"'" u -. .... < -,., ,. .. ......,__, __ ,.,..,_ .. _,,, .. u.,.-~"-"" !d lT_,_ __ ., _, ____ .. ____ ., _____ .,. __ -~,... ~---"'..--....,..,.. Eac-~-o.,,-, _. ...,. ..,,,__ _,..,., M _,.,.,.,..........., .. 1>o,.,, 1 1 ....... _"1<., ........... F. ,..i... ,i .,. l'n ltt, ,_ ...... .,,,p .,...., ... """"" "' "'flo""olld!d "'-"""'"" ""''"'"' 'l'P'' ... ,_ ., _r_s._ ,.,..,_.. 'f"8<1 ..,,.,_,,. ..... o1 ,.."""'"' s, """' s.,o -. :=.. ~ ...!!:7:'.:.:..~ M ~= .. ~.-i.N< ~Y ool.-'O,,....eo,po.._ ,.,. ~_,,,.,c. ;,_,..,,......,,._, ,,,,. ___ ,,_..._.,.,_ .. _____ .,_ ,_,_ H ,,,__, .... .,._,,__,,,_,,,, __ ,._,,,.,...,,,_..,.,,,_ -------------"" "-'-"-_,. _______ ,_,_, fOA MO R E INFORMATION CONTACT : Chemical Eng,r_.;,,g G,~1, Officlll 66-366. Ma5$8ChuSettllnsllluteolT9Cl'n>k>gy Carnt>nd98 MA02139 Phone: (617) 253~579: FAX : (1!11 7) 253-9695

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      Chemical Engineering at The University of Michigan

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      GRADUATE STUDY IN CHEMICAL ENGINEERING AT MICHIGAN STATE UNIVERSITY -""~---""--"""" o .....:.::' '''_.... nCLOWSHO ,S ---""'"".000.,._ ..... ._ __ '"'"'' """............. ____ ., ___ """''""' ""' --_,-~---'"'" '""'""'"' ---------c---C.W .COOl'l!R. _l_u, ..... ..... __ ,, __ .,_ _____ .. "'-"'""-"""" " ....... ,...,..,, ........... ........... ____ ,,_. ______ .,_ '"'"'"""' ............ _.,_.,_ ___ ., __ -----"""''9'0."""'_,.,........ ------' "'"' '-"' --..... =-~-===-:..":::-::-..:::::P'tLIL '",__,,_.,.... --------"-"" '"'"-..-.. _____ .,,,_.,._ "'"''""'-..-_, ...... .,_,_, __ ,,_ c....,...c-,._,._.._ ,..,_,,.,.., ............ ., R 1" A llOfT M = a., """"'"-"";,._..., . .... "-=" .. -'=,,. .. .. ..,,. __ ...._ ... __

      PAGE 112

      C H E MI CAL E N G I NEE RI N G M ichi g an Te chno l o g ical U nh' c r si t y P N>< ... ondplan < dNlp -A.&m .. ANo,,; ... Ph.D .N .. Mmo>Sta1o. l OBO ~~ s::~$. "7.;._,d),,an,J~ ,, ...,_,.,n <,ol o.o y ""'"'"' .,." Tomue.c.,.....-,Prof~-,u no f ,.. ...i .. ol.1 ,1o, ..,p.....,_ Ed w .,dR.f;,lw,l'r<,l'-od l! ad Ph.D.Johnol!op!;n,un;,..,..;,y,l961i ";:' .... W H ubb....._""".. o1o ~ p Ph.D Un,._.,;tyof W -n M ad-, l tM "-oon ...i ,.......,.., .,..., N an, K.K; m,,._;,,."""' Ph.D.M ..,
      PAGE 113

      UNIVERSITY OF MINNESOTA C h e mi ca l E n g in ee rin g a n d Ma t e ri a l s Scie n ce For in/<> r mation and application forms, ..,,;r, GraduateMmis.sion, ",:C,:;;~l~=gand Unismityof M in....,.. 42\WashingoonAve.S.E Minf'>Capolis.MN 5S4S5

