Chemical engineering education

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Title:
Chemical engineering education
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CEE
Abbreviated Title:
Chem. eng. educ.
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v. : ill. ; 22-28 cm.
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American Society for Engineering Education -- Chemical Engineering Division
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Chemical Engineering Division, American Society for Engineering Education
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Chemical abstracts
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Also issued online.
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Publication suspended briefly: issue designated v. 1, no. 4 (June 1966) published Nov. 1967.
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Full Text



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Fall 1993


Chemical Engineering Education

Volume 27 Number 4 Fall 1993


AWARD LECTURE
198 Interactive Dynamics of Convection and Crystal Growth,
William N. Gill

FEATURES
154 A Course in Applied Bifurcation Theory,
Vemuri Balakotaiah
162 Molecular Level Measurements in Chemical Engineering,
R.J. Smiley, W.N. Delgass
170 Applied Stochastics for Engineering,
Jay D. Schieber
176 PICLES: A Simulator for Teaching the Real World of Process Control,
Douglas J. Cooper
182 The Quest for Excellence in Teaching,
Raffi M. Turian
184 The Free Energy of Wetting,
William G. Pitt
188 Microprocessor-Based Controllers at Drexel University,
D.R. Coughanowr

208 Learning Through Doing: A Course on Writing a Textbook Chapter,
Phillip C. Wankat

212 The Du Pont Teaching Fellowship Program: 1991 Teaching
Experiences,
Steven A. McCluney, Ronald D. Shaver, Greg Fisher,
Michael Luyben, Linda J. Broadbelt

CLASS AND HOME PROBLEMS
206 Thermodynamics and Common Sense,
Octave Levenspiel

RANDOM THOUGHTS
194 What Matters in College,
Richard M. Felder

REVIEW/OPINION
168 The Changing Role of Academia,
Julio M. Ottino

DIVISION NEWS
196 The ASEE Chemical Engineering Division Lectureship Award,
George Burnet

161, 167 Book Reviews


CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the
Chemical Engineering Division, American Society for Engineering Education, and is edited at the
University of Florida. Correspondence regarding editorial matter, circulation, and changes of
address should be sent to CEE, Chemical Engineering Department University of Florida, Gainesville,
FL 32611. Copyright 1993 by the ChemicalEngineering Division, American SocietyforEngineering
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, Chemical Engineering Department.. University of Florida, Gainesville, FL 32611.










A Course in...



APPLIED BIFURCATION THEORY


VEMURI BALAKOTAIAH
University ofHouston
Houston, TX 77204-4792

ifurcation theory deals with the solution of
nonlinear equations and is useful to chemi-
cal engineers studying nonlinear phenom-
ena. Most of the traditional courses on applied math-
ematics offered by chemical engineering departments
cover only linear analysis. While linear analysis is
necessary, since it is the foundation of all nonlinear
techniques, it does not prepare students to deal with
the nonlinear problems that will be encountered later
in research. This is especially true for students work-
ing on stability problems in fluid flow, heat and
mass transfer, catalysis, reaction engineering, con-
trol, and separations.
For many years we have sent our University of
Houston students to the mathematics department
for courses on differential equations and dynamical
systems, bifurcation theory, nonlinear dynamics, sin-
gularity theory, and group theory. We found, how-
ever, that many of these courses were too special-
ized, were abstract, and had a narrow focus (from an
engineer's point of view). Typically, a student had to
take three or four of these courses to grasp a few
useful nonlinear techniques.
To address these problems, in 1989 the author
designed a new course on applied bifurcation theory
as a sequel to the two-semester applied mathemat-
ics course taught by Professor Neal R. Amundson.
The course was well-received by the students and
was repeated in the Spring of 1991, and with some
minor changes and updating is scheduled to be taught
in the Spring of 1994 and regularly thereafter.

Vemurl Balakotaiah is professor of chemical
engineering at the University of Houston. He
received his BTech degree from the Indian Insti-
tute of Technology (Madras) in 1978 and his
PhD from the University of Houston in 1982,
both in chemical engineering. He worked as a
Research Engineer at Shell Development Com-
pany and is a consultant to Exxon, Shell, and
the Westem Company of North America. His
main research interests are in the area of chemi-
cal reaction engineering.
Copyright ChE Division ofASEE 1993


COURSE DESCRIPTION
Introduction to Applied Bifurcation Theory
The main goal of the course is to expose chemical
engineering graduate students to some important non-
linear techniques and concepts. Table 1 gives an out-
line of the material that is covered in a fourteen-week
semester. Although the course is for 3 credits, 28
two-hour lectures are necessary to cover the topics
listed in Table 1.
The course is organized into six topics and two in-
troductory lectures. The introductory lectures give a
brief history of bifurcation theory, examples from vari-
ous disciplines, and the usefulness and limitations of
bifurcation theory. Several chemical engineering ex-
amples covering fluid flow, heat and mass transfer,
catalysis and reaction engineering, separations, con-
trol and multi-phase transport are selected as model
problems and are used throughout the course to
illustrate various concepts. All the examples are
deterministic models and vary from the following
simple (but non-trivial) two ordinary differential
equation models

= -a+(l-x)exp 1+07 (la)

Le +B(1-x)exp{ -a(0-0c) (lb)

describing the dynamic behavior of a CSTR in which a
first order exothermic reaction occurs to the follow-
ing, somewhat complicated, model involving a set of
six partial differential equations in three spatial coor-
dinates and time

V.v=0; Vn=-v- p-yez (2a)

+v.Vy= V2y+pDaexp 1 c (2b)
T Peh )r0~ cc+Y
Gc1 2 T1 '
+ +v*Vc= Vc-Daexp 1+y (O Pem (I' )+yc'


boundary conditions:
at the wall
at the inlet (z=0)

at the exit (z=l)


v-en=0, Vy.en=0, Vc-en= (2d)
y=O; c=1; vz=l (2e)

-z=o; l=0; I=I-1I (2f)
Chemical Engineering Education
Chemical Engineering Education










describing flow maldistributions and hot
spots in a down-flow cylindrical packed bed
reactor. After a brief discussion of model
formulation and the origins of various
nonlinearities, we discuss the advantages of
using the function space formalism. It is
shown that most of the models can be writ-
ten in the abbreviated form

C = F(u,p) (3)

where p is a vector of parameters, C is a
capacitance matrix, and the vector of state
variables u may be expressed in terms of the
elements of a function space having certain
properties, e.g., satisfying differentiability
conditions and the appropriate boundary con-
ditions. The function spaces of interest are
usually Banach or Hilbert spaces. The ca-
pacitance matrix C, the parameters vector
p, and the nonlinear operator F on the func-
tion space Y are identified for some selected
examples. Some of these include cases in
which C is not invertible (differential-


algebraic systems). For example, for Eqs. (1),
(1 0 (x(t)]
C= LeO, u= (t(t), = 2, pt =(Le,y,B,Da,a,Oc) (4a)
and

+(l-x)exp{0
F(u,p)= Da 1+0/y (4b)
a +B(l-x)ex 0 }-a( 0)

while for Eqs. (2)

o o 0 0 0 (v(z,r,O,t)'1
o o n(z,r,e,t)
C= u= pt=(Ra,Peh,Pem,y,P,Dao,H,ci,a) (5a)
o 0 1 0 c(z,r,o,t)
o0 0 0 ,y(z,r,9,t),


V.v
-Vn-v- y ez
Peh
F(u,p)= -vVy+ 1V2y+Daexp c
vV eh Vlc- +y)
-v.Vc+ 1 V2c-Daex T )c
Pem .1+y ,


TABLE 1
Course Outline for Applied Bifurcation Theory


Introduction
1. Definition and examples from different disciplines
2. Behavior of nonlinear systems; uses and limitations of
bifurcation theory
Nonlinear Functional Analysis
1. Operators on Banach spaces; Frnchet derivatives
2. Contraction mapping theorem; iterative methods for
nonlinear operator equations; uniqueness criteria
3. Implicit function theorem; necessary and sufficient condi-
tions for bifurcation; determination of stationary stability
boundary (Bifurcation Set)
Steady-State Bifurcation Theory
1. Liapunov-Schmidt reduction; elementary catastrophe theory
2. Singularity theory with a distinguished variable; classifica-
tion of bifurcation diagrams; construction of phase diagrams
3. Effects of discrete symmetry (Z2, D,)
4. Shooting technique with sensitivity functions; determination
of singular points of two-point boundary value problems;
singular points of elliptic PDEs
5. Effects of symmetry on boundary value problems
(Z2, 0(2))
Branching equations with symmetries
Dynamical Systems
1. Invariant manifolds; Hartman-Grobman theorem; stable and
center manifold theorems, applications
2. Amplitude equations; codimension 1, 2, 3 singularities
3. Poincar6-Birkhoff normal form; local codimention 1, 2
bifurcations


4. Floquet theory; degenerate Hopfbifurcations
5. Bifurcation theory for maps; normal forms of codimension
one bifurcations ;attractors and basins of attraction
6. Poincar6 maps; averaging method; Melnikov theory
7. Characterization of attractors ; attractor dimensions, K-
entropy, L-exponents; analysis of experimental data
8. Poincar6-Bendixson theory; degree and index theory;
group theory and normal forms; Hamiltonian chaos;
fractals
Nonlinear Partial Differential Equations
1. Linear stability analysis of coupled PDEs
2. Center-manifold reduction of coupled PDEs; amplitude
equations
3. Mode interactions; bifurcation with symmetry
4. Bifurcation in large systems (continuous spectrum);
Landau and Ginzberg-Landau equations; phase and
amplitude turbulence
5. Energy stability and Liapunov functions
6. Bifurcation theory for delay-differential, integral, and
integro-differential equations
Nonlinear Wave Phenomena
1. Review of basic concepts; physical examples
2. Analysis of traveling waves and pulses
Computational Methods in Bifurcation Theory
1. Arc length continuation technique; continuation of steady-
state and periodic branhces
2. Review of software on nonlinear dynamics and chaos


Fall 1993 155









and Y is the space of 6-tuples of continuous func-
tions in the variables (z,r,0) satisfying the appropri-
ate differentiability conditions and homogeneous
boundary conditions.
Next, an overview of bifurcation theory, and its
potential uses and limitations, are reviewed by a
discussion of the following frequently asked ques-
tions about nonlinear models: 1) Given a nonlinear
model of a physical system, what are the different
types of behaviors that are possible (for different
choices of the parameters vector p)? 2) What are the
regions in the parameter space in which the behav-
ior of a model may be described by a lower dimen-
sional simplified model containing fewer parameters
and/or a lower dimensional state space? What is the
simplified form of the model? 3) How does one con-
struct phase diagrams in the parameter space which
classify the p space into regions, in each of which a
different type of behavior exists? 4) How do the pre-
dicted features of a model change when it is sub-
jected to small perturbations (or equivalently, is the
model structurally stable)?
Theoretical, experimental, and computational re-
sults are presented for some model systems to illus-
trate each of the above four important concepts in
some detail. For example, the idea of constructing a
phase diagram of a mathematical model or a physi-
cal system is illustrated by using experimental re-
sults for Taylor-Couette flow'" and theoretical
results for the steady-state behavior of a CSTR.[2
It is also noted that phase diagrams for many
of the model problems (including the two above)
are not available.
The limitations of bifurcation theory are also dis-
cussed by emphasizing that its most important re-
sults are only local in nature and have to be supple-
mented by global techniques or numerical simula-
tions (often guided by the local theory) for a compre-
hensive analysis of the mathematical model or physi-
cal system under consideration.

Main Topics of Applied Bifurcation Theory
We now give a brief description of the six main
topics covered in the course. Before doing this, it
should be pointed out that each of these topics (and
most of the single lectures outlined here) is broad,
has considerable literature, and finds enough appli-
cations in chemical engineering to justify a full se-
mester course! As stated earlier, however, the pur-
pose of this general course is to present the most
important concepts and techniques in a unified man-
ner. Due to space limitations, we must omit many
details here. A longer version of this article contain-


ing details, equations, and commentary is available
from the author.
Nonlinear Functional Analysis The course starts with
nonlinear functional analysis which introduces the notation
and forms the basis for all later topics. First, the concept of
completeness and convergence in normed linear (Banach)
spaces is reviewed in a non-abstract manner. This is fol-
lowed by the definition of a Frichet derivative (or local
linearization) of a nonlinear operator, chain rule, partial and
higher-order Fr6chet derivatives, and Taylor's theorem in
function spaces. The model problems are used for illustra-
tion with formulas such as

DuF(uo.p).v= [F(uo +sv,p)l (6a)

D2uF(uo,p)*(v,w)= -[F(uo +sv+s2w,p)] 2 (6b)

for determining the Fr6chet derivatives of the nonlinear op-
erators (such as those in Eqs. 4b and 5b). Next, the concept
of a nonlinear operator being a contraction is introduced and
the contraction mapping theorem is stated. This theorem is
used to present a proof of the implicit function theorem. The
usefulness of these two main theorems of nonlinear func-
tional analysis is shown by discussing various applications.
For example, the contraction mapping theorem is used to
derive convergence criteria for the iterative method
Un+l= N(un) (7a)
as well as uniqueness criteria for the nonlinear equation
u=N(u) (7b)
where N is a nonlinear operator on some Banach space Y.
Specific examples dealing with algebraic equations (lumped
models of reactors with single and multiple reactions,
discretized models of convection), two-point boundary value
problems (diffusion-reaction and diffusion-convection-reac-
tion models in one spatial dimension), and elliptic partial
differential equations (diffusion-reaction models in 2/3 di-
mensions) are discussed. The implicit function theorem is
supplemented by stating sufficient conditions for bifurcation
and the form of the bifurcating solution in terms of the
eigenfunctions of the linearized operator. Application of the
implicit function theorem is illustrated by deriving the sta-
tionary stability boundaries for various physical systems
such as the CSTR with single and multiple reactions, classi-
cal Rayleigh-B6nard and Lapwood convection problems,
and the Brusselator model for stationary patterns.
Some lecture material on nonlinear functional analysis is
taken from references 3 through 5 and 'translated' by the
author into the engineer's language.
Steady-State Bifurcation Theory The second topic of
the course, steady-state bifurcation theory, is introduced by
discussing the idea of reducing the dimensionality of a prob-
lem, also known as the elimination of passive modes (engi-
neering), or the slaving principle (physics), or the Liapunov-
Chemical Engineering Education










Schmidt reduction (mathematics). This is followed by a
discussion of the branching equations and their Taylor ex-
pansions for finite dimensional problems and then is ex-
tended to infinite dimensional problems (Fredholm opera-
tors of index zero). For example, for the case of a single state
variable bifurcation problem (characterized by dim ker
DuF(uo,p) = 1), the branching equation is shown to be
g(x,p)= (v1,F(xy +W(xy ,p),p)) (8a)
where x is a scalar state variable (projection of the solution
onto ker L*), and yl,vl are the eigenfunctions corresponding
to the zero eigenvalue of L = DuF(uo,p) and L* (adjoint
operator), respectively. The function W(xyl,p) containing
the slave variables (modes) is defined by the implicit
equation
(I-E)F(xy +W(xy1,p),p)= 0 (8b)
where E is the projection operator onto the range of L. Next,
the main ideas of elementary catastrophe theory, such as
determinacy, transversality, and unfolding are discussed,
and Thom's classification and unfolding theorem is stated.
The geometry of the elementary catastrophes (fold, cusp,
swallowtail, butterfly, wigwam, and star) with the normal
form


k-2
G(Xp = x-k yEi+1Xi
i=O


(k= 2,3,4,5,6,7)


and their bifurcation sets in the e-space is discussed along
with applications to lumped models of reactors and equa-
tions of state in classical thermodynamics.
The next lecture introduces singularity theory with a dis-
tinguished variable. First, the distinction between elemen-
tary catastrophe theory and singularity theory with a distin-
guished parameter is explained. For example, it is noted that
the behavior of most physical systems is observed by mea-
suring their response as a function of a distinguished physi-
cal parameter or variable (such as residence time, inlet tem-
perature, etc.). In order to determine the different types of
responses (bifurcation diagrams), it is necessary to rewrite
the branching equation as
g(x,X,p*)=0 (10)
where X is the distinguished physical parameter and p* is the
vector of other parameters that are independent of X. Next,
the concepts of contact equivalence, unfolding, and normal
form are discussed, along with a list of defining and non-
degeneracy conditions for singularities up to codimension
three. The different types of bifurcation diagrams that exist
next to singularities of codimension one (hysteresis, isola,
and double limit), codimension two (pitchfork), and
codimension three (winged cusp) are reviewed. This is fol-
lowed by a discussion of the method of constructing phase
diagrams that divide the parameter space into regions with
different types of bifurcation diagrams. The appearance and
disappearance of solutions at the boundaries of the state
Fall 1993


variables and/or parameters is also discussed. The useful-
ness of the theory is illustrated by application to lumped
models of chemical reactors.
The third lecture on steady-state bifurcation theory intro-
duces the effects of symmetry. The occurrence of discrete
symmetry is illustrated by giving physical examples with
reflectional or Z2 symmetry (two coupled identical cells and
discretized models of convection) and permutational or D3
symmetry (three coupled identical cells). Next, some impor-
tant concepts of finite group theory such as subgroup, group
isomorphism, orthogonal representation, and irreducible
representation are discussed. The importance of these con-
cepts is illustrated by discussing the invariance properties of
kernel and range of L under the action of the group and the
structure of the branching equations in the presence of these
symmetries. This is followed by a statement of Thom's clas-
sification theorem for singularities with Z2 symmetry and
the geometry of the elementary catastrophes with this sym-
metry. The dihedral symmetry (D3) is discussed, using the
example of three coupled cells (simplest example where
symmetry forces repeated eigenvalues).
The next lecture deals with the bifurcation analysis of two-
point boundary value problems. First, it is shown that the
Liapunov-Schmidt reduction for many nonlinear two-point
boundary value problems (such as diffusion-reaction, con-
vection-reaction, and diffusion-convection-reaction models
in one spatial dimension) can easily be accomplished by
using the shooting technique and sensitivity functions. The
usefulness of this method is illustrated by deriving stability
criteria (cusp locus) for the catalyst particle and the tubular
autothermal reactor models. As the shooting technique is not
applicable in higher dimensions, a procedure is presented for
the determination of singular points of elliptic boundary
value problems of the form
Lu+N(u,p)=0 inn (u=0 on aL or Vu,n=0onan) (11)
where L has discrete spectrum with M zero eigenvalues, and
N(u,p) is quadratic or higher order in u. This problem is also
used to illustrate the equivalence of the two main approaches
to bifurcation theory, namely the Liapunov-Schmidt reduc-
tion and the perturbation (multi-scale) approach of looss and
Joseph[6] using the Fredholm Alternative. The physical ex-
amples we discuss include problems of diffusion-reaction
and diffusion-convection-reaction in higher dimensions con-
sisting of a single or a pair of nonlinear elliptic partial
differential equations with either Dirichlet, Neumann, or
Robin boundary conditions.
The last lecture on steady-state bifurcation theory deals
with the presence of symmetries in boundary value prob-
lems. First, examples of problems with reflectional (Z2) and
rotational symmetry (0(2)) are given (reaction-diffusion equa-
tions in a disk, ring, or line with Dirichlet or Neumann
boundary conditions, problems of flow in pipes as well as
artificially imposed periodic boundary conditions on physi-
157









cal systems). The presence of hidden symmetries (in the
boundary conditions) is also illustrated. Next, the derivation
of branching equations in the presence of Z2 symmetry with
single and double zero eigenvalue and 0(2) symmetry with
single (repeated) and double (repeated) zero eigenvalue is
discussed. The occurrence of these bifurcations and the local
bifurcation picture is illustrated by application to the buck-
ling of a rectangular plate and the Brusselator model of
pattern formation on a line and on a circular disk.
The lecture material on steady state bifurcation theory is
taken from references 6 through 19, the author's thesis,[2]
research publications, and notes.
Dynamical Systems The third major topic, for which
more than a quarter of the course is devoted, is bifurcation
theory for ordinary differential equations. It begins with a
review of the concept of asymptotic stability, the properties
of hyperbolic fixed points, and the invariance of the general-
ized eigenspaces of the linear system with constant coeffi-
cients (du/dt = Lu). This is followed by the linearization
theorem of Hartman and Grobman for the local behavior of
the nonlinear system

C- =Lu+N(u,p); N(0,p)=DuN(0,p)=0 ue YcRn (12)

and the stable manifold theorem for a fixed point. Next, the
slaving principle is explained in terms of the time scales
(eigenvalues) associated with the eigenmodes and the Center
Manifold theorem is stated. The usefulness of the Center
Manifold theorem as a rigorous perturbation technique (that
includes the classical regular perturbation/multiple-scale tech-
niques) is illustrated by considering a two-phase model of a
packedbed and deriving conditions under which it could be
reduced to a single phase (pseudohomogeneous) model and
the resulting model to infinite order!
The second lecture focuses on the application of Center
Manifold theorem to reduce the dimension of the bifurcation
problem defined by Eq. (12). First, a general procedure for
determining the amplitude equations when L has r eigenval-
ues on the imaginary axis is presented (the nonlinear func-
tional analysis and the notation are helpful in doing this in a
compact manner). Specific results for the case of single zero
eigenvalue, two and three zero eigenvalues, a pair of imagi-
nary eigenvalues, and zero plus a pair of imaginary eigenval-
ues is presented. (Students are encouraged to verify and
extend some of these formulas using symbolic manipula-
tion.) For example, when a trivial solution exists for all
values of the parameters vector p and there is a single zero
eigenvalue at po, it is shown that the amplitude equation to
cubic order is given by

dt -=ai lAiki +Ba +Cal (13)
i=l 1
where Xi =Pi Pio (i=1,...,M) are the components of the
parameters vector and pio are the parameter values at which
158


there is a simple zero eigenvalue. The coefficients Ai, B,
and C can be expressed in terms of some inner products
involving the eigenvectors and adjoint eigenvectors of the
linearized problem and higher order Fr6chet derivatives of
the function F(u,p).
The third topic of discussion is normal form theory, or
equivalently, the transformation of the amplitude equations
into their simplest form. First, it is shown that the calculation
of the normal form of a set of amplitude equations involves
near identity transformations and the solution of certain lin-
ear equations in polynomial vector spaces. Next, the normal
forms (along with their universal unfoldings) are presented
for some codimension one bifurcations (saddle-node and
Hopf) and codimension two bifurcations (Takens-Bogdanov,
zero, and a pair of imaginary eigenvalues and two pairs of
imaginary eigenvalues) followed by a discussion of the local
bifurcation behavior next to these singularities and the con-
struction of phase diagrams in the unfolding parameter space.
The application of the center manifold and normal form
theories is illustrated using lumped models of chemical reac-
tors (CSTR with single and multiple reactions) and discretized
models of convection (Lorenz model and the five equation
models of thermohaline and binary convection).
The fourth topic of discussion is Floquet theory and de-
generate Hopf bifurcations. First, the general theory of linear
systems with periodic coefficients, the method of calculation
of the monodromy matrix, and the Floquet multipliers are
reviewed. Next, the main theorem that gives the stability
of the periodic solution in terms of the Floquet multipliers
is stated. The two main degeneracies that may occur
when Hopfs hypotheses break down are stated (coalescence
of two Hopf points and the vanishing of the cubic co-
efficient in the normal form). The method of determining
periodic solutions by analyzing the zeros of a nonlinear
operator defined on the space of 27t-periodic functions is
discussed. The Fitzhugh-Nagumo equations for nerve
impulse, the Glycolytic model for oscillations, the Gray-
Scott isothermal autocatalysis model, and the CSTR
model are used for illustrating the construction of phase
diagrams in the parameter space.
The next lecture is devoted to discrete dynamical systems.
As in the case of continuous systems, the properties of
hyperbolic fixed points and invariance of the generalized
eigenspaces of the linear discrete system with constant coef-
ficients (Uk+1 = AUk) are reviewed. This is followed by the
stable and center manifold theorems for the local behavior of
the nonlinear system
Uk+1= F(uk,p)=Auk +N(uk,p); N(0,p)= DN(0,p)= 0 (14)
The calculation of the amplitude equations and the normal
forms for codimension one bifurcations (saddle-node,
transcritical, pitchfork, period doubling, and Naimark-Sacker)
are illustrated. The different types of attractors (fixed points,
periodic attractors, invariant circles, and strange attractors)
Chemical Engineering Education









of discrete dynamical systems, the types of bifurcations that
occur, the basins of attraction, and the fractal nature of the
basin boundaries are illustrated using classical examples
such as the logistic map, the delayed logistic map, the H6non
map, and the complex Newton iteration method for deter-
mining the fourth roots of unity.
The sixth lecture on dynamical systems is devoted to
Poincar6 maps, averaging methods, and Melnikov theory.
First, the reduction of a continuous dynamical system to a
discrete one through the Poincar6 map and the method of
construction of this map for three specific cases (near a
periodic orbit, near a homoclinic orbit, and for a forced
periodic system) as well as in the general case (using the
method of H6non) is illustrated. Next, the averaging theorem
is used to obtain the Poincar6 map for periodically forced
dynamical systems using the forced Duffing equation as an
example. At this stage, the dynamics of two-dimensional
maps near homoclinic points is explained intuitively and the
Melnikov method is presented for detecting the transverse
homoclinic points. Chemical engineering examples discussed
include periodically forced reactors and the dynamics of a
gas bubble in a viscous liquid with periodic pressure varia-
tions.
The next lecture deals with the routes to chaos, definition
and characterization of attractors, and the treatment of ex-
perimental data. First, the differences between the flows of
conservative and dissipative dynamical systems is reviewed.
Next, a strange attractor is defined and the three well-known
routes to chaos are illustrated using the example of two
coupled cells with the Brusselator kinetic scheme. Different
methods for the analysis of experimentally (or numerically)
generated time series are discussed. The calculation of
attractor dimensions (using the method of Grassberger and
Procaccia), Kolmogorov entropy, Liapunov exponents, and
power spectra (using FFT) is illustrated with examples.
The last lecture on dynamical systems is a survey of vari-
ous topics such as the global theory (Poincar6-Bendixson) of
dynamical systems in the plane, degree and index theory,
use of group theory to calculate normal forms, Hamiltonian
chaos, and fractals. The lecture material on dynamical sys-
tems is taken from references 20 through 31 and research
articles in Physica D. Examples and applications are taken
from the author's notes.
Nonlinear Partial Differential Equations The fourth
major topic of the course is bifurcation theory for nonlinear
partial differential equations. This topic is introduced with
the method of linearization of Eq. (3) around some base state
(uo), the solution of the system of linear partial differential
equations
dv Lv-D
C = Lv= DuF(uo)v (15)

and the properties of the eigenvalue problem (Ly=piCy) and
the adjoint eigenvalue problem (L*v= C*v). Next, the
Fall 1993


two main theorems stating the necessary and sufficient
conditions for simple and Hopf bifurcations are presented.
Applications of the theorems are illustrated by physical ex-
amples such as Taylor-Couette flow, Rayleigh-Benard con-
vection (principles of exchange of stabilities), Lapwood con-
vection, and pattern formation on a catalytic disk (station-
ary/oscillating patterns).
The second lecture deals with the application of center
manifold theory to partial differential operators in finite
domains (discrete spectrum). Center manifold reduction of a
system of PDEs and the derivation of the amplitude equa-
tions for M eigenvalues on the imaginary axis are illustrated.
(The unified notation is again helpful as the same formulas
are applicable for finite as well as for infinite dimensional
problems, the only difference being in the summations.) The
reduction of the Navier-Stokes equations for pipe and plane
Poiseuille flows to an infinite set of coupled quadratic ODEs
and the computation of the coefficients of the linear and
quadratic terms in the amplitude equations are illustrated.
Once again, the usefulness of the center manifold theorem as
a generalized perturbation technique is shown by discussing
a classical chemical engineering problem (Taylor-Aris dis-
persion) from a new perspective. (This example was taken
from the joint work of the author with Professor Chia Chang,
University of Notre Dame.)
The third topic of discussion is mode interactions in the
presence of symmetries. The derivation of amplitude equa-
tions in the presence of two zero eigenvalues with Z2 sym-
metry and two zero eigenvalues (repeated) and a pair of
imaginary eigenvalues (repeated) with 0(2) symmetry is
illustrated along with the local bifurcation diagrams. The
physical examples discussed include the problems of flow
maldistributions in packed beds, reaction driven convection
in a rectangular box, and stationary and moving temperature
patterns on a circular catalytic disk.
The fourth lecture is devoted to the case of continuous
spectrum (bifurcation in large systems). Here, the multiple
scale perturbation technique combined with the Fredholm
Alternative is used to derive the Landau (or the nonlinear
heat) equation

T=V2U+aU-bU3 (a,breal, U=realamplitude) (16)

for the case of continuous spectrum crossing the imaginary
axis at zero and the Ginzburg-Landau (or the Newell-
Whitehead-Segal) equation

-=U+(1+ia)V2U-(+ip)|U2U; a,3 real,U= complex (17)
at amplitude) '
for the case of complex continuous spectrum crossing the
imaginary axis. The spatio-temporal patterns predicted by
these equations and the concepts of phase and amplitude
turbulence are briefly discussed.
The fifth lecture on PDEs is devoted to global techniques
159









such as Liapunov functions and energy stability theory.
The classical Bdnard problem is used to determine the stabil-
ity boundary of the conduction state to finite perturbations
(which coincides with the linear stability boundary). The
example of through-flow in a porous medium is also used
to illustrate the possibility of subcritical bifurcations pre-
dicted by energy stability theory. Finally, the construction of
Liapunov functions is illustrated for some finite and in-
finite dimensional problems.
The last lecture is concerned with delay-differential,
integral, and integro-differential equations (a topic that has
applications in many areas of chemical engineering but is
often ignored). The three examples include a system with
time delay (Glass-Mackey model), a Fredholm integral
equation of first kind with a symmetric kernel describing a
diffusion-reaction problem, and an integro-differential
equation describing the dynamics of a catalyst particle
(with uniform internal temperature but non-uniform concen-
tration gradients). These models show simple and Hopf
bifurcations, period doubling, and chaotic behavior. For
some of these cases, the local theory to compute the normal
form is outlined.
The lecture material and examples on this topic are taken
from References 10, 15, and 32 through 36, Physica D, and
the author's research articles.
Nonlinear Waves The fifth topic is nonlinear waves.
Since the students are familiar with linear and hyperbolic
(shock) waves covered in the applied mathematics course,
some important concepts (such as phase velocity, group
velocity, dispersion, and front steepening) are reviewed. Next,
two chemical engineering examples (waves on a falling film
and temperature waves on a catalytic wire or ribbon) are
presented and some model wave equations, such as the long
wave equation and the generalized Fisher's equation

t = v- +f(u,p) (18)
at ax2
are derived. The rest of the discussion is concerned with the
wave properties of Eq. (18) and the nonlinear partial differ-
ential equation

+ uU +V au +a u 4u = (19)
at ax ax2 ax3 x4
which includes as special cases some of the most widely
studied equations, such as the Burger's equation (g. = 0, ; =
0), the Korteweg-de Vries equation (v = 0, X = 0), and the
Kuramoto-Sivashinsky equation (L = 0). Substituting the
traveling wave assumption
u(x,t)= h(z), z= x ct (20)
reduces Eq. (18) to a set of two ODEs (which can be ana-
lyzed by phase plane techniques) and Eq. (19) to a set of
three ODEs which exhibit periodic, quasiperiodic, and cha-
otic solutions. The physical interpretation of these solutions


as well as the variation of the wave speed with the param-
eters of the system are discussed.
The lecture material for this topic is taken from references
37 and 38, along with the author's notes.
Computational Methods The last two lectures are de-
voted to computational methods in bifurcation theory. First,
the arc length continuation technique as described by Kubicek
and Marek[39] is presented. This is followed by a review of
the software (such as DERPAR, AUTO2, etc.) for the con-
tinuation of steady-state and periodic branches. The recent
software package KAOS of Kim and Guckenheimer is also
reviewed and used by some students. It is also noted that
there are very few algorithms available for computing bifur-
cation branches in the presence of symmetries. The lecture
material for this topic is taken from references 39 and 40.

STUDENT PERFORMANCE
A set of fifty homework problems are given to the
students after the introductory lectures and the stu-
dents are asked to attempt five of them and submit a
written report on one problem. More than half of
these problems are open-ended and challenge the
students (four of the problems later became topics of
the students' PhD dissertations and led to several
refereed publications).
A combined total of twenty-four students took the
course for credit (and many others audited). In gen-
eral, the students fell into two groups: those who
were doing either experimental or theoretical re-
search on nonlinear systems, and those who took the
course to complete their graduate course require-
ments. The second group of students attempted
straightforward homework problems such as com-
puting the attractor dimensions or extending the
Liapunov-Schmidt/Center Manifold calculations
using symbolic manipulation. The first group of
students attempted open-ended problems, but their
solutions were incomplete (some were completed a
few years later).

CONCLUSIONS
Linear analysis played a key role in the develop-
ment of applied sciences during the nineteenth and
first-half of the twentieth century. It is believed that
nonlinear analysis combined with the power of the
computer will play a similar role in the next century.
The local nonlinear techniques of bifurcation theory
extend the traditional linear analysis and are essen-
tial in the development of algorithms for computa-
tion. They also guide the search for solutions of
nonlinear systems in multidimensional parameter
spaces. The computer experiments play a comple-
mentary role and extend and validate the local theory
Chemical Engineering Education










as well as lead to new and unexpected results (such
as the discovery of the soliton). It is the author's
opinion that some analysis and computational expe-
rience with nonlinear systems should be part of a
standard training program for all graduate chemical
engineers.

ACKNOWLEDGMENTS
The author is indebted to Professors Martin
Golubitsky and Giles Auchmuty of the mathematics
department at the University of Houston, with whom
he has had many discussions on singularity, bifurca-
tion, and group theories. This article was written
while the author was on sabbatical leave at the
University of Minnesota.

REFERENCES
1. Andereck, C.D., S.S. Liu, and H.L. Swinney, J. Fluid Mech.,
164, 155 (1986)
2. Balakotaiah, V., PhD Thesis, University of Houston, Hous-
ton, TX (1982)
3. Zeidler, E., Nonlinear Functional Analysis and Its Applica-
tions, Vols. I-V, Springer (1986)
4. Chow, S.N., and J.K. Hale, Methods of Bifurcation Theory,
Springer (1982)
5. Dieudonnd, J., Foundations of Modern Analysis, Academic
Press, New York, NY (1960)
6. Iooss, G., and D.D. Joseph, Elementary Stability and Bifur-
cation Theory, Springer (1990)
7. Vainberg, M.M., and V.A. Trenogin, Theory of Branching of
Solutions of Nonlinear Equations, Noordhoff (1974)
8. Haken, H., Advanced Synergetics, Springer (1986)
9. Golubitsky, M., and D.G. Schaeffer, Singularities and Groups
in Bifurcation Theory, Vol. I, Springer (1985)
10. Golubitsky, M., I. Stewart, and D.G. Schaeffer, Singularities
and Groups in Bifurcation Theory, Vol. II, Springer (1988)
11. Gibson, C.G., "Singular Points of Smooth Mappings," Res.
Notes in Math., 25, Pitman, London (1979)
12. Gilmore, R., Catastrophe Theory for Scientists and Engi-
neers, John Wiley (1981)
13. Thom, R., Structural Stability and Morphogenesis, Ben-
jamin, Reading, MA (1975)
14. Zeeman, E.C., Catastrophe Theory: Selected Papers, Addison-
Wesley, Reading, MA (1977)
15. Segal, L.A., Modeling Dynamic Phenomena in Molecular
and Cellular Biology, Cambridge University Press, 2nd cor-
rected printing (1987)
16. Nicolis, G., and I. Prigogine, Self-Organization in
Nonequilibrium Systems, Wiley (1977)
17. Rabinowitz, P.H., ed., Applications of Bifurcation Theory,
Academic Press (1977)
18. Murray, J.D., Mathematical Biology, Springer (1988)
19. Vanderbauwhede, A., "Local Bifurcation and Symmetry,"
Lec. Note in Math. #75, Pitman (1982)
20. Guckenheimer, J., and P.J. Holmes, Nonlinear Oscillations,
Dynamical Systems, and Bifurcations of Vector Fields, 2nd
corrected printing, Springer (1986)
21. Wiggins, S., Introduction to Applied Nonlinear Dynamical
Systems and Chaos, Springer (1990)
22. Carr, J., Applications of Centre Manifold Theory, Springer
(1981)
23. Marsden, J.E., and M. McCracken, The Hopf Bifurcation
and Its Applications, Springer (1976)
24. Arnold, V.I., Geometrical Methods in the Theory of Ordinary
Fall 1993


Differential Equations, Springer (1983)
25. Hassard, B.D., N.D. Kazarinoff, and Y.H. Wan, Theory and
Applications of Hopf Bifurcation, Cambridge University
Press (1981)
26. Schuster, H.G., Deterministic Chaos, Physik-Verlag (1984)
27. Sparrow, C., The Lorenz Equations: Bifurcations, Chaos,
and Strange Attractors, Springer (1982)
28. Coddington, E.A., and N. Levinson, Theory of Ordinary
Differential Equations, Robert E. Kreiger Publishing Com-
pany (1987)
29. Devaney, R.L., Chaotic Dynamical Systems, Benjamin, Read-
ing, MA (1987)
30. Marek, M., and I. Schreiber, Chaotic Behavior of Determin-
istic Dissipative Systems, Cambridge University Press (1988)
31. Moon, F.C., Chaotic Vibrations, John Wiley & Sons (1987)
32. Chandrasekhar, S., Hydrodynamic and Hydromagnetic Sta-
bility, Oxford University Press (1961)
33. Drazin, P.G., and W.H. Reid, Hydrodynamic Stability, Cam-
bridge University Press (1987)
34. Kuramoto, Y., Chemical Oscillations, Waves, and Turbu-
lence, Springer (1984)
35. Collet, P., and J.-P. Eckmann, Instabilities and Fronts in
Extended Systems, Princeton University Press (1990)
36. Joseph, D., Stability of Fluid Motions, Vols. I and II, Springer
(1976)
37. Segal, L.A., Mathematics Applied to Continuum Mechanics,
Dover, New York (1987)
38. Toda, M., Nonlinear Waves and Solitons, Kluwer Academic
Publishers, Boston, MA (1989)
39. Kubicek, M., and M. Marek, Computational Methods in
Bifurcation Theory and Dissipative Structures, Springer
(1983)
40. Roose, B.D., B.D. Dier, and A. Spence (eds.), Continuation
and Bifurcations: Numerical Techniques and Applications,
Kluwer Academic Publishers, Boston, MA (1989) 0


O book review


ELEMENTS OF CHEMICAL
REACTION ENGINEERING:
2nd Edition
by H. Scott Fogler
Prentice Hall, Englewood Cliffs, NJ (1992)

Reviewed by
P. R. Westmoreland
University ofMassachusetts

The second edition of this text already comes about
as close to universal usage as a chemical engineer-
ing text can, including wide international use in
addition to 108 schools (in a recent count) in the U.S.
It is not as well suited for graduate study, but (as far
as I am concerned) it is the best undergraduate
reaction engineering text available, based on its con-
tent, structure, and wide variety of good problems.
This edition, like the first edition did, covers the
necessary subject territory of reaction engineering
within its fourteen chapters:

Continued on page 166.












