CREL Annual Meeting
October 28, 2004
Chemical Reaction Engineering Laboratory
Department of Chemical Engineering
St.Louis, MO 63130
CHEMICAL REACTION ENGINEERING LABORATORY

(SLURRY) BUBBLE COLUMN AND GAS-LIQUID
STIRRED TANK REACTORS
A. Experimental Techniques and Measurements

Ashfaq Shaikh
Hydrodynamics Flow Regime Transition Scale-up

Hydrodynamics of High Pressure Bubble Column Slurry Reactor

Combination of two single modal tomographic techniques for three dynamic phase flow imaging

Evaluation of CT for regime identification
 New technique and its ‘flow regime identifiers’ developed
A new hypothesis proposed

Experimental evaluation of proposed hypothesis

Development of ANN correlations for hydrodynamic parameters

Homogeneous/Bubbly
Flow
Heterogeneous/Churnturbulent Flow
Different hydrodynamic characteristics

Explored the potential of CT for flow regime delineation in bubble column

Evaluated the developed approach with traditional methods such as Drift Flux method

Investigated the effect of operating pressure on flow regime transition

Lu Han, Muthanna Al-Dahhan. CREL, Oct. 2004
Slurry Bubble Column Reactors
• Vertical cylindrical vessels, three-phase gas-liquid-solid systems with solid particle sizes in the range 5-150 µm and solids loading up to
50% by volume
• Simple to construct and do not involve any mechanically moving parts
• Exhibit excellent heat and mass transfer characteristics
G – Reactant
L – Reactant and/or Product
S – Catalyst G
L+S
Applications:
– Fischer-Tropsch (FT) Synthesis
– oxidation and hydrogenation
– chlorination and alkylation
– polymerization, methanol synthesis
– waste water treatment
– bio and biochemical processes
L+S
G
The goal of this work is to measure the gas-liquid volumetric mass transfer coefficient, k
L a, in SBC with high gas velocity/pressure/solid loading, with assistance of hydrodynamic information obtained using CARPT/CT methodology.

Optical Oxygen Probe
Probe Tip
Sol-Gel
Light from the blue LED going to the probe tip
1.2
1
0.8
0.6
0.4
0.2
0
0
Exp.
ADM Fitting
CSTR Fitting
20 40 t, s
60 80
Comparison of Data Fitting Using
CSTR and ADM models
B.C. DC8”, air-water, 0.1MPa,
SGV 12cm/s, z/L=0.8
Overcoat
Sol-Gel
475 nm
600 nm
Collected fluorescence going to the spectrometer
Sol-Gel
O 2
O
2
O 2
O
2
O 2
475 nm
600 nm
1.2
1
0.8
0.6
0.4
0.2
0
0
He Tracer
Resp.
ADM Fitting
10 20 t, s
30 40
Gas Tracer Response Fitting Using
ADM Model (RTD)
B.C. DC8”, air-water, 0.1MPa, SGV
2cm/s
Gas Tracer Technique

A Novel Modeling Approach for Predictions of the Dynamic
Growth of Microalgae in Multiphase Photo-bioreactors
Flows Dynamics in An Internal Loop Airlift Column
Bioreactor
Producing And Carbonylating of Dimethyl Carbonate: A
Process Development Study
Hu-Ping Luo, Muthanna H. Al-Dahhan
Chemical Reaction Engineering Laboratory (CREL)
Bioprocess & Bioreactor Engineering Laboratory (BBEL)
Chemical Engineering Department
Washington University in St.Louis
CREL Annual Meeting
October 2004
CHEMICAL REACTION ENGINEERING LABORATORY

A Novel Modeling Approach for Predictions of the Dynamic Growth of
Microalgae in Multiphase Photo-bioreactors
Challenges in Reactor Design and
Scale-up
Complex interactions among microorganisms (cells) metabolism, kinetics, transportation, and hydrodynamics in Bioreactors
?
How to see through the system for LOCAL PHENOMENA of the flow pattern in bioreactors
A Case Study
Final Products t r2
Cell 2 t d
Substrates t r1
Cell 1 t d
Product 1 t d
Bubbles
Product 1
Airlift Column Photobioreactor:
Integrating metabolism of autotrophic microorganism with flow dynamics
CARPT &
CT
Findings
Photosynthesis Kinetics
Bubbles
Bubbles
80
70
60
50
Mass transfer in Bioreactors
40
30
20
10
SC_1cms
DC_5cms
BC_5cms
SC_5cms
DC_1cms
0
0 100
Time, hr
200
Bioreactor Performance
Please stop by this poster if interest