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      Departmemo1Chemica 1 Eng,noor i ng UNIVERSITY OF MISSOURI ROLLA ROLLA MISSOURI 65401 D r.S .L.R ose n Cha l rman Day Programs M S and Ph D Degrees FACULTY AND RESEARCH INTERESTS N .L BOOIC/,.,,,0 ,.Color-/ ~--Dos,g,, O. K. CIIOSS EA {""-D .. -) "' ~ M LF .. C>I.EY(f>lt.D ,,-/ --U.0.J.W.JOtlNSOH/"" D.""""''"' Odo> ~ A.S.KDEWNG( .... D .. Mi 0_,,../ -A.l,LlAPIS(""D.,Ef'H.2111/d>J -~ ~ o,,,.,, ...,, _""'9' G.K.PATTEASON/""O-.Mi t -J .. ,;,,g ,,_..._,,,,. &REED ,J A./""D .. MI-/ ..... ......,.,.,.,. .o..,, ......,.,.,.,. __,,,_ ..,... Udlr>dus tria/F911-0wsh,ps.Aidisalsocb/ainab/e//lrough lheM;J1erialsRasearchCenter.

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      Chemical Engineering ----'~-___ .. ___ ,_ _ .... _,,_ ---------------------~New -lnetitute of 1"chnology ft,,---0,_C ___ ,.,.._ .. -~ ---,,. ____ -t1111-U m...,._._..,..,_,,. --.. ..._ t_..,. ---

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      The University of N ew Mexico To 1c,n,,1,.dioaI proccs>int1of=amia Su r faceoci<.-noe n.ftoc"ut erial="'!o ..:t:":ii u.-.:en, ; =,::_ The uni..cBlly of New Mcrl<'O ,long .,llll S..ndla and LOo Alamo,f N ,, i.,,,,1 ,wdlocallndusuy,makcAlbuqucfj(:""'1lif,o ndresc.rch otnia, The chemical OnSOl1y p,nicipalc in thc SEMATECI I Cc: nt c r ofuccllcncel B OCmico ndu c 1 0 ,, coeo r ch ThcCcotc r fo rlll gh Tt>< hno ~M otcrlab ,ndth< l ... tltutclorSp..,.Nud,corl'Owo-srudla The O..mical l!ng;nttt1n3 ~runen< olf.,. r.,..,.,..1 aKI In Ill< form or,..,,:h ....asunu hi Pfpaying$1()-12,000pet yea p1.,.1uUon. Out.!Und;ng.,.ud "'gg,:d m0Ufll.iitlou$ .....,.., p,S..,_lin,i,h ik ingandwhitcw"cr"fling. f
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      CHEMICAL ENGINEERING NORTH CAROLINA STATE UNIVERSITY Ren ,:y_, 11 ..,., .,,.n Ch, l ; n eS.G,..n1 FA CUUYAND R HO. l!CH I NTUtUl1 C""'p,,r,,s>.wd MMf ""'""llllofSp,;,a/tyC.... 1,, / ,_.,,.S,Mlo /u,,o """"'''"""',,..,r..,ufw.--C..,""l-Guq;,atFW,,_,,..--ie... ,., s,~..., n w c.,. t1I (',...,,.,,t:;:f,t:,:.'"""'"E"",,.,,.""Jl:, ll ,c""'ml.l',molC,11 f'"'!1' W ,-...., /f _r::"'.S:.::%/l-'-K<""in;-..,,E..,,_,..-, C-.i:!'.:,Sot...,.,...-..""""'--&o,.--,lJJ,,__,,,