MOLECULAR LEVEL

MEASUREMENTS

IN CHEMICAL ENGINEERING


R. J. SMILEY, W. N. DELGASS
Purdue University
West Lafayette, IN 47907

or quality control of a complex polymeriza-
tion, or tracing the cause of poor paint adhe-
sion, or understanding substandard perfor-
mance of a catalyst batch, and for a host of other
challenges, practicing chemical engineers may well
find the greatest benefit by using a molecular level
approach to the problem. While it is likely that the
engineer will have to call on an expert to bring the
full power of a given technique to bear on a given
problem, it is important that he or she be sufficiently
aware of the molecular-level tools available to begin
asking the right questions.
At Purdue, an elective course, called "Molecular
Level Measurements in Chemical Engineering," for
juniors, seniors, and graduate students, was designed
to fill this need by sensitizing students to a variety of
microscopic and spectroscopic characterization tools.
Most students who graduate with a BS degree in
chemical engineering have had only limited expo-
sure to the characterization tools that will be avail-
able to them as professionals in industry or aca-
demia. Undergraduate engineering laboratory
courses tend to focus on traditional chemical engi-
neering equipment, and when chemistry laboratory
courses use modern spectroscopic methods, they
rarely make a connection to an engineering context.
In our course, a brief discussion of the basic theory,
instrument design, and sample requirements estab-
lishes the basic physics of the particular technique
and the type of information it can give. Applications
drawn from the literature illustrate the utility of the
method in addressing engineering problems.

COURSE PHILOSOPHY
The course grew out of a conviction that chemical
engineers can best extend their technical longevity
through an understanding of the molecular basis
of the properties and behavior of engineering


R.J. Smiley is a graduate chemical engineering
student at Purdue University. He received his
BS degree from Cornell University in 1989. His
research interests focus on studying interfacial
interactions of composite materials on the mo-
lecular level by X-ray photoelectron spectros-
copy, electron microscopy, and scanning force
microscopy.


SW. N. Delgass is Professor of Chemical Engi-
neering at Purdue University. He received his BS
in chemical engineering from the University of
Michigan, and his MS and PhD degrees from
Stanford University. His research interests are in
the kinetic and surface chemical characterization
S of solid catalysts and other advanced materials.

materials and processes. To use this understand-
ing, one must be able to make measurements on
the molecular level.
The primary objective of the course is to introduce
students to various tools that will extend their abil-
ity to solve problems. It is important to note that we
stress that the course only introduces the various
techniques and is not meant to make the students
experts in a particular field. We have chosen breadth
over depth to give students a wide scope of applica-
tions, but we try to include sufficient detail of some
techniques to foster an appreciation of the care it
takes to get the most information available.
The first of two secondary objectives of the course
is the effective reading of technical papers. Our reli-
ance on primary source material gives us an oppor-
tunity to emphasize critical evaluation of journal
articles. Problem sets designed around current ar-
ticles ask students to challenge and justify state-
ments they read, to derive equations and discuss
assumptions in the paper, and to consider what new
or corroborating evidence might be obtained from
alternative experimental approaches. For some stu-
dents, these exercises provide the first recognition of
the fallibility of the printed word and are, thus,
Copyright ChE Division ofASEE 1993
Chemical Engineering Education










important steps in learning the winnowing process
that is central to self-education.
Finally, we have incorporated laboratory exercises
into the course that will at least introduce students
to the hardware associated with advanced instru-
mentation. Each class day spent on an instrument
limits the breadth of topics the course can cover, but
the students confirm that talking about an experi-
ment does not have the same impact as doing it.
This past spring we included three lab periods to
cover X-ray photoelectron spectroscopy, electron mi-
croscopy, and infrared and nuclear magnetic reso-
nance spectroscopies.

COURSE DESCRIPTION
Table 1 gives the course outline. It begins with a
brief overview of the techniques that will be covered
in the class. Starting with the Propst diagram (see
Figure 1) and the energy spectrum, we discuss the
different ways of perturbing a sample with fields,
photons, ions, neutrals, and electrons, and point out
the types of information one might hope to learn.511
Emphasis on applications shows where the course is
heading and is intended to justify the need for the
two-week review of background material that fol-
lows. Discussion of deBroglie's equation, the uncer-
tainty principle, and Schrodinger's equation, together
with derivations for a particle in a box and simple
harmonic motion, and review of atomic and molecu-
lar orbital theory as well as some simple symmetry
concepts provide the foundation on which all the
molecular level techniques rest.
We begin quantitative surface analysis with a de-
tailed discussion of X-ray photoelectron spectroscopy

TABLE 1
Outline of Major Topics
1. Introduction and Background (2 weeks)
Propst Diagram
Classical and quantum mechanics
Symmetry
2. Quantitative Surface Analysis (4 weeks)
X-ray photoelectron spectroscopy (XPS)
Ion scattering spectrometry (ISS)
Secondary ion mass spectrometry (SIMS)
3. Bulk and Surface Structural Analysis (4 weeks)
Diffraction (XRD, LEED)
Electron microscopy (TEM, SEM, AEM)
Scanning probe microscopies (STM, SFM)
4. Chemical Characterization (4 weeks)
Infrared spectroscopy (IR)
Raman spectroscopy
Nuclear magnetic resonance spectroscopy (NMR)
Mass spectrometry (MS)
5. Case Studies (1 week)

Fall 1993


NEUTRALS IONS



PHOTONS SAMPLE ELECTRONS



HEAT FIELDS
Figure 1. The Propst Diagram. Arrows pointed inward
represent various probes used to perturb the sample. Dif-
ferent responses to perturbation, indicated by the outgoing
arrows, provide information about the sample.

(XPS), including important features such as surface
sensitivity, elemental and chemical state analysis,
and quantitative capabilities. Detailed lectures fo-
cus on spectral interpretation by analysis of peak
position, area, shape, and splitting.
In order to illustrate the potential of XPS, we spend
several lectures discussing spectra from papers in
the literature. One example of XPS analysis of the
interactions between metal and metal oxide films
shows students that surface properties are often
much different from bulk properties, and that these
differences directly affect the quality of the finished
product."2' These discussions are often the first time
students are asked to extract information from spec-
tra. Not surprisingly, they are initially reluctant to
volunteer opinions, but we find that giving them the
papers in advance and providing them with a few
key questions to consider stimulates discussion.
After a relatively detailed presentation of XPS, we
study Auger electron spectroscopy (AES), ion scat-
tering spectroscopy (ISS), and secondary ion mass
spectrometry (SIMS). Because much of the instru-
mentation and principles of XPS also apply to this
next group of techniques, we move quickly through
this part of the course to focus on applications of
these tools.
The next section is on examination of bulk and
surface structure by diffraction and microscopy. We
begin this part of the course with a discussion of
crystal structure and X-ray diffraction (XRD), elec-
tron diffraction, and low energy electron diffraction
(LEED). Lectures are designed to compare and con-
trast the instrumentation as well as the information
provided by each technique.
Scanning and transmission electron microscopies
are introduced next. One class period is a laboratory
demonstration of the potential of SEM and TEM
for studying biological and structural materials. Be-
fore the laboratory session, we devote a lecture to
163









contrasting the two types of microscopes and ex-
plaining the differences in resolving power, instru-
ment design, and sample requirements. Analytical
tools such as energy dispersive X-ray analysis (EDX)
and electron energy loss spectroscopy (EELS) are
also introduced.
The last topic is scanning probe techniques, in-
cluding scanning tunneling and scanning force
microscopies. The students read a paper by Hoff-
man which reviews many of the scanning probe
microscopies and applies them to characterization
of carbon fiber materials.31 In one problem set,
students are asked to compare the types of infor-
mation obtained by STM/SFM on carbon fibers
with the information learned from SEM and TEM,
and to explain the advantages and disadvantages
of each technique.
The last group of techniques we discuss includes
mass spectrometry and infrared, Raman, and nuclear
magnetic resonance spectroscopies, and focuses on
chemical characterization. At this point in the
course, students have become familiar with the pat-
tern of the presentation and can apply many of the
concepts they learned earlier to this last set of
tools. Thus, introducing each technique requires
less time and we are able to shift the lecture con-
tent to more complex problems requiring multi-
technique approaches. FTIR and solid-state NMR
exercises examine different polymer systems and
demonstrate the powerful analytical capabilities of
these two instruments.
With one week of classes left in the semester at
this point, we introduce a case study that involves
trouble-shooting a process restart. The problem state-
ment, (developed for us from plant experience by Dr.
George Swan, Exxon Research and Development,
Baton Rouge, Louisiana) includes a description of
the reforming process and the catalyst changeover
procedure, along with a flow sheet. Gas chromato-
graphic analysis of the product stream and discus-
sion of some of the attempts to find the cause of the
low octane rating are also presented and are read by
the students before the class discussion. In class, the
students seek the solution by suggesting causes and
analyzing consequences. When they suggest that new
data be gathered, the wisdom of such a move is
analyzed for its utility, cost, and time required. The
instructor's role is to keep the students on track with
a minimum of direction and to supply additional
data if it is asked for and available. The twist in this
problem is that the chromatography data are incom-
plete. Mass spectrometry is needed to discover a
heat-exchanger leak that allows some of the feed to


bypass the reactor. Even though this problem is
relatively simple from an instrumentation point of
view, the thought processes stimulated by the dis-
cussion are valuable for the students. We hope to
develop additional case studies using real plant situ-
ations as the course evolves.

COURSE REQUIREMENTS
The course work includes three exams, a term
paper, and ten problem sets. Exams focus on apply-
ing the principles learned. For example, one
question on the first exam asks students to formu-
late a series of experiments to differentiate between
three proposed reaction mechanisms, given a labora-
tory equipped with an XPS, ISS, SIMS, and a full
range of isotopes. Other types of questions ask stu-
dents to interpret spectra or to draw and label a
schematic of an instrument.
The objective of the term paper is to get students
to go into more depth for a particular technique.
We give students the option to discuss a specific
molecular measurement application of a technique
introduced in class, or to discuss a new technique.
They must submit paragraphs (which include
three references from the literature) presenting
their topics a month before the paper due-date so we
can make suggestions and be assured they have
started the assignment. Students normally choose
topics that are too broad in scope and they need help
focusing their ideas. A sampling of term-paper top-
ics is given in Table 2.
Finally, we use problem sets to follow students'
progress and to demonstrate application of techniques
to engineering problems. We find that students re-
spond most favorably to recent articles because they
recognize the importance of these techniques in solv-
ing existing problems. In one problem set we ask
students to read a recent paper, "High-Temperature
in Situ Magic Angle Spinning NMR Studies of Chemi-
cal Reactions on Catalysts."141 Although we do not
expect the students to grasp all the details of solid-
state NMR, we find they can understand how the


TABLE 2
Sample Term Paper Projects
Positron emission tomography
Scanning thermal microscopy
Using TEM to determine inhomogeneity of highly cross-linked
polymers
Solid state NMR investigation of polymer morphology by multiple
pulse spin diffusion experiments
Chain branching studies of polymers using 3C NMR
X-ray diffraction for measuring residual stress in materials

Chemical Engineering Education











technique is applied and what is learned, and they
can also answer questions about sample preparation
and suggest additional measurements which sup-
port the authors' overall conclusions.
We find it helpful, after handing back graded prob-
lem sets, to review questions which the students
find difficult. These discussions, in addition to ex-
plaining the specific problem, generate additional
questions. Oftentimes a student can be guided
to answer his or her own question, and in many
cases, help also comes from fellow classmates.
Although these lectures break from the traditional
lecture format, they are valuable for both the stu-
dents and the instructor because they foster a more
relaxed environment for learning, encourage ques-
tions, and give a measure of the students' under-
standing of the material.


RESOURCE MATERIALS
Because of the number of tools we cover and the
broad nature of the material, we do not use one
specific textbook. Instead, we use a compilation of
review articles, book chapters, and papers in the
literature. A chapter, "Catalytic Surfaces and Cata-
lyst Characterization Methods," in Chemical Indus-
tries Series'51 serves to introduce many of the topics
we cover. Since it focuses on catalytic systems, we
use lectures and problem sets to challenge students
to apply the techniques to other fields, including
composites, polymers, and semiconductors. Papers
in the literature are an excellent resource because
they can be chosen to demonstrate a particular prin-
ciple and to tailor the course to the interests of the
students. The list of papers used (see Table 3) shows
a balance of classics and the newest applications.


TABLE 3
Additional References Used


Books
1. Czanderna, A.V., and D.M. Hercules, Ion Scattering Spectroscopies,
Plenum Press, New York (1991)
2. Delgass, W.N., G.L. Haller, R. Kellerman, and J.H. Lunsford, Spec-
troscopy in Heterogeneous Catalysis, Academic Press, New York,
(1979)
3. Briggs, D., and M.P. Seah, Practical Surface Analysis, 2nd ed., John
Wiley and Sons, Inc., New York (1990)
4. Derome, A.E., Moder NMR Techniques for Chemistry Research,
Pergamon Press, New York (1987)
5. Harris, R.K., Nuclear Magnetic Resonance Spectroscopy, John Wiley
and Sons, Inc., New York (1986)
6. Harrick, N.J., Internal Reflection Spectroscopy, John Wiley and Sons,
Inc., New York (1979)
7. Wischnitzer, S., Introduction to Electron Microscopy, Pergamon Press,
New York (1981)
8. Kittel, C., Introduction to Solid State Physics, John Wiley and Sons,
Inc., New York (1976)
9. Atkins, P.W., Physical Chemistry, 3rd ed., W.H. Freeman and Com-
pany, New York (1982)
10. Giintherodt, H.-J, and R. Wiesendanger, Scanning Tunneling Micros-
copy I, Springer-Verlag, New York (1992)
Monographs
1. Lyman, C.E., "Analytical Electron Microscopy of Heterogeneous
Catalyst Particles," in Catalyst Materials: Relationship Between Struc-
ture and Reactivity, ACS Symposium Series 248 (1984)
2. Stokes, H.T., "NMR Techniques for Studying Platinum Catalysts," in
Catalyst Materials: Relationship Between Structure and Reactivity,
ACS Symposium Series 248 (1984)
3. Treacy, M.M.J., "Atomic Number Imaging of Supported Catalyst
Particles by Scanning Transmission Electron Microscope," in Cata-
lyst Materials: Relationship Between Structure and Reactivity, ACS
Symposium Series 248 (1984)
Review Articles
1. Niehus, H., and R. Spitzl, "Ion-Solid Interaction at Low Energies:
Principles and Applications of Quantitative ISS," Surf Interface Anal.,
17, 287 (1991)
2. Soethout, L.L., H. Van Kempen, and G.F.A. Van de Walle, "Scanning
Tunneling Microscopy: A Mature Surface-Science Technique," Adv.
Electron. Electron Phys., 79, 155 (1990)


Journal Articles
1. Bartha, J.W., P.O. Hahn, F. LeGoues, and P.S. Ho, "Photoemission
Spectroscopy Study of Aluminum-Polyimide Interface," J. Vac. Sci.
Technol., A3, 1390 (1985)
2. Tjandra, S., and F. Zaera, "Static Secondary Ion Mass Spectrometry as
a Tool for Studying Surface Reactions: The Decomposition of Ethyl-
ene over Ni(100) Surfaces," Langmuir, 7, 1432 (1991)
3. Kim, K.S., T.J. O'Leary, and N. Winograd, "X-Ray Photoelectron
Spectra of Lead Oxides," Anal. Chem., 45, 2214 (1973)
4. Taglauer, E., and W. Heiland, "Low Energy Ion Scattering and Auger
Electron Spectroscopy Studies of Clean Nickel Surfaces and Adsorbed
Layers," Surf Sci., 47, 234 (1975)
5. Chakraborti, S., A.K. Datye, and N.J. Long, "Oxidation-Reduction
Treatment of Rhodium Supported on Nonporous Silica Spheres," J.
Catal., 108, 444 (1987)
6. Jang, J.S.C., and C.H. Tsau, "Disordering of the Ni3S, Intermetallic
Compound by Mechanical Milling," J. Mater. Sci., 28, 982 (1993)
7. Jean, J.H., and T.K. Gupta, "Devitrification Inhibitor in Binary Boro-
silicate Glass Composite," J. Mater. Res., 8, 356 (1993)
8. Jean, J.H., and T.K. Gupta, "Crystallization Kinetics of Binary Boro-
silicate Glass Composite, J. Mater. Res., 7, 3103 (1992)
9. Vallet-Regi, M., V. Ragel, J.L. Martinez, M. Labeau, and J.M. Gonzalez-
Calbet, "Texture Evolution of SnO2 Synthesized by Pyrolysis of an
Aerosol," J. Mater. Res., 8, 138 (1993)
10. Primet, M., M.V. Mathieu, and W.M.H. Sachtler, "Infrared Spectra of
Carbon Monoxide Adsorbed on Silica-Supported PdAg Alloys," J.
Catal., 44, 324 (1976)
11. Hughes, T.R., and H.M. White, "A Study of the Surface of Decationized
Y Zeolite by Quantitative Infrared Spectroscopy," J. Phys. Chem., 71,
2192 (1967)
12. Chen, X., and J.A. Gardella, Jr., "Fourier Transform Infrared and
Electron Spectroscopy for Chemical Analysis Studies of Block Co-
polymers of Styrene and Dimethylsiloxane," Macromolecules, 25,6621
(1992)
13. Weeding, T.L., W.S. Veeman, L.W. Jenneskens, H. Angad Gaur,
H.E.C. Schuurs, and W.G.B. Huysmans, ""3C and 29S, NMR Investiga-
tions of Glass-Filled Polymer Composites," Macromolecules, 22, 706
(1989)
14. Li, Q., J. Megusar, L.J. Masur, and J.A. Cornie, "A High Resolution
Transmission Electron Microscopy Study of SiC-Coated Graphite Fi-
ber-Aluminum Composite," Mater. Sci. and Eng., A117, 199 (1989)


Fall 1993 161










Finally, we recommend the students dust off their
physical chemistry books when we review the back-
ground material at the beginning of the semester.

ON TEACHING TEACHERS
We would be remiss in closing this presentation
without commenting on the special circumstances
that brought Randy Smiley into this educational
partnership. Essentially all chemical engineering lec-
tures are given by faculty at Purdue, but we were
encouraged to try this experiment through a Du
Pont Fellowship granted to Randy. The success of
the experiment is probably best illustrated by his
own words:
I feel fortunate to have had the opportunity to teach a
course during my graduate studies at Purdue. I was amazed at
how markedly my lecture preparation and teaching style
changed as the semester progressed. I became more efficient
in preparing for lectures and much more relaxed in front of
the students, which gave me confidence and made the students
more responsive in class. The classes in which we discussed
journal articles were clearly the most unpredictable and the
most fun to teach. I also enjoyed developing the laboratory
exercises used in the course. The period we spent at the
Electron Microscopy Center gave students a view of the com-
plexities of the equipment and sample preparation which would
have been impossible to achieve in a classroom.
Professor Delgass came to class during the first few weeks
of the semester and gave me immediate feedback on my teach-
ing style. In addition, we typically met once a week to discuss
the class progress. Initially, this time was spent discussing
course content, but later in the semester we talked about the
other responsibilities facing a professor, including starting up
a research group and writing proposals. In addition to my
discussions with Professor Delgass, I found the book Teach-
ing Engineering"61 helpful. It has hints about teaching skills,
and discussions about tests, homework, and grading that are
insightful. Overall, teaching in this supportive environment
was a rewarding experience which I strongly recommend to
any student who has any desire to pursue a career in aca-
demia.

SUMMARY AND CONCLUSIONS
Understanding what tools are available and the
type of information each technique gives is critical
for engineers to be successful problem solvers. This
course gives students the foundation of many char-
acterization tools that will be available to them and
should help bring a molecular point of view to their
problem-solving skills. Exam questions and problem
sets are designed to expose students to the practical
potential of these tools and to hone their ability to
critically evaluate the technical literature. Labora-
tory exercises familiarize students with instrumen-
tation and sample requirements and demonstrate
the principles taught during the lectures. Finally,


case studies show students how techniques are ap-
plied directly to problems facing practicing engineers.

ACKNOWLEDGMENTS
We would like to thank the Du Pont Foundation
for awarding Randy Smiley a 1992-93 Teaching Fel-
lowship. Many thanks also to Dr. D. Sherman and
Professor C.E. Bracker at the Electron Microscopy
Center in the School of Agriculture at Purdue, and
to Dr. Brett Cowans and Robert Adams for their
help with the microscopy NMR and FTIR laboratory
demonstrations.

REFERENCES
1. Park, R.L., in Experimental Methods in Catalytic Research
111, edited by R.B. Anderson and P.T. Dawson, Academic
Press, New York (1976)
2. Winograd, N., W.E. Baitinger, and J.W. Amy, Science, 184,
565 (1974)
3. Hoffman, W.P., Carbon, 30, 315 (1992)
4. Oliver, F.G., E.J. Munson, and James F. Haw, J. Phys.
Chem., 96, 8106 (1992)
5. Delgass, W.N. and E.E. Wolf, in Chemical Reaction and
Reaction Engineering, edited by J.J. Carberry and A. Varma,
Marcel Dekker, Inc., New York (1987)
6. Wankat, P.C., and F.S. Oreovicz, Teaching Engineering,
McGraw-Hill, Inc., New York (1993) 0


REVIEW: Elements of CRE
Continued from page 161.
* Basic definitions (and the necessary un-definition that rate must
not be defined as dC/dt, despite what students have usually
learned in physical chemistry courses)
Power-law and Langmuir-Hinshelwood-Hougan-Watson kinet-
ics
Design of ideal reactors, both isothermal and nonisothermal
Using data to obtain rate expressions
Product selectivity
Mass transport in reaction engineering, including porous sol-
ids, slurry reactors, and mixing in nonideal flows
Parallel to the technical exposition are difficulty-
ranked problem sets and "Thoughts on Problem Solv-
ing" that are several-page end-segments of twelve
chapters which discuss such formal approaches to
problems as Kepner-Tregoe situation analysis.
The most striking additions woven into this edi-
tion are 1) treatments of chemical vapor deposition,
biotechnology, and polymerization, and 2) emphasis
on using packages for solving differential equations.
The first addition serves the obvious purpose of
introducing these areas into the core curriculum,
but even more subtly it also teaches how these
"emerging technologies" are treatable by the classi-
cal techniques of reaction engineering. For example,
I find the best way to introduce development of cata-
lytic rate expression for heterogeneous catalysis is to
Chemical Engineering Education









begin with Michaelis-Menten enzyme kinetics, which
is done well here. Unlike inorganic catalysis, the
"site" is a tangible, specific, and unambiguous loca-
tion for many enzymes, thanks to experiments and
molecular modeling (e.g., Science, 253, 872, 1991).
Fogler also treats multiphase reactors more effec-
tively by treating both classical slurry reactors and
aerobic bioreactors where air is bubbled through
aqueous slurriess" of cell mass.
Student use of O.D.E.-solvers in this course is pro-
moted through the book's examples and problems.
POLYMATH (CACHE Corporation) is used in most
cases, but other packages are also used or cited
(Chem. Eng. Ed., 24, 54, 1991). Simple codes for
some computer solutions are still provided, but the
equation solvers allow a quicker transition for the
students to explore solutions and effects of param-
eters. Fogler's approach forces emphasis on concepts
over techniques, in the spirit that to use an equation
solver effectively, you only need to know how it
works-not how to make one. In this text, reaction
engineering is the focus, while analytical or numeri-
cal methods are important tools to be used.
A strong point of the examples and problems is
that real reactants and reactions are generally used.
The types of chemistries involved are not structured
beyond homogeneous versus heterogeneous, but it
isn't (and shouldn't be) the purpose of this book to
organize the suite of chemical engineering chemis-
try. Many students enter chemical engineering be-
cause they like chemistry, and the reaction engi-
neering course is often the one place in the chemical
engineering sequence where they seem to realize the
connection with their chemistry courses. (Paradoxi-
cally, the curriculum is full of non-reaction chemis-
try, too, from chemical thermodynamics to materials
to molecular bases of transport properties. We need
to do a better job of pointing out the balance of
physics and chemistry that go into the chemical en-
gineering profession.)
Some worthwhile material has been omitted to
meet space restrictions, but not always seamlessly.
For example, analysis of trickle-bed reactors was
eliminated, apparently to allow inclusion of bioreac-
tors as multiphase reactors (certainly a defensible
choice) but, unfortunately, trickle-bed problems are
left unchanged from the first edition, as if the rel-
evant text material was still in place. Other sources
may be easily consulted, though, because references
for trickle-bed analysis and design are retained in
the "Supplementary Reading" section. Other topics
which are mentioned only briefly include fluidized-
bed and transport reactors.


Of course, not every topic can or should be
included in an undergraduate course on reaction
engineering. Fogler describes an excellent, semes-
ter-long sequence using about 60% of the book. Its
coverage and timeliness make it today's de facto
standard text for undergraduate kinetics and reac-
tion engineering. 0

e M book review


HAZOP and HAZAN: Identifying and
Assessing Process Industry Hazards,
3rd Edition
by Trevor Kletz
Published by the Institution of Chemical Engineers, United
Kingdom; distributed in the US and Canada by Hemi-
sphere Publishing Corporation, Bristol, PA; 150 pages,
$49.50 (1992)
Reviewed by
Daniel A. Crowl
Michigan Technological University
This book is a significant improvement over the
last release, a soft-bound edition published in
1986. This issue includes a hard cover (in standard
book size), redrawn and updated figures, new refer-
ences, and new content. It is divided into seven
chapters, with several chapter appendices and sup-
plemental material.
Chapter 1 provides a brief introduction to hazard
identification and assessment, including a discus-
sion of why it is important, how far one must be
prepared to go to eliminate hazards, and when in
the design of a chemical plant these methods should
be applied.
Chapter 2 presents the concept of hazard and op-
erability studies (HAZOP), a hazard identification
procedure which has become increasingly important
to the chemical industry. A detailed example using
the feed section to an olefin dimerization plant is
provided. The chapter also includes discussion on
why HAZOPs are important, who carries out the
HAZOP, and the limitations to HAZOPs. An inter-
esting appendix to the chapter describes nine acci-
dents which could have been prevented by a proper
HAZOP and one accident which most likely could
not have been prevented.
Chapter 3 introduces hazard analysis, which Pro-
fessor Kletz (and perhaps the British) is determined
to call HAZAN, for hazard analysis. As Kletz points
out, the United States prefers the term "quantita-
Continued on page 193.


Fall 1993









Review / opinion


THE CHANGING ROLE

OF ACADEMIA


JULIO M. OTTINO
Northwestern University
Evanston, IL 60208-3120

Academia is in turmoil. Higher education in
the United States has never been static, but
it is now undergoing rapid transformations,
seemingly with no overall plan, seeking a purpose,
pulled in many directions by forces that did not even
exist a decade ago. Academia is now accountable to
media pressure, to alumni, and to government. There
are concerns about teaching, tuition costs and allo-
cation of funding, weights given to graduate and
undergraduate education and research, scientific
misconduct, and in general about the perceived mis-
match between academia's wants and society's
needs. Critical reports have appeared in major news-
papers and on television: a Chicago Tribune article
on teaching at the University of Illinois at Urbana;
a 20/20 report on teaching at Berkeley. A decade
ago it would have been unthinkable to conceive of a
book like ProfScam.[ l
The pressures are irreversible and will not go away.
U.S. industry has been forced to deal with both
globalization and environmental concerns, and envi-
ronmental issues will not be reset as they were in
the 1950s. Similarly, what is now expected of aca-
demia is quite different from what was expected in
the 1960s and 1970s. Only the institutions that are
able to adapt will survive.
There is a wide gap between myth and the reality
of academic life. For this, academics have no one to
blame but themselves, since any attempt to commu-
nicate ideas to the general public is usually looked
upon with suspicion. The result is public ignorance
as to how leading science evolves, the prevailing
wisdom being that science somehow moves in recti-
linear fashion to immutable truths.
Contrary to popular belief, there is now renewed
attention being paid to undergraduate education in
many institutions. My own institution, McCormick,
Copyright ChE Division ofASEE 1993


Julio M. Ottino is Walter P. Murphy Professor
and Chairman, ChE Department, Northwestem
University. He received his PhD degree from the
University of Minnesota and his undergraduate
degree from the University of La Plata, Argen-
tina. His research interests are in mixing and
chaos, pattern formation-aggregation, breakup,
Sand dispersion-and mixing of immiscible and
complex fluids. He is the author of The Kinemat-
ics of Mixing: Stretching, Chaos, and Transport
(Cambridge University Press, 1989).

is a good example: there are financial incentives for
good teaching, such as rotating endowed chairs; 80%
of the full professors teach at least one undergradu-
ate course a year; and it is impossible to buy time
from teaching. The public at large, however, has
little idea of how professors spend their time.
Inside and outside forces are taking their toll, par-
ticularly on young academics who are expected to be
all things to all people-great researchers, effective
fundraisers, inspirational teachers. Recent statistics
are not encouraging: 53% of academics under forty
year of age report that "my job is a source of consid-
erable personal strain."[2]
Many institutions are trying to redefine their mis-
sions. An ever-increasing stream of speeches and
reports (many originating from captains of industry)
are telling academics what to do, how to teach, how
to manage their institutions, how to view research,
and how to re-examine the rationale for the support
of research. Some of this advice is well intended, but
naive-and copying models of industrial success and
applying things like TQM will help only up to a
certain point. In the same way that industry cannot
conduct research as if it were a university, univer-
sity research cannot be managed in an industrial
mode. There is just so much that can be left to
serendipity'31 but tight organization will undoubt-
edly kill creativity.
Changes do not come without pain. Nevertheless,
it is indisputable that in order for academia to re-
main productive, changes must be made and a new
vision of scholarship must be advanced. To echo the
Chemical Engineering Education









words of Thomas Kuhn, a paradigm shift is in the
air. As to what the new paradigm will be-that is
hard to predict. What rationale will colleges and
universities use to redefine their mission? Will things
evolve to a unique model of success? Will expecta-
tions regarding faculty performance be uniform across
institutions? Scholarship Reconsidered"2' offers one
of the best reasoned views of how this paradigm
might look and what considerations should be im-
portant when judging alternatives. In the following
paragraphs I will quote freely from this work, add-
ing a few interjections of my own and restricting the
remarks to research universities.
Universities have been too narrow in defining
the boundaries of acceptable behavior, especially
when contrasted to the historical record of aca-
demia's changing mission. The main thesis of this
report is that it is essential to broaden our defini-
tion of scholarship.
The current, dominant, picture is that to be a
scholar is to be a researcher. This was not always so
and, in fact, this view is of rather recent vintage.
Explicitly, or implicitly, the mission of academia has
changed throughout the years, evolving and trans-
forming itself from teaching to service to research.
The colonial college, patterned after British tradi-
tions, took a view of collegiate life that was almost
monastic. Teaching was a calling. The goal of Harvard
College in 1636 was to "advance Learning and per-
petuate to Posterity." The student was the center of
attention, and tutoring was the preferred mode of
teaching. This stage lasted for almost two hundred
years, until service was added to the role.
This transformation did not happen overnight. In-
stitutions gradually took an increased interest in
serving business and economic posterity. Rensselaer
Polytechnic Institute was founded in 1824 with the
premise that "the United States needs railroad-
builders, bridge-builders, builders of all kinds." The
practical side of higher learning appeared loud and
clear in the Land Grant College Act of 1862 and the
Hatch Act of 1887. By 1903, the presidents of Stanford
and Harvard would declare that the entire univer-
sity movement "is toward reality and practicality,"
and that "at the bottom, most of the American insti-
tutions of higher education are filled with the mod-
ern democratic spirit of serviceableness." The first
president of Cornell saw graduates "pouring into the
legislatures, staffing newspapers, and penetrating
the municipal and county boards of America." Aca-
demia saw itself as a major force in shaping society.
There was a conviction that higher education had a
moral mission to fulfill.


Where was research throughout this period? Cer-
tainly not within university walls. In fact, it took
quite some time before research found a hospitable
home within academia. The first advanced degree
obtained by an American goes back to early 19th-
century Germany, and it took another fifty years for
the first PhD degree to be awarded in the United
States (Yale, 1861-followed by Pennsylvania,
Harvard, Columbia, and Princeton). Things moved
quickly after that, however. The University of Chi-
cago, founded in 1891, made the PhD degree the
pinnacle of its academic program. In fact, within
four years of its founding, its president declared that
"promotions in rank and salary would depend chiefly
upon research productivity."
Then, two World Wars and the Depression set the
stage for a dramatic all-inclusive change, particu-
larly in the way that research was to be supported
by government.
The most quoted document involving interaction
between government and academia, Science: The
Endless Frontier-a report written for President
Roosevelt at the end of World War II by Vannevar
Busch of MIT, and eventually delivered to President
Truman- provided a blueprint that guided research
right up to the present day. Its implicit idea was one
of"societal return": that the societal return obtained
by government investment would be greater than
that produced by the same private investment."4'
Agencies such as the National Science Foundation
were created, and money started to pour into the
halls of academia. By some measures this has served
us well. Since 1945 United States scientists have
received 56% of the Nobel Prizes in Physics, 60% in
Medicine, and 42% in Chemistry.
The societal return concept does not work well in a
world-integrated economy; in fact the very idea of
only one country having the monopoly in education
is questionable and universities would do well to
think in broader terms. Nevertheless a firmly in-
grained consequence of operating under this para-
digm for the last half century is that academic suc-
cess (indeed, scholarship) has been associated with
research, and research, in turn, exclusively with dis-
covery. This might have been a narrow viewpoint,
but its appeal was unparalleled. All universities tried
to fit into the mode and faculty were judged prima-
rily as researchers; after all, there was money to be
garnered from successful academic enterprises.
Scholarship goes beyond research, however. By
and large, only one type of scholarship is routinely
acknowledged-the Scholarship of Discovery. Based
Continued on page 175.