Flows Dynamics in An Internal Loop Airlift Column Bioreactor
 Study the macro- and micro-mixing and the liquid flow field in the fully developed flow region as well as the Top and the Bottom regions
 Investigate the effects of superficial gas velocity and top and bottom clearance on the hydrodynamics
 Form the knowledge base for airlift reactors’ design and scale-up, and provide a database for CFD modeling validations.
CARPT
RTD analysis
CT
Local Gas Holdups
Please stop by this poster for details if interest
Bypassing and Stagnant may significant in both the Top and the Bottom regions

Producing And Carbonylating of Dimethyl Carbonate:
A Process Development Study
Hu-Ping Luo, Wen-De Xiao, Kai-Hong Zhu
East China University of Science and Technology, Shanghai, China
WHY Dimethyl Carbonate?
•
Environmentally benign chemicals
•
Environmentally benign processes
•
An excellent gesoline additives
•
A building block: containing both the carbonyl and the methyl group , an effective carbonylation agent, a useful methylation agent
•
An important organic solvent
O
Kinetic
Thermodynamic
Reactive Distillation
H
3
COCOCH
3
O
C
2
H
5
OCOCH
3
Trans-esterification: producing and carbonylating DMC
+
+
C
2
H
5
OH
C
2
H
5
OH cat cat
O
H
3
COCOC
2
H
5
O
+ CH
3
OH
C
2
H
5
OCOC
2
H
5
+ CH
3
OH
1
0.9
0.8
0.7
""" " " "
"
" "
Add new reactants
0.6
0.5
0.4
'
' '
' ' '' ' ' '
'
0.3
0.2
0.1
Catalyst E+P
0
0 10 20 30 40 50 60 70 80 90
Time(min) Catalytic System
Selectivity
360
350
340
Exp
UNIFAC prediction (old
parameters,Pattern 1)
UNIFAC prediction (old
parameters,Pattern 2)
UNIFAC prediction (this
work)
Methanol(1)+DMC(2)
0.0
0.2
0.4
0.6
0.8
1.0
x
1
, y
1 Phase Equilibrium
10
20
30
40
Methanol
Ethanol
DMC
MEC
DEC
50
0 20 80 100
Liquid composition (mol%)
Reactive Distillation Simulation

• The instantaneous heat transfer coefficient(h i
) can be obtained from the heat transfer flux(Q) and temperature difference between the probe surface(T s
) and the bulk(T b
).
h i

Q /( T s

T b
)
– The probe measures the instantaneous local heat flux(Q) and the surface temperature(T s
).
– Three thermocouples are used to measure the bulk temperature(T b
).
CHEMICAL REACTION ENGINEERING LABORATORY

1
2
3
Heat transfer probe
8
4
5
6
Heat transfer measurement unit
1: thermocouples, 2: probe, 3: DC power,
4: amplifier, 5: DAQ system.
4
Center
Wall
2
0 5 10 15
U g ( c m / s )
20 25
HTC measured in 6” air-water column under atmosphere
CHEMICAL REACTION ENGINEERING LABORATORY

Bubble Velocity, Chord Length and Specific Interfacial Area
Measurements in Bubble Columns Using Four-point Optical Probe
Junli Xue, M. H. Al-Dahhan, M. P. Dudukovic, R. F. Mudde d fiber
=0.2 mm
The performance of (slurry) bubble columns is governed by the hydrodynamics.
Validation of Computational
Fluid Dynamics (CFD) codes requires also local information on bubble properties.
Cofiguration of the Four-Point
Optical Probe
The measurement of bubble properties is difficult, especially in churn-turbulent flow. A four-point optical probe is employed in this study to measure the bubble properties.
CHEMICAL REACTION ENGINEERING LABORATORY

Four-Point Optical Probe Measurements in a
16.2 cm (6.4”) Bubble Column:
The operating conditions span from bubbly flow to churn-turbulent flow.
Superficail gas velocity: 2~60 cm/s
Pressure: 1~10 bar
Probe positioned downwards
Measuring position
The probe was positioned both upwards and downwards. So both bubbles moving upwards and downwards are measured.
Probe positioned upwards
CHEMICAL REACTION ENGINEERING LABORATORY