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      Chemical Engineering at Northwestern University S .Gettrino( E Tu,,-l'apo,otNtlo Hiochmole3lc...,;onttru ... "''''""",.;Pl)lkatk>""'""'"'" o ., ,.., Rya>Jn """""""''"""' ........... ...,.-..,,.,,,..,.,,.. ... r "' wo11, ..... H .hnd o pol" onlo
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      Gtihiilb111@itiPiii at Notre Dame The Uni ve.-.ity of Notno Dame offers prograffll of gradu.a\.e 1 tudyleadingtotheMaoterofScienceandDoctor ofPhil-,phy degreeainCl>emical Engineering. The n,quirementllforthe"""'' 1 degreearenormallycomp]et.ed intwelvetofourteenmonW.Thedoct.oralprogramrequire o about fou r year11offull-time0Uidybeyond the bachelor degree. Thee-e pr<>gram& ean u.&ually be tailored to accommodate8tudcnt11 w h()S(!undergradua1.edegree 1 a re in areao of oci ence or engineering other th,m chemical engineenng F:inancially attn>.ctive fellowohi po and a8" iatantahip 1 whlchincludeafulltuition waiv er.areavailabletootudenu pu rsuing either program. For further information, write to: DepartmentofChemical Engineerin g U nive rs ity of Notre Dame Notro0ame lndiana46556 FAC UL TY J.T. Banchero J.F.Brennecke J.J.Carberry H t f h~~1f J.C.Kantor J.P.Kohn D.T.Leighton,Jr MR~ t~~.:i~: W C Strieder A Varma E.E.Wolf R&SEARCH AREAS Advanced Ceramic Material Artificial Intelligence Catalygi o andSurfaceScicnce Chemical Reaction Engineering G aa Hquid Flows Nonlinear Dynamic s Phaoegquilibria Polymer Science Proce DJ'~~~: :, ri;J;;;~r;! Supercritical Fluid S uopenoionRheology 1'hermodynamic 1a nd Separation& 1'ranap0rt Phenomena

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      O h io Univers i ty Chemical Engineering q

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      GRADUATE STUDV IN CHEMICAL ENGINEERING W HY --=-OhloStato1org,adua t e'1udy ... C-al ~?Somoofthotac,,lllalmayin_,,,.,...,-....,.,., .,.., ... --.,.gt,m$10.000I0l 1 S.000......aly,pli)o We-..ldb9gladtopn>OOO'IO0<1S B,odk e y ,Wisconu'l!952 Turtlultnet Moong lrnago.t.nal\'$1$. Aeacl0<""9".0ll(IR!loology .ltHeryJ Chalmen .~1!18i!i,_E_"'ll,Pr"'""1E x cre ,.,,,,.... ____ ...,C.OA-...::to,08"9" o mHF.Dav ~.-""nlSl!l.'.-1ot-.,ce.~Dnlg,l,a<'lomaocaiMocloon; = H Fr i.o m o n .""""'-'r96r.BlomodicalE. lll'lo Sta'8 1966, Ro,._,, E-. cata!ysc, a.-.;! ::: r;C .-,...., .._./lofl,l!"6$ Tl'IOffl""11'nam1CS Or.!O,ogRoOnC,Oochllmoeal Thom H L s-, Cass !962 Ml'ollul""1ContrOl Heal T,aos .... a.., Leg>IAsf>O
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      PAGE 123

      P lliN Un i vers it y o f P e nn sylva ni a C h e m ica 1 E n gineering St"W.Cliurysicl>I --Sl1,dcn,.mayf,,1rhe;r.rud;es;,..,,.,.of,M"""""""om>1of 11H,dn.....,,_Th,,fu//,_,n,,of1h;,ivy~.,,.l>'>clo#li"1 1he\l'hanon$t:hoolofllu,l,wuand.,,,..ofthi,ca,nr,Y1/o,,,-'n..Jiro/ ~,.,,.,a,.,omUaW..ro11uMnl,inl1Mi,,,_m.TllocuNurolodmn,_ hi,lorirolauel,.and ....,,.,., /ior,a/fi,ci/i/inofo V"' ldlyo l'lf Milhm..-olk in5d/GlanceoftheUni ..,r,//y Dl.-o(Gnd...,o.W.... ~ol~ll:nfl.. 31LAT_,_8u;ld; .. uo1, ... 1,,o1-.uy1 .... i. l'h l~ lph ;. ,.....,,, ,yl,..nU19100.ff393