Fall 1993












APPLIED STOCHASTICS

FOR ENGINEERING


JAY D. SCHIEBER
University of Houston
Houston, TX 77204-4792

here is an old joke that says that a statisti-
cian is someone who drowns while trying to
cross a river with an average depth of three
feet. But that sounds to me like the definition of a
bad statistician. On the other hand, I have run across
many otherwise good engineers who recognize the
perils of considering only an average quantity, but
have avoided probabilistic models altogether. I be-
lieve that engineers might serve themselves better
in the long run by becoming good statisticians and
good stochastic modelers.
There is a perceptible increase in the interest of
stochastics in the chemical engineering community,
evidenced by two observations: the fall 1993 AIChE
meeting is slated to contain a session on "Probabilis-
tic Models," and no less than three articles from the
1989 issues of this journal included some discussion
of stochastic models in a new course description.
Clearly, stochastics is playing an increasing role in
chemical engineering.
Last spring our department initiated a course in
introductory stochastics designed to introduce
graduate students to this rapidly expanding field.
Fourteen students enrolled in the course, two stu-
dents audited it, and two faculty also attended regu-
larly. The sophistication of the semester projects
that were turned in suggests that the students
learned a lot, and the course appeared to generate a
great deal of enthusiasm.
In this article we will consider the following ques-
tions in order:
* What is Stochastics?
* Why is it of interest to chemical engineers?
* What tools can be taught in a single semester course?
WHAT IS STOCHASTICS?
One day in 1910, Albert Einstein had just finished
working on a stochastic problem involving Brownian
motion when his young son Hans Albert asked him
Copyright ChE Division ofASEE 1993
170


Jay D. Schieber is Assistant Professor of ChE
at the University of Houston, where he has
been since 1991. He received his BS from the
University of Illinois, Urbana, and his PhD from
the University of Wisconsin in 1982 and 1989,
respectively. He spent a year at the University
of Freiburg (Germany) and another at McGill
University (Canada) as a postdoctoral fellow.
He has an active research program in kinetic
theory, transport phenomena, fluid mechanics,
and polymer rheology.

for a Rechenaufgabe." He thought up the following
probability problem: "How long will it take til the
ground is wet if it rains at the rate of 10mm/hr?" The
problem is probabilistic, because rain does not fall
uniformly, but rather in drops which cover (roughly)
circular regions on the ground when they hit. After
some portion of the ground is wet, the next drop may
land completely on a dry area, completely on a wet
area, or partly on each. There is no way to know
where a given drop will land, so it must be treated
statistically. Therefore, how long it takes a given
portion of land to be completely wetted is not a
deterministic question but a statistical one. We can
find only the probability that it will take any given
time to wet the ground.
Or, consider a second problem. Suppose that I take
my red 1966 Volkswagen Beetle to a particular point
in the salt flats in Arizona, fill it with one quart of
gas, push-start it (as usual), point it north, put it in
first gear, set a brick on the gas pedal, and let it go
without a driver. Where will the Beetle be when it
runs out of gas? If there were no wind we might
be able to predict all of the forces on the Beetle and,
in principle, calculate where the car will end up.
But, in reality there is wind, the strength and di-
rection of which we cannot predict. If we run the
experiment many times, the Beetle will end up in a
different place each time. We quickly understand
that the car is subject to both random and determin-
istic forces, and the final position of the Beetle de-
pends upon both.
"Solving" the above two problems means that we
seek the probable distribution of possible outcomes.
Chemical Engineering Education









The corresponding equations are called "stochastic"
equations.* We can then roughly define stochastic
equations as equations that describe a quantity (the
position of the Beetle) whose evolution (in time) is
determined by both deterministic (the motor, the
grade, etc.) and random (wind) influences.

WHY SHOULD CHEMICAL ENGINEERS
LEARN STOCHASTICS?
The engineer can quickly think up other, more
relevant examples of when outside random influ-
ences can have a result on a final answer than the
two given above: outside random influence on labo-
ratory experiment measurements or plant processes;
randomly fluctuating temperatures or pressures; ran-
dom changes in feed stream compositions. But there
are many other examples which are less than obvi-
ous. For example, concentration is the average num-
ber of molecules per volume in a region of space, and
each molecule is acted upon randomly by other mol-
ecules. The actual number of molecules in a region of
space is stochastic. The pore structure in a catalyst,
or in an oil reservoir, is random. The transport of
substances through these structures depends upon
the random pore network. Cells in vitro undergo
Brownian motion as they are bombarded by sur-
rounding fluid molecules. Populations of cells may
be described by stochastic birth-death equations.
Polymer chains may take random conformations and
be bombarded by Brownian forces.
We can make a general observation here. When
working with a large, complex system (and chemical
engineers are certainly interested in large, complex
systems) in which it is effectively impossible to in-
clude all degrees of freedom in the system, the num-
ber of variables being considered must be curtailed.
Nonetheless, in any real system, the other degrees of
freedom not accounted for explicitly still have an
influence, and if this influence is not considered
deterministically, it must be considered statistically.
At that point, the mathematical equations corre-
sponding to the physical process are stochastic.
We can safely say that chemical engineers need to
learn stochastics in order to tackle many of the new
problems entering the field. Why? Because chemical
engineering is moving toward smaller and smaller
length scales as processes become more efficient and
less consumptive of material resources. Bugs per-
forming bioremediation are being jostled by water
molecules; electrons in plasmas are colliding and
reacting with large neutral species; molecules in low-
pressure reactors are bouncing off of walls, diffusing
* We are using a broader definition of the term "stochastics" than
that used by some mathematicians.
Fall 1993


on surfaces, and jumping between activation sites.
At these length scales, the influence of individual
molecules becomes important. But there are still too
many molecules to handle explicitly for any timescale
of interest, and Brownian forces will be important.
On the other hand, many degrees of freedom acting
on wildly different length scales appear to be ideally
suited for stochastic models.
Understanding stochastics allows us to write down
well-posed mathematical equations corresponding to
intuitive probabilistic pictures. Equally important,
that understanding helps us to design simple com-
puter codes to solve the resulting complex partial
differential equations numerically.

COURSE STRUCTURE
The course structure is outlined in Table 1. No
textbooks are required for the course, but two are
highly recommended. The first, by C.W. Gardner, is
called Handbook of Stochastic Methods for Physics,
Chemistry and the Natural Sciences.[2] It is an excel-
lent handbook for mathematical solutions, is well
organized conceptually, and has a good mix of theo-
rem and description. But its background in prob-
ability is too thin for most engineers, the connection
to physical problems is often minimal, and it con-
tains no problems.

TABLE 1
Outline of Material in the Applied Stochastics Course
(Although not explicitly shown, examples are
scattered throughout the course.)
1. Background ideas and definitions
Averages, variance, moments
Probability density function, cumulative probability
Conditional probabilities, Bayes' Rule, joint probabilities
Contraction or marginal probabilities
Characteristic functions, moment generating functions
Sample distribution functions: Gaussian, Poisson
2. Probability transformations
General formula
Generating random numbers
Deterministic processes with random initial conditions
Central limit theorem
3. Markovian concept
Definition
Chapman-Kolmogorov equation
4. Equations characterizing Markovian stochastic processes
Differential Chapman-Kolmogorov equation
Liouville equations
Master equations
Fokker-Planck equations
Stochastic differential equations
5. Examples of Markovian processes
Problems with analytic solutions
Brownian dynamics simulations
Dynamic Monte Carlo simulations









On the other hand, the second recommended text,
by N.G. van Kampen, Stochastic Processes in Phys-
ics and Chemistry, 3 is organized more like a physics
book and contains many problems. In general, we
followed more closely the overall organization of
Gardiner, but used van Kampen for all develop-
ments involving master equations. Unfortunately,
neither text contains information of numerical meth-
ods; a few texts do exist with some discussion of
numerical techniques."4'5]
Typically, most engineers have no formal back-
ground in probability or statistics, so a significant
amount of time must be spent in the beginning with
the basic definitions and concepts shown under the
first heading in Table 1. For example, while most
engineers know what an average and a variance
are, less familiar are probability density and
autocorrelation functions, or a conditional proba-
bility. We begin by playing with typically simple
probabilistic (gambling) problems, incorporating
these ideas so that the student gets a good feel
for what information the quantities contain. This
section of the course takes about three weeks. Some
of the important definitions introduced here are
shown in Table 2.
This is a also good time to introduce an essential
concept used to great extent throughout the course:
the dual descriptive character of stochastic processes.
We can characterize a Markovian stochastic process
either through the deterministicc) time evolution of
the probability density function or through the sta-
tistical properties of an equation describing the evo-
lution of a single trajectory. These two viewpoints
are roughly analogous to Hamilton's versus
Liouville's description of classical mechanics.
When we reach the second section, probability
transformations, we are ready to begin solving physi-
cal problems. This section deals with the general
problem of transforming some random variable, X,
to some new random variable, Y := f(X), when the
statistics of X are known and we wish to know the
statistics ofY. A physical example is the orientation
of network strands in a deformed rubber. Before
deformation, the strands have random orientations
whose distribution is isotropic, but when the rubber
is deformed affinely, each strand moves determinis-
tically to a new orientation. We are interested in
finding the new orientation distribution of strands
after the deformation.
Probability transformation also plays a role in gen-
erating random numbers with given distributions
from random numbers drawn from a uniform distri-
bution. The mathematician John von Neumann has


been quoted as saying, "Anyone who considers arith-
metical methods of producing random digits is in a
state of sin." We largely avoid these problems, how-
ever, and assume that we have a suitable pseudo-
random number generator available. Knuth"61 dis-
cusses statistical tests of pseudo-random number
generators, and Press, et al.,"71 provide some concrete
examples. A recent article by Hayes"8' (who cites the
above quote) discusses more recent ideas and ob-
stacles of such generators. The ideas contained
therein are discussed briefly in class.
This is a good time to introduce the central limit
theorem for three reasons: it contains all of the
probability concepts introduced before; it plays an
important role in many physical systems; and a
concrete example, namely random walks on a one-
dimensional lattice, provides a good segue into the
next topic.
All of the concepts introduced so far are for general
stochastic processes. However, the vast bulk of the
mathematical literature, most physical models, and
nearly all of the numerical work utilizes Markovian
processes. Thus, we introduce the mathematical defi-
nition and physical interpretation of a Markov pro-
cess. Intuitively speaking, these are processes where
we need to know only the current state of the system
in order to know future probabilities; knowing all of
the past states of the system gives us no additional

TABLE 2
NOTE: The symbol Prob {... reads as "the probability that"
and := means "is defined as." The integrals must be taken over
all possible values of the integration variables.
<...> represents taking an ensemble average.

Probability density function
P(x;t)dx := Prob{The random variable X takes values
between x and x+dx at time t} (1)

Joint probability function
P(x,t;y,t')dxdy := Prob{The random variable X takes
values between x and x+dx at time t and values
between y and y+dy at time t'. } (2)

Conditional probability function
P(x;tly;t')dx := Prob{The random variable X takes
values between x and x+dx at time t
given that it had value y at time t'. (3)

Averages may be found from these by
(f(X))t = JxP(x,t)dx (4)

Autocorrelation functions are found by
(X(t)x(t')) = fJxyP(x,t;y,t')dxdy (5)

Chemical Engineering Education









insight into future probabilities if we know the current state.
Using the definition of Markov and Bayes' rule, we can derive the
Chapman-Kolmogorov equation, a nonlinear, integral equation for the
conditional probabilities of Markovian processes. This form of the equa-
tion has only limited practical use, so we can derive from that the so-
called differential Chapman-Kolmogorov equation which has greater


C hapman-Kolmogorov Equation )

S Differential
Chapman-Kolmogorov Equation


Liouville Equation Master Equations ) (Fokker-Planck Equations
It "$ S "
Equations of Motion Langevin-like Equations) (Stochastic Diff. Equations
I T 1 T I T
Molecular Dynamics Dynamic Monte Carlo Brownian Dynamics

Figure 1. Interrelation between important equations for Markovian processes.

TABLE 3
The vector A describes the deterministic forces on the random vector, and B
(or b) describes the random forces. The transition probability W(xlz,t) de-
scribes the probability per unit time that the random vector makes a discon-
tinuous and instantaneous jump from z to x at time t. The Wiener process,
dW,, is a delta-correlated, Gaussian white noise.

Chapman-Kolmogorov equation:
P(x3;t3l|x;ti)= P(x;t t2)P;t (x2;t2zxl;tl)dx2 (6)

Differential Chapman-Kolmogorov equation
aP(z;tly;t')= [Ai(z,t)P(z;tJy;t)] 1+ -j a2 [Bij(z,t)P(z;t.y;t )]
ly' \ ) = 1 ai 2 11ziazj 1

+ f[W(zlx;t)P(x; ty;t') W(xlz;t)P(z;tly;t')]dx (7)

Master equation
P(z;tly;t) = J[W(zlx;t)P(x;tJy;t') W(xlz;t)P(z;tly;t')]dx (8)

*Fokker-Planck equation
*P(z;tly;t)= a-i[Ai(z,t)P(z;tly;t')]+ a [Bi(bz,t)P(z;tly;t')] (9)


*Liouville equation
-P(z;t3|Y;t2)= [Ai(z,t3)P(z;t3|y;t2 )] (10)
i az
Langevin equation
dXt = A(X,t)dt + b(X,t) dWt (11)

Fall 1993


utility for our purposes: namely, the
solution and description of stochas-
tic processes. Most of the equations
for the rest of the course are spe-
cific cases of the differential
Chapman-Kolmogorov equation.
The differential Chapman-
Kolmogorov equation can also be
split into three rough categories: 1)
master equations for discrete or dis-
continuous jump processes; 2)
Fokker-Planck equations for con-
tinuous (but nondifferentiable) dif-
fusion processes; and 3) the
Liouville equation for deterministic
processes which may or may not
have random initial conditions. The
general forms for these equations
are shown in Table 3, and the in-
terconnection between them are
shown in Figure 1.
Before deriving the differential
Chapman-Kolmogorov equation
from the Chapman-Kolmogorov
equation, we go through derivations
of simple examples of each type of
equation. In addition, we repeat
Langevin's derivationg91 of the first
stochastic differential equation.
An entire week is spent deriv-
ing the differential Chapman-
Kolmogorov equation and analyz-
ing its different subclasses as
combinations of deterministic mo-
tion, diffusive motion, and jump
processes. Emphasis is placed on
interconversion between the
evolution equation of the probabil-
ity density function and sample tra-
jectories of the equivalent process.
In this way the students get a feel
for how to translate physical pic-
tures into, say, master equations,
or how to interpret the physical pro-
cess represented by, for example, a
Fokker-Planck equation. Many
simple examples are useful here.
Finally, in this section we cover
stochastic differential equations,
which are intuitively very appeal-
ing-but mathematically they are
usually intimidating for students on
their first exposure. The primary
173









impediment for students is that this is often the first
time they need non-Riemannian calculus to inte-
grate equations. But we have borrowed an introduc-
tion strategy from Gardiner that seems to be suc-
cessful in getting across the importance of attaching
an interpretation to any stochastic differential equa-
tion with multiplicative noise.
By the end of the section most students have little
problem working with either It6, Stratonovich, or
the more recent kinetic interpretations.t101 This sec-
tion requires two weeks of coverage to make the
students comfortable, but the payoff for the hard
work is unquestionably great since Brownian dy-
namics simulations are straightforward once the in-
terpretation questions have been tackled.
I find discussion of numerical techniques to be a
natural extension to the analytical solutions found
for these equations. It is also at this point in the
course that the students begin to see the power of
stochastics. They see that complicated master equa-
tions have straightforward interpretations and may
be solved easily by dynamic Monte Carlo techniques.
Likewise, a complicated Fokker-Planck equation in
thirty dimensions may be solved by a straightfor-
ward Brownian dynamics simulation without resort-
ing to finite element methods.
The numerical techniques of stochastic dynamic
simulations exploit the equivalence between equa-
tions of the third and fourth rows shown in Figure 1.
Just as molecular dynamics techniques solve
possible trajectories of interacting particles rather
than the distributions function in Liouville's equa-
tion, Brownian dynamics simulations track the
trajectories of realizations to estimate the probabil-
ity density function in the Fokker-Planck equation.
In the course, examples of Brownian dynamics
simulations are given for simple polymer and cell
motility models.
Likewise, the trajectories of realizations of sto-
chastic processes described by master equations
can be described by Langevin-like equations,
which suggest dynamic stochastic algorithms. We
show detailed examples of nonlinear reaction mod-
els that can be solved by such dynamic Monte Carlo
techniques.
We spend most of the rest of the semester going
through examples of how to model chemical reac-
tions,111 cell migration,[121 population balances, poly-
mer dynamics,"13' transport equations,14' lattice gas
dynamics "1 for thermodynamic predictions, etc., as
stochastic equations, solve them analytically or nu-
merically, and interpret the results. These examples


174


TABLE 4
Term Project Topics Chosen by Students
Critical Review of Single Technical Paper
Modeling of mechanical degradation of dilute polymer solutions
A stochastic model of persistent currents in mesoscopic rings
General Review of Research Area
Application of dynamic Monte Carlo simulation method in study
of surface kinetics
Stochastic models for turbulent diffusion
Diffusion models for characterizing the firing sequences of
neurons
Stochastic two-phase flow in porous media
Stochastic representation of reservoir heterogeneity
Markov models for behavior
Stochastic modeling of air pollution
Original Research
Stochastic dynamic simulation of cubic autocatalytic reactions to
study bifurcations in chemical reactions
Stochastic modeling of coalescence of viscous drops in liquid-
liquid dispersion
Stochastic simulation of combined molecular diffusion and
chemical reaction
Solution of the Boltzmann equation by using dynamic Monte
Carlo simulation
Brownian dynamics simulation of a Hookean dumbbell with
internal viscosity in steady shearing flow


pull together all of the ideas introduced in the course,
provide concrete examples of their utilization, and
show how powerful and simple the techniques are.

TERM PROJECTS
Many of the examples in engineering are quite
new. Nonetheless, I require that the students do a
term project that fits into one of three categories:
1. A critical review ofa single technical manuscript that
utilizes stochastic modeling.
2. A general review of stochastic modeling in a chosen
field critiquing several manuscripts.
3. Original work using stochastic modeling for a re-
search project.
I recommended the third category primarily for
those students who may have had an original idea
for a simple project while working on a project in the
first category. After discussion, I made specific rec-
ommendations to a few students for original projects
which they followed up on.

CONCLUSIONS
Table 4 shows a list of the projects chosen by the
students in each category. Surprisingly, one-third of
the class chose projects which were strictly original,
whereas the projects in the first category included
some original work and research suggestions.
The quality of the original work was quite good,
Chemical Engineering Education









suggesting that problems of interest to chemical en-
gineers are fertile ground for the use of stochastics.
Also, the students doing critiques of manuscripts for
projects often found that much well-respected work
can be greatly improved by someone with a working
knowledge of stochastics.
In summary, I can write with a high probability of
certainty that any chemical engineering faculty us-
ing stochastic modeling in research will find that
introducing colleagues and graduate students to these
techniques can be very fruitful.

REFERENCES
1. Einstein, H.A., "Probability, Statistical and Stochastic Solu-
tions," in Stochastic Hydraulics: Proceedings of the First
International Symposium on Stochastic Hydraulics, edited
by Chao-Lin Chiu, University of Pittsburgh, School of Engi-
neering Publication Series, Pittsburgh, PA, p 10 (1971)
2. Gardiner, C.W., Handbook of Stochastic Methods for Phys-
ics, Chemistry and the Natural Sciences, 2nd ed., Springer-
Verlag, Berlin (1985)
3. van Kampen, N.G., Stochastic Processes in Physics and
Chemistry, 2nd ed., Amsterdam, North Holland (1992)
4. Honerkamp, J., Stochastiche dynamische Systeme, VCH,
Weinheim (1990)
5. Kloeden, P.E., and E. Platen, Numerical Solution of Sto-
chastic Differential Equations, Springer-Verlag, Berlin (1992)
6. Knuth, D., The Art of Programming: Vol. II. Seminumerical
Algorithms, 2nd ed., Addison-Wesley, Reading, MA, Ch. 3
(1981)
7. Press, W.H., S.A. Teukolsky, W.T. Vetterling, and B.P.
Flannery, Numerical Recipes, 2nd ed., Cambridge Univer-
sity Press, Cambridge, England (1992)
8. Hayes, B., "The Wheel of Fortune," Amer. Sci., 81, 114
(1992)
9. Langevin, P., Academie des Sciences, 146, 530 (1908)
10. Klimontovich, Yu L., Physica A, 163, 515 (1990)
11. Erdi, P., and J. T6th, Mathematical Models of Chemical
Reactions: Theory and Applications of Deterministic and
Stochastic Models, Princeton University Press, Princeton,
NJ (1989)
12. Stokes, C.L., and D.A. Lauffenburger, "Analysis of the Roles
of Microvessel Endothelial Cell Random Motility and Che-
motaxis in Angiogenesis," J. Theor. Biol., 152, 377 (1991)
13. Ottinger, H.C., Stochastic Processes in Polymeric Fluids,
Springer Verlag, Berlin: in press
14. Laso, M., A Stochastic Dynamic Approach to Transport Phe-
nomena, preprint
15. Volume 47 of Physica D (1991) is devoted to articles on
lattice gas dynamics O



ROLE OF ACADEMIA
Continued from page 169.
on this historical record, the Scholarship Reconsid-
ered report argues, however, that there are at least
three other types of scholarship: Scholarship of Teach-
ing, Scholarship of Integration, and Scholarship of
Application-and that our current thinking might
be too narrow to value all of them.


Scholarship of Teaching entails not only transmit-
ting knowledge, but also transforming it and extend-
ing it as well; Scholarship of Integration is to "give
meaning to isolated facts, putting them in
perspective...making connections across disciplines,
placing issues in a larger context, illuminating data
in a revealing way, often educating nonspecialists
too." This clearly points toward interdisciplinary work
and drawing unexpected connections between dis-
similar areas (without which some disciplines might
wane and die). An acceptance of Scholarship of Ap-
plication demands that we broaden our horizons as
well. The usual mode is that pure is better than
applied, and that things are discovered and then
applied. This need not be so: new intellectual under-
standings can arise out of the very act of application.
The best use of the human potential already in
place calls for recognition of diversity. Faculty diver-
sity should be celebrated, not restricted, and faculty
evaluation should be flexible as well as systematic-
it will be increasingly more difficult to impose
uniform standards on something that by its very
mission should be diverse. A professor's job descrip-
tion is often unchanged over an entire lifetime; in-
stitutions should explore alternatives on how to
sustain productivity. Creativity contracts-an
arrangement where faculty define their profess-
ional goals for a three-to-five year period, possibly
shifting from one principal scholarly focus to an-
other-might offer an alternative.
It is imperative that universities become more
structurally robust. Only in this way are they going
to be able to deal with the pressures imposed by an
ever-broadening mission. The dual mission of dis-
seminating and transforming old knowledge while
at the same time pushing the boundaries of what is
known can only be fulfilled by a combination of tal-
ents and an acceptance of peaceful and profitable
coexistence of various modes of scholarship. Yet, at
the same time, universities cannot be all things to
all people. A broader viewpoint including different
models of success seems to be called for if the institu-
tions that have served so well in the past are to
withstand the pressures of the future.

REFERENCES
1. Sykes, Charles J., ProfScam: Professors and the Demise of
Higher Education, Regnery Gateway, Washington, DC (1988)
2. Boyer, Ernest, Scholarship Reconsidered: Priorities of the Pro-
fessoriate, Princeton: The Carnegie Foundation (1990, reprinted
1993)
3. Eliel, Ernest L., Science and Serendipity: The Importance of
Basic Research, American Chemical Society (1993)
4. Armstrong, John A., "Research and Competitiveness: The Prob-
lems of a New Rationale, MRS Bulletin, 18 4-9 (1993) 0


Fall 1993












PICLES

A Simulator for

Teaching the Real World of Process Control


DOUGLAS J. COOPER
University of Connecticut
Storrs, CT 06269-3222

Process control classes often become more like
abstract mathematics courses as the semester
proceeds. Many instructors rightly believe that
there is a need for students to experience the appli-
cation of classroom theory to real processes so they
may appreciate not only the nuances but also the
main points of the lectures.
Having spent three years in the real world of pro-
cess control with Chevron Research Company, I be-
came frustrated when I began teaching at the uni-
versity level and discovered that (outside of the lab)
few tools were available to me to teach many of the
lessons I considered important.
Too many important concepts are lost when the
bulk of assignments begin, "Start with this transfer
function and .." For example, students must learn
the serious implications that arise because transfer
functions disregard that real processes are nonlinear
and have measurement noise and other nonideal
behaviors. They must learn to quickly and reliably
perform identification studies (real-world production
people can be downright ornery if one asks to experi-
ment with their process). If they succeed in obtain-
ing data from the process, students must learn to
use it to reasonably approximate the local process
behavior with a linear model-and that only then do
they have the transfer function for use with their
classroom design theory.
When their analysis is complete, students must


Copyright ChE Division ofASEE 1993


learn that their controller design, no matter how
sophisticated the approach, is only an initial ap-
proximation-that it must be fine-tuned on the real
process. In the real world, this fine-tuning proceeds
by trial-and-error and must consider both set point
tracking and disturbance rejection.
The best instruction concerning the real world
(short of the school of hard knocks) is obtained
through carefully constructed laboratory experiences.
Although we have several nice process control ex-
periments in our laboratory at the University of
Connecticut, the reality is that each study can take
several hours to perform. As such, it is not reason-
able to have the students explore more than the
most major issues in the lab.
To teach these important lessons, the Process Iden-
tification and Control Laboratory Experiment Simu-
lator (PICLES) was developed. The contribution
PICLES brings to an existing course is that it en-
ables the students to quickly explore many of the
lessons by following the same procedures they would
have to follow if working with a real process.

WHAT IS PICLES?
Let me begin by pointing out that PICLES is not a
control system analysis or design package. Quite the
opposite, this software provides realistic processes
that students can use to practice the analysis and
design methods they are taught. Students say that
PICLES is easy, and even fun, to use. Most com-
mands can be executed with simple key-strokes. Col-
orful graphics help the students follow the action on
the screen as the results of their decisions unfold.
The processes in PICLES encompass a variety of
behaviors. The processes have varying degrees of
nonlinearity so students can explore how process
behavior can change with the operating regime. This
also lets them practice compromising controller
tunings to maintain stability over a wide range of
nonlinear operation.
The processes range from low to high order and
Chemical Engineering Education


Douglas J. Cooper is Associate Professor of
Chemical Engineering and has been teaching
process control at the graduate and undergradu-
ate level for the past eight years. He received
his BS from the University of Massachusetts in
1977, his MS from the University of Michigan in
1978, and his PhD from the University of Colo-
rado in 1985 after three years of industrial expe-
rience with Chevron Research Company












Having spent three years in the real world of process control with Chevron Research Company,
I became frustrated when I began teaching at the university level and discovered that
(outside of the lab)few tools were available to me to teach many
of the lessons I considered important.


have different process gains, time constants, and
apparent dead times, so students can investigate
how these phenomena affect process behavior and
controller stability. The processes have noise in
the sampled data so students can see that, in prac-
tice, the difference between a 10% overshoot and a
15% overshoot can sometimes be indistinguishable.
In the current release (version 2.1), available con-
trollers are all PID, and with PICLES it is easy to
explore all combinations from P-only to full PID
control. Because each process has colorful, dynamic
graphics, after performing a controller design stu-
dents can implement their solution and obtain im-
mediate visual feedback on system performance.
There is a PID Velocity algorithm and a PID Posi-
tion algorithm, so students can observe the conse-
quences of reset windup. They can select "Derivative
on Measurement" or "Derivative on Error" so they
can see what "derivative kick" is all about. Some
controllers require the student to enter the bias or
null value, while others have a bumpless feature
where the bias is automatically set in a fashion
similar to what they would encounter with some
commercial controllers.
There are also model-based controllers in PICLES.


74150 MINSECI P I C L E S
PROCESS GRAVITY DRAINED TANKS
CONTROLLER: MANUAL MODE
DATA STORAGE: OFF
CONTROLLER OUTPUT CCM^3/SEC)
40.
30.
20.
to. ____
.
o. MEASURED LEVEL (CM)
100. *---------------
75. ...
50.
25.
0.
20 15 10 5 C
DATA HISTORY (CINS)


Figure 1. Gravity Drained Tanks shows nonlinear beh
Fall 1993


A Smith predictor enables students to observe how
dead time affects controller performance and that
dead time compensation offers real benefits. A Feed
Forward element permits them to see how distur-
bance rejection works using both static and dynamic
compensators. Decouplers enable them to explore
methods for minimizing loop interaction on the dis-
tillation column.

COMPUTER SYSTEM REQUIREMENTS
PICLES is designed to run on IBM-compatible per-
sonal computers. The computer must have at least
EGA graphics, although VGA graphics provides bet-
ter resolution. For rapid execution, a computer with
a '386 or '486 processor should be used. A math
coprocessor is not required, but it adds additional
speed to program execution.

THE PICLES PROCESSES
Gravity Drained Tanks This process, shown
in Figure 1, is two non-interacting gravity-drained
tanks in series (see assignment lb later in this ar-
ticle for more about the figure). The manipulated
variable is the flow rate of liquid entering the first
tank. The measured/controlled variable is the liquid
level in the second tank. This process displays a
nonlinear behavior because the drain
rate from each tank is proportional to
nODE the square root of the hydrostatic head
VALUE (liquid level in the tank). The distur-
AGE ON/OFF
.UE bance, or process load, is a flow out of
AL ONLY) the second tank due to a positive dis-
OR GRAPHIC
placement pump. Hence the distur-
bance is independent of level except
that it loses suction at extremely low
liquid levels in the second tank.
Heat Exchanger This process,
shown in Figure 2, is a counter-cur-
rent lube oil cooler (see assignment
S3e later in this article for more about
Z; this figure). The manipulated vari-
able is the flow rate of cooling water
OUIATE on the shell side. The measured/con-
S.5 trolled variable is lube oil tempera-
ture exiting the exchanger on the tube
side. An interesting characteristic of
avior. this nonlinear process is that distur-


C -CHANGE CONTROLLER M
D -CHANGE DISTURBANCE
F -TURN DATA FILE STOI
S -CHANGE SETPOINT VAL
I -CHANGE INPUT MANUALA
T -TOGGLE BETWEEN MENU


INLET ...
FLOWRATE





OPEN LOOP
LEVEL
I 73.9 I


DISTURBANCE
FLOWRATE
1 2.5 I L


1










bances, generated by changing the flow rate of warm
oil that mixes with the hot oil entering the exchanger,
display an inverse or nonminimum phase behavior.
The process also has a negative steady state gain.
Design a Process Design a Process has a
display, shown in Figure 3, that is similar to that
found on commercial controllers (see assignment 6a
for more about this figure). It permits students to
input a transfer function and obtain a visual appre-
ciation when studying problems found in textbooks.


Distillation Column The Distillation Col-
umn, shown in Figure 4, is a binary distillation
column that separates water and methanol (see
assignment 8a for more about this figure). The col-
umn dynamics are simulated using a model pub-
lished by Wood and Berry.'11 There are two con-
trolled variables and two manipulated variables. The
reflux rate controls the distillate composition and
the rate of steam to the reboiler controls the bottoms
composition. The feed rate to the column is the dis-


The student can specify a steady state
process gain, an apparent dead time,
up to three process time constants,
and a valve time constant. It is also
possible to specify a "linearity factor"
if a nonlinear process is to be designed.

Mystery Processes These pro-
cesses are not really mysterious.
Rather, they are simply Design a Pro-
cess with a fanciful name and with all
parameters pre-specified and hidden
from the student. Thus each Mystery
Process displays a behavior that
ranges from first to fourth order and
has different overall process gains,
time constants, apparent dead times,
and degrees of nonlinearity. Because
there is no a priori indication of ex-
pected process behavior, the student
must rely strictly on process identifi-
cation studies for controller design.
This simulates the disassociation that
is often felt when tuning controllers
from a remote control room and makes
the simulations perfect for project work
later in the semester. All of the mys-
tery processes use the same graphic
as shown in Figure 3.
Pumped Tank This process is a
surge tank. The manipulated variable
is brine flow rate out of the bottom of
the tank and is adjusted with a throt-
tling valve at the discharge of a con-
stant pressure pump. This approxi-
mates the behavior of a centrifugal
pump operating at relatively low
throughput. The measured/controlled
variable is the liquid brine level. This
surge tank presents an interesting con-
trol challenge because of the integrat-
ing nature of the process. The distur-
bance variable, or process load, is the
flow rate into the tank.


22iii OMINISECI P I C L E S
PROCESS HEAT EXCHANGER
CONTROLLER: P-ONLY CONTROL
DATA STORAGEl OFF
0 CONTROLLER OUTPUT CGPM)

30. 1


20. 4 --...


40 30 20 10
DATA HISTORY (MINS)


C -CHANGE CONTROLLER MODE
SD -CHANGE DISTURBANCE VALUE
F -TURN DATA FILE STORAGE ON/OFF
S -CHANGE SETPOINT VALUE
I -CHANGE INPUT (MANUAL ONLY)
I T -TOGGLE BETWEEN MENU OR GRAPHIC


Figure 2. Heat Exchanger under P-Only control with different controller
gains.


164130 NINISEC P I C L E S
PROCESS MY PROCESS
CONTROLLER: PID VELOCITY (D ON MEAS.)
DATA STORAGE OFF
CONTROLLER OUTPUT (%)


MEASURED VARIABLE C%)






40 30 20
DATA HISTORY (MINS)


I


C -CHANGE CONTROLLER MODE
D -CHANGE DISTURBANCE VALUE
F -TURN DATA FILE STORAGE ON/OFF
S -CHANGE SETPOINT VALUE
I -CHANGE INPUT (MANUAL ONLY)
T -TOGGLE BETWEEN MENU OR GRAPHIC


I 52.0 -) 50.0-1
52.0 50.0
PROCESS DISTURBANCE
INPUT
100 10 -

80- 80 -
60- 60 -

40 40-
20 20-
0- 0-
52. 49.7 0.0
10 0 CONTROLLER MEASURED SETPOINT
OUTPUT VARIABLE


Figure 3. Design a Process under PI control with differing amounts
of dead time.
Chemical Engineering Education


MEASURED TEMPERATURE C(F)


I











turbance variable. This process illustrates interac-
tion between two controllers.

AVAILABLE CONTROLLER MODES

The control algorithms in the current version of
PICLES are all PID and include

Manual Control
P-Only Control (Manual Bias)
Velocity PID Control (Derivative on Measurement)
Velocity PID Control (Derivative on Error)


136 MINUTES P I C
PROCESS: DISTILLATION
TOP CONTROLLER: PID VELOCITY
UOT CONTROLLER: MANUAL MODE
DATA STORAGE' OFF


DISTILLATE COMP (%)

97.0

96.5

96.0

95.5
BOTTOMS COMP (X)
2.0

1.5
... .....
1.0

0.5
0.0
50 40 30 20 10
DATA HISTORY (MINS)


L E S C -CHANGE CONTROLLER M
COLUMN D -CHANGE DISTURBANCE
(D ON MEANS ) F -TURN DATA FILE STORE
S -CHANGE SETPOINT VAL
I -CHANGE INPUT (MANUA


SELECTED CONTROLLER TOP


FEED
RATE 2
CONC 46.50


REFLUX
RATE I
i_ 1.956] I
-----------
SI


STEAM
RATE
S1. 710
_-^"s"0
^^'^


?c^


Figure 4. Distillation Column with Distillate under PI con
Bottoms in Manual


I 20440 MINISECI P I C L E S


PROCESS HEAT EXCHANGER
CONTROLLER: PID VELOCITY CD ON MEANS )
DATA STORAGE: OFF


40.
40. CONTROLLER OUTPUT (GPM)

30.

20.

10.

0.
MEASURED TEMPERATURE C-F)

160.

150.


130.
40 30 20 10 C
DATA HISTORY (MINS)


C -CHANGE CONTROLLER
D -CHANGE DISTURBANCE
F -TURN DATA FILE STO
S -CHANGE SETPOINT VA
I -CHANGE INPUT (MANUl
T -TOGGLE BETWEEN MEN
A -ACTIVATE DESIGN ME
SIMULATION DE
DISTURBANCE 10
MEASUREMENT NOISE 2

CONTROLLER DE
CONTROLLER PID VELOCI
PROCESS INPUT 9
SETPOINT 160
CONTROL BIAS
CONTROL GAIN 0.
RESET TIME 50
DERIV TIME 20.
HIGH ALARM POINT 190
LOW ALARM POINT 130
SMITH PREDICTOR
MODEL GAIN
PROCESS TAU
DEAD TIME


Figure 5. Design Menu of Heat Exchanger under PID col
measurement noise.


Fall 1993


Position PID Control (Bumpless)
Velocity PID with Smith Predictor
Velocity PID with Feed Forward
Velocity PID with Decoupler (Distillation Column
Only)
Version 3, which will be available in 1994, will
include I-Only control and a discrete controller
algorithm.

Figure 5 shows the Design Menu used to specify
controller parameters. The process being simulated
in this figure is the Heat Exchanger
process (see assignment 5a for more
lODE about this figure). Note that the
VALUE simulation noise level can be changed
AGE ON/OFF if it is appropriate for an assign-

L ONLY) ment. Also, in the spirit of the "real
world," high and low alarms can be
DISTILL set to provide additional challenge in
RATE 1.1 .
:ONC 95.99 using the program.