3D VIEW OF BIAZZI HYDROGENATION REACTOR
CONFIDENTIAL
References:
Projects realized:
•
41 plants built
•
16 of which cGMP
•
Maximum 110 bar and 300
°C
Customers:
•
Fine Chemicals
•
Pharmaceuticals
•
Resins and Intermediaries
•
Speciality sugars
•
Edible oils
Operation modes:
•
Continuous
•
Dedicated cGMP and regular
•
Multipurpose cGMP and regular
Countries:
•
Europe: Italy, Belgium, Austria,
Switzerland, Netherlands, Germany,
England, Spain, France,
•
Americas: Brasil, USA,
•
Asia: South Korea, India, Japan,
Taiwan R.O.C., China, Russia
25, Ch de la Tavallaz, CH-1816 Chailly s/Montreux, Switzerland - Tel.: +41 21 989 2121 - Telefax: +41 21 989 2120 - www.biazzi.com

Testing of Phase Transition and Bubble Dynamics Using A Four-Point Optical Probe
Adam Wehrmeister, Junli Xue, M. H. Al-Dahhan, M. P. Dudukovic
Chemical Engineering Department, Washington University in St. Louis
Center for Environmentally Beneficial Catalysis
Chemical Reaction Engineering Laboratory
The four-point optical probe installed in a 2D bubble column.
 Sketch of the ideal probe response to a bubble piercing the four tips of the optical probe.
 Provides data on bubble size, bubble velocity, local gas hold-up, and specific interfacial area.
Bubble
T
0
 t
1 T
1
 t
2 T
2
 t
3 T
3
Liquid
Time
Tip0
Tip1
Tip2
Tip3
1 1
Probe
Tip3
Tip1 r
Tip2
L

2 mm
Tip3
 
Tip2 r
Tip0
 r r

0.6 mm

Tip1
Tip0
0.8
0.6
0.8
0.6
Side view Bottom view
(Field of view 5x5 mm)
0.4
0.2
1
0.8
0.6
0.4
0.2
0
0.18
0.19
0.2
Tip 1
Tip 2
Tip 3
Tip 4
0
0 1 2
Time (seconds)
3
Figure 6. Probe response for decane/CO
2 at 43 o C and ~1000 psi
0.4
0.2
1
0.8
0.6
0.4
0.2
0
1 1.05
1.1
1.15
1.2
Tip 1
Tip 2
Tip 3
Tip 4
0
0 1 2
Time (seconds)
3
Figure 7. Probe response for decane/CO
2 at 32 o C and ~1050 psi

(SLURRY) BUBBLE COLUMN AND GAS-LIQUID
STIRRED TANK REACTORS
B. Modeling and Computational Fluid Dynamics (CFD)

CHEMICAL REACTION ENGINEERING LABORATORY

CARPT
FLOW
PATTERN
CT SCAN
-R
Gas
D zz
D rr
CFD +
CARPT + CT
0
1e
L
(r) u z
(r)
R
AFDU
7
6
5
4
3
2
1
DET.
Gas
Gas Tracer
1 1.0
0.8
0.8
Temperature =250 Deg. C
Ug = 25 cm/s
0.6
0.6
0.4
0.4
Sim_L1
Prediction
Sim_L4
Exp_L4
Sim_L7 time (s)
0.2
0.2
0 0.0
0 20 40 60 80 100
0 20 40 60 80 100
Time (sec)
1
0.8
0.6
Liquid
Tracer
0.4
0.2
Detector Level 6 time (s)
0
0 100 200 300 400
1
0.8
0.6
0.4
Detector Level 1
0.2
0 time (s)
0 100 200 300 400
CHEMICAL REACTION ENGINEERING LABORATORY

Needed information:
Gas holdup profile
Eddy diffusivity correlation
Liquid mixing length correlation
Phenomenological
Model
Mixing and
Transport
Characteristics
Assessment
• CFD
• Experiments
•
Correlation
Reactor Performance
CHEMICAL REACTION ENGINEERING LABORATORY

Computational Modeling of Gas-Liquid Flow in Bubble Columns
P. Chen, M. Rafique and M. P. Dudukovic
Outlines
•Hydrodynamics of bubble columns
•Eulerian-Eulerian Two-Fluid model
•Algebraic Slip Mixture Model (ASMM)
•Hydrodynamics of (passive) tracers (gas/liquid) in bubble column flows