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      PENN STATE 91 \. ,-~:,,~ . .,1~i ~-1" it~ ...~ .... ___ ,, __ ... ... ea.,..,., ,_ -LMK'.:OR.COI..,. ,_ way,,ocut11s ,...,_, AonololP.~ ---ThomNE.O.._ ( __ ) -- ,..J.Engo+ ___ .,_ _ ,_, Jd>oA.F,_. 1,.,,.1 -~Kn alOnF"'"'"""' l-1 ----~ -.,L K _(W ----Jollo A Mo -1 -~......... ..... ,,_,_, ______ ,, __ __ Jo._s.u- , ,,_.,..,_.__c,,,, ,. _._,v_ ,_,s. v ,_. ,_,) ----

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      University of Qu ee n s land ADJVNCTSTAFF 0.1.,,R>I AppliNIMothematiO"S yat< m1 '1\ ,. .. Cu ll u,.. En,y,,.. f;n~n..-,ing l\nvirnnmen"'lControl P toss f:..omi <0 ~hnot a l r.-ing Ad...,,,_"'11 1'tombr onol'r<""' Hyhridom T t< hn ology 1'-um.,iownbuilding i 1 woll 1 up])O>'ttrali.a, with ,no,e 1h o n 18,000 "dento Bri obo n e, ,.;th J::"::~t:.,::~::;:i.:t;on, pleasont
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      Rens se laer Ph.D. and M.S. Prog r a m s in C h emical Engi n ee r ing A dv a n ce d St ud y a n d Research Areas a Advanco
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      Rice University Graduate Study in Chemical Engineering u.,-,....,Gmd ... ,.eom m,_ llopartmmoo!Chmlf<,,.,.tllond;,,3candldat., Facult y : ~~:~~:.::~~c::::. ... ,,,,,, -=, ... Wol1..-Cli,1!1M) Samll.Unls,lr./Mff,1957) 0.tol.C.Dyoon/umdon.1966/ J.Dovid!lollu,o,{Mkhi/J"n,I961/ Joo\V.ll~IOWff/}ohnsllopl:in, J/1,;JJ ~ilJKoblyoshl /Michigo J : :; .. ~,:,~1~:1'; 1 1~:~::,,:;2:!1 : ~~-~;: s.~~:::r::: 4 t" o{Te
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      C h e m ical Engi n eer i11 g a. I tli e UNIVERSITY OF ROCHESTER JOIN US .. -.r '1fi;-~,11.; _/,! ;~v 1 C:n,duo1 0 Study o nd 11...., orc h l ...i;n,to \1 .$. nd l 'h.D ...--. s.. ...... -....,~,.,.,.,,._ .,..,;i.1,1.,,.... fttttinJ"'IOdn,. .. ..,~.. -0 "'~:-, s F ac ult y 1tnd R ese1tn: h Are11 11 !J. U .CHK.,;.rt,.1) _196 1,M,n Pr,J:,-,S,.,,.,.Hdf: .... -,q,Th, ___ "' ...... "'""""" :. u .c 1n~10w 1 T1" Ph .D _J982,c.,,.....,""' ~=,.,__..,1,,10,..,, . s.,.,,..c,,,.,.,1ix1.,,,.,,,.. Jll ll.FV.ISl!lmn .l'llll,1"611 l"n c-,,i,, __ S_,lpp.,.,/,lo/-l"" .1 .C. FllllsOl l'. l't,_l)_J965,C a h'"'ij.. A..IK.>IY.K II K. l,i_D1!185,)hn /~S,---o...iKq,-,-,:./f _,,,a...i "'_,,.,,,,,_c,., .. >rnt111 .... 11:..,.,,_.,.,._f __ ~_.,.,,._,..1M.,,.-.C,,

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      The University of South Carolina Get to the Point!