7 Although the limitation to PID al-
--........ 4CC)
TPINT gorithms is viewed as a serious limi-
-2. station by some, I try to exploit this

fact within the classroom lectures. For
]example, I establish that the PID con-
troller is a special case of the Internal
Model Control design method. Also, I
BOTTOMS show how the Smith Predictor is a
RATE1 1.269
CONClimiting case of some predictive con-
S troller design methods. Thus, PICLES
can be used to explore certain aspects
itrol and of these newer design standards.

USING PICLES IN THE COURSE

I start with the Gravity Drained
MODE Tanks process. The model can be eas-

RAGE ON/OF ily derived in class, it behaves intu-
LUE itively, and the nonlinear behavior is
AL ONLY)
U OR GRAPHIC modest. The simulation graphics also
NU BELOW provide realism to help give the stu-
SIGN dents an understanding of the dy-
.0 GPM
.5 oF namic behavior of the process.

SIGN Since I believe that some practice
TY CD=MEAS.)
.9 GPM in programming is important, I also
GPM have the students code up their own
23 GP/F Gravity Drained Tanks process based
00 SEC on the equations derived in class. I
.0 OF
.0 OF then have them determine the pro-
MODEL cess parameters which cause their
OF/GPM
SEC simulation to approximate the dynam-
SEC
ics of the PICLES simulation.

After several assignments in pro-
itrol with cess dynamics and process identifica-
tion, I move on to the Heat Exchanger.
179


I









It is a slightly more complicated process, but it still
behaves intuitively. It has a higher degree of
nonlinearity and also has a negative steady state
gain, which reinforces my lecture that gains not only
have magnitude and units, but also a sign. The
nonminimum phase or inverse dynamics of the dis-
turbance response provides another new twist.
After they have explored several investigations of
process dynamics, some identification methods, and
explored a few controllers and design techniques
using Gravity Drained Tanks and Heat Exchanger, I
use the Mystery Processes for project work. I assign
a different Mystery Process to each group of stu-
dents and let them tie things together by doing an
identification, preliminary controller design, and
finally determining a single "best" tuning for
both set point tracking and disturbance rejection, all
as one assignment. Because the processes are non-
linear, each student can have his or her own project
by specifying different ranges of operation for each
problem (i.e., Amy must design for an output range
of 20-30%, etc.).
I use Design a Process intermittently to isolate
specific process behaviors. For example, I ask the
students to implement a true first-order process un-
der P-Only control and let them demonstrate that
such a process is unconditionally stable for all val-
ues of controller gain. They then show that a second-
order process under P-Only control can approach the
limit of stability, and finally, that higher order pro-
cesses under P-Only control can go unstable. When
combined with a class discussion on system stability
using root-locus, the students benefit from relating
theory to practice while the subject is being taught.
As another example of using Design a Process
later in the course, I assign a set of time constants
and a process gain and ask the students to design
and validate a controller. Then, keeping those pro-
cess variables and tuning parameters fixed, they
add dead time to the process and discuss their
observations on the effect dead time has on closed-
loop performance. Finally, they design and imple-
ment a Smith predictor to relate our in-class
derivations and discussions with actual application
to assist them in understanding the benefits of
dead-time compensation.
When the students start feeling confident, I give
them the Pumped Tank process. The integrating
nature of the process really surprises them and re-
quires me to do a lot of explaining ("Why is there no
offset with a P-Only controller?" "How come with a
PI controller, this process goes unstable when the


controller gain is too high and too low?").
Finally, the Distillation Column lets the students
see what can happen when more than one controller
is operating on the same process. The interactions
show them that optimizing controllers individually
does not necessarily produce an optimum solution
when the controllers begin to interact. Also, the stu-
dents can investigate how model-based decouplers
can work to minimize this interaction.

EXAMPLE HOMEWORK ASSIGNMENTS
To illustrate how PICLES can be integrated into
an existing course in process control, this section
lists sample homework assignments. These assign-
ments follow the order of development used in
most textbooks and let students visually appreciate
these important concepts. The five figures previ-
ously discussed also serve as partial answers to
selected problems.

Assignment on Process Dynamics
1. Using Gravity Drained Tanks in Manual mode:
a. Plot and discuss how the measured level responds to step
changes in the manipulated inlet flow rate and the distur-
bance flow rate. Comment on the natural stability of the
process.
b. Starting from three different steady state operating regimes,
plot how the measured level responds to manipulated inlet
flow rate perturbations of fixed size. Based on these plots,
discuss the nonlinear nature of the process. (Answer: Figure
1 shows the nonlinear nature of the process because the
measured level responds differently for three step changes of
equal size in the manipulated inlet flow rate.)
Assignment on Process Identification
2. Using Design a Process:
a. Generate an open loop input/output step response curve for a
true first-, second-, and third-order process. How does the
time to 63.2% of change compare to the time constants
assigned? Discuss your conclusions.
Assignment on P-Only Control
3. Using the Heat Exchanger in P-Only mode:
a. For a design operating temperature, determine the value and
units of the controller bias.
b. Obtain a FOPDT (first order plus dead time) model describ-
ing process dynamics around this design temperature and
use it to compute a P-Only controller gain using ITAE,
direct synthesis, IMC, etc.
c. Starting with this controller gain and bias value, use trial-
and-error to find the "best" gain, where for this assignment
"best" is defined as a 10% overshoot for set point steps of a
specified size. Now show the ability of this "best" controller
to reject step disturbances.
d. Starting from the design operating temperature and using
your "best" tuning, make set point step changes of various
sizes in both directions. Discuss your observations on offset.


Chemical Engineering Education










e. Pick a specific set point change and plot the response of the
process when using your "best" controller gain, half of that
gain, and twice that gain. Discuss your observations on the
relationship between controller gain and offset. (Answer:
Figure 2 shows set points steps with two different controller
gains, and that offset and the oscillatory nature of the re-
sponse changes as controller gain changes.)
Assignment of PI Control
4. Using Gravity Drained Tanks or Heat Exchanger in PI velocity
mode:
a. Explain why no bias is necessary for this controller.
b. Obtain FOPDT model describing process dynamics around
a design point of operation and use it to compute a PI
controller gain and reset time using ITAE, direct synthesis,
IMC, etc.
c. With these parameters as a starting point, use trial-and-error
to find the gain and reset which provide a "best" perfor-
mance. Here, "best" performance is defined as a 10% over-
shoot and a 25% decay ratio to a set point step of specified
size. Why can we design for two performance criteria with a
PI controller, but only for one with a P-Only controller?
d. Plot a matrix of process responses for the same set point step
where this matrix includes all combinations of your "best"
tuning, a gain that is double and half of your "best," and a
reset time that is double and half your "best." Use your
observations to explain the roles of gain and reset time on
controller performance.
Assignment ofPID Control
5. Using the Heat Exchanger in PID velocity mode:
a. Design and implement a PID controller and compare its
performance to PI control. For this comparison, test a num-
ber of set point and disturbance scenarios and show where
the derivative action really pays off. Plot the distinctive
scenarios and use them to explain why or why not any
performance benefit occurred. (Answer: Figure 5 shows that
derivative action can produce very poor performance when
employed on a noisy measured variable.)
Assignment on Dead Time and the Smith Predictor
6. Using Design a Process in PID with Smith Predictor mode:
a. For the assigned process gain and set of time constants,
design and validate a PI or PID velocity mode controller that
gives a 10% overshoot and a 25% decay ratio for a given set
point step. Keeping the process variables and tuning param-
eters constant, add dead time to the process and discuss your
observations on the effect dead time has on closed-loop
performance for this same set point step. (Answer: Figure 3
shows two sets of set point steps. PI controller tuning is fixed
throughout. Controller performance is markedly different
for the first set point steps where the process possesses no
dead time compared to the second set of steps where the
process possesses thirty seconds of dead time.)
b. Keeping the same process gain, set of time constants, and
including the dead time, tune your controller to again pro-
duce a 10% overshoot and a 25% decay ratio. Compare this
plot and tunings to the case where no dead time was present.
Discuss your observations.
c. Now design and implement a Smith Predictor and again tune
the controller to produce a 10% overshoot and a 25% decay


ratio. Compare this plot and tunings with the previous two
cases and discuss the pros and cons of dead-time compensa-
tion.
Assignment on Disturbance Rejection and Feed Forward
7. Using Gravity Drained Tanks or Heat Exchanger in PID with
Feed Forward mode:
a. For the design point of operation, develop a FOPDT model
of the disturbance-to-output dynamic relationship. Using this
model, compare a static and a dynamic feed-forward com-
pensator for step changes in the disturbance variable.
b. For the Gravity Drained Tanks, the disturbance immediately
impacts the measured variable while there is a lag before
input variable manipulations can compensate. Explain how
this influences your comparison of the static and dynamic
compensators.
c. For the Heat Exchanger, there is a reasonable lag before a
disturbance impacts the measured variable. Discuss how this
influences your comparison of the static and dynamic com-
pensators.
Assignment ofMultivariable Control and Decoupling
8. Consider controller design for the Distillation Column when
given specified design operating concentrations for the distillate
and bottoms.
a. While the bottom controller remains in Manual mode, de-
sign and implement a PI controller for the top controller.
Plot the performance of the controller for distillate concen-
tration set point steps both up and down. (Answer: Figure 4
shows one possible solution to this question.)
b. While the top controller remains in Manual mode, design
and implement a PI controller for the bottoms controller.
Plot the performance of the controller for bottom concentra-
tion set point steps both up and down.
c. Using the controller tuning parameters from a and b above,
implement PI controllers on both loops. Make set point
changes for both controllers and discuss loop interaction.
d. Now design and implement both static and dynamic control-
lers. Perform the same set point changes as in part c and
discuss the impact of model-based decoupling.

FINAL NOTE
For more information about PICLES and available
teaching materials, write to the author at the Chemi-
cal Engineering Department, University of Connecti-
cut U-222, Storrs, CT 06269-3222.

ACKNOWLEDGMENTS
I would like to thank the students without whom
PICLES would not exist. These include Architects:
Allen Houtz, Robert Schlegel, and Adam Lalonde,
and Builders: Scott Ferrigno, Ralph Hinde, Jr.,
Larry Megan, C. Steven Micalizzi, Phil Pearson, and
Yan Wan.

REFERENCES
1. Wood, R.K, and M.W. Berry, "Terminal Composition Con-
trol of a Binary Distillation Column," Chem. Eng. Sci., 28,
1707(1973) O


Fall 1993











THE QUEST FOR

EXCELLENCE IN TEACHING


RAFFI M. TURIAN
University of Illinois at Chicago
Chicago, IL 60680


believe that teaching is the most transcendent
of all the responsibilities of a university profes-
sor, and that the search for excellence in teach-
ing must stand as a continuing quest for each of us.
There is a view, held by some, that teaching and
research are antagonistic endeavors; that one can
only be done well at the expense of the other. I do
not share this view. I believe that, carried out in
proper balance, teaching and research should be
mutually reinforcing.
Nonetheless, although it is expected that being a
contributor to creating knowledge is a defining at-
tribute of teaching at the university level, there are
good teachers who do not do research. They are not
usually recognized. Yet, the obligation to teaching is
so primary and broad that, in instances when re-
search or other obligations are in conflict with it, it
must take precedence.
I believe the prerequisites for excellence in teach-
ing to be: mastery of subject; broad knowledge of the
field; meticulous preparation; faith in the potential
of, and the promise in, each student; the ability to
invest one's subject with purpose; the sensitivity to
temper rigor with forbearance and firmness with
compassion; the courage to hold to one's convictions;
and the humility to admit error. It is difficult to
measure excellence in teaching with precision. In-
deed, it is difficult to define good teaching, although
one will recognize it when one sees it. Good teachers
are shaped by personal experience; the perception of
what constitutes excellence in teaching is uniquely
personal. This constitutes my personal statement on
excellence in teaching. It is a tribute to those who
have taught me.
My high school was an English boarding school in
Cyprus. We took English, French, classical Greek,
Latin, biology, differential equations, physics,
chemistry, the history of the British Empire, and
cold showers at 5:00 every morning. It was rigorous
Copyright ChE Division ofASEE 1993


Raffl M. Turlan is Professor of Chemical En-
gineering at the University of Illinois at Chi-
cago. He received his BS from the University
of Maryland, and his MS and PhD from the
University of Wisconsin. He has held faculty
positions at Syracuse and Texas Tech Univer-
sities and has also worked with Shell and the
National Science Foundation. His teaching and
research are in transport and fluid-particle pro-
S cesses.

and it was hard. But it was bearable, except for
the English food.
I remember high school as a time when I discov-
ered that I loved poetry, literature, history, music,
the sunrise, and mathematics. High school was a
profoundly enriching experience; learning was a con-
tinual process of discovery. It was also a time of self-
discovery. I had great teachers. They all had degrees
in their subject areas and a deep interest in the
subjects they taught. They did not seem to be both-
ered by whether or not we were having fun. They
were very serious about their tasks.
We did not study American history in high school.
Later, as a freshman at Maryland, my teachers were
intrigued by my curiosity and interest in American
history. Little did they suspect that when one has
been taught to get excited about Disraeli, Palmerston,
Metternich, and the politics of the balance of power
in Europe, it is not difficult to get excited about
Jefferson, Madison, and the politics of the power of
human rights in the New World.
American history, modern poetry, and Homer stand
out as the most memorable subjects from those Mary-
land days. It was not that chemical engineering
couldn't also be exciting-but that was to come later.
As a graduate student at Wisconsin I sat in the
classes and in the midst of inspiring teachers: Olaf
Hougen, R. Byron Bird, W. R. Marshall, Edwin
Lightfoot, and Warren Stewart. Chemical engineers
recognize them as men of towering scholarly reputa-
tions. I, however, stand as witness to the fact that of
all their impressive achievements, the most memo-
rable measure of their standing was the special car-


Chemical Engineering Education









ing with which they held the humblest of students. I
was in the presence of great teachers, and I felt it. I
knew that I would be fortunate if I succeeded in
emulating any of them as my personal example.
Through the years I have continued to learn and
draw inspiration from many others: colleagues such
as Chi Tien at Syracuse and Sohail Murad here, and
students like Raj Rajagopalan of Houston, Alkis
Payatakes of Patras, and Hemant Pendse of Maine.
Perhaps I have taken something from each of my
different teachers, and if so, I hope I have passed on
the legacy to my own students. Great teachers are
our link to greatness from the past, as our students
are our link to the future. That is why the quest for
excellence in teaching is a solemn obligation. Great
teachers are also good students.
Good teaching is done inside as well as outside the
classroom. One must have mastery of subject to
enrich content, and broad knowledge of the field
to place it in context and to invest it with purpose.
But command of subject cannot replace preparation.
Good organization, careful writing, and a pace of
presentation appropriate to material and audience
suggest respect for subject, seriousness of purpose,
and sensitivity to student needs. The classroom
presentation is not a performance, with the
teacher as actor and the students as audience; they
are the entire show.
Chemical engineering is a human activity. I try to
infuse my classroom presentations with examples of
brilliant achievements of real chemical engineers,
teachers, and practitioners. I tell them that a great
nation needs good chemical engineers just as it needs
good poets. Otherwise, neither could its chemical
engineers do a good job refining its oil, nor its poets
reach for refinement in expressing its values or fram-
ing its ideals. Perhaps, ideally, a great nation needs
good chemical engineers who are poets.
Good teachers are humorous when appropriate,
and try to make their lectures exciting, without mak-
ing entertainment or the kindling of deep emotions
their highest aims. Above all, good teachers stand
before students and teach them something that they
know well and believe in deeply.
There was a time when I told my students that the
purpose of education was not to teach them how to
make money, but how to spend it well after they
made it. That time is gone. Today we must teach
them how to make money as well as how to spend it
wisely. But I do not lament the passing of those
gentler times. The challenge before us now is how to
turn our students into concerned, thinking individu-


I try to infuse my classroom presentations
with examples of brilliant achievements of real
chemical engineers, teachers, and practitioners. I
tell them that a great nation needs good chemical
engineers just as it needs good poets.

als with durably marketable skills, without making
the catering to a current job market our highest aim.
Great teachers do not yield to current fads; that is
what university administrators do.
Being a good teacher means spending a lot of time
with the weakest students, without losing touch with
the best. It means being able to recognize and cel-
ebrate what is best in each student, without being
blind to what is deficient. It means taking the time
to discuss an exam with them, without conceding
that the grade they have received is only a first offer.
It means writing recommendation letters, even on
short notice. It means helping some get scholar-
ships, others to find jobs or to get into graduate
school, and still others to get help or to seek counsel-
ing. It means meeting with parents, describing to
them what we do, and if they have trust in us, as
most of them still do, to demonstrate that their trust
is well-placed; and if they have misgivings, as in-
creasing numbers do, to reassure them that we are
aware of their concerns and that we care.
Above all, good teaching requires that we call stu-
dents to duty and that we insist they assume pri-
mary responsibility for their own learning. The hall-
mark of education is honesty, and honesty requires
that students be told that learning is hard; often
painful. That not all of us are great teachers, or even
care to be. That it is possible to have fun here, but if
that is all they want, there are better places for
them-perhaps a tropical resort. That if they set
their threshold for excitement high they will miss all
that is full of wonder around them. That if
they learn to have reverence for small wonders, they
will discover exaltation in bigger ones. And that
there is no entitlement to a degree in chemical engi-
neering; only a fair chance at earning it-through
hard work and honesty.
I believe that excellence in teaching is not a
state of being, but rather a continual search. It is
said that with prose one transmits thought, with
poetry one reaches for revelation. I hope that some
day before I take up poetry full time, I will have
touched it in my teaching.
But then, great teaching is not in the attainment;
it is in the quest. 0


Fall 1993












THE FREE ENERGY

OF WETTING


WILLIAM G. PITT
Brigham Young University
Provo, UT 84602

he wetting and spreading of liquids on solids
is frequently encountered in the chemical in-
dustry. Examples include the application of
herbicides, adhesives, inks, paints and other coat-
ings, flotation of minerals, containing and cleaning
chemical spills, waterproofing, cloud seeding, lubri-
cation, corrosion protection, enhanced oil recovery,
and more. Despite its importance, however, wetting
and spreading in the chemical process industries is
often without a home in most undergraduate chemi-
cal engineering curricula.
The subject could be taught in classes on engineer-
ing materials, plant design, or separations. An infor-
mal survey of nine undergraduate texts1-9'] on engi-
neering materials found that six of them mentioned
the concept of surface energy, but only in the context
of nucleation[1-5 and fracture propagation.[5'61 Only
one of these texts introduced the concept of contact
angle and presented Young's equation in a discus-
sion of heterogeneous nucleation,m and none dis-
cussed wetting or spreading of liquids on other liq-
uids or solids. Unfortunately, the only text on engi-
neering materials that discussed contact angle,
spreading, and wetting is no longer in print."10
This paper will present some simple but powerful
thermodynamic concepts that can be taught in a 1-
hour lecture on wetting and spreading. We approach
the subject through the theme of the minimization of
free energy-a concept with which chemical engi-
neering students are well acquainted.

TO SPREAD OR NOT TO SPREAD
The two practical questions about spreading and
wetting which an engineer usually addresses are:
* Does the liquid spread completely or only partially on
the solid surface?
If partial spreading occurs, what is the contact angle
of the drop on the surface?
To address these questions we begin with the defi-


William G. Pitt is an associate professor in the
Chemical Engineering Department at Brigham
Young University. He is active in AIChE as the
student chapter advisor at Brigham Young Uni-
versity and as chair of the National Student Pa-
per Competition. He obtained his BS from Brigham
Young University and his PhD from the Univer-
sity of Wisconsin, Madison. His research activi-
ties deal with adhesion phenomena on biomedi-
cal polymers and in polymer composites.


nition of the surface energy, y, which is defined as
the change in free energy as new surface area is
created. If new surface is created under reversible
conditions at constant pressure, temperature, and
number of molecules, this surface energy is the
change in Gibbs free energytl"

7= (S)} (1)

where G is Gibbs free energy and A is the surface
area. If the surface is created at constant volume,
temperature, and number of molecules, this surface
energy is the change in Helmholtz free energy

(2)
Because pressure is generally a more constant pa-
rameter than volume, Eq. (1) is sometimes (but not
always) preferred. In this paper, the term free energy
can refer to either of these definitions, depending on
whether the wetting and spreading occurs under
constant pressure or volume. Thus, the free energy
associated with the surfaces of a system is simply
the surface area of each phase boundary multiplied
by y for that boundary. Subscripts of y refer to the
surface free energy of the interface between the liq-
uid, solid, and yapor phases.
Next let us perform a thought experiment sug-
gested by Figure 1 in which we force a small drop to
spread over a large surface. Before a drop of liquid
contacts the surface, the surface free energy of the
system is the solid-vapor surface free energy, Ys,,
multiplied by the solid area (assuming the original


C Copyright ChE Division of ASEE 1993


Chemical Engineering Education









area of the drop is much smaller than the solid
area). When the liquid is spread completely on the
solid, the system now consists of two interfaces (the
solid-liquid and the liquid-vapor interfaces), and the
surface energy of the system is y,i + 7y, multiplied by
the solid area. One may now ask the question, "Does
the system attain the lowest free energy when the
drop is spread completely on the solid?" If so, com-
plete spreading will occur. We can see that if the yv
is larger than the sum of y, + y,,, the reduction in free
energy will drive the drop to spread completely over
the surface. Thus, spreading occurs if
7sv > Ylv + Ysl or 0 < Ysv (Yiv + Ysl) (3)
Complete spreading will also occur if
Ysv = Yiv + Ysl
because the drop will flatten out until it has a con-
tact angle of zero (as will be shown in the next
section).
In the early 1920s, Harkins and Feldman[12' stud-
ied the spreading of organic liquids on a number of
solid and liquid substrates. They defined a "spread-
ing coefficient," S, as the difference between the
work of adhesion, Wa, and the work of cohesion We.
The work of adhesion is the work per interfacial area
needed to separate two adjacent (solid and liquid)
phases:
Wa = Ylv + Ysv Ysl
The work of cohesion is the work per area needed to
separate a single liquid phase:
Wc = 2 yv
Therefore, the spreading coefficient becomes
S = Wa Wc (4)
S= Ysv -(Yiv +Ysi) (5)
Harkins and Feldman observed that liquids spread
completely when S > 0, which is consistent with Eqs.
(3) and (5).
One final note on spreading concerns the rate or
kinetics of spreading. The velocity of the moving
three-phase contact line at the edge of the drop can
be as high as 30 cm/s and is dependent upon the

Before After

(Liq uiL ys Yd) YI I
,. v \ Liq,,d /L_.qu



Figure 1. Process of complete spreading of a liquid drop
on a solid substrate.
Fall 1993


This paper presents some
simple but powerful thermodynamic
concepts that can be taught in a 1-hour lecture on
wetting and spreading. We approach the
subject through the theme of the
minimization of free energy...

viscosity and surface energy of the spreading liq-
uid."' Brochard and deGennes show that the change
in the drop radius, R, with time (the velocity) is
proportional to R9.'31 Thus the latter stages of spread-
ing can be a slow process.
If the spreading occurs on a liquid instead of a
solid, the velocity varies inversely with the substrate
viscosity.[141 The viscosity of the surrounding fluid
also plays a role, especially if the fluid is a liquid
(instead of a gas). The spreading velocity increases
as the viscosity of the displaced liquid decreases.
More importantly, a stable liquid film separating
the drop from the substrate prevents the initial for-
mation of the three-phase contact line, and in most
practical cases, the stability of this liquid film con-
trols spreading. Thus, spreading entails multifari-
ous phenomena, and its complexity should not be
underestimated by the simplicity of the thermody-
namic statement of Eq. (3).

PARTIAL SPREADING
We will now examine the case in which the solid
surface energy is less than y, + y%, or in which S is
negative and the spreading is not complete. In this
case the drop forms a sphere or spherical cap on the
solid as long as the drop is small enough that gravi-
tational distortion of the shape is negligible. The
contact angle is defined as the angle between the
solid-liquid interface and the liquid-gas interface at
the edge of the drop. In 1805, Thomas Young stated
(without proof) that the equilibrium among the at-
tractive forces between particles of fluid and par-
ticles of solid will cause the fluid to form a certain
angle with the solid.116 This angle was defined by
Fs =Fs +FIcosO (6)
where the F,, F,,, and F, refer to the forces of the
solid, the common surface, and the liquid, respec-
tively. This was the genesis of Young's equation, a
mechanical balance of rather ill-defined forces. In
introductory texts, Young's equation is often taught
as a force balance at the edge of the drop. While this
model of a force balance is convenient and easy to
teach, many students find it unsettling. They see
little logic in a force balance in the horizontal direc-
tion, but not in the vertical direction. They may also
185









have trouble conceiving surface energy as a
force per linear distance because most chem-
istry courses introduce y as an energy per
surface area.
Of course, both of these apparent incon-
sistencies can be adequately addressed.17'181
There is a force balance in the vertical di-
rection: just as students learn in their intro-
ductory physics course, when you push
against an immovable wall, the wall exerts
an equal force in the opposite direction, so
the solid substrate exerts an equal force in
the downward direction at the three-phase
boundary. Interesting experimental evidence
of this vertical force is shown by drops of
liquids on elastic hydrogels-the drops ac-
tually pull the hydrogel upward at the pe-
riphery of the drop.1 19
Unlike Young, Willard Gibbs related the
contact angle to the more familiar concept
of surface energy. He proposed that the
three-phase boundary line (between an in-
soluble solid and two fluids) would displace
along the solid surface until it reached a
point at which any further displacement of
the line would create an increase in the free
energy associated with the three-phase
boundary line.'20' This condition of equilib-
rium reduces to
Yiv cos 0 = Ysv Ysi (7)
which has the same form as Young's equa-
tion, but which employs surface energies
instead of surface forces. While the student
may feel more familiar with the language of
surface energy, Gibb's derivation is usually
not intuitively obvious. It also has the draw-
back (as does Young's derivation) that the
derivation is done in two-dimensional space.
Most classical textbooks on colloidal and sur-
face chemistry derive Young's equation us-
ing free energy concepts and a differential
change in contact area. 1151

A CONCEPTUALLY
STRAIGHTFORWARD APPROACH
A straightforward approach to teaching
the concept of contact angle and incomplete
wetting is to combine the familiar rule that
"a system moves to its state of lowest free
energy" with a simple model of a liquid drop
contacting a solid surface. Referring to the
discussion of the spreading coefficient, we
see that if


Ysv < Yiv + Ysi
then the free energy of the system is not minimized at a state of
complete spreading, and so the drop will not spread completely.
The question now becomes, "How far must the drop spread to
minimize the free energy of the system?" The answer is given
by formulating the equation that describes the change in free
energy: we simply subtract the energy "before" from the energy
"after" the drop wets the surface. The surface energy before the
drop contacts the surface is

Total surface energy before = STYsv + 4 n rd Y1v (8)
where ST is the total area of the solid surface and rd is the
radius of the drop. After the drop has contacted the surface, it
spreads to form a spherical cap with a contact angle 0 as shown
in Figure 2. The total surface energy after the wetting of the
drop is
Total surface energy after = (ST AI)Ysv + AcYiv + AIys (9)
where AI is the area of the interface between liquid and solid,
and A, is the liquid-vapor interfacial area of the spherical cap of
liquid. AI and A, are given by


AI = r(21- Cos2 )


Ac = 2r2(1- cos0)


where r, is the radius of curvature of the spherical cap. The
change in free energy of the system is found by subtracting Eq.
(8) and Eq. (9)

AG = 2 y (r2 (1-cos )-2 r2)+ n r (1-cos2 )(sl- Ysv) (12)
The minimum in free energy is found by equating to zero the
derivative of Eq. (12) with respect to cos 0, and then solving for
cos 0


dAcQ0 O .[(1 -ySV)+(1-c2)(yS y 2)}
dAG =0= 2[l (-. ) dr 22rf(Ysi )Ysv).
d(cos0) do :12c
(13)
where o is a shorthand notation for cos 0. The spherical cap has
constant volume


Figure 2. Process of partial spreading of a liquid drop
to form a spherical cap with radius r, and contact
angle 0 on the solid.
Chemical Engineering Education










v=r3 +3

so we can use implicit differentiation under condi-
tions of constant volume to derive that

dr2 _2r2 (1-)2
da 2 30 + 0
Combining Eqs. (13) and (14) and solving for a gives

S=cos = (sv -s (15)
Ylv
which is identical to Eq. (7).

DISCUSSION
This derivation contains several important points
that the students should understand about wetting
and contact angles. On the practical side, nearly all
liquids partially or completely spread on solid sur-
faces. It is very rare to have a contact angle of 1800
(no wetting). Equation (15) indicates that an angle
of 1800 would require ys, = yv + yv. This is rarely the
case for aqueous solutions or organic liquids because
the interfacial free energy usually has a value that
is less than yv. In the case of liquid metals (such as
mercury) on organic solids, y, and y., are both so high
that y, becomes negligible and a contact angle of
180 is approached. This does not mean that "water-
proofing" a porous surface is impossible. If the con-
tact angle is greater than 90, capillary pressure will
resist the penetration of a liquid into a porous solid.
Another point on the practical side is that this
derivation employed an ideal system that assumed
the absence of gravity, surface roughness, surface
contamination, surface chemical heterogeneity, sur-
face mobility, liquid viscosity, line tension, or other
real effects that often cause contact angles to depart

Ideal
Tntermediate


Figure 3. Real and hypothetical ideal paths of an arbi-
trarily shaped liquid forming a spherical cap on a solid.
Fall 1993


from the contact angle predicted by Eq. (15).[211 These
real complications and departures from the ideal
case can often aid in understanding the nature of
complex surfaces, but they are not the focus of this
discussion. (More information on these topics can be
found in references 17 and 21.) In some very clean
and specialized experiments, all of these complica-
tions can be eliminated with the exception of gravity
and line tension.
If one cannot eliminate gravity and line tension
effects in real measurements, one should at least
understand what perturbations they may impose
upon the theoretical contact angle. Gravity always
distorts the drop shape from a spherical cap to an
oblate spheroidal cap, but this distortion is negli-
gible for sufficiently small drops. For example, with
water on polyethylene, gravity distortion becomes
noticeable if the drop volume is greater than about
2pl. This distortion causes the surface area of the
cap (A,) and the interface area (AI) to increase over
that of the ideal case.
Line tension is the one-dimensional analog to sur-
face tension and can be defined as the excess free
energy per distance at the three-phase boundary
line between the liquid, solid, and vapor at the pe-
rimeter of the cap. Assuming that the free energy
contribution from line tension is positive, a drop will
not spread as far (compared to the case without line
tension) before it reaches the minimum in free en-
ergy, and thus it will have a larger contact angle
than predicted by Eq. (15). Both gravity and line
tension contribute to the free energy of the system,
and the net result upon equilibrium contact angle is
still a subject of controversy.[221
In the ideal case neglecting gravity and line ten-
sion, the contact angle is independent of the initial
spherical drop size. The following argument also
shows that contact angle is independent of initial
drop shape; i.e., a volume of liquid or arbitrary ini-
tial shape will form a spherical cap having Young's
contact angle. Given that the resultant drop shape
and contact angle is only a function of the free en-
ergy state, we can break the pathway of going from
initial to final energy state into two hypothetical
paths, neither of which may have actually occurred,
but which represent the change in free energy states
of the system (see Figure 3). The first path mini-
mizes the free energy of the liquid shape by forming
a sphere not yet in contact with the surface. The
second step minimizes the free energy after the liq-
uid sphere contacts the surface and results in a
Young's contact angle according to the derivation
presented above. Since both steps are minimizations
Continued on Page 193.













MICROPROCESSOR-BASED

CONTROLLERS

at Drexel University


D. R. COUGHANOWR
Drexel University
Philadelphia, PA 19104


In the United States, all chemical engineering
curricula accredited by ABET (Accreditation
Board for Engineering and Technology) must
have a course in process dynamics and control. Very
few students, however, have any exposure to mod-
ern industrial microprocessor-based control systems.
During the past six years, the Department of Chemi-
cal Engineering at Drexel University has offered an
elective course in advanced control which provides
such exposure to these modern control systems. In
the first phase of the development, we used Taylor
MOD-30 controllers, but more recently, we have used
Foxboro I/A (integrated automation) systems.
Many reasons are given for not providing students
with hands-on experience on modern control sys-
tems: some faculty members who teach control be-
lieve that students need only a fundamental theo-
retical course and that a laboratory involving mod-
ern control equipment is unnecessary; other reasons
include the high cost of the equipment and the com-
plexity of the software. Furthermore, the vendors of
control hardware and software have shown very little
interest in trying to introduce their equipment into
the laboratories of engineering schools. The author
of this paper, however, believes that exposing stu-
dents to modern industrial control equipment can be
a valuable experience for them, that it motivates the
application of control theory, and that the acquisi-

Donald R. Coughanowr has been at Drexel
University since 1967. Before coming to Drexel,
he taught at Purdue University for eleven years.
He received his BS degree from Rose-Hulman,
his MS from the University of Pennsylvania,
and his PhD from the University of Illinois, all in
chemical engineering. His areas of research
include process dynamics and control, aerosol
technology and environmental engineering, dif-
fusion with chemical reaction, and mathemati-
cal modeling.
Copyright ChE Division of ASEE 1993


The emphasis in the course
was on the use of the control hardware
and software, while the use of mathematics was
limited to stability calculations and tuning.

tion and use of such control equipment is financially
feasible.
Our department offers a series of three courses in
process control. They combine theory, applications,
and laboratory experience, and make extensive use
of digital computers to simulate and control chemi-
cal processes. The courses and the number of hours
per week during a ten-week term are:
4.5 cr. Process Systems Engineering; 3 hr. lecture, 3 hr. laboratory
3 cr. Process Systems Engineering; 3 hr. lecture (graduate course)
3 cr. Applications of Computers to Control; 2 hr. lecture, 2 hr. labo-
ratory
The first course, Process Systems Engineering, is
required of all undergraduate students in chemical
engineering and covers open-loop systems, closed-
loop systems, stability, frequency response, and con-
troller tuning. In the laboratory, the students simu-
late control processes with simulation software
(TUTSIM) and operate a modern industrial micro-
processor-based control system (Foxboro I/A system).
It is also a prerequisite for the third course, Applica-
tions of Computers to Control.
In the second course (a graduate course), advanced
topics such as stability, root locus, sampled-data
control, multi-loop control (cascade, feed-forward,
internal model control, etc.), and nonlinear control
are covered.
The third course, Applications of Computers to
Control, is an elective course which is primarily de-
voted to the study of a modern industrial micropro-
cessor-based control system, and covers configura-
tion, tuning, and operation of a Foxboro I/A system.
Control applications include single-loop and multi-
loop control systems.
Chemical Engineering Education









A TYPICAL
MICROPROCESSOR-BASED CONTROL SYSTEM
This paper will describe the use of the Foxboro I/A
system in the graduate course Applications of Com-
puters to Control. The equipment for the course was
obtained with the help of an NSF grant from the
program on Instrumentation and Laboratory Im-
provement. This grant, a 50-50 matching grant, pro-
vided three Foxboro systems. The 50% funding to
match the NSF share came from industry, Drexel
University, and a grant in the form of a discount
from the Foxboro Company (the NSF program per-
mits a discount from the equipment supplier to be
part of the matching funds).
Each of the three control systems costs about
$22,000 and consists of the following components:
HP Vectra ES/12 Computer with 70 Mb hard disk, color monitor,
mouse, and keyboard
OK Data 80-column printer
Local enclosure including power supply and two fieldbus modules
(FBM) for communication with real processes: One FBM transmits
0-10 volt signals; the other 4-20 ma signals
Allen Datagraph strip chart recorder
The equipment described above can be used to
control a process which is either a simulated process
in the computer or which is a real process connected
through hard wiring to the fieldbus modules.
The Foxboro I/A system, which was first released
in 1986, is a powerful distributed parameter control
system which is able to control many loops of a
complex industrial process. For the purpose of in-
struction in a university setting, the simplest ver-
sion of the system, referred to as Personal Worksta-
tion for Fieldbus Interface (PW-FB), was purchased.
The version used for a large plant would include
several computers, a larger enclosure with more
fieldbus modules, and more input/output devices
(such as printers, monitors, operator input panels,
etc.). The software provided in the simpler PW-FB
system, however, is exactly the same as that used in
the most extensive systems. Figure 1 shows the con-
nections between the computer and the process for
the PW-FB system. Foxboro provides different types
of FBMs for analog signals and for digital signals.
Each FBM can handle several inputs and outputs.
Up to sixteen FBMs can be connected to the com-
puter for the PW-FB system.
Each control system comes with a five-volume set
of user's manuals. As with most manuals provided
with complex equipment, their availability does not
guarantee that one can simply hook up the compo-
nents and begin using the equipment. Even though
the software packages are loaded into the computer's
hard disk at the factory and a field engineer from
Fall 1993


Figure 1. PW-FB connections to process


the company sets up the equipment, it is recom-
mended that the purchaser attend one or two courses
on using the equipment that are offered by the manu-
facturer. The Foxboro Company (among many other
suppliers of control equipment), offers a wide variety
of short courses that last from just a few days to
several weeks. The author took two two-week courses
on the Foxboro I/A system. The Foxboro Company
also sells a training kit for the PW-FB system that
consists of a manual, computer disks, and audio-
visual tapes. This kit is very useful for self-study of
the Foxboro I/A system.
The primary task of a microprocessor-based con-
troller is implementation of a control algorithm; but
the presence of a computer makes it possible to also
assign a number of peripheral tasks that are useful
in process control. Some of these tasks provided in a
modern control system are to
Implement classical and advanced control algorithms
Provide static and dynamic displays on the monitor
Provide process and diagnostic alarms
Provide mathematical functions
Provide data acquisition and storage (archiving)
More detail on the nature of these tasks can be
found in Chapter 35 of Coughanowr.111 The soft-
ware to support all of these tasks is supplied by the
manufacturer of the control equipment. In the
Foxboro I/A system, these tasks are supported by
the following seven software elements:
Control subsystem
Process display
File utility
Workstation environment
System management
Historian (optional)
Spreadsheet (optional)









Only the first five elements are essential for using
the system. The spreadsheet and historian elements
were omitted at some savings in cost (they are con-
sidered luxuries in a university teaching laboratory).
In an undergraduate laboratory course, the students
need to use only the control subsystem and process
display software. The teacher or laboratory techni-
cian will use the system management, file utility,
and workstation environment software to set up the
computer control system for laboratory experiments.
Specific examples of the use of these three software
elements for course development will be given later.