Debangshu Guha, M.P.Dudukovic &
P.A.Ramachandran
CREL Annual Meeting, 2004

 Reactor Performance = f (kinetics, flow pattern and mixing)
 Mixing = f (flow pattern and turbulence characteristics)
 Most available phenomenological models for mixing do not account for the flow pattern and the turbulence inhomogeneities in the reactor
 The performance prediction can be improved if flows and turbulence characteristics can be used from CFD

Solve macroscopic
Macroscopic equation consists of convection due to main flow, dispersion due to turbulence and the reaction terms

: CARPT/CT Measurements and CFD Simulations
• CARPT/CT measurements were obtained in
STR for gas-liquid flows
•Can liquid phase velocity profiles be predicted apriori with no experimental inputs?
•Can the gas holdup profiles in the STR be predicted via modeling?
•Role of Lagrangian measures from CARPT in validating CFD approaches ?
•Extension of Computational Snapshot to predicting two phase flows in STR ?
Grid Details : r
  
z : 58

95

64
Impeller blade: 14

3

18
Inner region : 12

k

53
j

42

PACKED BED, STRUCTURED BED,
CRICULATING FLUIDIZED BED

Poster 1
Solids Flow Mapping in a Fast Fluid Bed
Satish Bhusarapu,
M. H. Al-Dahhan and M. P. Dudukovi ć
CREL Annual Meeting
October 28, 2004
Chemical Reaction Engineering Laboratory
Department of Chemical Engineering
St.Louis, MO 63130
CHEMICAL REACTION ENGINEERING LABORATORY

Challenge : Obtain solids flow mapping in the riser
1.5 m (5 ’)
0.6 m (24 ”)
CARPT in a Pilot-plant set-up
46 Sc particle coated with a polymer (Parylene® density 1.1 g.cm
-3 ) to adjust the density and prevent attrition of the radioactive tracer z = 5.85 m
L/D = 38.5
r
= 2.5 g.cm
-3 ; d p
(sauter mean) = 150 m m
ParyleneN coating
(7 m m thickness) z = 4.6 m
7.9 m (26 ’)
L/D = 30.5
(6 ”) I.D.
46 Sc particle
(136 m m)
Soft glass beads Radioactive tracer particle
CHEMICAL REACTION ENGINEERING LABORATORY
1 m (3.3
’) tall
0.1m (4 ”) I.D.
(18 ’) tall
(2 ”) I.D.

Poster 2
Solids RTD in a Gas-Solid Riser at Low and High Fluxes:
Single Radioactive Particle Tracking
Satish Bhusarapu,
M. H. Al-Dahhan and M. P. Dudukovi ć
CREL Annual Meeting
October 28, 2004
Chemical Reaction Engineering Laboratory
Department of Chemical Engineering
St.Louis, MO 63130
CHEMICAL REACTION ENGINEERING LABORATORY

Challenge : To obtain RTD in an “open” system like riser
Impulse responses in “open-open” systems are not representative of the RTD. Naumann &
Buffham, 1983.
0.15
0.1
0.05
Solids FPTD in the Riser with "closed-closed" Boundaries
1
Mean of FPTD = 13.52 sec
Stdev of FPTD = 33.6 sec
   Dz = 2.1 m 2 /s
0.5
In recirculating systems like CFBs, first passage times in the riser cannot be determined uniquely from impulse responses. Shinnar et al.
, 1971.
0
0
0.04
0.03
1 4 5
0
Solids RTD in the Riser with "open -open" Boundaries
1
Mean of RTD = 39.7 sec
Stdev of RTD = 59.94 sec
   Dz = 0.8 m 2 /s
0.5
Single Radioactive Particle Tracking
Transient response function as would be obtained from conventional tracer injection
Overestimates:
Mean residence time by 64%
Underestimates:
Dimensionless variance by 31%
Dispersion coefficient by 38%
0.01
0
0
0.02
1 4 5
0
Transient Response Function from a Conventional Tracer Experiment
1
0.01
Mean of TConv. = 65.13 sec
Stdev of TConv. = 81.9 sec
   Dz = 0.5 m 2 /s
0.5
0
5
0
CHEMICAL REACTION ENGINEERING LABORATORY