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      l'nc ul ty J.A.llie .. nbo,t,&T(PhD,P,in,;et,,nU.l G,B.0.lany(PhD,Pitubu~hU.) C.G.Goe,,o( f'hD Pr i,,,,.tonU J R. G,;,key ( PhD, Ca,nii ln ~ Th.) D.M.Kalyon(PhD,M$"1ou(PhD,lpment G RADUATE PROGRAMS I N C HEMICAL ENG INEERI NG Full and p an -,ime J~ a nd evening progr-.m MASTERS C HEMICAL ENGINEER PH.D. ,,.., __, ,...,,_, ............ o.....,,,.n,ofci-u..., .. 4Cll
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      /<>hnC.lley,/u.,,mer Cy11thiaS.llirtu-/ (C/rninr,a ,, ) G,o,geC.Ma,tin l'l,ili1A.Ri u As Jrol Sa,ogani /~no ,.A Srhwa,: for info r mation : .,,_,.. w,11 ,.is-,,_ ,w, .~"""',.,m s,_.,,u,,;,.,,,,,,_.,,c_,.., Dr.Geow,C..\fortin Depwmwmo/Chemical Ent;~~;;;;i-;:,, re Syracuse University 320flindsllall Syrocuse U 11 i, usit y Chemi<~l E ngineering and Mterials Science Syrocuse.Nl'13244 (315)443-2557

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      Chemical Engineering at Texas -"... _., _ ....,mu UUJ4ll-o,tl --&0..--,. ----_. ,,_, __ ----E-OI~ -.... """"""'"' --~ --------_,.......,_.., ---~ -~ ---R.Bo:,ci,; ~ =_,_ ...,,_ -~A.I.Joi"' _,P,.._,. ~,..,_ E-M.

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      The University of Toledo Gradu a t est udy!ow&rdt he M .$.a ndPh.D Oegr MS A W$ta n ts hi ps nd ~ l o w s h i pti a Y a ila ble K ......,. n,J DoWin ,Ph.0 .. '-"'-"',-.T-...... ----...... l FouPh.0 .. -0I ___ ,."""'"'""'' __ """-~--~ --..... 0 .. .. __ ----"'~-"'1'_,,._..,,._c.y.u,;.,..,,. .,.,,_w ,._ _ P!>.O .. OhoStolo\.n -P,-..,,,Chomocai_,,__ -o.sq,---E~ .i.. '""" ""o .. -OI _____ __ ---~--~ ... _,_ ooof.Poln;, o-m.n.""-o .. -... "'-,~-,..,,_ -Vo,onool PhO.,Stolo,._..,.OI -v""'""""-,,,_,c_ _,...., ..,__ E.,,.... K......,._ __ ,,_ 0. 8. E. ,,__ ena.,,,_ _,,,_ .. ,,,._., / 419/53Mftl9

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      89 YEARS OF CHEMICAL ENGINEERING AT TUFTS UNIVERSITY I M.S.andPh.O.Programsln I Chemlcal a ndBlochem!calEngln M rlng RESEARCH AREAS ..,.........., ... ..... ., 0.,,.,,..-olcr.omal~ 1 ... ,~ -(817):)111-:IUS A P.!IINCJEAClilUfllO M """""