FEATURES OF THE FOXBORO I/A SYSTEM
All of the software for the Foxboro PW-FB system
is stored on a 70-Mb hard disk. The control strategy
for a control loop is configured by connecting several
blocks together to form a structure called a com-
pound. The connections are made by computer
commands entered through the keyboard and
mouse. There are about forty blocks available. A
partial listing of the blocks (along with their names)
is as follows:
analog input (AIN)
analog output (AOUT)
conventional control (PID)
control with self-tuning (PIDE)
lead lag (LLAG)
dead time (DTIME)
switch (SWCH)
There are also blocks which process digital (or logic)
signals (on/off) such as comparators, selectors, and
timers which are needed for automatic plant start-
up and shut-down and for batch operations.
Figure 2 shows that the block diagram for a com-
pound for conventional single-loop control requires
three blocks: AIN, PID, and AOUT. The AIN
and AOUT blocks are used for converting and
conditioning signals to and from the process for
use in the computer. The PID block performs the
control function. A compound for a cascade control
system requires five blocks: two AIN, one AOUT,
and two PID blocks.
One of the most important and complex blocks is
the PID block, which has 81 parameters. Initially,
one may be bewildered by the number of parameters
to be set, but most of them can be left at their default
values for a number of experiments. Many of these
parameters are concerned with measurement alarms
and limits on control variables.
One parameter that is common to most of the
blocks is the sampling period, which can be varied


FBM FBM

AIN PID -AOUT


PROCESS


Figure 2. Compound for single-loop control

from 0.1 sec to 1 hr. For the PW-FB system, the
lowest sampling period is 0.5 sec. Most of the experi-
ments for the elective control course use a sampling
period of 0.5 sec.

CONTENT OF THE ELECTIVE CONTROL COURSE
In the prerequisite undergraduate control course,
the experiment using the Foxboro system is at the
end of the course, after the student has studied
tuning of closed-loop systems. It consists of using a
pre-configured control law (PID) to tune a third-
order system which is simulated on an analog com-
puter. This limited experience stimulated enough
interest that many students subsequently consid-
ered taking the elective control course, which covers
the use of the Foxboro system in greater detail.
Because the elective course is limited to four hours
per week for ten weeks, only continuous control
blocks are used in the experiments. An outline of the
course is shown in Table 1. In addition to the topics
listed in the table, lectures are given on sampled-
data control, implementation of practical control al-
gorithms, multi-loop control strategies (cascade,
feedforward, etc.), and process identification and tun-
ing. Some knowledge of sampled-data control is
needed in order to understand the difference be-
tween continuous control (pneumatic and electronic)
and microprocessor-based (digital) control and the
destabilizing effect of sampling on the stability of
the closed-loop system.
In the lecture on the implementation of practical
control algorithms, we discuss the use of external
feedback to show how the integral action is obtained,
which avoids reset windup. We also discuss a practi-
cal method used for obtaining a derivative action in
which the measurement signal (not the error signal)
is sent through a filter such as a lead-lag filter. The
Foxboro software uses a Butterworth filter to obtain
derivative action.
For years, one of the goals of control engineers has
been to develop a device for automatically tuning a
process on-line. Many suppliers of control hardware


Chemical Engineering Education









now provide self-tuners; Foxboro's version is called
EXACT, which stands for EXpert Automatic Con-
trol Tuning. The self-tuning algorithm, being
proprietary information, is described only in general
terms in the user's manual accompanying the con-
trol equipment. The lecture on system ident-
ification and tuning gives the students some idea of
how the tuning algorithm may work, especially
the pre-tune phase which analyzes an open-loop
response. In this case, the Cohen-Coon tuning method
is conceivably the approach used to obtain prelimi-
nary tuning parameters.
With the availability of modern computer control
systems and their great variety of blocks (such as
those mentioned above), the control engineer has for
the first time the possibility of configuring complex
control strategies which are limited only by his/her
imagination and knowledge of the process. It is now
feasible to implement advanced control strategies,
such as Smith predictor control and internal model
control, by blocks which simulate first-order, lead-
lag, and transport lag transfer functions.
The configurators for creating displays are a very
important part of the Foxboro software. The dis-
plays make it possible for the operator to observe the
process variables and to control the process. In the
elective control course, the students use the group
display configurator since it is easy to use; they are
not required to use the software (Display Builder
and Display Configurator) which is needed to create
elaborate dynamic displays showing flow diagrams

TABLE 1
Applications of Computers to Control
2 hr. lecture, 2 hr. lab: 3 creditsfor 10 weeks

This course, which is primarily devoted to the study of a
modern industrial microprocessor-based control system,
covers configuration, tuning, and operation of a Foxboro
(PW-FB) I/A system. Control applications include single-loop
and multi-loop control systems.

1. Overview of microprocessor-based control system hardware and
software
2. Tasks performed by a distributed control system: control algo-
rithms, displays, alarms, mathematical functions, data storage,
reports
3. Operation and control of a single-loop process using a Foxboro I/A
control system; observe effect of sampling on stability
4. Configuration of control systems using various blocks
5. File utilities: storage and transfer of control data bases
6. Configuration of displays: detail, group, process
7. Alarms: system alarms, process alarms
8. Use of Foxboro I/A control system for Advanced Control
Strategies: cascade, feedforward, internal model, self-tuning, etc.
9. System management: monitoring the state of control equipment

Fall 1993


of a process and which connect display objects (tank
level, number fields, etc.) dynamically to block pa-
rameters and system variables. These process dis-
play configurators require too much time and effort
and provide little educational benefit. Those experi-
ments which use such process displays were config-
ured in advance by the instructor.
The experiments performed in the course are listed
in Table 2 on the following page (with a brief de-
scription and the objective of each experiment).
The emphasis in the course was on the use of the
control hardware and software, while the use of
mathematics was limited to stability calculations
and tuning. Some students were pleasantly sur-
prised to find a course in control that was not
overburdened by mathematics, as is usually the case
in the first course in control.
The experiments involved the control of processes
simulated in the digital computer and processes simu-
lated by an analog computer. The analog computer
simulated process is considered a "real" process since
0-10 volt signals are transmitted to and from the
analog computer through wires connected to the
fieldbus module. A more realistic situation would be
to control processes such as liquid-level, heat ex-
change, or pH, although such processes would re-
quire a substantial investment in measuring ele-
ments, control valves, and process equipment.
At the Foxboro training center, one of the laborato-
ries uses with each microprocessor a process cart
which holds a second-order liquid level system. If
funds were available, such a process would provide
the student with a more realistic view of the hard-
ware components of a process control system. As a
compromise, one such "real" process should be added
to the laboratory. For those interested in using an
analog computer for simulation of the process,
Comdyna, Inc., of Great Barrington, Illinois, sells an
8-amplifier, 10-volt computer for about $2,000.

SUGGESTIONS FOR PLANNING
A COMPUTER CONTROL LABORATORY
After acquiring the control equipment and the
knowledge to use it, time must be found to develop
interesting experiments that provide a balance be-
tween practice and theory. An excellent way to pre-
pare laboratory experiments is to direct one or two
students in a special projects course to develop and
test several experiments. Laboratory outlines and
some course notes on using the software must be
written; the user's manuals are too detailed for use
as course notes, although they can be used as a
reference and should be available in the laboratory
191











TABLE 2
Applications of Computer to Control
Experimentsfor Foxboro I/A System


Experiment 1
* Control of tank level in a "get acquainted" experiment
In this experiment, the student uses a compound and displays which
are already configured. The objective is to learn how to use the
keyboard and a mouse to enter commands and parameters and to see
the types of displays which can be provided by the software. The
process being controlled is simulated in the digital computer using
Foxboro blocks.
Experiment 2
* PI control of a third-order process simulated on an analog computer
In this experiment, a third-order system [1/(rs+lY] simulated on the
analog computer is controlled by a PID controller. The student tunes
the controller by using Ziegler-Nichols rules. The time constant of the
process, r, is set to 4 seconds, with the result that the system responds
quickly.
Experiment 3
* Configuration of a compound for PID control of a third-order process
and configuration of a group display
The objective of this experiment is to learn how to use the control
configurator software to devise a PID controller that controls a third-
order process simulated on the analog computer. The same process of
Experiment 2 is controlled.
Experiment 4
* Changes in configuration of compound of Experiment 3 (set point
tracking, alarm parameters, etc.)
In this experiment the PID controller compound of Experiment 3 is


for students to use. No more than two students should
be assigned to a computer workstation. The use of
the software can be learn-by-practice (trial-and-er-
ror) at the keyboard. If more than two people are
assigned to a workstation, only the most assertive
member of the group will learn much.
In addition to the usual tasks involved in running
a laboratory, the instructor should reserve time for
maintaining equipment and computer files. After a
course is completed, the old files for compounds and
displays must be deleted so that they do not get used
by students when the course is offered again. It is
also necessary to restore pre-configured compounds
to their original form as required in some of the
experiments, and master copies of files for compounds
and displays must be saved. The file utility software
is used to maintain files.
The workstation environment software is needed
to develop new environments and to password-pro-
tect existing and new environments. An environ-
ment is a selection of "buttons" along the top menu
bar of the monitor which is used by the operator to
gain access to configurators, displays, compounds,
and other software items. The Foxboro I/A system
comes with some standard environments, such as


modified to include process alarms, limits on process variables, and set-
point tracking. The control system is operated to see that the system
actually responds to the changes in configuration.
Experiment 5
* Control of a simulated process
To see that the process can be simulated by controller blocks in the
computer, the student controls a process consisting of a first-order
transfer function and a dead time.
Experiment 6
* Cascade control
This experiment shows how the control blocks can be configured for
cascade control. The process controlled is a third-order system simu-
lated on the analog computer. The student shows the benefit of cascade
control by comparing the responses of cascade control and single-loop
control of the same process.
Experiment 7
* PID control with PIDE block (self-tuning)
In this experiment, a PID block with self-tuning is used to control a third-
order [1/(Ts+l)3] process simulated in the computer. After obtaining
preliminary controller settings with the pre-tune phase of the tuning
algorithm, the process is placed on automatic and the closed-loop system
is tuned on-line by introducing a sequence of step changes in set point.
After about five changes in set point, the tuning parameters (PB, ,z T,)
settle at values which are not too far from the tuning parameters calcu-
lated by Ziegler-Nichols rules. Watching the on-line self-tuning algo-
rithm update the tuning parameters with each disturbance is fascinating.


"process operator's environment," "process control
engineer's environment," etc. All of the environments
can be prevented from being used by requiring a
password to open an environment and all the fea-
tures associated with that particular environment.
In a course which has many inexperienced users, it
may be advisable to password-protect all environ-
ments except those needed to perform the experi-
ments. In this way, the corruption of files and sys-
tem breakdowns will be reduced.
The use of commercially available microprocessor-
based control systems in undergraduate courses at
Drexel has been favorably received by the students.
The first time the elective course was offered, more
students registered for the course than could be ac-
cepted. Since there are only three Foxboro systems,
enrollment was limited to six people per course sec-
tion. If more time is available, more experiments
could be introduced which involve complex multi-
loop strategies and batch operation. Short courses
using microprocessor-based controllers should be of
interest to engineers in industry.

REFERENCES
1. Coughanowr, D.R., Process Systems Analysis and Control,
2nd ed., McGraw-Hill (1991) 0
Chemical Engineering Education










FREE ENERGY OF WETTING
Continued from page 187.
in free energy, the total path represents a minimum
in free energy, and Young's angle is the result.
In summary, when a liquid contacts a solid, either
partial or complete wetting occurs. The extent of
wetting is determined by a simple thermodynamic
rule familiar to all students: the system will move to
the state of lowest free energy. Although the rules
are simple, the implications of the rules are pro-
found and can have important consequences in many
areas of applied chemistry.
ACKNOWLEDGMENTS
The author would like to thank the Exxon Educa-
tion Foundation for a grant supporting education
and research associated with this study.
REFERENCES
1. Smith, William F., Principles of Materials Science and En-
gineering, 2nd ed., McGraw-Hill, Inc., New York, NY (1990)
2. Shackelford, James F., Introduction to Materials Science for
Engineers, 3rd ed., Macmillan Publishing, New York, NY
(1992)
3. Askeland, Donald R., The Science and Engineering of Mate-
rials, 2nd ed., PWS-KENT Publishing, Boston, MA (1989)
4. VanVlack, Lawrence H., Elements of Materials Science and
Engineering, 6th ed., Addison-Wesley Publishing, New York,
NY (1989)
5. Flinn, Richard A., and Paul K Trojan, Engineering Materi-
als and Their Applications, 3rd ed., Houghton Mifflin Co.,
Boston, MA (1990)
6. Callister, William D., Materials Science and Engineering,
2nd ed., John Wiley and Sons, New York, NY (1991)
7. Budinski, Kenneth G., Engineering Materials, 4th ed.,
Prentice Hall, New Jersey (1992)
8. Newey, Charles, and Graham Weaver, Materials Principles
and Practice, The Open University, England (1990)
9. Keyser, Carl A., Materials Science in Engineering, 4th ed.,
Charles Merrill Publishing Company, Ohio (1986)
10. Jastrzebski, Zbigniew D., The Nature and Properties of En-
gineering Materials, 3rd ed., John Wiley & Sons, New York,
NY (1987)
11. Adamson, A.W., Physical Chemistry of Surfaces, 4th ed.,
John Wiley & Sons, New York, NY (1982)
12. Harkins, W.D., and A. Feldman, J. Amer. Chem. Soc., 44,
2665(1922)
13. Brochard, F., and P.G. deGennes, J. Physique Lett., 45, L-
597 (1984)
14. Ahmad, J., and R.S. Hansen, J. Colloid Interface Sci., 601
(1972)
15. Ross, S., and I.D. Morrison, Colloidal Systems and Inter-
faces, John Wiley and Sons, New York, NY; p. 87 (1988)
16. Young, T., Miscellaneous Works, G. Peacock, Ed., Murray,
London, England; Vol. 1, 432 (1855)
17. Andrade, J.D., L.M. Smith, and D.E. Gregonis, Surface and
Interfacial Aspects of Biomedical Polymers, J.D. Andrade,
Ed., Plenum Publishing Co., New York, NY; Vol. 1, 260
(1985)
18. Pirie, B.J.S., and D.W. Gregory, J. Chem. Educ., 50, 682
(1973)
19. Andrade, J.D., R.N. King, D.E. Gregonis, and D.L. Coleman,
Fall 1993


J. Polym. Sci. Symp., 66, 313 (1979)
20. Gibbs, J.W., The Scientific Papers of J. Willard Gibbs, Do-
ver, New York, NY; Vol. 1, 326 (1961)
21. Morra, M., E. Occhiello, and F. Garbassi, Adv. Colloid Inter-
face Sci., 32, 79 (1990)
22. Gaydos, J., and A.W. Neumann, J. Colloid Interface Sci.,
120, 76 (1987) a


REVIEW: HAZOP and HAZAN
Continued from page 167.
tive risk assessment" (QRA) or "probabilistic risk
assessment" (PRA). This chapter includes very
introductory material on calculating human risks
and equipment reliability. There is an interesting
section on calculating the cost of saving a life,
demonstrating a huge range of cost values for
various activities.
Chapter 4 is a manager's guide to hazard analysis
and discusses the problems associated with hazard
analysis in a managerial environment.
Chapter 5 discusses the most common objections
raised against HAZOP and HAZAN, and the
author provides a convincing case for applying
these techniques.
Chapter 6 is a very short chapter which dis-
cusses sources of data and confidence limits, and
Chapter 7 presents an interesting history of
HAZOP and HAZAN.
I am a considerable fan of the author, Trevor Kletz,
and buy all of his books as soon as they are pub-
lished. He uses a powerful technique of mixing case
histories with discussion to provide convincing cases
for his material. Furthermore, he has a unique way
of looking at things and often arrives at an "obvious"
result that no one else even thought of.
The content of this book is introductory in nature
and would be suitable for anyone with an interest in
learning about basic HAZOP and HAZAN methods.
It does not discuss techniques for decomposing large
process units into suitable subunits for HAZOP
analysis, a major problem for industrial practi-
tioners, nor does it include some of the more recent
organizational methods for managing a large HAZOP.
There are some simple calculations related to equip-
ment reliability, but nothing particularly difficult
for chemical engineering students.
This book, along with Trevor's other books, would
be a suitable reference or supplemental material
for a chemical engineering design course or a course
in chemical process safety. The students would be
most responsive to the case histories and examples
that are provided. 0










Random Thoughts...




WHAT MATTERS IN COLLEGE


RICHARD M. FIELDER
North Carolina State University
Raleigh, NC 27695-7905

Most faculty lounge discussions of educa-
tional matters are not exactly models of
rigorous logic. The "everyone knows" argu-
ment offered with no substantiation whatever is per-
haps the most common gambit ("Student evalua-
tions don't mean anything-everyone knows the high-
est student ratings always go to the easiest
graders"), and the straight line through one data
point is a close second ("Herman Frobish in Me-
chanical Engineering published eighteen papers last
year and also won an outstanding teaching award,
which proves that the best researchers are also the
best teachers").
If you occasionally get into discussions about edu-
cation and would like to buttress your arguments
with something a bit more substantial, I recommend
that you keep within easy reach a monumental work
by Alexander Astin titled What Matters in College.'1'
No single data point here! Astin collected longitudi-
nal data on 24,847 students at 309 different institu-
tions and determined the influences of a host of
institutional characteristics on the students' college
experience. The data include 146 input variables
that characterize the entering students, including
demographic measures, information about parental
education and socioeconomic status, precollege aca-
demic performance measures, and self-predictions of
a number of outcome variables; 192 environmental
variables relating to institutional and faculty char-
acteristics, including measures of the size and type
of the institution, faculty demographics and atti-
tudes, institutional emphasis on research, and the
nature and extent of student-faculty and student
peer group interactions; and 82 outcome variables,
including measures of academic achievement, reten-


Richard M. Felder is Hoechst Celanese Pro-
fessor of Chemical Engineering at North Caro-
lina State University. He received his BChE
from City College of CUNY and his PhD from
Princeton. He has presented courses on
chemical engineering principles, reactor de-
sign, process optimization, and effective teach-
ing to various American and foreign industries
and institutions. He is co-author of the text
Elementary Principles of Chemical Processes
(Wiley, 1986).

tion, career choice, self-concept, patterns of behav-
ior, self-reported growth in skills, and perceptions of
and satisfaction with the college experience.
Several results that I find particularly noteworthy
are listed below. All of the cited correlations are
positive (unless otherwise noted) and significant at a
levelp < .0001.
The quality of the college experience is strongly
affected by student-faculty interactions. The fre-
quency with which students talk with professors
outside class, work with them on research projects,
assist them in teaching, and visit their homes, corre-
lates with student grade-point average, degree at-
tainment, enrollment in graduate or professional
school, every self-reported area of intellectual and
personal growth, satisfaction with quality of in-
struction, and likelihood of choosing a career in
college teaching.1: 383-3841
A frequently debated issue is whether institutional
size affects educational quality. Astin's findings in-
dicate that smaller may indeed be better. Both
smaller enrollments and lower student/faculty ra-
tios correlate with satisfaction with instructional
quality, enrollment in graduate school, interest in
college teaching careers, and self-reported increases
in overall academic development, cultural aware-
ness, writing skills, critical thinking, analytic and
problem-solving skills, leadership skills, public speak-


Copyright ChE Division ofASEE 1993


Chemical Engineering Education









ing ability, and interpersonal skills.[: 326-329] The bet-
ter showing of smaller institutions is undoubtedly
due in part to the greater incidence of personal stu-
dent-faculty contacts at such institutions, suggest-
ing the desirability of trying to increase such con-
tacts at large universities.
Astin concludes, however, that as important as the
student-faculty relationship may be, "...the student's
peer group is the single most potent source of influ-
ence on growth and development during the under-
graduate years."[: 3981 Frequency of student-student
interactions (including discussing course content with
other students, working on group projects, tutoring
other students, and participating in intramural
sports) correlates with improvement in GPA, gradu-
ating with honors, analytical and problem-solving
skills, leadership ability, public speaking skills, in-
terpersonal skills, preparation for graduate and pro-
fessional school, and general knowledge, and corre-
lates negatively with feeling depressed."' 3851
Many of the study findings specifically point to the
benefits of cooperative learning-students working
in teams toward a common goal. Frequency of group
work has positive correlations with most areas of
satisfaction, all self-ratings, and all areas of self-
reported growth except foreign language skills. Tu-
toring other students-which may be done formally
but also occurs in a natural way when teams of
students work and study together-has positive cor-
relations with all academic outcomes and with choice
of careers in college teaching.1 3871 As Astin notes:
Classroom research has consistently shown
that cooperative learning approaches produce
outcomes that are superior to those obtained
through traditional competitive approaches,
and it may well be that our findings concern-
ing the power of the peer group offer a possible
explanation: cooperative learning may be more
potent... because it motivates students to
become more active and more involved partici-
pants in the learning process. This greater
involvement could come in at least two differ-
ent ways. First, students may be motivated to
expend more effort if they know that their work
is going to be scrutinized by peers; and second,
students may learn course material in greater
depth if they are involved in helping teach it to
fellow students.1: 4271
A number of results illustrate how emphasis on


Fall 1993


research at an institution affects the quality of that
institution's instructional program. Astin's conclu-
sion is that
Attending a college whose faculty is heavily
research-oriented increases student dissatisfac-
tion and impacts negatively on most measures
of cognitive and affective development. Attend-
ing a college that is strongly oriented toward
student development shows the opposite pattern
of effects.1:3631
A disturbing finding is that majoring in engineer-
ing correlates negatively with students' satisfaction
with the quality of their instruction and overall
college experience and positively with feeling
overwhelmed and depressed. "Clearly, these find-
ings indicate that the climate characterizing the
typical institution with a strong emphasis on engi-
neering is not ideal for student learning and per-
sonal development."1: 360-3611
In the concluding chapters of the book, Astin
proposes possible solutions to the educational qual-
ity problems raised by his study, suggesting that
the first step is having an institutional leader-
ship that understands the problems and is willing to
do something to deal with them. "As long as faculty
in the research universities are expected simulta-
neously to perform research, teaching, advising, uni-
versity service, and outside professional activities,
teaching and advising will continue to receive low
priority." He proposes negotiated contracts with
faculty members that would provide for a better
institutional balance among the different functions
of the professoriate.1: 4211 He also suggests that cur-
ricular planning efforts will pay off better if they
focus less on formal structure and content and put
more emphasis on pedagogy and other features of
the delivery system.1: 427]
This brief synopsis-which is intended only to whet
your appetite-should raise all sorts of questions in
your mind about the data and statistical methodol-
ogy that led to the stated conclusions, how possible
variable interactions and competing effects were ac-
counted for, and what else Astin discovered. I en-
courage you to get the book and find the answers.

REFERENCE
1. Astin. A.W., What Matters in College: Four Critical Years
Revisited, Jossey-Bass, San Francisco, CA (1993) 0


195










THE ASEE

CHEMICAL ENGINEERING DIVISION

LECTURESHIP AWARD

Thirty-One Years of
Recognizing Outstanding Achievement in
Fundamental Chemical Engineering Theory or Practice


GEORGE BURNET
Iowa State University
Ames, IA 50011
he first time I heard a divisional lectureship sug-
gested was during an informal discussion following
a meeting of the AIChE Education Projects Commit-
tee at the Institute's 1962 national meeting in Chicago. In
addition to this writer, Charlie Wilke and Max Peters were
present. The discussion dealt with what could be done to
strengthen the program of the Chemical Engineering Divi-
sion of ASEE and to make membership in the Division more
attractive to chemical engineering educators.
A number of suggestions were made, including joint ASEE/
AIChE sessions at AIChE meetings, promoting the journal
Chemical Engineering Education, emphasizing research ad-
ministration and funding in programs at ASEE annual con-
ferences, and increasing industrial participation.
It was Max Peters who first suggested an annual lecture-
ship with the purpose of recognizing and encouraging
outstanding achievement in an important field of fundamen-
tal chemical engineering theory or practice. A chemical
engineering educator would deliver the lecture as part of
the annual program of the Division. The idea was adopted
quickly, and the Executive Committee of the Division
proceeded to name Art Metzner as the first annual lecturer.
The winner received a framed certificate in recognition
of the lecture.
The annual lectureship proved to be popular and was well
received. Attendance at the 1964 lecture exceeded 150 people.
Publicity about the lectureship and each year's lecture was
submitted to Chemical Week, Chemical & Engineering News,
Chemical Engineering Progress, and Chemical Engineer-
ing, where news items and accompanying photographs of
the lecturer were often published.
At the 1965 Annual Conference, the Executive Committee
of the Division, under the chairmanship of John West, rec-
ommended that the annual lectureship become an award and
that an industrial sponsor for the award be sought. This
writer was asked to spearhead the effort, and a formal pro-


posal was developed calling for an honorarium of $1,000,
reimbursement of travel expenses, $300 for publication of
the full text of the lecture in Chemical Engineering Educa-
tion, and reimbursement to ASEE headquarters for the cost
of administering the award.
In addition, the proposal identified the following accom-
plishments that were to be considered by the annual lecture-
ship award committee in selecting the recipient.
1. Achievement, through formulation or creative application
offundamental theory and principles, or important
advances which have been accepted by colleagues and by
others in the field of specialization, with promise of
making further significant contributions.
2. Improvements oflasting influence to chemical engineer-
ing education through books, technical articles or
laboratory or other teaching equipment, and demonstra-
tion of success as a teacher as well as the ability to
inspire students to high levels of accomplishment.
3. Evidence of the ability to conduct original, sound, and
productive research, personally or as a director of a
research team, and to evaluate and report the significant
results obtained.
4. Interest in furthering technical progress in chemical
engineering through participation in professional and
educational societies.
The proposal further specified the duties and terms of
service of an annual lectureship award committee and the
information to be required in a nomination. Finally, it was
noted that the award recipient would be required to submit a
suitable manuscript based on the lecture to the journal Chemi-
cal Engineering Education.
Largely through the efforts of Wendel W. Burton, at that
time Director of Employment for the 3M Company, 3M
agreed to sponsor the award on a continuing basis. Mr.
Burton had been active in ASEE for many years, having
served most recently as its national treasurer.
In 1965, the Executive Committee of the Division en-
dorsed the overall plan, and the proposal went simultaneously
Copyright ChE Division ofASEE 1993
Chemical Engineering Education










to Glenn Murphy, ASEE Vice President for the Projects
Operating Unit, Harold E. Heath, Chair of the ASEE
Awards Policy Committee, and Leighton Collins, ASEE
Executive Secretary. By May, 1966, the Division had autho-
rization to proceed, and Octave Levenspiel was named the
first 3M Lecturer. A book-size brochure containing infor-
mation about the award, a list of previous lecturers, and
biographical information of the recipient was widely distrib-
uted at the Annual Conference and was used in other ways to
publicize the award.
The first lectureship award committee was appointed in
1966, and consisted of Robert Beckmann, Robert L. Pigford,
and this writer. Over the next few years Joseph A. Bergantz,
Andreas Acrivos, Myron Chetrick, and William Corcoran
also served on this committee.
In 1973, Wendel Burton asked the Division to suggest
ways the lectureship award could be enhanced to insure that
its stature be maintained, and the following year a lecture
tour by the awardee was implemented. Additional funds
were provided by 3M to cover travel and subsistence to
deliver the lecture at three universities during the academic
year following its presentation at the ASEE annual confer-
ence. An additional honorarium of $500 was paid the awardee
when the lecture tour was completed.

In 1989 the award was increased to $2,000, with a lecture
tour honorarium of $1,000, and every fifth year the lecture
has been presented at the ChE Division summer school. 3M
continued its sponsorship of the award up to and including
the 1991 annual conference.

During 1992 and 1993 the Division continued the award
without an industrial sponsor. Expenses and a reduced hono-
rarium were paid to the recipient, using funds from the
Division treasury.
Thanks to the efforts of John Friedly, Chair of the Division


for 1992-93, and Lewis Derzansky, University Relations
Representative from Union Carbide, we will have the
Union Carbide Lectureship Award beginning with the 1994
annual conference. The criteria, selection procedure, and
responsibilities of the lecturer remain unchanged, the lecture
will continue as a major event of the ASEE annual confer-
ence, and the full text of the lecture will be published in
CEE. A lecture tour by the awardee remains as an option
open to Union Carbide.
The lectureship award was the first and is still one of the
most highly regarded of the twenty-one divisional awards. It
is acknowledged as the premier award of the chemical engi-
neering education community in the United States. A sig-
nificant measure of the importance of the lectureship award
lies in the prestige of its recipients. This list is a veritable
"Who's Who" of chemical engineering education (see the
boxed listing of winners). Twenty of the thirty-one recipi-
ents have been elected to the National Academy of Engi-
neering, the highest professional recognition our country
confers upon an engineer.
Much of the credit for the long and distinguished history
of the award must go to the 3M Company for its encourage-
ment, active participation in Division affairs, and financial
support. The award has promoted quality and new advances
in ChE education that have benefited the entire profession.
As we look to the future, we must note with approbation
the commitment Union Carbide has made to a long-term
association with the Lectureship Award. The rapid and chal-
lenging changes in science and technology will place in-
creasing demands on chemical engineering education and
practice. The lectureship award will continue to play an
important role in meeting these demands. O
Editor's Note: The 1992 Award Lecture, given by William N.
Gill at the ASEE ChE Division Summer School in June of 1992,
appears on the following pages.


SChemical Engineering Division Lectureship Awardees


1963 Arthur B. Metzner; Non-Newtonian Fluids
1964 Charles R. Wilke; Mass Transfer in Turbulent Flow
1965 Leon Lapidus; Aspects of Moder Control Theory and Application
1966 Octave Levenspiel; Changing Attitudes to Reactor Design
1967 Andreas Acrivos; Matched Asymptotic Expansion
1968 L. E. Scriven; Flow and Transfer at Fluid Interfaces
1969 Cornelius J. Pings; Some Current Studies in Liquid State Physics
1970 Joe M. Smith; Photochemical Processing: Photo-Decomposition of
Pollutants in Water
1971 William R. Schowalter; The Art and Science ofRheology
1972 Dale F. Rudd; Synthesis and Analysis in Engineering
1973 Rutherford Aris; Diffusion and Reaction in Porous Catalysts
1974 Elmer L. Gaden, Jr.; Biotechnology: An Old Solution to a New
Problem
1975 John M. Prausnitz; Molecular Thermodynamics for Chemical
Process Design
1976 Abraham E. Dukler; The Role of Waves in Two-Phase Flow
1977 Robert C. Reid; Superheated Liquids: A Laboratory Curiosity and
an Industrial Curse
1978 Theodore Vermeulen; Dynamics of Runaway Systems


1979 Daniel D. Perlmutter; A New Look at an Old Fossil
1980 Klaus D. Timmerhaus; Fundamental Concepts and Application
of Cryogenic Heat Transfer
1981 Arthur Westerberg; Design Research: Both Theory and Strategy
1982 Lowell B. Koppel; Input Multiplicities in Process Control
1983 Warren E. Stewart; Simulation and Estimation by Orthogonal
Collocation
1984 TW Fraser Russell; Semiconductor Chemical Reaction
Engineering
1985 Dan Luss; Analysis and Modeling of Steady State Multiplicities
1986 Robert S. Brodkey; The Potential for Image Processing and
Analysis in Turbulence Research
1987 James J. Christensen; Reflections on Teaching Creativity
1988 Stanley I. Sandler; Physical Properties and Process Design
1989 J.L. Duda; A Random Walk Through Porous Media
1990 Brice Carahan; Computers in Engineering Education
1991 Darsh T. Wasan; Interfacial Transport Processes and Rheology
1992 Willian N. Gill; Interactive Dynamics of Convection and Crystal
Growth
1993 Morton M. Denn; Polymer Flow Instabilities


Fall 1993 197










Award Lecture ...




INTERACTIVE DYNAMICS OF


CONVECTION AND CRYSTAL GROWTH


WILLIAM N. GILL
Rensselaer Polytechnic Institute
Troy, NY 12180-3590


Would have liked this article to be the story of
how basic theoretical and experimental break-
throughs have contributed to the spectacular
advances in making and using new materials for the
various "revolutions" we have witnessed since World
War II. But it quickly became clear to me that the
scope of such a story is beyond my competence to tell
coherently. Therefore, I will attempt to give here a
chemical engineer's view of some rather recent work
on dendritic growth, which has generated many sur-
prises over the last fifty years-only a part of the
story I had hoped to tell.
The macroscopic properties of materials and the
uses to which they can be put depend on their inter-
nal structure. In turn, the microstructure of materi-
als depends on the details of the processes used to
make them. Furthermore, the making of a material
and its placement in a system for final use may
occur simultaneously as, for example, with thin di-
electric or metallic films made by chemical vapor
deposition for integrated circuits. In this case, both
the microstructure and the macrostructure (unifor-


William N. Gill was presented with the Thirtieth
Annual Chemical Engineering Division Lectureship
Award for this lecture, which he gave at the ASEE
ChE Division summer school meeting at Montana
State University in August of 1992. The award
is bestowed annually on a distinguished engineer-
ing educator and is designed to recognize and
encourage outstanding achievements in important
fields of fundamental chemical engineering theory
or practice.
Professor Gill is Russell Sage Professor in Chemi-
cal Engineering and the Center for Integrated Electronics at Rensselaer
Polytechnic Institute, and has been a faculty member at Syracuse University,
Clarkson University, and the State University of New York at Buffalo. He
served as chairman of the ChE departments at Clarkson and RPI, Dean of
Engineering at Buffalo, Fulbright Senior Research Scholar in England and
Australia, and Glenn Murphy Distinguished Professor at Iowa State.
Gill's research has focused on several areas, including turbulent convec-
tion, Taylor diffusion, membrane separations, and various aspects of crystal


mity, absence of keyholes, step coverage, etc.) of the
materials profoundly influence the performance of
the devices which are made from them.
Microstructure and composition determine the
properties of advanced materials, including alloy cast-
ings, polymer-ceramic composites, and films, and
convection may profoundly affect all of them. The
transport of energy and the redistribution of solute
in the solidification of alloys are influenced by con-
vection in different ways (depending on whether the
transformation occurs in the vapor or liquid phase)
because the transport properties differ enormously
in gases and liquids.
The subject of interactive dynamics has very prac-
tical implications because it includes efforts to un-
derstand how process conditions, the microstructure,
and macroscopic configuration of materials go to-
gether, as they are manufactured, to maximize their
usefulness in various applications. If our goal is to
create materials and structures with the properties
we wish them to have, then an understanding of how
to control the way they may be made to achieve this
goal is of prime importance.
When crystals grow in a melt of pure liquid, from a
solution of several components or from the vapor


growth. His contributions are summarized in more than 150 articles balanced
between theoretical and experimental content. His motivation is the under-
standing of chemical and physical phenomena that underlie processes of
practical importance from both industrial and environmental viewpoints. His
work has been cited about 2000 times in a large number of joumals and
books in many fields, including medicine, biophysics and biochemistry, chem-
istry, geophysics, applied mathematics, condensed matter physics, virtually
all areas of engineering, and materials science.
He has investigated the effects of concentration polarization, the interac-
tion among components in the feed, ways to model hollow fiber and spiral
wound systems, and the fundamental processes that underlie transport in
membranes. His most recent area of interest has been crystallization, includ-
ing dendritic growth and rapid solidification, and currently with chemical vapor
deposition of copper and interlayer dielectric films for integrated circuits.
Gill has worked with many graduate students and has been thesis advisor
to thirty-one PhD recipients. These former students currently have faculty
positions at universities in the United States, Israel, Korea, Taiwan, India,
Iran, and Europe. He has been editor of Chemical Engineering Communica-
tions since 1979 and serves on several boards.