Poster 3
An Alternating Minimization Algorithm for Image
Reconstruction in Computed Tomography
Satish Bhusarapu,
M. H. Al-Dahhan and M. P. Dudukovi ć
CREL Annual Meeting
October 28, 2004
Chemical Reaction Engineering Laboratory
Department of Chemical Engineering
St. Louis, MO 63130
CHEMICAL REACTION ENGINEERING LABORATORY

Challenge: To improve image quality of the CT data
A
  ln


I
 r  m
 eff , ij
I o



 l
  r  m  eff , ij

K
 r  m

K , ij
 l ij
 e
K , ij
Beer Lambert’s Law
-
-
Estimation - Maximization
An approximation is made in the solution which is true only for low attenuation values
Phase holdup profiles at various axial positions
Implement an Alternating Minimization (AM) algorithm (O’Sullivan and Benac, 2001), where each step of minimization is exact.
CHEMICAL REACTION ENGINEERING LABORATORY

Maxime Capitaine
M.P. Dudukovic, M.H. Al-Dahhan
Chemical Reaction Engineering Laboratory (CREL)
Washington University in St. Louis
St. Louis, MO
J. Bousquet, D. Védrine, P. Tanguy
Centre Européen de Recherche et Technique, TOTAL
Harfleur, FRANCE

Hydrodynamics Parameters
• Liquid Distribution
• Pressure Drop
• Liquid Hold Up
Measurement Methods
• Collector Tray
• Computed Tomography
Results
• Effects of liquid and gas superficial velocities and packed bed height

Cell Network Modeling For
Catalytic Trickle-Bed Reactors
J. Guo, Y. Jiang, P. A. Ramachandran,
M. Al-Dahhan, M. P. Dudukovic
Washington University
St. Louis, Missouri
CREL Annual Meeting
10.28.2004
CHEMICAL REACTION ENGINEERING LABORATORY

Single Cell
Layer i
1D Cell-Stack
Cell (i, j)
Layer i+1 Cell (i+1, j)
Layer i+2 Cell (i+2, j)
Layer i+3
Cell (i+3, j)
Mixing
Splitting i,j
2D Cell-Network i-1, j i, j-1 i, j i, j+1 i+1, j
CHEMICAL REACTION ENGINEERING LABORATORY

R C Ramaswamy
Advisors
P A Ramachandran, M P Dudukovi ć
CREL Annual Meeting
Fall, 2004
CHEMICAL REACTION ENGINEERING LABORATORY

-
ΔH
A B
+
ΔH
C D
Endothermic
Exothermic
Directly Coupled Adiabatic Reactor
(De Groote et. al. 1996, De Smet et. al. 2001, Hohn and Schmidt 2001)
Counter Current Reactor
(Frauhammer et. al. 1999, Veser et. al. 2001, Kolios et. al.
2001, Kolios et. al. 2002)
Exothermic
Reaction
Regenerative
Coupling
Heat
Recuperative
Coupling
Endothermic
Reaction
Exothermic
Endothermic
Endothermic
Exothermic
Reverse Flow Reactor
( Kulkarni and Dudukovic 1996, Kolios et. al. 2000)
Co-Current Reactor
(Ismagilov et. al. 2001, Kolios et. al. 2002, Zanfir et. al.
2003)

Regenerative Coupling
Exothermic
Reaction
- Combustion
Heat
Endothermic
Reaction
- Synthesis Gas
Generation
Mixed Catalyst Bed
(Exothermic &
Endothermic Catalysts)
Products
Exothermic
Catalyst Bed
Endothermic
Catalyst Bed
Reactants
Simultaneous DCAR Sequential DCAR

CH
4
(2:1)
& O
2
T in
~773 K
Partial Oxidation (Exo)
&
Steam Reforming (Endo)
H
2
/CO ~ 2
CO
2
& H
2
O
T exit
~ 1300 K

Synthesis Gas (mixture of H
2 and CO)
(Pena et. al. 1996)
– Feed stock for synthesis of liquid fuels, methanol
– Source of hydrogen for fuel cells
– Feed stock for ammonia plant, hydrogenation plant etc
Catalytic Partial Oxidation of Methane to Syngas
(De Smet et. al., CES 56 , 2001)
( 1 ) CH
4