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      VANDERBILT UNIVERSITY Department of Chemical Engineering Gradua l e Study Leading to the M.S. and Ph.D. Degrees Kenneth A.Debelak ( Ph.D.,Kentu,;;ky ) -~_..,,,,,,,..._,<:OaJ __ ...,,,......,.$,$0,,r,,,,t,,,i.s~,.,,,., __ ,,..,. .,,.....,..,.,,..,.,._,_ Tomlinson Fon ( Ph.D. Tennessee ) =~ ... ------~-po/ymffl.~~ ToddD .Glo,gio (Ph.D.,Rice) Rl>eoiog;ca,asp,,,:uol!IIOO$/!l--ol-O'l/t~. Thomas M. Godbold ( Ph.D Nont1 Caro/Ina State) COll/py,oly,isllfldr;as,lica'10n;sullt;,,,.,,.,.,,,irn,m,""""";---~. John A.Roth { Ph.D .,L oulsv/1/e) ~~ ,_ ..,,_""''"'""""" '""""""'"was>tm.,_. ~_,,,. KarlB S<;hnelle J,. ( Plt.D. ,Ca meg/ 91,fe//on ) E-........i,on~:~r,oll,.,""IX><>W'. Roben D. Tan ne r { Ph.D . Case W estern R e -} ::::::::::.t::::::;:;,,;;;;;..,,"'!:.;;::::::;._"fllllonye,,;ri,'1Wlhaod,,,_,,_,.,.,,, V A NDERB ILT -"-~ENGINEERIN G --._

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      n,r .,.~.c .... ,n...i1,1oa1 GcaduMe S tudy I n Chemiul En,;IDN!cln,; at th e U n l~ ~n hy of Vlc,;lnla c;...,.1oc .... ,P1o.D.,U.innio,olDol,--, A-p1-,.,A-.,.;,,.,1ooi:., ..... B ..... ln1S..,._.,.,.. ~!i.'.,~~ 0 ;.r:!:':;.!'.".;.i:.i:'.-;-,::t1t~1:=::1 .... D<,r. ... Robo,1 l. o,.;,, ro.,s, .. fwd u., .... ~,, s .. 1 .. ci.. .. 1o1.,,c .. .i,,.;,,R ... ,.,.E.1i-1 En k J_,...-,.,,P1, D.,u ,_,,,,otc.wo..;..a..1o1tr o;.,.._,.iEoc......._,Mac-x-1..,.._ ::-...:.~ ~~-~!.'!.~.: E!-"L.Caoln,J,.,Pt,.D.,Col.-.Uo....,~r llio< ....... >1Eo1.,_.;"1,"'-Doo...,__MdO..,, :r-..:. ~~~::'1..,~f;~/;:.::;t:.ti;ii::::.,, llio<.,mX,I Eo1i-,i 1 ~f.!~l~f~?.:.!1~~R:~ .... r::~!t.~~:!.;~~1 .. ... ~e. ~:~~~!"",.;;;:~:-, ... a.. .. ..,, LoalMU.LilloloM,Plo.D.,Uoiwn~yolW...., f1>ool M .. h ;.,,, lk < "II--, M,~;p,hN Ir.-. Al<,.,;., Eor, Jot,~ P. O'Co ,11, Plo.D., u,;-..,..., ol C I"""';,, a.. ,1,y i:i,:/::/~:::-i"''""' w i,Appl~h,.. .. r,ox.i....i

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      Use Virginia Tech as your catalyst to a good education. At Virginia T ech's Chemical Engin eeri ng Departm e nt you will learn about: SUAFACESCIENCE modd"""'lr,,,)'>lt-...,....,.. ,...{,,;cdndlmmu.-11',oim,..,_;., .,..,,. .......... r:.,.._ ... p1i11<-. FUJIDPAl!TICLt:S'fflTEMS :::""~""'~ol POLVMERSCIENCEAHD ~-~"&"""f'holol1 =~-=~ For lu~her in lormalion, contaCI lhe OepartmentofC!i.....C .. Er,g.._jng, R nNdi<>J ;,,m.,...,.~ mobm,g WJ'...c.k DudiudbNb.