Copyright ChE Division ofASEE 1993

198 Chemical Engineering Education









The subject of interactive dynamics has very practical implications because it includes
efforts to understand how process conditions, the microstructure, and macroscopic configuration
of materials go together.... If our goal is to create materials and structures with the
properties we wish them to have, then an understanding of how to control the
way they may be made to achieve this goal is of prime importance.


phase by deposition on a substrate, an interface is
created, the shape and movement of which depends
on the conditions that prevail on both sides of the
interfacial region and within that region itself. In
other words, the movement and shape of the inter-
face creates an active pattern which evolves in time
and which is inherently three-dimensional in sys-
tems of practical interest. The quantitative descrip-
tion of this spontaneous nonlinear dynamic process
is one of the objectives of the theory of pattern for-
mation, and one particular aspect of it includes the
interactive dynamics of convection and crystal
growth. Convection is coupled with the growth of the
crystals involved, and each affects the other because
of the movement of the mobile interface.
The problems associated with studying interactive
dynamics are formidable, but progress is being made
which will contribute to the development of some of
the extraordinary materials of the future. The Octo-
ber 1986 issue of Scientific American contains thir-
teen articles, well worth reading, on various aspects
of the development of materials, providing an
interesting perspective on the modern aspects of ma-
terials engineering and science by people who are
not chemical engineers. A physicist's viewpoint on
dendrites and the theory of pattern formation is
given by J.S. Langer in Science (March 1989); this
perspective was updated with his more recent ar-
ticle in Physics Today (October 1992) in which he
appealed for a rational approach to materials re-
search on the national level.
An applied mathematician's viewpoint on interac-
tive dynamics in crystal growth is given in two
review articles published recently by Huppert"1
and Davis[2' in the Journal of Fluid Mechanics.
Brown,3"' a chemical engineer, has reviewed various
interesting aspects of single semiconductor crystal
growth from the melt, especially for electronic and
optoelectronic devices.
The Handbook of Crystal Growth (Edited by
Hurle; Elsevier, 1993) contains a number of chap-
ters which review subjects related to this one. Also,
a conference was held in March of 1992 in Chamonix,
France, the papers from which have been pub-
lished as Interactive Dynamics of Convection and
Solidification (Kluwer Academic Publishers, edited
by Davis, et al.).
Fall 1993


L. r





Figure 1. Photographs of an anisotropic ice dendrite with
AT= 0.60K, R,/R,-28, magnification 26x:
(A) edge view with tip radius, R,;
(B) Basal plane with tip radius, R2.

When they are still undergraduates, chemical en-
gineers begin learning to deal with heat, mass, and
momentum transport coupled with chemical reac-
tions in the bulk phase or on the boundaries of the
system. At Rensselaer, for example, individual
courses in fluid mechanics, heat transfer, separation
processes, and chemical reactor design are required
in the third and fourth years of the undergraduate
program. The exposure to separation processes, re-
actor design, and the option to take a fourth-year
course in transport phenomena provides a good foun-
dation for graduate-level course work and research
in materials processing.

THE ROLE OF
TRANSPORT PROCESSES IN CRYSTAL GROWTH
It is important to understand the roles of heat,
mass, and momentum transfer in crystal growth
processes. One or more of these phenomena may be
of crucial importance, depending on the phase change
system involved and how the process is carried out.
To illustrate this, we will consider dendritic growth
which, according to Glicksman and Marsh,[4] is the
most prevalent form of solidification.
In the simplest case involving dendrites, the free
growth of crystals (unencumbered by walls) from
pure undercooled melts produces dendritic structures








in which the leading tip of the main stem of the
dendrite propagates in the preferred crystallographic
direction, as shown in Figure 1. These reproducible
patterns have small dimensions and large cur-
vature. They seem to occur in nature due to the
competition among the kinetic resistance to the at-
tachment of molecules at the surface, the effect of
the surface energy of the solid-liquid interface, and
the rate of removal of heat from the surface into
the subcooled melt. The underlying reasons for why
dendrites form the patterns they do are not com-
pletely clear and currently are being investigated
on a worldwide basis. Figure 1 illustrates how
different ice dendrites appear when viewed from the
basal plane, where one sees a rich sidebranch struc-
ture, and from the edge plane, which has no
sidebranches at all. Figure 2 shows the typical
shape of a water drop in equilibrium with the ice
matrix in which it is encased. This drop also demon-
strates strong anisotropy.
Surface tension depresses the melting point of an
interface which is convex to the melt, and attach-
ment kinetics reduce the driving force for heat trans-
fer, both of which stabilize the solidification front.
The rate of heat removal by conduction to the under-
cooled melt may be influenced significantly by ther-
mal or forced convection, which will have an effect
on the properties of the crystal. A successful theory
of this seemingly straightforward problem from which
one hopes to predict the size, shape, and growth rate
of the crystal, has proved to be elusive.
Grain size (and its distribution in a material) is
one of the properties that is of importance in crystal
growth processes, ranging from the making of steel
to the deposition of thin metallic films in integrated
circuits. Within each grain of a structural material
(such as a titanium-based alloy) is a microstructure
formed by dendritic growth. The microstructure
consists of a pattern in which the interstices be-
tween the main stems and the sidebranches of alloy
dendrites are filled with material which is rich in
solute. The solution in the interstices solidifies more
slowly than that contained in the dendrites. This
microstructure determines many of the macroscopic
properties of structural materials, and thus the uses
for them. Therefore it is of major importance to un-
derstand how to control the rate of dendritic growth,
the size of the dendrites, and the spacing between
their sidebranches.
It has been known for a long time that processing
techniques can have a profound influence on the
microstructure of materials. Indeed, the basic
ideas regarding some of the methods currently used
200


to produce exotic materials, such as directional so-
lidification, modified directional solidification to pro-
duce single crystals, and rapid solidification, had
their roots in the 1960s. These processing methods
have had a major impact on the development of
advanced structural materials because they influ-
ence the microstructure in predictable ways. Fur-
thermore, the methods used are all related to con-
trolling the transport processes involved in the mak-
ing of these materials.
Examples of the dramatic improvements in mate-
rials due to the procedures used to process them
abound. The use of directionally solidified metal struc-
tures has resulted in an increase of 1500C to 200C
in inlet temperatures for turbines, which substan-
tially increases their efficiency. One can actually
obtain amorphous metal alloys by rapid solidifica-
tion, and these have properties which may substan-
tially reduce the energy losses which occur in the
distribution of power. Thus it is important from both
a basic and a practical viewpoint to understand the
role of various transport mechanisms in determin-
ing rates of production, the length scales that corre-
spond to the rates of production, and how a particu-
0.2mm 1
Ii (A)


Figure 2. Equilibrium shape of highly anisotropic water
drop in ice matrix: (A) basal plane; (B) edge plane.
Chemical Engineering Education









Convection is the organized movement of large
groups of molecules on a macroscale, and (as
required by Newton's laws of motions) it results
from force fields which may be subtle and
difficult to manipulate or control.

lar growth path is selected, which determines what
the length scales and rates are. Here, I will concen-
trate on some of the ways natural and forced convec-
tion affect the crystal growth process-it is a subject
on which some of my students and I have spent a
considerable amount of time.

CONVECTION AND CRYSTAL GROWTH
Convection is the organized movement of large
groups of molecules on a macroscale, and (as re-
quired by Newton's laws of motions) it results from
force fields which may be subtle and difficult to
manipulate or control. For example, flow may be
caused primarily by buoyancy forces which are
ubiquitous on earth due to its gravitational field.
If one uses the microgravity levels offered by a
space station to reduce gravity by several orders of
magnitude, surface tension forces may become
more important than gravity in determining the na-
ture of the flow and, therefore, in materials process-
ing. Also, convection may be useful in enhancing
heat and mass transfer rates and in reducing pro-
cessing time. Or it may adversely affect product
uniformity, as can happen in the chemical vapor
deposition (CVD), of thin films in a flow field that is
not oriented properly.
Essentially, all of the mathematical work aimed at
understanding the role of convection in dendritic
growth has dealt with needle crystals in which the
sidebranches are neglected and one concentrates on
the region near the tip of the dendrite. The first
exact solution for the growth of a dendrite from the
melt was obtained by Ivantsov almost fifty years
ago. His classical analysis applied to isothermal
needle crystals growing in a stationary melt with
zero velocity, U = 0. Some of the work my students
and I have done has focused on trying to add a
realistic description of convection in the melt to gen-
eralize Ivantsov's analysis. Thus, Dash and Gill5"'
showed that a similarity variable could be used to
solve the energy equation given by
T + U VT = aV2T (1)

for an isothermal needle crystal including convec-
tion in the melt, if the velocity field U in the convec-
tive term U VT on the left-hand side of Eq. (1) is
given by the Oseen or potential flow models.
Fall 1993


Ananth and Gill'6' and Saville and Beaghton[71 for
Oseen flow, and Ananth[81, and BenAmar, et al., 9 for
potential flow, used variations on the similarity ap-
proach to study the growth of parabolic dendrites.
Ananth and Gill considered the growth of crystals in
the form of an elliptical paraboloid and gave exact
solutions to the Oseen flow and energy equations
in an effort to understand better the growth of ice
crystals which are anisotropic. The body shapes,
flow fields, and thermal fields which yield self-
consistent solutions for the steady growth of den-
drites into a melt which itself is in motion, U # 0,
were determined by Ananth and Gill. Among sur-
faces of revolution only a parabolic crystal grows
steadily, and either the Stokes flow, Oseen viscous
flow, or potential flow approximations must be made
in order to obtain an exact solution for the growth
Peclet number
VGR
PG -
where VG is the growth velocity, R is the tip radius,
and a is the thermal conductivity of the melt. Stokes
and potential flows are valid in the limit

Re = UR -0 and Re-> -

respectively. As discussed by Lagerstrom and Cole"o0
and Lagerstrom,[11 the Oseen approximation to the
Navier-Stokes equations is uniformly valid for a semi-
infinite three-dimensional paraboloid of revolution
at very small Reynolds numbers.
The growth of shape-preserving (near the tip) den-
drites in subcooled melts has been observed experi-
mentally in detail for succinonitrile (SCN) by Huang
and Glicksman[121 and for ice by Fujioka,[131 Tirmizi
and Gill,1141 and Koo, et al.[5' In these experiments
crystals grow from a capillary tube into a melt which
is quiescent. Near the crystal-melt interface, how-
ever, there is a natural convection flow generated
by gravity acting on a density distribution created
by the temperature gradients, caused by the
spreading of the heat of fusion into the melt. The
intensity of this natural convection is indicated by
the Grashof number, Gr.
In order to compare their Oseen flow solutions to
experimental data on the dendritic growth of SCN,
Ananth and Gill interpreted Re = VGr and showed
reasonable agreement with the data of Huang and
Glicksman. They found that the Grashof number
increases as undercooling, AT, which is the driving
force for the flow, decreases. This counter-intuitive
result occurs because the length scale, R, which ap-
pears as R3 in










Gr = gATR3
v2
increases as AT decreases in the experiments on
SCN. Koo, et al., demonstrated that the same behav-
ior is observed with ice dendrites if one uses the
harmonic mean
2 RIR2
m-R1+R2
of the tip radii, RI and R, of the edge and basal
planes as the length scale. This result is shown in
Figure 3, and Gr is seen to change by several orders
of magnitude. Ananth and Gill also solved approxi-
mately the fully nonlinear thermal convection prob-
lem, where Gr arises naturally, and they demon-
strated excellent agreement between the mathemati-
cal results and the data on SCN. Subsequently,
Canright and Davis[161 studied the limiting case of
the effect of very weak buoyancy driven flows on the
shape of dendrites and showed that their analysis
was complementary to that of Ananth and Gill.

THEORIES OF SELECTION IN DENDRITIC GROWTH
The experiments mentioned above all show that
the growth velocity, VG, and the tip radius of the
dendrite, R, are determined uniquely when the un-
dercooling, AT, is fixed. In contrast, Ivantsov's
pure conduction solution indicates that the Peclet
number, PG, is fixed when the dimensionless
undercooling given by the Stefan number, St, is
specified. Consequently, only the product, VGR, is
determined by fixing AT, and the individual values
of VG and R cannot be predicted. Thus, the theory is
incomplete if one assumes that the dendrites are
isothermal and smooth.
If one includes natural convection, or forced con-
vection, VG increases and R decreases, but the same
degeneracy exists in the theory. Therefore consider-
able effort has been expended over many years to
find a selection criterion for VG and R, and these
efforts in one way or another revolve around the
introduction of surface tension in the problem. The
selection criterion is an additional relationship be-
tween VG and R which enables each of them to be
chosen uniquely for given values of AT and U,.
Until the middle of the 1970s, the maximum-veloc-
ity hypothesis was used for this purpose, and it
assumed that the operating point was the maximum
in the VG versus R curve. This assumption was used
for about thirty years until it was shown to be incor-
rect by the careful experiments on succinonitrile of
Glicksman, et al.,'171 in which both VG and R were
measured as a function of AT with U, = 0.


I Dimensionless Subcooling, St = AT/(L/Cp)
Figure 3. Use of thermal convection analogy, Gr = Re2,,
with selection parameter, a* = 0.075 to estimate level of
natural convection. Comparison of Grashof numbers
observed experimentally with those predicted by Stokes
flow theory.

Then Langer and Muller-Krumbhaar[181 proposed
the marginal stability theory based on the introduc-
tion of surface tension as a perturbation. This led to
the relationship
= = constant (2)
VGR2
where
do = mC C/L2, the capillary length
a = thermal diffusivity
y = surface tension
Tm,Cp,L = melting point, heat capacity, heat of fusion
The notion that VGR2 is independent of AT also had
been proposed by Oldfield"'19 on the basis of com-
puter experiments in which he balanced the heat
transfer by conduction against the stabilizing effect
of surface tension.
More recently the selection of the growth velocity
and length scale in the absence of fluid flow has been
addressed in many articles which discuss the micro-
scopic solvability theories. For detailed reviews of
this work I refer the reader to the work by Langer[23'
and Kessler, et al.[201 They showed that no solutions
can be found in the presence of finite surface tension
unless anisotropic effects (variation in surface ten-
sion around the surface of the crystal), no matter
Chemical Engineering Education






























Figure 4. Forced convection growth cell provides rigid
body motion of melt with dendrite fixed in space.

how small, are taken into account, and that the
fastest growing tip is selected because it gives the
only dynamically stable solution.
Anisotropy refers to the variation in surface ten-
sion around the dendrite in the azimuthal direction.
When the anisotropy, e, is about 0.5%, the micro-
scopic solvability theory yields according to Mushol,
et al.,[211 a result which is given by

*= do .0.01
VGR2
This result is smaller by a factor of two than that
obtained from the marginal stability hypothesis of
Langer and Muller-Krumbhaar which neglects the
anisotropic effects. Both theories are in qualitative
agreement with the experimental value of o* 0.02
for the data on succinonitrile of Huang and
Glicksman, and Lee, et al.,1221 when the subcooling is
large and the effect of convection is small.
The agreement between microscopic solvability
theory (MST) and the experiments for succinonitrile
was encouraging, and it led to a feeling that real
progress was being made in our understanding of
dendritic growth. But Langer,[231 who is an original
contributor to MST, raised warning signals several
years ago, indicating that the predictions of MST
had not been confirmed experimentally. Unfortu-
nately, the experimental evidence which has been
accumulating lately on different materials does not
seem to be consistent with MST and suggests that
Langer's concerns were well founded.
Fall 1993


SOME EXPERIMENTAL TESTS OF
SELECTION THEORIES
Two types of experiments yield results which are
significantly different from those predicted by MST.
I will try to describe both of these experiments, but I
will concentrate more on the forced convection ex-
periments carried out by my research group. Be-
cause we had worked on the theoretical problem of
including forced convection in the melt, my students
and I naturally were interested in performing ex-
periments under conditions which corresponded as
closely as possible with the assumptions we made to
obtain forced convection solutions of Eq. (1).
Forced convection experiments seemed attractive
because they introduced the velocity of the melt at a
large distance from the crystal, which is a new quan-
tity, U-, that can be varied independently of AT.
As usual, these experiments proved to be more diffi-
cult and time consuming than we originally thought
they would be.
First, we wanted to study a material whose prop-
erties were well known so that we could reproduce
previous results for U~ = 0 before attempting to do
something entirely new. Second, the material
(succinonitrile) which we settled on had to be
ultrapure (99.999% or better) and was extremely
expensive at the time. Therefore we had to think
small in designing an apparatus. Third, we realized
that our forced convection velocities, U-, would have
to be very well defined and large enough to render
natural convection negligible. Fourth, the melt had
to be transparent because we wanted to track the
crystal-melt interface and measure precisely both
the growth rate and the tip radius in real time.
Fifth, we would have to photograph and make video
tapes of the experiments to enhance our understand-
ing of the physical processes involved. Sixth, we
would have to control the temperature of the growth
cell to extremely close limits. The solutions to these
and other problems are described in a thesis by
Lee'[" which had significant contributions by Ananth
(who was working with me as a post doc at the time).
In forced convection experiments on crystal growth,
one has to deal with three different velocities: VG,
Us, and U.. It is important to understand clearly the
meaning of each because they all exist simulta-
neously. In our experiments we observed the shape
of the interface of the dendrite which we character-
ize by the tip radius, R, the motion of the interface
denoted by the velocity VG, and the velocity of the
melt with respect to a fixed frame of reference, U,.
We could not observe or measure the velocity due to
natural convection, UN. Therefore we used theory to









estimate it and conducted our experiments so that
UJUN and UJVG ranged up to about 40 and 300,
respectively, as indicated by Gill, et al.[251
The apparatus in which the forced convection ex-
periments were carried out is described in detail
by Lee1241 and is shown in Figure 4. The basic idea is
to keep stationary the capillary from which the
crystal emerges and to have the cell containing
about 100 cm3 of SCN move so that it creates a rigid
body motion of the melt relative to the crystal over
the range 0 < U_ < 1 cm/sec. The cell is operated in
a constant-temperature bath which is controlled
to 0.001 K, and after purification the SCN re-
mains hermetically sealed throughout the experi-
ments. The patterns formed by the dendrite-melt
interface are observed through a microscope and
recorded on video film. The measurements of VG and
R deviated from their mean values by less than
2.5% and 5%, respectively.
The goals of this work were to measure various
characteristics of the dendrite, including VG, R, dis-
tance from the tip to the first sidebranch, distance
between sidebranches, and other quantities, as func-
tions of the undercooling, AT, and the forced convec-
tion velocity, U-, which can be varied independently.
However, here I shall discuss only the steady state
measurements of VG and R and their implications
when they are combined to obtain o*, which is de-
fined in Eq. (2). In this way we can obtain
o*=o*(AT,U,-) (3)


The results obtained by Lee, et al., 22] show that V
increases and R decreases monotonically with bot]
AT and UI. All four of the quantities (VG, R, AT, an
U,) were measured in our experiments. There-
fore we were able to determine if VG increases
more or less quickly than R2 decreases, and this
shows how VGR2 behaves either with AT or U,.
In this way one can establish experimentally
the behavior of the selection parameter, o*, as a
function of (AT, U-).


By determining the dependence of r* on
(AT, U,), we can test one of the basic pre-
dictions of microscopic solvability theory.
Bouissou and Pelce[261 used microscopic solvabil-
ity theory to calculate this dependence, and they
reported that o* decreases with increased
(UJVG), which is the opposite of what the ex-
periments of Gill, et al.,[251 and Lee, et al.,1221
show. Figure 5 displays the measured values of
Y* as a function of UJVG.
In Figure 5 we see that o* increases by more
than 50% as UJV, increases, as shown by Gill,


et al.1251 Since this behavior is contrary to that pre-
dicted by the two-dimensional analysis of Bouissou
and Pelce, it appears that microscopic solvability
theory does not predict even qualitatively the cor-
rect dependence of o* on U_ for SCN. A more dra-
matic contrast between theory and experiment is
shown by Lee, et al.,[221 in their Figure 4 in which the
slope of the data is negative and opposite to the
prediction of MST.
Let us now consider the growth in quiescent melt
of dendrites other than SCN and attempt to deter-
mine ifMST predicts the proper dependence ofo* on
the anisotropy, e. Muschol, et al., made careful mea-
surements of e, and we shall outline briefly only
their results and the information needed to under-
stand them qualitatively. The Gibbs-Thompson equa-
tion for a cubic crystal can be written
Ti = T[1-(y +yee) / L] (4)
where
y surface tension
y7e second derivative of y with the angular coordi-
nate, e
0 measures position around the surface of the
dendrite
K total curvature
L heat of fusion
Tm melting point of a flat surface
T. local interfacial temperature
If the surface tension is represented by


y= Yo[l+em cos me]
combining Eqs. (4) and (5) obtains the
tion


G
h
d


(5)
approxima-


Ti=Tm -2 T[1 -acosme] (6:
RL


Figure 5. Selection parameter, a* = (2ad,)/(VGR2) for SCN den-
drites increases by more than 50% as ratio of forced convection
velocity, U,, to growth velocity, V,, increases.
Chemical Engineering Education


AT
0.035 0.230 cm
0 0.346 0.1 V 0.460 sec
X 0.772
A 1.000
0.030 0
O
S.(2a do 0
0.025 V


0.020 -


0.015 II III
0 50 100 150 200 250
U,
V


0.0195



300









where
R mean value of the tip radius
a anisotropy factor used by Mushol, et al.[21]
In Eq. (5), a is related to em by a = (m2-1)em. As
pointed out by Glicksman and Marsh, (who subse-
quently made similar comparisons to those of Mushol,
et al.) Eq. (6) shows that the equilibrium melting
point at a point on an anisotropic solid-liquid inter-
face depends on both its curvature and the orienta-
tion of the interface normal with respect to the prin-
cipal crystallographic axes.
Mushol, et al., computed theoretical values for the
selection parameter, ao, based on various MST ana-
lytical models and numerical codes for materials for
which a had been measured. The results were disap-
pointing, and they concluded (as did Glicksman and
Marsh) that the predictions of MST do not agree
well with the available experimental evidence for
dendrites grown in quiescent melts. Therefore, it
seems that both forced convection experiments
(UI > 0) with SCN[22'25J and experiments on the rela-
tionship of o* with E for other materials including
alloys, do not support MST. It would appear that
something fundamental is missing from the theory.

CONCLUDING REMARKS

Where does this leave us? Where do we go from
here? It is obvious that great progress has been
made in developing new materials, and this pro-
gress has been aided and abetted by a continually
expanding body of experimental and theoretical
knowledge about crystal growth. Furthermore, the
available experiments have been getting more pre-
cise, which is important when testing new ideas and
insights. Indeed, one can expect that as new ex-
periments accumulate, they will suggest new theo-
retical concepts, as has been the case in virtually
all fields of science. Also, incredibly fast computers
and intriguing mathematical methods have been
developed which will facilitate the integration of
theory and experiments.
It is impossible to predict just when a fully satis-
factory, predictive theory of dendritic growth will be
available. I doubt it will take another 350 years, as
apparently has been required to prove Fermat's last
theorem. When it arrives, new doors no doubt will
open up, and it probably will be helpful in control-
ling the microstructure of even more useful and ex-
otic materials. In the meantime, there is a need for
precise experiments on multicomponent materials of
practical importance. Based on past experience, I
think such experiments will stimulate new develop-
Fall 1993


ments of technological importance-and deeper theo-
retical understanding as well.

ACKNOWLEDGMENT
Work on this article was supported in part by the
New York State Energy Research and Development
Authority and by the New York SEMATECH Center
of Excellence at Rensselaer.

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21. Muschol, M., O. Liu, and H.Z. Cummins, Phys. Rev., A46,
1038(1992)
22. Lee, Y.W., R. Ananth, and W.N. Gill, "Selection of a Length
Scale in Unconstrained Dendritic Growth with Convection
in the Melt," J. Cryst. Growth, in press (1993)
23. Langer, J.S., in Chance and Matter, 629, eds J. Souletie, J.
Vannimenus, and R. Stora, North Holland, New York (1987);
Science, 243, 1150 (1989); Physics Today, 24 October (1992)
24. Lee, Y.W., PhD Thesis, Rensselaer Polytechnic Institute
(1991)
25. Gill, W.N., Y.W. Lee, K.K. Koo, and R. Ananth, "Interaction
of Thermal and Forced Convection with the Growth of Den-
dritic Crystal," p. 93 in Interactive Dynamics of Convection
and Solidification, NATO ASI Series, Kluwer Academic
Publishers, S.H. Davis, et al., eds (1992)
26. Bouissou, P., and P. Pelce, Phys. Rev., A40, 6673 (1989) O
205











- 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 presenting a
particular principle in class, or in a new light, or that can be assigned as a novel home problem, are
requested, as well as those that are more traditional in nature and which elucidate difficult concepts. Please
submit them to Professors James 0. Wilkes and Mark A. Burns, Chemical Engineering Department, Univer-
sity of Michigan, Ann Arbor, MI 48109-2136.



THERMODYNAMICS

AND

COMMON SENSE


OCTAVE LEVENSPIEL
Oregon State University
Corvallis, OR 97331-2702


Though it is one of science's grandest pure-
logic structures which awes and enraptures
its faithful, thermodynamics unfortunately
causes much grief for the student who is studying
the subject.
Why?
Let's look at a simple situation-that of a batch
system of internal energy U going from state 1 to
state 2. Here we see written in all texts
AU= Q-W (1)
But if the system is raised or lowered (potential
energy change, AEp), speeded or slowed (kinetic
energy change, AEk), or swelled or shrunk (expan-
sion work, Wpv) then the above first law expres-
sion becomes more generally


Octave Levensplel is author of four chemi-
cal engineering texts. One of them is over
thirty years old but is still widely used and
has been translated into ten languages.
Another, his favorite and funniest, is practi-
cally unknown today. Octave is now a re-
tired (emeritus) professor, enjoying him-
self and struggling to understand thermo-
dynamics.


AU+ AEp + AEk= Q Whaft Wpv (2)
Clear?
Do you accept this?
Yes?
GOOD!
Let us apply this to a column of isothermal
ideal gas, such as air, at equilibrium. What hap-
pens to the pressure as a chunk of this gas is
raised slowly from elevation Z, to elevation Z,?
Applying the above general first law expression,
noting that AU = 0 at constant temperature, we
find
2
+ AEp + A4k =9-sXhaft JpdV (3)
1
Now, for an isothermal ideal gas we can write


nRT
P V


V2 P1
V1 P2


so for a mass m (or n moles) of gas raised from Z,
to Z, we get


Copyright ChE Division ofASEE 1993


Chemical Engineering Education














































2
mg(Z2 Z) nRT dV
gc V
1
and, since the molecular mass

mw =
n


Z2--- l-

'P2V2




column of
isothermal volume
ideal gas changes
at equilibrium






z-- / /



piVi

Zo=O ------


Fall 1993


rearranging gives, finally

g(Z2 -Z) = RTn P2 (4)
mw Pl
This is an interesting expression. Look at the
left-hand side. It is positive, so the right-hand
side must also be positive.
This means that P2 > Pi!!
What this says is that as you climb a mountain
the air gets thicker, contrary to experience.
What kind of nonsense is this?
Results like this remind me of the story"1 of
the great physicist Arnold Sommerfeld, who had
written a series of books on various topics in
physics. When asked why he hadn't written one
on thermodynamics, he is supposed to have said
It's a funny subject. The first time you go
through it you don't understand it at all.
The second time through you think you
do except for one or two minor points.
The third time you know you don't un-
derstand it, but by then you are so used
to it, it doesn't bother you.
At the time he was killed in an accident, the
physicist was in the middle of writing a book on
... guess what? Yes-thermodynamics!
To get back to the problem, though-where is
the error? Please help me straighten out this
curious conclusion.

REFERENCE
1. Angrist, S.W., and L.G. Helper, Order and Chaos, Ba-
sic Books, page 215 (1967) This gem of a book is unique,
contains only three equations, and makes thermo al-
most fun.


The author welcomes comments and solutions to this problem.

A later issue of CEE will list those who have saved

thermodynamics from disgrace.


207













LEARNING THROUGH DOING

A Course on Writing a Textbook Chapter


PHILLIP C. WANKAT
Purdue University
West Lafayette, IN 47907

People learn best when they become involved
in the process of doing something.[1] While
actually working on a project, there is great
motivation to learn those things that are needed to
finish the project.[2' Properly organized projects which
allow students to function as engineers and to re-
ceive feedback are an excellent teaching method.
In the course described in this paper, graduate
students completed projects which required them to
perform one of the functions of a chemical engineer-
ing professor-writing an advanced textbook chap-
ter. The idea for a seminar course in this form came
from a book by Eble,[31 and the result was a course
wherein the students worked harder and learned
more than the professor. This is in stark contrast to
a "normal" course where the professor works harder
and learns more than the students.

THE COURSE
The course was titled "Seminar in Separation Re-
views," but the methodology can be used for any
technical topic. The prerequisite for the course,
an advanced class in ChE separations, ensured that
time did not have to be spent teaching basics.
Since this was a graduate-level elective, it was not
necessary to cover a specific body of material, and
the students could pick their own topic. This proce-
dure has the advantage that the students cannot
later blame the instructor if their topic proves to be
difficult for them.
The seminar was advertised to all students who
met the prerequisites, and four students eventually
registered. Two other students were interested
but could not take the course because of schedule
conflicts. A larger class could easily be taught (see
"Possible Course Modifications" appearing at the end
of this article).
The students were told to produce a professional


quality textbook chapter on an advanced topic in
separations. To make sure that writing was done for
this course, the topic could not be on the subject of
their thesis research. This requirement meant that
everyone started with a very modest knowledge base
of the chosen topic. This mimics industrial practice
where engineers are often assigned projects in areas
outside of their expertise. The topic had to come
from a list of over fifty separations, the chapter was
to be written at the graduate level, and the students
were to work in teams of two. The course grade was
based on this project.
During the first class meeting I introduced the
course objectives and rules and presented an over-
view of separations. In the second class, the stu-
dents analyzed the structure of a separations text-
book to determine what is typically included in a
textbook chapter. They concluded (with my help)
that the following sections are necessary: introduc-
tion; body, with appropriate figures and tables;
examples, including some for real systems; sum-
mary; notation; references; and homework, with a
separate solution manual.
In the third class the students critiqued a recent
paper from the literature. Fortunately, the paper
chosen by the professor had several flaws, and a
lively discussion developed-the flaws made it clear
that not all papers are created equal. The students
were then given a list of journals which included
papers on separations, and they were told to skim
through several to obtain topic ideas. They came to
class with a list of three topics.
We spent much of the fourth class period in team-
ing up students who had an interest in working
Chemical Engineering Education


Phil Wankat received his BSChE from Purdue
and his PhD from Princeton. He is currently a
professor of chemical engineering at Purdue
University. He is interested in teaching and coun-
seling, has won several teaching awards at
Purdue, and is Head of Freshman Engineering.
His research interests are in the area of separa-
tion processes, with particular emphasis on cy-
clic separations, adsorption, preparative chro-
matography, and simultaneous fermentation and
separation.


Copyright ChE Division ofASEE 1993









together, and this was eventually accomplished to
everyone's satisfaction. The remainder of the period
was consumed by a mini-lecture on the different
work styles for doing big projects. For example,
some engineers prefer to do the work serially by first
collecting all the information, then doing cal-
culations, and then writing the report. Others pre-
fer parallel processing and mix their work on the
different aspects.
A librarian from the engineering library gave
three lectures on manual and computer library
search methods. To get started, the teams worked
with the librarian on performing computer searches
using Dialog. The groups were required to do a
patent search and to include patents in their bib-
liographies. Once they had learned how to do
computer searches, the students did their searches
independently.
We spent much of the remainder of the semester in
individual group meetings. I met with each group for
twenty-five minutes during the regularly scheduled
class meetings, and since each group met with me
three times during the week, procrastination was
not a problem. On a few occasions the students told
me that they had not had time to do any work since
the previous meeting, but this never happened twice
in a row. I used the group meetings to discuss tech-
nical points and work habits.
One work habit that both groups needed assis-
tance with was how to efficiently read journal ar-
ticles. The students had a tendency to try to read all
of the papers thoroughly in an effort to completely
understand each article. So we had a discussion on
how all papers are not of equal importance. I illus-
trated the concept of triage to them-that through
skimming, papers can quickly be classified into three
piles: important, possibly important, and unimpor-
tant. Since only the important papers need to be
read carefully, triage can save considerable time.
Later in the semester I used the group meetings
to discuss the outlines, the written sections, the ex-
amples, and the homework problems. On occasion,
when I felt the students were overwhelmed, the group
sessions became pep talks. This kind of support fa-
cilitates learning.[1,21
I dispersed other class activities throughout the
semester. Once the students had read a reasonable
number of articles, I critiqued their notes on the
articles. I found that, almost invariably, the stu-
dents were not keeping complete enough reference
citations. Each group presented two informal progress
reports to the class during the semester. In addition
to serving as informal communication practice, these
Fall 1993


reports forced the students to integrate their progress
and see what else had to be done.
After mid-term break and shortly before the chap-
ter outlines were due, I gave a lecture on organizing
papers and writing, following the ideas of Peter El-
bow.14' Briefly stated, Elbow's idea is that writers
should do the first draft as quickly as possible, and
then rewrite and rewrite. Toward the end of the
semester a technical communication expert gave
a lecture on common mistakes in written English
and a lecture on oral presentations. I gave a mini-
lecture on critiqueing papers after the students
turned in their first drafts.
In addition to the two informal progress reports, I
used a series of partial assignments on the project in
an effort to prevent procrastination. A couple of weeks
after the mid-term break the teams turned in a
detailed outline of their chapters which I quickly
returned to them with extensive comments on what
could be deleted and what should be added. Then a
first draft of the entire chapter (without homework)
was turned in and was critiqued by both myself and
the other student team-I told the students to read
the chapter and to respond as students who were
trying to learn the material. The teams then com-
pleted a final version of the chapter which corrected
the rough draft. The final draft was due on the last
class day of the semester, and during finals period
each group gave a formal oral presentation.
THE PROFESSOR'S DUTIES
In this class, the professor's duties differ from those
in a normal lecture class. The professor must
Develop the class schedule and arrange for the
guest lecturers
Present three of the eight lectures
Lead the discussion on book chapters, critique the
literature article, and critique the first drafts
Develop an extensive list of acceptable topics and
set the criteria for acceptable projects
Serve as a facilitator for selection of groups and
topics
Read and grade the first drafts and the final
chapter plus the solution manual
Listen to and grade the oral reports
Serve as a consultant and listen, question, encour-
age, and prod during the remaining thirty class
periods
(Perhaps the most important) Set the tone that the
students could and would produce a professional
quality chapter.
Since little preparation time was needed, during
most of the semester I averaged about four hours a
week on this course. This number increased, how-









ever, during the two weeks that reports were graded.
Overall, the professor's workload in a class of this
type is so low as to be almost sinful. Yet, the stu-
dents learned a lot and the class was very success-
ful! Student learning depends much more on how
hard the student works than on how hard the pro-
fessor works. Since I was able to focus most of
my attention on the students instead of on the
material, they received much more personal atten-
tion than normal. This class was also fun to teach.
The students all worked hard in a positive and en-
couraging atmosphere.
The professor's technical knowledge plays a defi-
nite role, but it is not as obvious as it is in a lecture
class. An experienced professor can quickly tell when
the students are getting bogged down on relatively
unimportant points; he can look at their chapters
and evaluate how a student who did not know the
material would react to it; he can see when the
students are developing reasonable knowledge struc-
tures and including most of the important material;
he can understand the text material, the examples,
and the homework problems and thus can evaluate
them even though he may not have read many of the
cited papers. In my opinion, it would be extremely
difficult to teach a class like this if the professor is
not an expert in the general topic.