2 O
2

CO
2

2 H
2
O ,

H
773 K
 
800 KJ / Mol
( 2 ) CH
4

H
2
O

CO

3 H
2
,

H
773 K

222 KJ / Mol
( 3 )
( 4 )
CH
4
CO


H
2 H
2
O
2
O

CO
2

CO
2


4 H
H
2
,
2
,

H
773 K

H
773 K

185
 
37
KJ
KJ /
/ Mol
Mol
High Active Catalysts (Rh)
Short Contact Time
Reactors
(4-15 milli seconds)
Hohn & Schmidt, 2001

Iso-butane (P) + Butene (O)  Alkylate (A - gasoline)
• A is the desired product
• X & Y deactivate the catalyst P

O

S
O

O

S
D

S
 k
3
A

O

S
Rearranging , k
4
X
P

O

S
O

O

S k k
2 k
1
1
 k
4

 k
3 k
2 k
1 k
2
A
D
Y


S
S
A

S


 
Y
D

S k
3
X
The configurations to consider are
• CSTR (both P & O in low conc)
• P in high conc (Plug flow) and O in low conc – CSTR in series with addition of O in each
CSTR

Performance studies of a solid-catalyzed gas-liquid monolith reactor: Effect of flow maldistribution
Shaibal Roy
Muthanna Al-Dahhan
CREL Annual Meeting
28 th October 2004
Liquid in
Introduction
• Multiphase reactors (for solid catalyzed gasliquid reaction) used extensively in petroleum, petrochemical, biochemical, material, and environmental industries
Gas in
Gas out
Liquid out
Gas in
Gas out
Gas out
Liquid out
Liquid in
Gas in
Gas in
• Catalytic monolith reactor have shown promise to overcome some of the drawbacks of conventional reactors as well as give higher productivity (Krautzer et al. 2003, Nijhaus et al., 2001)
CHEMICAL REACTION ENGINEERING LABORATORY
Liquid out
Gas out

Background
Previous researches have assumed uniform flow distribution across a monolith cross-section in the Taylor flow regime.
Experimental performance studies
(small diameter reactor)
Monolith reactor performance modeling (single channel model)
Nijhaus et al., 2001
Krautzer et al., 2003
Liu, 2001
Edvinsson et al. 1994
Cybulski et al. 1999
Nijhaus et al., 2003
However, this is not always the case as demonstrated by recent non-invasive flow measurement techniques (Mewes et al., 1999; Gladden et al., 2003)
Objectives
Gladden et al 2003 using MRI
Mewes et al. 1999 using Capa. Tomo.
•What is the effect of the following operating parameters on the flow distribution:
•Gas and liquid velocities
•Type of liquid distributor
•Cell density and void fraction of monolith
•How is the performance of monolith reactor (conducted in a large diameter reactor) affected by flow distribution
•How does monolith reactor performance compare with trickle bed reactor
•Does monolith scale reactor model (integrating flow distribution in the model) fare better than single tube model

Two friendly user simulation packages have been developed.
User specifies several parameters needed in reactor design calculations.
Liquid-solid circulating bed reactor for alkylation process
Trickle bed reactor for phenol oxidation process

MICROREACTORS

• Radmila Jevtic, Milorad Dudukovic, and
Muthanna Al-Dahhan
(taken from http://www.mikroglas.com
)
CHEMICAL REACTION ENGINEERING LABORATORY

The potential advantages of using microreactors instead of conventional reactors are
(Jensen, 2001):
• Higher surface to volume ratio
• Higher mass and heat transfer rates
• More aggressive reaction conditions with higher yields
• Safer operation
• Higher throughputs
• Minimal environmental hazards
CHEMICAL REACTION ENGINEERING LABORATORY

O
2
OH
+
O
HNO
3 Caprolactam
& Adipic acid
>120 C
~15 bars cobalt catalysts
KA-mixture
4% conversion of cyclohexane ;
80% selectivity is for cyclohexanol and cyclohexanone
.
Nylon 6 and
Nylon 66
The reaction has been performed under atmospheric pressure, both at room and the elevated temperatures (up to 90 o C), with or without catalyst (cobalt naphthenate), and with various oxidants
(air, oxygen, ozone, and hydrogen peroxide).
CHEMICAL REACTION ENGINEERING LABORATORY