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      Thollopa!I01enlOllttst"'3<>J01<1 rucuchp .... ramtnde,o,llentph)'IICII ftcllltla.plu,.ouppMlotlllulltlOI O gndu1tootudonto.Approxlrn1toly11S ~1~.!:~-rn::~=1, .io.-. .... --._, Gloo ... ,.-.-"""'~Y-1 a.,.-,,ttllo1110W>d!"tc,,,hunolopponun1uaand1111por ollolodout<>utlho E;~:::i ... ;~:::,::~:!:~I Yourlnqulna.,.wolcom o. Fo,l,,in hor lnbmorlonpltuewn""

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      WASHINGTON STATE UNIVERSITY Chemical Engineering Departm e nt Hereat W ashingu,nStateUniveroily, waareproudofourgraduateprogram a nd ofourstudenui The program haa ::~ ':;i::t!t~ro'!:a~~d quality, Poradepartmentofthi 11 i..,,the range of facultyreoearcllinteresUlio very broad. Students choose rerieuch projectaofinterestt.othem,thcnhavethe opportunity ndthere1p0naibility to make an individual contribution. Througbacombinationofcorecou r&es and manyelec\ive o otudent o cangain a thoroughunderstandingofth.ebasi ce of chemical engineering ~,.;~i: :i~-~~~=:~..... -,-.--~ -~--.-_______ ..... _ :.:: ::: :-i--.. -::: ~~.=--~-;~~-. -_: ~a~~EE ~:~~""; R.1..-I Pn.D.,.......,.. y OIC<>lo, .... ); ~ """""....,.,_ ...., .,~,..-ono. -~ .. "'"91 GRADUATEDEGREEPROGRAMSaTWSU ===-~--Ph.0.loC.-_En$1_"11 ==:. t ==--~ .. ';.."'~ _....,.,....,.,, ..,.,.,.,_o_,.-,. oo <&C ........ t .. ,o,y. O,__,. c ..... 1 ,,.., ... .,,,,,.,_ ore-..., wg1.-ng, W1 olllng00,,Sl8t1.w....tty, ... IOIWl, WA N 1 ... 2710 ..,.,,,...,. ... ..,.,,, .. ,..,, 6

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      Wisconsin A tradition of excellen ce in Chemical Engineering =------..... ...... .,,._ ---------=------==--.. ... ._. ... --------~_:_--- . _.., ---------------

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      YALE DouglasD.Frey Ph.D.Berkeley Garyl.Halter Ph.D Northwestern CsabaG.Horvath Ph.D.Frankfurt James A O Brien Ph.D.Pennsylvania lisaD Pfellerle PhD.Pennsylvania TheodoreW.Randolph Ph.D .Be rke/ey DanielE Rosner Ph.D.Princeton RobertS.Weber Ph.D .S tanlord D9panmentotChem,calEng,ne<111ng YaleUn,ve,sity 2159YaleStauon NewHave n,C106520 Phooe:1203)432-2222 FAX:]203)432-7232 Department of Chemical Engineering Adsorption Aggregation, Clus1ering Biochemica/Engineenng Catalysis Chemical Reaction Engineering Chemical Vapor Deposition Chromatography Combustion Enzyme Technology Fine Particle Technology Heterogeneous Kinetics lnterfacia/Phenomena Molecular Beams Mulliphase Transport Phenomena Separation Science and Technology Sratistical Thermodynamics Supercritical Fluid Phenomena

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      Brow n (~i Grad u ate Study U ni versity \,ljl,.1 in Chemica l Eng i neeri n g f >ooOo
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      THE C I TY COLLEGE ol~ .!;_ i_!! Universityo f New York c ........ ,..~ ==-S:::E:..:.:' -s-6---"'""" ~.,.,c-:-.. -.,._, Grad uat e St u dies i n C h emiul En g ineering 11 ,t.S c. and D.Eng. Progra m s G.A.C..l-IC........ 1 La_,.((>._ ..... ) D.TH-"'fll'J'I> D.I. __ _ .... d!'~------==r-