THE STUDENT REACTIONS
The students all became very involved in this
course. They invested too much time on their
projects and had to work to keep the chapters
manageable. They thought that learning how to
do library searches was extremely useful and ex-
pressed the wish that they had learned how to do
this sooner. The following quote from Quarderer is
appropriate: "Four to six weeks in the lab can save
you an hour in the library.""[5
The students also thought that writing was useful,
but difficult. The difficulty involved in developing
good homework and example problems surprised
them. They found that writing a problem requires
better understanding than they could get from merely
reviewing the literature.
The students chose to write on Reactive Distilla-
tion and on Supercritical Fluid Extraction of Solids.
The first topic was almost ideal for this course. There
are enough references, but not so many as to over-
whelm the students. The material is not covered in
any depth in existing distillation texts, but is of
considerable industrial and academic interest. As-
pen Plus was used to develop example and home-
work problems and solutions.


The second topic was much more of a challenge,
mainly because of the huge number of references
(almost 19,000 were identified in the computer
search). This team had more difficulty in limiting
their chapter and in finding appropriate data for
examples and homework. They eventually decided
to focus on coffee decaffeination since it is the most
important industrial process and since there is more
information available on this process than on others.
They also wrote their own computer programs to
solve some of the examples and homework problems.
The reports were excellent as student papers and
would be acceptable, but not outstanding, as profes-
sional contributions. After one semester of studying
a topic, the students' knowledge base remained thin.
This was evident from their inability to critically
evaluate the work they were reporting on and from
their difficulty in writing good examples.
Student evaluations showed that half the
students agreed, and half strongly agreed, with
the statement that this was among the best courses
they had ever taken. Three of the students strongly
agreed, while one student was undecided, about the
statement that this instructor was among the best
teachers they had known. Since the professor did
not teach in the traditional sense, it is difficult to
interpret this result.
In general, the students thought the course was
intellectually fulfilling, that it contributed signifi-
cantly to their professional growth, and it provided a
good background for further study. They also put a
lot of effort into the class, were satisfied with their
accomplishments, and thought they had done well.
POSSIBLE COURSE MODIFICATIONS
By putting the students into groups of three, one
professor could handle up to twelve students. Group
meetings with the instructor every other class
meeting (that is, three times every two weeks) for
twenty-five minutes should be sufficient. With three
people in the group, students would still receive
significant individual attention. The effort required
to grade projects would double with four groups, but
grading only occurred twice during the semester.
The basic format should be retained with this num-
ber of students, including the checkpoints used to
minimize procrastination.
The students suggested requiring, or strongly en-
couraging, all new students to take this course dur-
ing their second semester. At this point in their
studies, new students have chosen a thesis project
and a major professor, so the textbook chapters could
be written on their thesis topics. Because of the
Chemical Engineering Education









broad range of topics involved, however, one profes-
sor could not teach the course without assistance.
The professor in charge could serve as a course coor-
dinator and could present the lectures, while other
professors would be involved in working with the
groups containing their new students. This proce-
dure would structure the process of learning how to
do library research, it would give the students a
chance to get a good start on understanding the
literature in their research area, and it would pro-
vide an early opportunity to improve communication
skills. During the process of developing their chap-
ters (particularly the examples and the homework)
most students will obtain a good picture of what
needs to be done in a given area, and the net effect
should be a faster start in research.
The difficulties of a team-taught course include
ensuring uniformity in the group meetings and in
grading. In addition, students who have not had a
graduate-level course in the general area of their
topic may have extreme difficulty reading the litera-
ture. They would either have to delay taking the
course or get extra help from their major professor.

COMMENTS
This course was unusual as a graduate course in
chemical engineering since the focus was on learn-
ing the processes of doing library research and writ-
ing a book chapter instead of on learning specific
knowledge. Since the students found their own
sources and charted their own paths, there was very
little structure for the technical material. But there
was quite a bit of structure and support for the
processes of doing library research and in develop-
ing a book chapter. This structure (deadlines, lec-
tures, and continual meetings) is probably necessary
to prevent procrastination.
Obviously, the students learned technical content
in addition to the process. The content learned was
in one narrow area, but with significant depth. A
normal lecture-homework-test course could probably
cover at least twice as much content, but it is doubt-
ful that the students would learn the material as
well, and they certainly would not learn how-to-
learn as well as they did in this course.
The original course plan was to ask students to
write critical reviews. Discussions in the graduate
committee convinced me, however, that this was
inappropriate since the students did not have
enough expertise to critically evaluate papers. So
the course plan was changed to have the students
write textbook chapters. In addition, the students
would have to develop example and homework


problems. Developing problems stretched the stu-
dents and forced them to learn material they might
otherwise only half learn. Including problems also
forced the students to write computer programs or to
use simulation programs. Overall, asking the stu-
dents to write a textbook chapter is an excellent
pedagogical approach.
The students had to work in teams, and this, of
course, follows normal industrial practice. In addi-
tion, the projects were too big to be done by a single
student within a reasonable period of time, so the
team members encouraged each other when the task
appeared overwhelming (as it did midway through
the semester). The members of one team worked
very well together. Their chapter meshed well and it
was not obvious which student wrote which section.
The other team, however, needed significant encour-
agement to work together. For much of the semes-
ter, the group meetings with the professor served as
this team's only point of contact. Their chapter
showed a seam where the two parts were glued
together. Of course, the presence of seams in multi-
author textbooks is not unusual.

SUMMARY
In this seminar course, the students became in-
volved in the processes of doing a literature search
and in writing a textbook chapter. As a result of
learning these processes, in the future they will be
able to learn more efficiently on their own. The pro-
fessor functioned as a consultant rather than a lec-
turer, and the net result was that most of the effort
and learning was done by the students.

ACKNOWLEDGMENT
The assistance of the engineering librarian, Ms.
Jean Poland, and the technical communication ex-
pert, Dr. Frank Oreovicz, in teaching this course is
gratefully acknowledged. Discussions with Profes-
sor Nick Delgass were crucial to the course design.
The enthusiasm and participation of the students
made the course a success.

REFERENCES
1. Wankat, P.C., and F.S. Oreovicz, Teaching Engineering,
McGraw-Hill, New York, Chaps. 1 and 15 (1993)
2. Rogers, C.R., Freedom To Learn, Charles E. Merrill, Colum-
bus, OH, Chap. 7 (1969)
3. Eble, IKE., The Craft of Teaching, 2nd ed., Jossey-Bass, San
Francisco, CA, p. 102 (1988)
4. Elbow, P., Embracing Contraries: Explorations in Learning
and Teaching, Oxford University Press, New York, Chaps. 2
and 3 (1986)
5. Felder, R.M. "Random Thoughts," Chem. Eng. Ed., 27(2)
(1993) 0


Fall 1993











THE DU PONT

TEACHING FELLOWSHIP PROGRAM

1991 Teaching Experiences


Editorial Note:
The DuPont Teaching Fellows Program was initiated in 1990 to complement the
objectives of the DuPont Fellowship Program in chemical, mechanical, and electrical
engineering. The Teaching Fellows Program was initiated to encourage high-quality
students to obtain PhD degrees and enter academia..
There were six DuPont Teaching Fellowships awarded in chemical engineering in
1991: Linda J. Broadbelt, Gregory S. Fisher, Walter M. Hart, Michael L. Luyben,
Steven A. McCluney, and Ronald D. Shaver. DuPont teaching fellows were required to
have responsibility for one undergraduate course. The following article describes the
teaching experience of five of these students, written by the students themselves.
We thank Professor TW Fraser Russell, who provided the inspiration, advice, and
compilation of the material for this presentation.


NAME: Steven A. McCluney
DEPARTMENT: Chemical Engineering UNIVERSITY: Texas A&M University
COURSE TAUGHT: "Chemical Engineering Reactor Design/Kinetics" NUMBER OF STUDENTS: 24
TEXT USED: Fundamentals of Chemical Reaction Engineering, by Charles D. Holland
and Rayford G. Anthony; Prentice Hall Book Company, Publisher
FACULTY MENTOR: Dr. Rayford Anthony
NUMBER OF YEARS OF GRADUATE EDUCATION COMPLETED: 6
THESIS TOPIC: Modeling AC Impedance Behavior of Coated Electrodes
THESIS ADVISOR: Dr. Ralph White


faculty mentor several times during the semester,
but, in general, I was solely responsible for prepar-
ing each lecture, and my lectures were not moni-
tored. Since my mentor coauthored the course text-
book, I had a clear guideline of the material I was
expected to cover. I was also given examples of ex-
ams and course notes from previous semesters. On
an average, I spent one to two hours preparing each
lecture, depending on its content. I also worked each
homework assignment so I would be able to explain
the concepts as clearly as possible to the students.
In summary, teaching an undergraduate course
was a rewarding experience. I now have a greater
respect for professors who work hard to be good
teachers in addition to researchers. I hope to eventu-
ally have a career which will allow me to teach
college-level courses--either as a college professor or
as a guest instructor from industry. O
Chemical Engineering Education


Teaching an undergraduate course was an ex-
tremely valuable and enjoyable experience for me. I
feel that in many ways I learned as much as I taught,
and I was surprised to find that I still remembered a
lot of the material that I had not used for several
years. I also discovered that teaching a subject is the
best way to become thoroughly familiar with it, both
through preparing lessons and through trying to
answer students' often in-depth questions. Finally,
I learned that teaching involves dedication and
patience. In order to teach well, one must be willing
to put in the necessary time to carefully prepare
a lesson and to try to anticipate any questions
which may be raised. One must also be willing
to take the time to explain a concept clearly and at
the students' level.
I was given almost complete freedom in teaching
the course; I discussed my teaching plans with my









NAME: Ronald D. Shaver
DEPARTMENT: Chemical Engineering UNIVERSITY: Oklahoma State University
COURSE TAUGHT: "Introduction to Chemical Process Engineering" NUMBER OF STUDENTS: 24
TEXT USED: Elementary Principles of Chemical Processes, 2nd ed.;
by Richard M. Felder and Ronald W. Rousseau; John Wiley & Sons, Inc., Publisher
FACULTY MENTOR: Dr. Ruth Erbar
NUMBER OF YEARS OF GRADUATE EDUCATION COMPLETED: 3.5
THESIS TOPIC: Equation of State Development for Equilibrium Predictions
THESIS ADVISOR: Dr. KA.M. Gasem


Having the opportunity to serve as a 1991-92
DuPont Teaching Fellow gave me some valuable
insights into teaching at the college level. The course
I taught was the sophomore-level "Introduction to
Chemical Process Engineering."
Traditionally, chemical engineering attracts only
the best students, and this course represents the
first challenging course that most of them take. This
teaching experience taught me how to properly orga-
nize a fast-paced engineering course and how to
recognize when students properly understand the
necessary concepts, as well as when they do not.
Daily preparation for the course required much
more time than I had originally thought it would. I
found that not only must the lectures be presented
in an organized, logical manner, but also that every
possible question that may be asked by someone
being exposed to the material for the first time must
be anticipated.
Throughout the semester I had the privilege of
being able to consult the late Dr. Ruth Erbar about
details of course organization and how to structure
some special projects to ensure that the students


obtained the maximum benefit and preparation for
later courses. We often talked about the students'
reactions to various situations; for example, we both
felt that in order for students to best learn the cov-
ered topics, they should be pushed to the limit of
their abilities. Although many students were ini-
tially intimidated by exams that challenged even the
best students in the class, several of them com-
mented at the end of the course that the material
they best understood was the material they initially
had the most trouble comprehending.
Throughout the course I maintained an open-door
policy and encouraged the students to come discuss
any problems they might be having with the course
material. There is a wonderful satisfaction in seeing
students' eyes light up when they first truly under-
stand a concept that they've been struggling with,
and even more joy in seeing students become excited
about a topic and excelling beyond that which is
required or expected of them.
Being a DuPont Teaching Fellow was a wonderful
experience, and I fully intend to pursue university
teaching at some future point in my career. 0


NAME: Greg Fisher
DEPARTMENT: Chemical Engineering UNIVERSITY: Michigan State University
COURSE TAUGHT:" Material and Energy Balances" NUMBER OF STUDENTS: 52
TEXT USED: Elementary Principles of Chemical Processes, 2nd edition; by Richard M. Felder
and Ronald W. Rousseau; John Wiley & Sons, Inc., Publisher
FACULTY MENTOR: Dr. Alec Scranton
NUMBER OF YEARS OF GRADUATE EDUCATION COMPLETED: 5
THESIS TOPIC: The Effect of Interphase Composition on Adhesion in Polyphenylene Sulfide/Carbon Fiber Composites
THESIS ADVISOR: Dr. Lawrence T. Drzal


The time I spent as a DuPont Teaching Fellow was
time well spent. The experience was overwhelm-
ingly positive, both as an introduction to college-
level lecturing and in organizing familiar material
into a package that beginners could understand.
I actually received instruction from my faculty men-
tor the term before I taught the course when I served


as his teaching assistant. This enabled me to be
completely on my own during the time I taught the
course, heightening the experience even more for
me. Teaching the course required approximately
ten to fifteen hours a week. The help of a teaching
assistant and two homework graders allowed me to
concentrate on writing and giving lectures, on writ-


Fall 1993









ing exams, and on assigning grades.
It was disappointing to discover that some stu-
dents expected a 3.0/4.0 grade "just for showing up,"
and that often the students who needed extra help
the most were the very ones to request it too late. On
the other hand, I was delighted to find that many
students were eager to learn the material, that some
of the students who struggled in the beginning
worked hard and did well in the end, and that estab-
lishing a good rapport with most of the students was
relatively easy.
The most difficult part of teaching the course was
designing a fair grading scale, and keeping as many


of the students as possible involved in lectures pro-
vided another challenge. Working with the students
to help them learn was the most rewarding aspect of
teaching the course.
I enjoyed the teaching experience a great deal and
would like to pursue a career in teaching after gain-
ing some industrial experience. Since chemical
engineering is such an applied field, I believe stu-
dents appreciate instructors who have actually
worked in industry.
I believe the DuPont Teaching Fellows program is
a worthwhile program and truly appreciate the op-
portunity I had to participate in it. O


NAME: Michael Luyben
DEPARTMENT: Chemical Engineering UNIVERSITY: Princeton University
COURSE TAUGHT: "Introduction to Chemical Engineering" NUMBER OF STUDENTS: 45
TEXT USED: Elementary Principles of Chemical Processes, 2nd ed., by Richard M. Felder and Ronald W. Rousseau; John
Wiley & Sons, Inc., Publisher
FACULTY MENTOR: Dr. S. Sundaresan
NUMBER OF YEARS OF GRADUATE EDUCATION COMPLETED: 4
THESIS TOPIC: A Multi-Objective Optimization Approach for Analyzing the Interaction of Design and Control
THESIS ADVISOR: Dr. C.A. Floudas


My service as a DuPont Teaching Fellow in 1991
at Princeton University provided a valuable oppor-
tunity for me to learn about teaching. The course I
taught, "Introduction to Chemical Engineering," con-
tained material with some approaches, terminology,
and jargon which were unfamiliar to the first- and
second-year undergraduates, and it was important
to remember and consider this when I was planning
classes and answering questions.
The course challenged me to communicate ideas as
clearly and enthusiastically as possible, since suc-
cess in this respect usually engaged the students'
intellectual curiosity and challenged them to think
clearly and independently. Teaching involves not so
much an imparting of information as it does training
students' minds to think critically and teaching
them to approach problems both systematically and
creatively. Such a goal demands a lot of practical
experience, and this opportunity to teach gave me
that experience.
The course culminated in a case-study project which
required the students to work in groups and to tie
together all of the material they had learned in the
course. This gave them a better perspective on the
type of analysis used in chemical engineering and
demanded more sophistication in applying general
principles to a problem that was larger than the
weekly homework assignments to which they were


accustomed. The students seemed to think this was
a helpful survey of the course material and it proved
to be a valuable educational tool.
I cannot make generalizations about how students
learn since each of them is an individual. Some
of them understand the subject quickly just by read-
ing the book, while some learn from doing the
homework assignments and still others have to
come by the office and ask questions to clarify the
material. The real teaching challenge lies in finding
an appropriate balance of difficulty in the course
material. Many students have a lot of pressure on
them with their coursework load, and it compounds
the problem when universities place so much em-
phasis on research rather than on teaching. The
DuPont Teaching Fellows Program contributes sig-
nificantly to support teaching ability and works to
counteract this trend.
The course required three to four hours a week of
lecture preparation; I also spent quite a bit of addi-
tional time with the individual students, answering
questions. The faculty mentor for the course occa-
sionally attended class while I taught, and at least
once a week we discussed teaching, course material,
and overall plans.
I would like to again thank DuPont for providing
this opportunity for me to gain undergraduate teach-
ing experience. I found that I greatly enjoy teaching
Chemical Engineering Education









and want to pursue it as a career. I feel it will be a
challenging and rewarding occupation. DuPont has
generously provided the support and encouragement


for me and for other graduate students in chemical
engineering to consider careers in teaching through
their Teaching Fellows Program. 0


NAME: Linda J. Broadbelt
DEPARTMENT: Chemical Engineering UNIVERSITY: University of Delaware
COURSE TAUGHT: "Chemical Engineering Kinetics" NUMBER OF STUDENTS: 20
TEXT USED: Chemical Reaction Engineering, 2nd ed., by Octave Levenspiel; John Wiley & Sons, Publisher
FACULTY MENTOR: Dr. TW Fraser Russell
NUMBER OF YEARS OF GRADUATE EDUCATION COMPLETED: 3
THESIS TOPIC: Thermal Degradation of High Performance Polymers and Integration of Structure,
Reactivity, and Property
THESIS ADVISOR: Dr. Michael T. Klein


The experience I had as a DuPont Teaching Fellow
was extremely positive and reinforced my desire to
pursue a teaching career. It also forced me to in-
crease my knowledge of reaction engineering and
kinetics. Most importantly, it revealed to me that it
is quite different to be up in front of the class teach-
ing a course than it is to sit at a desk and listen!
Teaching style is directly related to an individual's
personality. I found I was most comfortable when I
did not try to adopt someone else's style and just
acted naturally. I learned a great deal, however,
from watching and listening to Drs. Russell and
Orbey when they taught.
I found that in-class problem sessions were invalu-
able. The problems generated excellent class discus-
sion and dramatically reinforced learning while at
the same time providing ample opportunity for stu-
dent-teacher interaction. It also prevented a mo-
notonous, long-winded monologue at the blackboard.
I had the benefit of sitting in Dr. Orbey's lecture in
advance of mine. The course was taught in two 20-
student sections. This allowed me to improve my
own grasp of the material, and more importantly, to
assess the students' responses to the various facets
of the lecture. Dr. Russell sat in on most of my
lectures and gave me excellent feedback about my
style and the students' reactions. He was also an
invaluable resource during a lecture, providing
knowledge and insight from his years of experience.
Having such an active and interested mentor was
the most crucial element in making my teaching
experience so rewarding and successful.
I also received invaluable feedback from the stu-
dents. It was not hard to determine when a certain
approach was successful-the students were not
afraid to participate in discussions or to voice their
frustrations when they had them. They enjoyed the
in-class problems and felt they were beneficial to


learning the material. They also voiced appreciation
of any extra effort I expended, such as long office
hours, help sessions, etc., and took advantage of any
help I offered. I found that one of the most important
elements of establishing good rapport with the stu-
dents was knowing and calling them by name.
A more negative facet was that teaching reminded
me what it was like to be an undergraduate student,
when the end goal was not necessarily the learning
or the acquired knowledge, but the grade received.
Students frustratingly begged for additional points,
asked for extensions on their homework, com-
plained about unfair or difficult exams, or lamented
the poor choice of a textbook. I had to remind myself
that only hard work earns a high grade and that
learning is always the ultimate goal. I found assign-
ing grades at the end of the course to be the most
difficult part of teaching. It was hard not to let an
element of subjectivity to creep into the grade of a
student with whom I had significant personal inter-
action. While there is room in the grading system for
effort expended and class participation to be consid-
ered along with reliance on numerical analysis of
exams and homework, I tried not to let personal
feelings cloud my judgment.
The time commitment involved was immense and
involved preparing lectures, exams, and interesting
homework in addition to student-teacher interaction
outside of class. I had the benefit of two excellent
mentors who made all the tasks much easier and
less time consuming. I estimate that we spent two or
three hours a week discussing lecture preparation,
class material, exam preparation and grading, and
teaching style.
I feel very fortunate to have been a part of the
DuPont Teaching Fellows program. My mentors were
exceptional and contributed greatly to making the
experience so rewarding. 0


a


Fal19 1


215


Fall 1993


n














The



0Wjzv;271tY


DEPARTMENT

OF

CHEMICAL

ENGINEERING


GRADUATE PROGRAM


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.
The deadlinefor assistantship applications is February 15th.

FACULTY RESEARCH INTERESTS


G. A. ATWOOD1
G. G. CHASE
H. M. CHEUNG
S. C. CHUANG
J.R. ELLIOTT
L. G. FOCHT
K. L. FULLERTON
M. A. GENCER2
H. L. GREENE'
L.K.JU
S. LEE
D. MAHAJAN2
J. W. MILLER2
H. C. QAMMAR
C. K. RIEW2
R. W. ROBERTS1
N.D. SYLVESTER
M. S. WILLIS


Digital Control, Mass Transfer, Multicomponent Adsorption
Multiphase Processes, Heat Transfer, Interfacial Phenomena
Colloids, Light Scattering Techniques
Catalysis, Reaction Engineering, Combustion
Thermodynamics, Material Properties
Fixed Bed Adsorption, Process Design
Fuel Technology, Process Engineering, Environmental Engineering
Biochemical Engineering, Environmental Biotechnology
Oxidative Catalysis, Reactor Design, Mixing
Biochemical Engineering, Enzyme and Fermentation Technology
Fuel and Chemical Process Engineering, Reactive Polymers, Waste Clean-Up
Homogeneous Catalysis, Reaction Kinetics
Polymerization Reaction Engineering
Hazardous Waste Treatment, Nonlinear Dynamics
Reactive Polymer Processing
Plastics Processing, Polymer Films, System Design
Environmental Engineering, Flow Phenomena
Multiphase Transport Theory, Filtration, Interfacial Phenomena


'Professor Emeritus 2 Adjunct Faculty Member
Cooperative Graduate Education Program is also available.
For Additional Information, Write *


216


Chemical Engineering Education


FIAT LUX
o1870









CHEMICAL ENGINEERING

PROGRAMS AT

THE UNIVERSITY OF

ALABAMA


The University of Alabama, located in the
sunny South, offers excellent programs lead-
ing to M.S. and Ph.D. degrees in Chemical
Engineering.
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).

FACULTY
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. J. 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)

RESEARCH INTERESTS
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.
Fall 1993










THE UNIVERSITY OF ARIZONA
STUCSON, AZ

The Chemical and Environmental Engineering Department at the University of Arizona offers a
wide range of research opportunities in all major areas of chemical engineering and environmen-
tal engineering, and graduate courses are offered in most of the research areas listed below. The
department offers a fully accredited undergraduate degree as well as MS and PhD graduate
degrees. Strong interdisciplinary programs exist in bioprocessing and bioseparations,
microcontamination in electronics manufacture, and environmental process modification. Finan-
cial support is available through fellowships, government and industrial grants and contracts,
teaching and research assistantships.

THE FACULTY AND THEIR RESEARCH INTERESTS


ROBERT ARNOLD, Associate Professor (Caltech)
Microbiological Hazardous Waste Treatment, Metals Speciation and
Toxicity
JAMES BAYGENTS, Assistant Professor (Princeton)
Fluid Mechanics, Transport and Colloidal Phenomena, Bioseparations,
Electrokinetics
MILAN BIER, Professor (Fordham)
Protein Separation, Electrophoresis, Membrane Transport
CURTIS W. BRYANT, Associate Professor (Clemson)
Biological Wastewater Treatment, Industrial Waste Treatment
WILLIAM P. COSART, Associate Professor (Oregon State)
Heat Transfer in Biological Systems, Blood Processing
EDWARD FREEH, Adjunct Professor (Ohio State)
Process Control, Computer Applications
JOSEPH GROSS, Professor Emeritus (Purdue)
Boundary Layer Theory, Pharmacokinetics, Microcirculation, Biorheology
ROBERTO GUZMAN, Assistant Professor (North Carolina State)
Protein Separation, Affinity Methods
BRUCE E. LOGAN, Associate Professor (Berkeley)
Bioremediation, Biological Wastewater Treatment, Fixed Film Bioreactors



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

For further information, write to

Chairman,
Graduate Study Committee
Department of
Chemical and Environmental 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.


KIMBERLY OGDEN, Assistant Professor (Colorado)
Bioreactors, Bioremediation, Organics Removal from Soils
THOMAS W. PETERSON, Professor and Head (CalTech)
Aerosols, Hazardous Waste Incineration, Microcontamination
ALAN D. RANDOLPH, Professor (Iowa State)
Crystallization Processes, Nucleation, Particulate Processes
THOMAS R. REHM, Professor (Washington)
Mass Transfer, Process Instrumentation, Computer Aided Design
FARHANG SHADMAN, Professor (Berkeley)
Reaction Engineering, Kinetics, Catalysis, Reactive Membranes,
Microcontamination

RAYMOND A. SIERKA, Professor (Oklahoma)
Adsorption, Oxidation, Membranes, Solar Catalyzed Detox Reactions
JOST 0. L. WENDT, Professor (Johns Hopkins)
Combustion-Generated Air Pollution, Incineration, Waste Management
DON H. WHITE, Professor Emeritus (Iowa State)
Polymers, Microbial and Enzymatic Processes
DAVID WOLF, Visiting Professor (Technion)
Fermentation, Mixing, Energy, Biomass Conversion


Chemical Engineering Education












ARIZONA STATE UNIVERSITY

CHEMICAL, BIO, AND MATERIALS ENGINEERING


Sa a
r aO CHEMICAL SC,,40


L aRTIFICIAL

B10 *SE


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Graduate Research in a High Technology Environment


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, Semiconductor 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 Systems
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
Zwiebel, Imre, Ph.D., Yale Adsorption
of Macromolecules, Biochemical
Separations


Bioengineering
Dorson, William J., Ph.D., U. of
Cincinnati Physicochemical
Phenomena, Transport Processes
Guilbeau, Eric J., Ph.D., Louisiana Tech *
Biosensors, Physiological Systems,
Biomaterials
Kipke, Daryl R., Ph.D., University of
Michigan Computation Neuroscience *
Machine Vision, Speech Recognition,
Robotics Neural Networks
Pizziconi, Vincent B., Ph.D. Arizona State
Artificial Organs, Biomaterials,
Bioseparations
Sweeney, James D., Ph.D., Case-Western
Reserve Rehab Engineering, Applied
Neural Control
Towe, Bruce C., Ph.D., Penn State *
Bioelectric Phenomena, Biosensors,
Biomedical Imaging
Yamaguchi, Gary T., Ph.D., Stanford *
Biomechanics, Rehab Engineering,
Computer-Aided Surgery


Materials Science & Engineering
Alford, Terry L., Ph.D., Cornell U. Elec-
tronic Materials Physical Metallurgy *
Electronic Thin Films Surface/Thin Film
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
Krause, Stephen L., Ph.D., U. of Michigan
Ordered Polymers, Electronic Materials,
Electron X-ray Diffraction, Electron
Microscopy
Mayer, James, Ph.D., Purdue *Thin Film
Processing Ion Bean Modification of
Materials
Stanley, James T., Ph.D., U. of Illinois *
Phase Transformations, Corrosion


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.

Fall 1993 21









BRIGHAM YOUNG UNIVERSITY

T H E W O R L D I S O U R C A M P U S


GRADUATE S

in










Biomedical Engineering

Chemical Propulsion

Coal Combustion & Gasification

Computer Simulation

Electrochemistry

Thermodynamics

Fluid Mechanics


STUDIES IN CHEMICAL

the beautiful Rocky Mountains of


ENGINEERING

Utah










Kinetics & Catalysis

Mathematical Modeling

Materials

Transport Phenomena

Molecular Dynamics

Process Design

Process Control


For additional information write to:
Graduate Coordinator
Department of Chemical Engineering, 350 CB
Brigham Young University
Provo. Utah 84602
Tel: (801) 378-2586


Asa7


--.- '-- -a7









U DEPARTMENT OF CHEMICAL AND

M N PETROLEUM ENGINEERING
TM
THE The Department offers graduate programs leading to the M.Sc. and
UNIVERSITY Ph.D. degrees in Chemical Engineering (full-time) and the M.Eng.
OF CALGARY degree in Chemical Engineering or Petroleum Reservoir Engineering
(part-time) in the following areas:


FACULTY
R. G. Moore, Head (Alberta)
A. Badakhshan (Birmingham, U.K.)
L. A. Behie (Western Ontario)
J. D. M. Belgrave (Calgary)
F. Berruti (Waterloo)
P. R. Bishnoi (Alberta)
R. M. Butler (Imperial College, U.K)
A. Chakma (UBC)
R. A. Heidemann (Washington U.)
A. A. Jeje (MIT)
N. Kalogerakis (Toronto)
A. K. Mehrotra (Calgary)
E. Rhodes (Manchester, U.K)
P. M. Sigmund (Texas)
J. Stanislav (Prague)
W. Y. Svrcek (Alberta)
E. L. Tollefson (Toronto)
M. A. Trebble (Calgary)


Biochemical Engineering
& Biotechnology
Biomedical Engineering
Environmental Engineering
Modeling, Simulation & Control
Petroleum Recovery
& Reservoir Engineering
Process Development
Reaction Engineering/Kinetics
Thermodynamics
Transport Phenomena

Fellowships and Research Assistantships are available to all qualified applicants.

For Additional Information Write *
Dr. A. K. Mehrotra Chair, Graduate Studies Committee
Department of Chemical and Petroleum Engineering
The University of Calgary Calgary, Alberta, Canada T2N 1N4


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.
Fall 1993 221










THE UNIVERSITY OF CALIFORNIA AT


6 BERKELEY...


RESEARCH INTERESTS

BIOCHEMICAL ENGINEERING
ELECTROCHEMICAL ENGINEERING
ELECTRONIC MATERIALS PROCESSING
ENERGY UTILIZATION
FLUID MECHANICS
KINETICS AND CATALYSIS
POLYMER SCIENCE AND TECHNOLOGY
PROCESS DESIGN AND DEVELOPMENT
SEPARATION PROCESSES
SURFACE AND COLLOID SCIENCE
THERMODYNAMICS


... 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 cul-
tural offerings of the San Francisco Bay Area
and the recreational activities of California's
northern coast and mountains.


FACULTY

ALEXIS T. BELL
HARVEY W. BLANCH
ELTON J. CAIRNS
ARUP K. CHAKRABORTY
DOUGLAS S. CLARK
MORTON M. DENN (CHAIRMAN)
ALAN S. FOSS
SIMON L. GOREN
DAVID B. GRAVES
ENRIQUE IGLESIA
JAY D. KEASLING
C. JUDSON KING
SCOTT LYNN
ROYA MABOUDIAN
SUSAN J. MULLER
JOHN S. NEWMAN
JOHN M. PRAUSNITZ
CLAYTON J. RADKE
JEFFREY A. REIMER
DAVID S. SOANE
DOROS N. THEODOROU


PLEASE WRITE: DEPARTMENT OF CHEMICAL ENGINEERING
UNIVERSITY OF CALIFORNIA
BERKELEY, CALIFORNIA 94720-9989
Chemical Engineering Education








UNIVERSITY OF CALIFORNIA


RVI


NE


Graduate Studies in

Chemical and Biochemical Engineering

for
Chemical Engineering, Engineering, and Science Majors


PROGRAM

Offers degrees at the M.S. and Ph.D. levels. Research in
frontier areas in chemical engineering, including biochemi-
cal engineering, biotechnology and materials science and
engineering. Strong molecular biology, biochemistry, mi-
crobiology, and other engineering and science research
groups on campus.

LOCATION

The 1,510-acre UC Irvine campus is in Orange County,
five miles from the Pacific Ocean and 40 miles south of Los
Angeles. Irvine is one of the nation's fastest growing resi-
dential, industrial, and business areas. Nearby beaches,
mountain and desert area recreational activities, and local
cultural activities make Irvine a pleasant city in which to
live and study.

FACULTY

Nancy A. Da Silva (California Institute of Technology)
G. Wesley Hatfield (Purdue University)
Juan Hong (Purdue University)
James T. Kellis, Jr. (University of California, Irvine)
Henry C. Lim (Northwestern University)
Martha L. Mecartney (Stanford University)
Betty H. Olson (University of California, Berkeley)
Frank G. Shi (California Institute of Technology)
Thomas K. Wood (North Carolina State University)


RESEARCH
AREAS

Bioreactor Engineering
Bioremediation
Environmental Chemistry
Environmental Engineering
Interfacial Engineering
Materials Processing
Metabolic Engineering
Microstructure of Materials
Optimization
Process Control
Protein Engineering
Recombinant Cell Technology
Separation Processes
Sol-Gel Processing
Water Pollution Control

For further information
and application forms,
contact

Biochemical Engineering Program
School of Engineering
University of California
Irvine, CA 92717-2575


Fall 1993








CHEMICAL ENGINEERING AT


UIA


RESEARCH
AREAS
* Thermodynamics and
Cryogenics
* Process Design, Dynamics,
and Control
* Polymer Processing and
Transport Phenomena
* Kinetics, Combustion, and
Catalysis
* Surface and Interface Engi-
neering
* Electrochemistry and
Corrosion
* Biochemical Engineering
* Aerosol Science and
Technology
* Air Pollution Control and
Environmental Engineering


FACULTY
D. T. Allen
Y. Cohen
T. H. K. Frederking
S. K. Friedlander
R. F. Hicks
E. L. Knuth
(Prof Emeritus)
V. Manousiouthakis
H. G. Monbouquette
K. Nobe
L. B. Robinson
(Prof Emeritus)
S. M. Senkan
O. Smith
W. D. Van Vorst
(Prof. Emeritus)
V. L. Vilker
A. R. Wazzan


PROGRAMS


UCLA's Chemical Engineering Department of-
fers a program of teaching and research linking
fundamental engineering science and industrial prac-
tice. Our Department has strong graduate research
programs in environmental chemical engineering,
biotechnology, and materials processing. With the
support of the Parsons Foundation and EPA, we are
pioneering the development of methods for the de-
sign of clean chemical technologies, both in gradu-
ate research and engineering education.


Fellowships are available for outstanding ap-
plicants in both M.S. and Ph.D. degree programs.
A fellowship includes a waiver of tuition and fees
plus a stipend.
Located five miles from the Pacific Coast,
UCLA's attractive 417-acre campus extends from
Bel Air to Westwood Village. Students have ac-
cess to the highly regarded science programs and
to a variety of experiences in theatre, music, art,
and sports on campus.


CONTACT





224 Chemical Engineering Education











UNIVERSITY OF CALIFORNIA



SANTA BARBARA


* FACULTY AND RESEARCH INTERESTS *


L. GARY LEAL Ph.D. (Stanford) (Chairman) Fluid Mechanics; Suspension and Polymer Physics.
ERAY S. AYDIL Ph.D. (University of Houston) Microelectronics Materials Processing
SANJOY BANERJEE Ph.D. (Waterloo) Two-Phase Flow, Chemical & Nuclear Safety, Computational Fluid Dynamics,
Turbulence.
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.
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.) (Vice Chairman) Mechanics of Materials, Radiation Damage.
DIMITRIOS MAROUDAS Ph.D. (M.I.T.) Structure and Dynamics in Heterogeneous Materials.
ERIC McFARLAND Ph.D. (M.I.T.) M.D. (Harvard) Biomedical Engineering, NMR and Neutron Imaging, Transport
Phenomena in Complex Liquids, Radiation Interactions.
DUNCAN A. MELLICHAMP Ph.D. (Purdue) Computer Control, Process Dynamics, Real-Time Computing.
G. ROBERT ODETTE Ph.D. (M.I.T.) High Performance Structural Materials
DALE S. PEARSON Ph.D. (Northwestern) Rheological and Optical Properties of Polymer Liquids and Colloidal
Dispersions.
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 ofGroningen, 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.


PROGRAMS
AND FINANCIAL SUPPORT

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


THE UNIVERSITY

One of the world's few seashore cam-
puses, UCSB is located on the Pa-
cific Coast 100 miles northwest of
Los Angeles. The student enrollment
is over 18,000. The metropolitan
Santa Barbara area has over
150,000 residents and is famous for
its mild, even climate.


For additional information
and applications,
write to

Chair
Graduate Admissions Committee
Department of Chemical and
Nuclear Engineering
University of California
Santa Barbara, CA 93106


Fall 1993







Chemical Engineering at the


yTuo CALIFORNIA


891 1z INSTITUTE
\OF

N OF


TECHNOLOGY

"At the Leading Edge"


Frances H. Arnold
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
Nicholas W. Tschoegl (Emeritus)
Zhen-Gang Wang


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


Fluid Mechanics
Materials Processing
Microelectronics Processing
Microstructured Fluids
Polymer Science
Process Control and Synthesis
Protein Engineering
Statistical Mechanics of Heterogeneous
Systems


For further information, write
Professor Mark E. Davis
Chemical Engineering 210-41 California Institute of Technology Pasadena, California 91125

Chemical Engineering Education


)h


Cm













Joh L. Anderson



Loen Blee *


Pa l DiSll



Mihe M. -oac Ufias goin on



Igai E. UGro ssmann -S


Uila S. 5 Ha mc
Oinnt M. Jacobson 5









Ayun S. S -.