CATALYSIS CHARACTERIZATION AND
DEVELOPMENT

Funded by the National Science Foundation’s GOALI (Grant Opportunities for Academic Liaison with Industry) Initiative
Research Personnel:
Professor John Gleaves
Professor Gregory Yablonsky
Dr. Anne Gaffney
Mrs. Rebecca Fushimi
Mr. Mike Rude
Mr. David French
Miss. Pam Buzzetta
Mr. Sean Mueller
Mr. Joseph Swisher
Mr. Josh Searcy
Heterogeneous Kinetics and Particle Chemistry Laboratory
Department of Chemical Engineering
Washington University, St. Louis MO
Monomers Research
727 Norristown Road, PO Box 904
Spring House, Pennsylvania

Changing the Surface Transition Metal Composition of Bulk
Catalysts
Creating Nanoscale Concentration Gradients of Transition Metal Species on Bulk
Metal Oxide Catalysts
Laser beam
Transition metal source
Atomic beam
Catalyst particle
Vibrate bed
Sample holder in transfer arm
(Vacuum - 10 -8 torr)

Changing the Surface Transition Metal Composition of Bulk
Catalysts
VPO catalyst
Preliminary Results
P
Ox
, T
Rx
, t
Rx
+ O
2
Pulsed Hydrocarbon
Reduction
RO x
Butene

Furan
Oxygen-enriched nanolayer
1
0.8
0.6
0.4
0.2
0
0
VPO - Te Deposition
20 40
VPO - Cu Deposition
60
Pulse Number
80
VPO
100
1
0.8
0.6
0.4
0.2
0
0
VPO - Te
20
VPO
VPO - Cu
40 60
Pulse Number
80 100

Rebecca Fushimi 1 , Sergiy O. Shekhtman 1 , Michael Rude 1 , Anne
Gaffney 2 , Scott Han 2 , Gregory S. Yablonsky 1 , John T. Gleaves 1
1 Dept. of Chem. Eng., Washington University
2 Rohm & Haas Company


All studies were performed in
TAP-2 experimental system using a three-zone reactor configuration at normal and vacuum conditions.
Microreactor
TC
Pulse valve
Reactant mixture
Catalyst
Vacuum (10 -8 torr)
Mass spectrometer

Steady-State Normal Pressure
1
0.8
Cnv.Pr
Cnv.O2
AA
CO
CO2
AcA
Complete Oxygen
Conversion on the “upper” branch
Cooling
Regime
Oxygen
Conversion
0.6
High CO
2
yield on the “upper” branch
Propane
Conversion
0.4
CO
2
High AA yield on the “lower” branch
0.2
Acrylic Acid
CO
Acrolein
0
240 280 320
Temperature (˚C)
360 400
Figure 2. Conversion and yield versus temperature. Contact time = 3.5 s. Oxygen = 19.1%, propane = 9.2%, balance argon passed through water bubbler at 65

C

Elizabeth Maroon, Zhengjun Zhang, Michael Rude, Gregory S. Yablonsky
Department of Mathematics, Washington University
Department of Chemical. Engineering, Washington University

Pure Diffusion – is it Normally Distributed?

BIO-REACTORS, ENVIRONMENTAL

A Bioenergy-Based Bench-Scale Experiment for
Undergraduate Engineering Students Using Fermiol Super HA ®
Bia Henriques, Fan Mei, Kursheed Karim, Muthanna Al-Dahhan
Objectives:
To create an experiment for undergraduate chemical engineering students that exposes them to bioprocesses and biofuels
To give the students hands-on experience and knowledge about the dry grind corn to ethanol process
To determine the effects of different sets of parameters on the fermentation process
To study the effect of initial substrate concentration on ethanol production and yeast growth
To examine the following:
1) Effects of different yeast strains on fermentation
2) Optimization of parameters of a kinetic model and prediction of fermentation performance
3) Effects of various design and operation parameters on corn syrup fermentation and product inhibition
Accomplishments:
Studied the effect of substrate concentration on corn syrup fermentation using a specific strain of Saccharomyces cerevisiae
Collecting and analyzing data to validate existing kinetic models with and without the product inhibition term
Optimized batch model parameters using experimental data
Chemical Reaction Engineering Laboratory