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      HOWARD UNIVERSITY Chemical Engineering MS Degree --Facull y / ResearchAreas -M. E. /lLU KO ,Ph.D .. UC(S.ntaS.rt>aro) ,.._,,~_,,-c-,,, __ _,,, J N C /l NNON Ph.D .,Color adO ----r-.,f-S, A C.C H A WL ,., P!i,D.,Wa,,..State IIN
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      Imperial College of Science Technology and Medicine University of London Department of Chemic! Engineering nd CllemicI T ec hnology .. ,..,_,, ,_""_ .. .. ..,.._..,. ... ....,. ................ ... -,,-~.._ ... ,_ .. ._ ... ,..._ ... ... _""""'.,,..._.,. ......,_.,., .. ,._. _,..,. ,...,,~_,..,,,.,.._ .. .... .. .. _......,. ..... n. c.....,,,_.__..,._ .... .. ___ .., ,, ...... ...... _,_, ____ ,._,_ ..... .....,._,.,._. __ ,..,.,.,_,_,,.,. ~---,,c_,_,,, .... -; .. ,..,....... .--_,_,_;/,r;,,,, --,...,,._.,.,_,,_.._,./.W.lo .. -,-1""oo /l'l,.<> .. r, ___ ,_ .,..., .... f .. "'"'y .. .,,.., ,. 11,.11.,c, .1p;'';.,,x.,;_,.,, c"lr.,,., , ,.,_.,_._, ... ; ....... . ,..,... _ ,,._ ....... ,.,,;,,. .. ,)' ....... ,,.,.~ .. ___________ ... .......,,,__. ,.,,.. .... _ -., _,_.,c_., l """"" ._,SW70BY,Ult ~fil[i;jlfillfil []l]~~W~OO@ml'W Graduate Study In Chemical Engineering Master of Engineering Master of Engineering Science Doctor of Engineering FACULTY : 0. M .C M(M ( P tl.0 . 0lll>Om S,al t Un/o,./ J R HOPPER (Pt1.0.,Lo,,S,a,.Un1"./ ,T C.MO (Pn.O .,K .,,ussi, .. u,,;,, ,J ![ : f ~t~f : ~~f;:??l!/ RESEAACHAAEAS : .__ __ __ ,,_., _,,_,..., __ -----". ,, ___ ,, _ _ _,. .. ..._, __ _ .. _,..,,co., ___ _ ............ _,_ ..__._ .... ITI! ---....,---

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      Manhattan College Design Oriented Ma s ter's D e gree Program in Ch e mical Engi n e e ri n g This w ellestoblished grodoareprogromemphasizes t heoppliulionofbosic p,inc i plestothe.olutionofproc,,ssengineeringproblem1 financial1idisavai l 1bl e ,inclvdingindu11rial fe l lows h i p> ;n a on.yHr program involving p,,rt i cip,,rion of th,e following comp,,nies Al,Product ndC he mlc o l s, lnt E u on Corpo, o tlon A K ZOC n om ~ o l o lnc Mob l! OII Corpor o 11 on Con1olkl a l o d Edi so n co PII H r Inc JlOMltoC.U.g,i,/omtli Riunlal;, H aUm
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      Princeton University M.S.E. and Ph D Programs in Chemical Engineering RESU RCHAREAS ~;~;c,..,,_-.,,..~E~.-~.CobdM__,. ~"'-"'9":-~:Po/ymMSc.Mco;,.,_ec,,,,,,,,F,-o/G,lnJW-. ,,,_, __ ,.,.,.,_,,. __ Aoldt,_Soill,Q:~--E..-.. .M18,,w,,;g.,.-(.c.; to F'l>Di'""""") S.H,C .. PhO("""'-"') R.H C.-. F'Ml(-~) R.K COGO PhO (Comol) A.J, .,_,;,, PhO (0-") J.~ PhO(Tot"""') M.f A.Pl'IO{T""""I ~.W G,.,.._,_ f'hOIO.-' ol 1.J .... ""PhO llkMn1-! C.C.Hou ""O(Tuu) P J l,l,; ......,?hO IO.-'ol 8.W.W how .. iPhO l"""I --==~ _ .. ~-=-=-==_ .. a-.i..a_ o.--.... _..._.,.,._.,_ ,._,...

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