*_m n 1 Ko


3ar J. Powers -




)eni C. S U -

Je nie L. Sinclair*



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6oer D. Tilton 0












Chemical Engineering in


the 21st Century?


Diamond crystals synthesized by graduate student C. Kovach.


For more information contact:

The Graduate Coordinator
Department of Chemical Engineering
Case Western Reserve University
Cleveland, Ohio 44106


Want to learn what the future holds for
chemical engineers?

Consider graduate study at


CASE

WESTERN

RESERVE

UNIVERSITY

Opportunities for Innovative Research in

Advanced Energy Conversion *
Chemical/Biological Sensors
Intelligent Control *
Micro- and Nano-Materials *
Novel Separations/Processing *


Faculty and Specializations


John C. Angus, Ph.D. 1960, University of Michigan
Diamond and diamond-like films, redox equilibria
Coleman B. Brosilow, Ph.D. 1962, Polytechnic Institute of
Brooklyn
Adaptive inferential control, multi-variable control,
coordination algorithms
Robert V. Edwards, Ph.D. 1968, Johns Hopkins University
Laser anemometry, mathematical modeling, 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, electro-
deposition AN


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 dynamics, light scattering, Langmuir-
Blodgett films, stochastic processes
Philip W. Morrison, Jr., Ph.D. 1987, University of California
(Berkeley)
Materials synthesis, semiconductor processing, in-situ diagnostics
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
Applied electrochemistry, electrochemical system simulation and
_optimization, electrode processes


CASE WESTERN RESERVE UNIVERSITY


Chemical Engineering Education









The

UNIVERSITY

OF

CINCINNATI


ILJL


Opportunities for

GRADUATE STUDY
in Chemical Engineering

M.S. and PhD Degrees
in Chemical Engineering

SFinancial Aid Available *


Faculty


The city of Cincinnati is the 23rd largest city in the United States, with a greater
metropolitan population of 1.7 million. The city offers numerous sites of architec-
tural and historical interest, as well as a full range of cultural attractions, such as
an outstanding art museum, botanical gardens, a world-famous zoo, theaters,
symphony, and opera. The city is also home to the Cincinnati Bengals and the
Cincinnati Reds. The business and industrial base of the city includes pharmaceu-
tics, chemicals, jet engines, autoworks, electronics, printing and publishing, insur-
ance, investment banking, and health care. A number of Fortune 500 companies
are located in the city.


Amy Ciric
Joel Fried
Stevin Gehrke
Rakesh Govind
David Greenberg
Daniel Hershey
Sun-Tak Hwang


Robert Jenkins
Yuen-Koh Kao
Soon-Jai Khang
Jerry Lin
Glenn Lipscomb
Neville Pinto
Sotiris Pratsinis


n 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.
0 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.
o Coal Research
New technology for coal combustion power plant, desulfuriza-
tion and denitritication.

0 Material Synthesis
Man ufacture of advanced ceramics, opticalfibers and pigments
by aerosol processes.
0 Membrane Separations
Membrane gas separations, membrane reactors, sensors and
probes, equilibrium shift, pervaporation, dynamic simulation of
membrane separators, membrane preparation and characteri-
zation for polymeric and inorganic materials.

a Polymers
Thermodynamics, thermal analysis and morphology of polymer blends, high-temperature polymers, hydrogels, polymer
processing.
a Process Synthesis
Computer-aided design, modeling and simulation of coal gasifiers, activated carbon columns, process unit operations,
prediction of reaction by-products.
For Admission Information *
Director, Graduate Studies
Department of Chemical Engineering, # 0171
University of Cincinnati
Cincinnati, Ohio 45221-0171
Fall 1993 229


I


EU.L LUUI I**







Graduate Study in

CHEMICAL ENGINEERING


AT CLARKSON

* CENTER FOR ADVANCED MATERIALS PROCESSING
* NASA CENTER FOR THE DEVELOPMENT OF
COMMERCIAL CRYSTAL GROWTH IN SPACE
INSTITUTE OF COLLOID AND SURFACE SCIENCE


For details, please write to:
Dean of the Graduate School
Clarkson University
Box 5625
Potsdam, New York 13699-5625


Clarkson University is a nondiscriminatory, equal opportunity, affirmative action educator and employer.
Chemical Engineering Education











Clemson University


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 break.
Like enjoying the
beautiful mountain
scenery. Or fishing,
swimming, sailing, and
water skiing in the
clean lakes. Or hiking
in the nearby Blue
Ridge Mountains. Or


in Chmia Engneein


driving to South Caro-
lina's famous beaches
for a weekend. Some-
thing that can really
relax you.
All this and a top-
notch Chemical
Engineering Depart-
ment, too.
With active research
and teaching in poly-
mer processing, com-
posite materials, pro-
cess automation, ther-
modynamics, catalysis,
and membrane applica-
tions what more do
you need?


I I
The University Photo Courtesy of Patrick Wright
The University
Clemson, the land-grant university of South Carolina, offers 72 undergraduate and 70 graduate fields of study
in its nine academic colleges. Present on-campus enrollment is about 17,000 students, one-third of whom are in the
College of Engineering. There are about 4,100 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 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 and a descriptive brochure, contact:
Graduate Coordinator, Department of Chemical Engineering
Clemson University Clemson, South Carolina 29634-0909 (803) 656-3055


CLEMSON
UNIVERSITY
College of Engineering


Fall 1993


231










UNIVERSITY OF COLORADO


BOULDER


Graduate students in the Department of Chemical Engineering may also participate in the popular,
interdisciplinary Biotechnology Training Program at the University of Colorado
and in the interdisciplinary NSF Industry/University Cooperative Research Center for Separations Using Thin Films.


FACULTY

CHRISTOPHER N. BOWMAN Assistant Professor
Ph.D., Purdue University, 1991
DAVID E. CLOUGH Professor
Ph.D., University of Colorado, 1975

ROBERT H. DAVIS Professor and Chair,
Co-Director of Colorado Institute for Research in Biotechnology W
Ph.D., Stanford University, 1983

JOHN L. FALCONER James and Catherine Patten Professor
Ph.D., Stanford University, 1974

YURIS O. FUENTES Assistant Professor
Ph.D., University of Wisconsin-Madison, 1990
R. IGOR GAMOW Associate Professor
Ph.D., University of Colorado, 1967

HOWARD J. M. HANLEY. Professor Adjoint
Ph.D., University of London, 1963
DHINAKAR S. KOMPALA Associate Professor
Ph.D., Purdue University, 1984
WILLIAM B. KRANTZ Professor and President's Teaching Scholar,
Co-Director of NSF I/UCRC Center for Separations Using Thin Films
Ph.D., University of California, Berkeley, 1968
RICHARD D. NOBLE Professor
Co-Director of NSF I/UCRC Center for Separations Using Thin Films
Ph.D., University of California, Davis, 1976
W. FRED RAMIREZ Professor
Ph.D., Tulane University, 1965

THEODORE W. RANDOLPH -Associate Professor
Ph.D., University of California, Berkeley, 1987
ROBERT L. SANI Professor
Director of Center for Low-gravity Fluid Mechanics and Transport Phenomena
Ph.D., University of Minnesota, 1963
EDITH M. SEVICK Assistant Professor
Ph.D., University of Massachusetts, 1989

KLAUS D. TIMMERHAUS Professor and President's Teaching Scholar
Ph.D., University of Illinois, 1951


RESEARCH INTERESTS
Biotechnology and Bioengineering
Bioreactor Design and Optimization
Mammalian Cell Cultures
Protein Folding and Purification
Chemical Environmental Engineering
Global Change
Pollution Remediation
Materials Science and Engineering
Catalysis and Surface Science
Colloidal Phenomena
Polymerization Reaction Engineering
Membrane Science
Chemically Specific Separations
Membrane Transport and Separations
Polymeric Membrane Morphology
Modeling and Control
Expert Systems
Process Control and Identification
Thermodynamics
Cryogenics
Statistical Mechanics
Supercritical Fluids
Transport Phenomena
Fluid Dunamics and Suspension Mechanics
Materials Processing in Low-G


PAUL W. TODD Research Professor
Ph.D., University of California, Berkeley, 1964

RONALD E. WEST Professor
Ph.D., University of Michigan, 1958


FOR INFORMATION AND APPLICATION, WRITE TO
Director, Graduate Admissions Committee Department of Chemical Engineering
University of Colorado, Boulder Boulder, Colorado 80309-0424
*FAX (303) 492-4341
Chemical Engineering Education













COLORADO OF

O

SCHOOL OF




MINE S 1874


THE FACULTY AND THEIR RESEARCH

R. M. BALDWIN, Professor and Head; Ph.D., Colorado School of Mines.
Mechanisms and kinetics of coal liquefaction, catalysis, oil shale process-
ing, fuels science.
A. L. BUNGE, Professor; Ph.D., University of California, Berkeley. Mem-
brane transport and separations, mass transfer in porous media, ion
exchange and adsorption chromatography, in place remediation of con-
taminated soils, percutaneous absorption.
J.R. DORGAN, Assistant Professor; Ph.D., University of California, Berke-
ley. Polymer science and engineering.
J. F. ELY, Professor; Ph.D., Indiana University. Molecular thermodynamics
and transport properties of fluids.
J. H. GARY, Professor Emeritus; Ph.D., University of Florida. Petroleum
refinery processing operations, heavy oil processing, thermal cracking,
visbreaking and solvent extraction.
J.O. GOLDEN, Professor; Ph.D., Iowa State University. Hazardous waste
processing, polymers, fluidization engineering
M.S. GRABOSKI, Research Professor; Ph.D., Pennsylvania State University.
Fuels Synthesis and evaluation, engine technology, alternate fuels
:-1, A A. J. KIDNAY, Professor and Graduate Dean; D.Sc., Colorado School of
Mines. Thermodynamic properties of gases and liquids, vapor-liquid equi-
s libria, cryogenic engineering.
J.T. McKINNON, Assistant Professor; Ph.D., Massachusetts Institute of Tech-
nology. High temperature gas phase chemical kinetics, combustion, haz-
ardous waste destruction.
R. L. MILLER, Associate Professor; Ph.D., Colorado School of Mines. Liq-
uefaction co-processing of coal and heavy oil, low severity coal liquefac-
tion, particulate removal with venturi scrubbers, interdisciplinary educa-
tional methods
M. S. SELIM, Professor; Ph.D., Iowa State University. Heat and mass
transfer with a moving boundary, sedimentation and diffusion of colloidal
suspensions, heat effects in gas absorption with chemical reaction, en-
trance region flow and heat transfer, gas hydrate dissociation modeling.
E. D. SLOAN, JR., Professor; Ph.D. Clemson University. Phase equilibrium
measurements of natural gas fluids and hydrates, thermal conductivity of
coal derived fluids, adsorption equilibria, education methods research.
J. D. WAY, Research Professor; Ph.D. University of Colorado. Novel separa-
tion processes, membrane science and technology, membrane reactors,
ceramic and metal membranes, biopolymer adsorbents for adsorption of
heavy metals.
V. F. YESAVAGE, Professor; Ph.D., University of Michigan. Vapor liquid
equilibrium and enthalpy of polar associating fluids, equations of state for
highly non-ideal systems, flow calorimetry.

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

Chemical Engineering and Petroleum Refining
Colorado School of Mines


Fall 1993









J university ol



nnecticul


Graduate Study in
Chemical Engineering

M.S. and Ph.D. Programs for Scientists and Engineers

FACULTY RESEARCH AREAS
Luke E.K. Achenie, Ph.D., Carnegie Mellon University
Modeling and Optimization, Neural Networks, Process Control
Thomas F. Anderson, Ph.D., University of California, Berkeley
Modeling of Separation Processes, Fluid-Phase Equilibria
James P. Bell, Sc.D., Massachusetts Institute of Technology
Structure-Property Relations in Polymers and Composites, Adhesion
Carroll 0. Bennett, Professor Emeritus, Ph.D., Yale University
Catalysis, Chemical Reaction Engineering
Douglas J. Cooper, Ph.D., University of Colorado
Process Control, Neural Networks, Fluidization Technology
Robert W. Coughlin, Ph.D., Cornell University
Biotechnology, Biochemical and Environmental Engineering, Catalysis,
Kinetics, Separations, Surface Science
Michael B. Cutlip, Ph.D., University of Colorado
Kinetics and Catalysis, Electrochemical Reaction Engineering, Numerical Mett
Anthony T. DiBenedetto, Ph.D., University of Wisconsin
Composite Materials, Mechanical Properties of Polymers
James M. Fenton, Ph.D., University of Illinois, Urbana-Champaign
Electrochemical and Environmental Engineering, Mass Transfer Processes,
Electronic Materials, Energy Systems
Suzanne (Schadel) Fenton, Ph.D., University of Illinois
Computational Fluid Dynamics, Turbulence, Two-Phase Flow
Robert J. Fisher, Ph.D., University of Delaware
Biochemical Engineering and Environmental Biotechnology
G. Michael Howard, Ph.D., University of Connecticut
Process Systems Analysis and Modeling, Process Safety, Engineering Educatic
Herbert E. Klei, Professor Emeritus, Ph.D., University of Connecticut
Biochemical Engineering, Environmental Engineering
Jeffrey T. Koberstein, Ph.D., University of Massachusetts
Polymer Blends/Compatibilization, Polymer Morphology,
Polymer Surface and Interfaces
Harold R. Kunz, Ph.D., Rensselaer Polytechnic Institute
Fuel Cells, Electrochemical Energy Systems
Montgomery T. Shaw, Ph.D., Princeton University
Polymer Rheology and Processing, Polymer-solution Thermodynamics
Richard M. Stephenson, Professor Emeritus, Ph.D., Cornell University
Mutual Solubility Measurements, Liquid-Liquid Equilibrium
Donald W. Sundstrom, Professor Emeritus, Ph.D. University of Michigan
Environmental Engineering, Hazardous Wastes, Biochemical Engineering
Robert A. Weiss, Ph.D., University of Massachusetts
Polymer Structure-Property Relationships, Ion-Containing and
Liquid Crystal Polymers, Polymer Blends

FOR MORE INFORMATION
Graduate Admissions, 191 Auditorium Road
University of Connecticut, Storrs, CT 06269-3222
Tel. (203) 486-4020









CHEMICAL ENGINEERING



CORNELL


UNIVERSITY


At Cornell University students have the flexibility to design
interdisciplinary research programs that draw upon the resources of
many excellent departments and NSF-sponsored interdisciplinary
centers such as the Biotechnology Center, the Cornell National
Supercomputing Center, the National Nanofabrication Facility, and
the Materials Science Center. Degrees granted include the Master of
Engineering, Master of Science, and Doctor of Philosophy. All MS
and PhD students are fully funded with attractive stipends and
tuition waivers. Situated in the scenic Finger Lakes region of New
York State, the Cornell campus is one of the most beautiful in the
ID 111111 country. Students enjoy sailing, skiing, fishing, hiking, bicycling,
Boating, wine-tasting and many more activities in this popular
vacation region.








Distinguished Faculty ...
A. Brad Anton Robert P. Merrill H
Paulette Clancy William L. Olbricht
Claude Cohen
A. Panagiotopoulos
T. Michael Duncan
Ferdinand Rodriguez ... With Research In
James R. Engstrom Biochemical Engineering Polymer Science
Keith E. Gubbins Michael L. Shuler Applied Mathematics Fluid Dynamics
Computer Simulation Rheology and Biorheology
Daniel A. Hammer Paul H. Steen Environmental Engineering Process Control
Kinetics and Catalysis Molecular Thermodynamics
Peter Harriott William B. Street Surface Science Statistical Mechanics
Donald L. Koch John A. Zollweg Heat and Mass Transfer Computer-Aided Design

For Further Information, Write:
Graduate Field Representative Cornell University Olin Hall of Chemical Engineering Ithaca, NY 14853-5201


Fall 1993








Chemical En gneerin at
The Faculty
Giovanni Astarita
Mark A. Barteau
Antony N. Beris
Kenneth B. Bischoff
Douglas J. Buttrey
Stuart L. Cooper
Costel D. Denson
Prasad S. Dhurjati
Henry C. Foley
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
Androew 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 Photovoltaic
Processing, Biomedical Engineering, Biochemical Engineering, and Colloid
and Surfactant Science.


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


I
The Universi
Delawa


ty of
ire


Chemical Engineering Education









Modern Applications of

Chemical Engineering

at the



University of Florida


Graduate Study Leading to the MS and PhD


FACULTY.
TIM ANDERSON Semiconductor Processing, Thermodynamics
IOANNIS BITSANIS Molecular Modeling of Interfaces
SEYMOUR S. BLOCK Biotechnology
OSCAR D. CRISALLE Electronic Materials, Process Control
RICHARD B. DICKINSON Biomedical Engineering
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
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
Fall 1993 237










Reeac an Srdut S tde in Chmia EngSnS erinS













Adane Maeral (Ceramic, Clod, an Polymers




3 *fPiifi Iili 3



Cheica Vaor epoito Fa u t
Composite material
Comp lex Fluids Pedro 3 *ii Ph.D.
Phase Transitions Purdue University, 1990

13*3** Ph3e33mena Ravi*3hell Ph.D.
Mo^romolecular Transport in.Polymer Gel Media Univ eity o fM a tts,198
4333 Processing

Se iod3 trad*3ecodco Prcssn Da.. Edlo P. D.
Throynmc Yal Unvesiy 41949
Biegnern .a i 333etai 3h.D.
3i~ ta i Conl 3*vesiy 31389*

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Prcs Sytei an Coto
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Rochste Univer3 ty,3 198
Prcs .Optimization
Exer Sytm Bruc Lok Ph.D.3 5

Surface~~~~~~~~ ~ ~ ~ ~ ~ ~ ScecCtlssan3nrai3'ei! sNrhCrln taeUiest,18
Fli M caic fCrsa Got 3rnia 3* an i P. D.4

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Hetrogno CtalsisandRecto Dei3 Mihe Pe 3r Ph.D

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Fo Inor ato Wrt so Jorg Vifl Ph.D.













'DYO,


CHEMICAL ENGINEERING



The Faculty and Their Research


Heterogeneous
catalysis,
surface
chemistry,
reaction
kinetics

Pradeep K. Agrawal


Process
design and
control,
spouted-bed
reactors


Microelectron-
ics, polymer
processing

itrup


Molecular
thermo-
dynamics,
chemical
kinetics,
separations
arles A. Eckert


W Reactor
design,
catalysis

1lliam R. Ernst


E Molecular
modeling of
polymeric
materials

,ter J. Ludovice


w Mechanics of
aerosols,
buoyant
plumes and jets

LarryJ. Forney



Aerocolloidal
systems,
interfacial
phenomena,
fine-particle
technology

Michael J. Matteson


Heat transport
phenomena,
fluidization

)rton


Polymer
engineering,
energy
conservation,
economics


John D. Muzzy


EPulp and
paper

Jeffrey S. Hsieh


Biomechanics,
mammalian
cell structures


Robert M. Nerem


Photochemical
processing,
chemical
vapor
deposition


M Emulsion
polymeriza-
tion, latex
technology

Gary W. Poehlein


Optimal
process
design and
scheduling


atthewJ. Realff


Reactor
engineering,
process
control,
polymeriza-
tion, reactor
dynamics

Joseph Schork


Catalysis,
kinetics,
reactor design


ark G. White


M, Biochemical
engineering,
mass transfer,
reactor design

Ronnie S. Roberts


Mass transfer,
extraction,
mixing, non-
Newtonian
flow

A. H. Peter Skelland



Biochemical
engineering,
cell-cell
interactions,
biofluid
dynamics

Timothy M. Wick


i Separation
processes,
crystallization

Ronald W. Rousseau


SProcess design
and simulation

Jude T. Sommerfeld


Electrochemical
engineering,
thermodynam-
ics, air
pollution
control


Jack Winnick


Biochemical
engineering,
microbial and
animal cell
cultures

Athanassios Sambanis


Process synthe-
sis and simula-
tion, chemical
separation,
waste manage-
ment, resource
recovery

D. William Tedder


Biofluid
dynamics,
rheology,
transport
phenomena

Ajit P. Yoganathan


Polymer
science and
engineering

Robert J. Samuels


Thermody-
namic and
transport
properties,
phase
equilibria,
supercritical
gas extraction


Amyn S. Teja


For more information,
contact:
Professor Ronald Rousseau,
Director
School of Chemical Engineering
Georgia Institute of Technology
Atlanta, Georgia 30332-0100
(404) 894-2867


Polymer
science and
engineering


S. Abhiraman








What do graduate students say about the

University of Houston

Department of Chemical Engineering?


"It's great!"


"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 of your choice. The choice of
advisor is yours, too, and you're given enough time to make the right decision. You can see
your advisor almost anytime you want because the student-to-teacher ratio is low."

If you'd like to be part of this team, let us hear from you!


AREAS OF RESEARCH STRENGTH
Biochemical Engineering Chemical Reaction Engineering
Electronic and Ceramic Materials Multiphase Flow
Environmental Remediation Nonlinear Dynamics
Improved Oil Recovery Polymer & Macromolecular Systems


FACULTY
Neal Amundson Ernest Henley
Vemuri Balakotaiah John Killough
Abe Dukler Dan Luss
Demetre Economou Kishore Mohanty


Richard Pollard Jay Schieber
William Prengle Cynthia Stokes
Raj Rajagopalan Frank Tiller
Jim Richardson Richard Willson
Frank Worley


For an application, write: Dept. of Chemical Engineering, University of Houston, 4800 Calhoun, Houston, TX 77204-4792, or call 713/743-4300.
The University is in compliance with Title IX.
o0 Chemical Engineering Education













U The University of Illinois at Chicago

I Department of Chemical Engineering



MS and PhD Graduate Program *


FACULTY

Irving F. Miller
Ph.D., University of Michigan, 1960
Professor and Head

John H. Kiefer
Ph.D., Cornell University, 1961
Professor

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

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

Ludwig C. Nitsche
Ph.D., Massachusetts Institute of Technology, 1989
Assistant Professor

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

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

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

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

Bert L. Zuber
Ph.D., Massachusetts Institute of Technology, 1965
Professor


RESEARCH AREAS


Transport Phenomena: Slurry transport, multiphase fluid flow
and heat transfer, fixed and fluidized bed combustion, indirect
coal liquefaction, porous media.

Thermodynamics: Transport properties of fluids, statistical
mechanics of liquid mixtures, bioseparations, superficial 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
technology, surface chemistry, optimization, catalyst preparation
and characterization, structure sensitivity, supported metals.

Bioengineering: Membrane transport, pulmonary deposition
and clearance, biorheology, physiological control systems,
bioinstrumentation.


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 1993









Chemical Engineering at the


University of Illinois

at Urbana-Champaign


The combination of distinguished fac-
ulty, outstanding facilities and a di-
versity of research interests results in
exceptional opportunities for graduate
education.


The chemical engineering department
A offers graduate programs leading to the
M.S. and Ph.D. degrees.
ON
Richard C. Alkire Electroche
OF Richard D. Braatz Advanced
Thomas J. Hanratty Fluid Dyn
Jonathan J. L. Higdon Fluid Mec
CE Douglas A. Lauffenburger Cellular Bi
Richard I. Masel Fundamen
Semiconc
Anthony J. McHugh Polymer Si
William R. Schowalter Mechanics
Edmund G. Seebauer Laser Stud
Mark A. Stadtherr Chemical I
Optimiza
Frank B. van Swol Computer
K. Dane Wittrup Biochemic
Charles F. Zukoski IV Colloid an


mical Engineering
Process Control
amics
hanics and Transport Phenomena
oengineering
ital Studies of Catalytic Processes and
luctor Growth
science and Engineering
Sof Complex Fluids
ies of Semiconductor Growth
Process Flowsheeting and
tion
Simulation and Interfacial Studies
al Engineering
d Interfacial Science


For information and application forms write:
Department of Chemical Engineering
University of Illinois at Urbana-Champaign
Box C-3 Roger Adams Lab
600 S. Mathews Ave.
Urbana, Illinois 61801-3792


Chemical Engineering Education


TRADITI




EXCELLENT









GRADUATE STUDY IN CHEMICAL ENGINEERING AT


Illinois Institute of Technology


THE UNIVERSITY


* Private, coeducational and research university
* 4800 undergraduate students
* 5400 graduate students
* 3 miles from downtown Chicago and 1 mile west of
Lake Michigan
* Campus recognized as an architectural landmark


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


THE DEPARTMENT
* One of the oldest in the nation
* Approximately 40 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


THE FACULTY

* HAMIDARASTOOPOUR (Ph.D., IIT)
Multiphase flow and fluidization, flow through porous
media, and powder and material processing
* RICHARD A. BEISSINGER (D.E.Sc., Columbia)
Transport processes in chemical and biological
systems, rheology of polymeric and biological fluids
* BARRY BERNSTEIN (Ph.D., Indiana University)
Rheology, non-newtonian flows, mechanical behavior
of polymers
* ALl CINAR (Ph.D., Texas A & M)
Chemical process control, distributed parameter
systems, expert systems
* DIMITRI GIDASPOW (Ph.D., IIT)
Hydrodynamics of fluidization, multiphase flow,
separations processes
* HENRY R. LINDEN (Ph.D., IIT)
Energy policy, planning, and forecasting
* SATISHJ. PARULEKAR (Ph.D., Purdue)
Biochemical engineering, chemical reaction engineering
* J. ROBERT SELMAN (Ph.D., California-Berkeley)
Electrochemical engineering and electrochemical
energy storage
* FYODOR A. SHUTOV (Ph.D., Institute for Chemical
Physics, Moscow)
Polymer composite materials and plastic recycling
* FOUAD TEYMOUR (Ph.D., University of Wisconsin, Madison)
S.C. Johnson Polymer Assistant Professor
Polymerization reaction engineering, and dynamic
system analysis
* DAVID C. VENERUS (Ph.D., Pennsylvania State U)
Polymer rheology and processing, and transport
phenomena
* DARSH T. WASAN (Ph.D., California-Berkeley)
Interfacial phenomena, separation processes,
enhanced oil recovery


* APPLICATIONS *
Dr. A. Cinar
Graduate Admissions Committee
Department of Chemical Engineering
Illinois Institute of Technology
I.. T. Center
Chicago, IL 60616


Fall 1993






Looking for a graduate program

that's right

for you?


Since 1929,
1404 determined students have
graduated from the Institute of
Paper Science and Technology.

Of those 1404 alumni, 963 are still actively
working.

Of those 963 individuals, 27% are CEOs, COOs,
Presidents, Vice Presidents, Technical Directors,
or Mill Managers of major paper companies.

These numbers do not include those
dedicated, well-educated alumni
who are on their way to becoming
the pulp and paper leaders
of the future.

BE A STATISTIC.


Institute of Paper Science and Technology
A Unique, Multidisciplinary Graduate Program
for Engineers and Scientists
The Institute of Paper Science and Technology offers a unique, multidisciplinary program at
the graduate level for highly qualified students with a B.S. degree in chemical or mechanical engineering,
chemistry, paper science, biology, or other physical sciences.
The IPST academic program provides a broad technical education in engineering and science topics
relevant to the paper industry. This broad perspective enables graduates to manage complex technical
issues of importance to the industry.
Students who are citizens of North America receive full tuition scholarships and graduate
fellowships of $15,000 or $17,000 per year (12-month basis), depending on the degree program. Opportu-
nities also exist for summer employment in the industry, providing income, as well as exposure to the
challenges of the paper industry.

For more information, contact the Office of Academic Affairs at 404-853-9556, or write to the Institute of
Paper Science and Technology, Office of Academic Affairs, 500 10th Street, NW, Atlanta, GA 30318-5794.






GRADUATE PROGRAM FOR M.S. & PH.D. DEGREES
IN CHEMICAL AND BIOCHEMICAL ENGINEERING

FACULTY


GREG CARMICHAEL
Chair; U. of Kentucky,
1979, Global Change/
Supercomputing


RAVI DATTA
UCSB, 1981
Reaction Engineering/
Catalyst Design


DAVID MURHAMMER
U. of Houston, 1989
Animal Cell Culture


J. KEITH BEDDOW
U. of Cambridge, 1959
Particle Morphological
Analysis


JONATHAN DORDICK
MIT, 1986,
Biocatalysis and
Bioprocessing


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


AUDREY BUTLER
U. of Iowa, 1989
Chemical Precipita-
tion Processes


DAVID LUERKENS
U. of Iowa, 1980
Fine Particle Science


V.G.J. RODGERS
Washington U., 1989
Transport Phenomena
in Bioseparations


For information and application write to:
GRADUATE ADMISSIONS
Chemical and Biochemical Engineering
The University of Iowa
Iowa City, Iowa 52242
319-335-1400


THE UNIVERSITY OF IOWA







IOWA STAm
OF SCIENCE AND--r!4



a- -i


Impop A-


For additional
information, please write
Graduate Office
Department of
Chemical Engineering
Iowa State University
Ames, Iowa 50011
or call 515 294-7643
E-Mail Seagrave@IASTATE.EDU


U


Biochemical and Biomedical Engineering
Charles E. Glatz, Ph.D., Wisconsin, 1975.
Carole A. Heath, Ph.D., R.P.I., 1988.
PeterJ. Reilly, Ph.D., Pennsylvania, 1964.
Richard C. Seagrave, Ph.D., Iowa State, 1961.

Catalysis and Reaction Engineering
L. K. Doraiswamy, Ph.D., Wisconsin, 1952.
Terry S. King, Ph.D., M.I.T., 1979.
Glenn L. Schrader, Ph.D.. Wisconsin, 1976.

Energy and Environmental
George Burnet, Ph.D., lowa State, 1951.
Thomas D. Wheelock. Ph.D.. Iowa State, 1958.

Materials and Crystallization
Kurt R. Hebert, Ph.D., Illinois, 1985.
Maurice A. Larson, Ph.D., Iowa State. 1958.
Gordon R. Youngquist, Ph.D., Illinois, 1962.

Process Design and Control
Derrick K. Rollins, Ph.D., Ohio State, 1990.
Dean L. Ulrichson, Ph.D., Iowa State, 1970.

Transport Phenomena and Thermodynamics
James C. Hill, Ph.D., Washington, 1968.
Kenneth R. Jolls, Ph.D., Illinois, 1966.


__~__ ___._._ ._ _I


=-~a









Graduate Study and Research in



Chemical


Engineering


TIMOTHY A. BARBARI MARK A. MCHUGH
Ph.D., University of Texas, Austin Ph.D., University of Delaware
Membrane Science High-Pressure Thermodynamics
Sorption and Diffusion in Polymers Polymer Solution Thermodynamics
Polymeric Thin Films Supercritical Solvent Extraction
W. MARK SALTZMAN
MICHAEL J. BETENBAUGH Ph.D., Massachusetts Institute of Technology
Ph.D., University of Delaware Transport in Biological Systems
Biochemical Kinetics Polymeric Controlled Release
Insect Cell Culture Cell-Surface Interactions
Recombinant DNA Technology W. H. SCHWARZ
Dr. Engr., The Johns Hopkins University
MARC D. DONOHUE o Rheology
Ph.D., University of California, Berkeley Non-Newtonian Fluid Dynamics
Equations of State Physical Acoustics and Fluids
Statistical Thermodynamics Turbulence
Phase Equilibria
Phase Equilibria KATHLEEN J. STEBE
JOSEPH L. KPh.D., The City University of New York
Interfacial Phenomena
Ph.D., University of Chicago Electropermeability of Biological Membranes
Nucleation Surface Effects at Fluid-Droplet Interfaces
Crystallization
Flame Generation of Ceramic Powders DENIS WIRTZ
Ph.D., Stanford University
Phase Transitions and Critical Phenomena
Polymer Systems Far from Equilibrium
Pattern Selection in Convective Systems

For further information contact:

The Johns Hopkins University
G. W.C. Whiting School of Engineering
Department of Chemical Engineering
Baltimore, MD 21218
(410) 516-8480
E.O.E./A.A.
1-1 pn In Q~


Fall 1993
















GRADUATE STUDY

IN CHEMICAL AND PETROLEUM

ENGINEERING


GRADUATE PROGRAMS
* M.S. degree with a thesis requirement in both chemical and
petroleum engineering
* Ph.D. degree 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.)

RESEARCH AREAS
Catalytic Kinetics and Reaction Engineering
Chemical Vapor Deposition
Controlled Drug Delivery
Corrosion
Economic Evaluation
Enhanced Oil Recovery Processes
Fluid Phase Equilibria and Process Design
Kinetics and Homogeneous Catalysis for Polymer Reactions
Plasma Modeling and Plasma Reactor Design
Phase Behavior
Process Control
Supercomputer Applications
Supercritical Fluid Applications
Waste Heat and Pollution of Combustion Processes

FINANCIAL AID
Financial aid is available in the form of fellowships and research and
teaching assistantships ($13,000 to $16,000 a year)


FACULTY
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)
Russell D. Osterman (Ph.D., Kansas)
Marylee Z. Southard (Ph.D., Kansas)
Bala Subramaniam (Ph.D., Notre Dame)
Galen J. Suppes (PH.D., Johns Hopkins)
Brian E. Thompson (Ph.D., MIT)
Shapour Vossoughi (Ph.D., Alberta, Canada)
G. Paul Willhite, Chairman (Ph.D., Northwestern)

RESEARCH FACILITIES
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, 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
Th* TT;nivrs-;it .f I na st


.111 vI L oIALY V- ILalIa
THE UNIVERSITY The Graduate Adviser
Department of Chemical and Petroleum Engineering
The University of Kansas is the largest and most comprehensive 4006 Learned Hall
university in Kansas. It has an enrollment of more than 28,000 and Lawrnc KS Lal66045-2
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.


Chemical Engineering Education


THE UIRTOK S













































Durland Hall Home of Chemical Engineering


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

Financial Aid Available
Up to $17,000 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
Proces 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


Fall 1993


Ic~ni

KCANSAS
STATE
9TRIVERSrT


tAtxjw'


249












Far From An
Ordinary Ball
Research with advanced
materials (carbon fibers,
nitride catalysts, supercon-
ducting thin films, and liquid
crystalline polymers) and with
Buckyballs is ongoing here in
Lexington.

Anything But An
Ordinary University
At the University of Kentucky-designated by
the Carnegie Foundation as a Research
University of the First Class, and included in
the NSF's prestigious list-
ing of Top 100 research
institutions in America-
CHOICESfor Chem. E. grad-
OK uate students are anything
but ordinary. There are
joint projects with Pharmacy, the Medical
School, the Markey Cancer Center, and
Chemistry researchers. And abundant opportu-
nities for intense interaction with extraordinary
faculty, as well as access to state-of-the-art
facilities and equipment, including an IBM ES
3900/600J Supercomputer.


With Out-Of-The-
Ordinary
Chem. E.
Specialties
Aerosol Chemistry and
Physics-Weighing picogram
particles in electrodynamic balance,
measuring monolayer adsorption, data
with seven significant figures.
Cellular Bioengineering-Rheological
and transport properties of cell membranes; cell
adhesion, cancer research, transport of drugs
across membranes, and membrane biofouling.
Computational Engineering-Modeling turbulent
diffusion in atmospheric convective boundary


layers; modeling growth of multi-
component aerosol systems.
Environmental Engineering-
EPA-approved analytical labora-
tory; global atmospheric
transport models; atmospheric
photochemistry; control of
heavy metals and hazardous
organic; water pollution research.
Membrane Science-Development of
low pressure charged membranes; thin
film composite membranes; development of bio-
functional synthetic membranes.


From A
Uniquely
Un-Ordinary
Faculty
Recent national awards won by our faculty
include: Larry K. Cecil AIChE Environmental
Division; AIChE Outstanding Counselor Award,
1983, 1991; ASM Henry Marion Howe Medal;
AAAR Kenneth T. Whitby Memorial Award; BMES
Dr. Harold Lamport Award for a Young Investiga-
tor; and two NSF-Presidential Young Investigators.
Recent University-wide awards by faculty include:
Great Teacher;
Research Professor;
Excellence in Under-
graduate Education;
and Alumni Professor.



All Of Which
Create Some
Extraordinary
Opportunities For You
Doctoral incentives well worth your consideration:
Up to $20,000 per year stipends plus tuition,
books, research supplies, travel allowances.
Interested in obtaining a degree of extraordinary
worth? Contact Dr. K.W. Anderson, Department of
Chemical Engineering, University of Kentucky,
Lexington, KY 40506-0046


SUniversity of Kentucky Department of Chemical Engineering


606-257-4956


I Uilvei-sity of Kemucky I




Full Text