Simulation and Design of a Process Control System for a Pilot
Plant-Scale Distillation Unit
Bia Henriques, Jonathan Lowe, Robert Heider, Terry Tolliver, Rachel Vazzi, Kwaku Opoku-Mensah
Objectives:
To simulate the distillation unit of SIU-E corn to ethanol pilot plant in HYSYS
To study the design of the distillation unit by configuring its process control system in
DeltaV
To interface HYSYS and DeltaV to provide optimum process and process control design to SIU-E
To study the behavior of the distillation unit’s control system and devise the best tuning method for the system
To create an interactive model of the distillation unit in order to teach operators how the system works for better use of controls
Accomplishments:
Created an interactive learning model of SIU-Es pilot plant distillation unit
Studied the effect of different tuning methods on the distillation process control
Developed interface to use process simulation in HYSYS to control the system in DeltaV
Optimized process performance by studying the behavior of the process control system
Modeled all piping and instrumentation equipment found in SIUE’s distillation unit
Chemical Reaction Engineering Laboratory

2004 CREL Annual Meeting
October 28, 2004
Chemical Reaction Engineering Laboratory (CREL)
Bioprocessing and Bioreactor Engineering Laboratory (BELL)





Breakdown of organic molecules by microorganisms to produce methane gas which can be used as an energy source
Waste management option that is a renewable energy source




Substrate and microorganism distribution throughout the reactor
Ensures uniform pH and temperature
Prevents stratification and scum accumulation in dilute waste slurry
Prevents accumulation of inert solids which decreases the active volume of a digester

Effect of mixing is not well understood. Past research shows contradictory findings

Objective:
Study the effect of mixing intensity, or applied shear, on digester performance, microbial ecology, and syntrophic relationships
Hypotheses:

Higher mixing intensities have a detrimental effect upon reactor stability.

Different mixing intensities selectively create different microbial communities within each reactor.

Higher mixing intensities break up and/or prevent the formation of larger flocs of syntrophic microorganisms

Objective:
Evaluate the UASR as a new approach for animal waste slurry digestion and bioenergy production, focusing on the effect of increased solids concentration on digester performance

M.N. May and R.L. Heider

– Co-product of dry grind ethanol process
– Used in animal feed
– Develop predictive models for chemical and physical properties of DDGS
• Improve quality of DDGS product
– Derive meaning from complicated data and detect trends
– Applicable in any industry to gain insight and answers to process questions





Chemical Reaction Engineering Laboratory (CREL)
Bioprocess and Bioreactors Engineering Laboratory (BBEL)
th
CHEMICAL REACTION ENGINEERING LABORATORY


Unsafe and improperly disposed
Level 2

Level 1





Surface & groundwater contamination
Ammonia leaching
153 mm 334 mm
Gas injection port
Methane emission
Odors
153 mm
50 Waste can be used to generate Methane
140 mm Methane = Energy, 1 m 3 biogas = 1.7 kWh of electricity
153 mm
Diameter
Level 1 mm

Biomass has applications of fertilizer and land fill
26mm 40 mm
40 mm
0
25 Angle
26mm
0
25 Angle

Gas mixed anaerobic bioreactors are found to most the popular choice.
CHEMICAL REACTION ENGINEERING LABORATORY
Objective of The Present Work

Prakash Kumar, M. P. Dudukovic, Da-Ren Chen, Richard Axelbaum, Ronald Indeck, Pratim Biswas
Biomedical Applications o
Biocompatible ferromagnetic particles for targeted drug delivery o
Selective deposition of magnetic particles for Tumor necrosis o
Magnetic particles guided by external magnetic field for Aneurysm treatment
SEM –γ Fe
2
O
3
Flame Reactor
Modified DMA
Key Results o X-ray diffraction and VSM results of the powder collected show the presence of pure

Fe
2 with high saturation
O
3 magnetization. o Flame pyrolysis of Iron pentacarbonyl gives
Maghemite, Ferrocene gives Magnetite; whereas
Iron nitrate gives Hematite.
oPost heat treatment of maghemite and magnetite showed to gradually transform to hematite at
500 o C.

• New Courses Added:
– New Product and Process
Development (ChE 450)
– Product Development
Methodologies (ChE 452)
• Unconventional Topics:
– Creativity and Innovation
– Intellectual Property
– The Theory of Inventive
Problem Solving (TRIZ)
– Design of Experiments
– Impact of the
Customer/Consumer
– Fermi Problems
– Product Focused Economics
• The Instructor:
– Nick Nissing, Adjunct Faculty
– Ex-P&G product development
– Patent agent
– Corporate IP Consultant
• How could we be useful to industry?
– Brainstorming?
– Consumer testing?
– New Product Ideas?
– In class or outside of class?