Reaction Engineering for

Environmentally Benign Processes

Reactor Selection Strategy

M.P. Dudukovic

Module 6

Homogeneous systems

Heterogeneous systems

Systems (multi-scale) approach

S1

Approach to Reactor Selection

1. Identify number of phases present at reaction

conditions (thermodynamics)

– Single – Homogeneous system

– Multiple – Heterogeneous systems

2. Identify stoichiometry, number of reactions,

energy requirements (e.g. adiabiatic temperature

rise/fall)

3. Identify mechanism (if possible) and plausible

reaction pathways and active intermediates

4. Decide on the purpose of reactor selection

Evaluation of kinetic data

Data for scale-up

Commercial designS2

Chemical Reaction Engineering BasicsMolecular Level

– Mechanisms and kinetic rates

Eddy (Particle) Level

– Micromixing & kinetics

– Intra phase diffusional effects (Thiele modulus,

effectiveness factor)

– Inter phase transport effectsReactor Level

– Ideal flow patterns (CSTR, PFR)

– Non-ideal flow patterns between phases

– Contacting patterns

– MixingS3

For Homogeneous Systems:

Identify the magnitude of heat transfer requirement

Assess the effect of ideal flow patterns on volumetric

productivity and selectivity

Select the best ideal flow pattern (batch, semi-batch,

continuous flow stirred tank reactor – CSTR, plug flow

reactor – PFR)

Optimize your objective function (related to profit) using

as manipulative variables:

- Feed reactant concentrations and their ratio

- Feed temperature

- Reactor temperature or temperature profile

Keep things simple whenever possible!

Approach the ideal by practical design as much as

possible.

S4

HOMOGENEOUS SYSTEMS

(Optimizing Volumetric Productivity)Batch Reactor

Plug Flow Reactor (PFR)

Continuous Flow Stirred Tank Reactor (CSTR)

FA0

CA0

FA = FA0(1-XA)

T = const.

FA0

CA0 FA = FA0(1-XA)

0

imereaction t down timeshut

unit timeper reacted

A of Moles

1,

,00

0

0

A

A

C

C A

As

s

AA

AAA

AA

R

dCtt

tt

VXC

XCCtt

CCt

VRXF AAA

0

unit timeper reacted

A of Moles

AX

A

A

A

AAA

R

dX

XV

VRXF

0

0

]1

/[

unit timeper reacted

A of Moles

S5

where is the ratio of stoichiometric coefficients

Volumetric Productivity for Product P then is

lumereactor vo

unit timeper produced of moles P

V

Fp

A

CSTR

pR

a

p

V

F

For CSTR

AX

A

A

A

A

PFR

p

R

dX

X

apR

a

p

V

F

0

1For PFR

ap

The ratio of volumetric productivities in the two systems

A

A

CSTRp

PFRp

R

R

VF

VF

Is the ratio of average reaction rate in a PFR and the reaction rate at exit

conditions of the CSTRS6

Homogeneous Systems (optimizing selectivity)

A + B P desired product2nd Order

A + A S undesired product2nd Order

• Which is the optimal flow pattern ?

• What is the optimal selectivity ?

(at fixed feed concentrations, feed ratio of FA0/FB0 and conversion of B)

BPFR

A P+S

A P+SPFR

B

B P+SPFR

A

B

A P+S

initially only B

A

initially only A

B

S7

In multiple reactions it is useful to consider the point yield behavior

reactantkey of ncedisappeara of rate

product desired offormation of rate

A

R

R

R

exitAAoexitR CCC Then in CSTR

Ao

exitA

C

C

AR dCC While in PFR

Production rate of R is maximized: In a CSTR for systems with d/dCA<0 (undesired reactions of higher

order than the desired one)

CA

CA

CA

In a reactor combination for nonmonotonic yield curve

In a PFR for systems with df/dCA>0 (undesired reactions of lower

order than the desired one)

S8

Other Simple Rules Worth Remembering

In consecutive reactions production of intermediate is always more favored in a PFR than in a CSTR

For exothermic reactions maximum volumetric productivity is reached at an optimal temperature which is a function of conversion

When desired reaction has the highest activation energy select the highest temperature for best selectivity

When desired reaction has the lowest activation energy lowest practical temperature optimizes selectivity

For intermediate activation energy of desired reaction an optimal temperature or temperature profile can be found

For lumping complex reaction schemes into patterns to

analyze see Levenspiel, O., Chem. React. Eng.

S9

Avoid!Bad!

model seriesin or tanks dispersionby Model

1

10

1

01

stagnancy indicate uesLesser val

2

2

o

2

2

2

o

CSTR

PFRdttEtt

t

Q

VdttEtt

Recognize that selected ideal flow patterns may only be approached in

practice.

Determine the deviation from ideal flow patterns by examining the residence

time distribution (RTD) of the system either derived from the solution of the flow

field or experimentally determined on a reactor prototype (cold flow model), pilot

plant or on the actual unit.

tdttE around timeresidence of outflow offraction

tdttE about timeresidence of outflow offraction

E

t

E

t

E

tt

PFR CSTRBetween

PFR & CSTR

exponential

decay

tt

S10

oA

AoR

R

C

Characteristic reaction time

system dominated mixing-effect microscale Strong5

slimitation transportmicroscale No3.0

R

D

R

D

massunit per disspatedenergy

viscositykinematic41

3

K

In between micromixing models needed!

2

DD

KD

Characteristic diffusion time

In scale-up of systems with broad RTD we need to assess whether

transport limitations can develop on a micro-scale (i.e. in bringing reactants in

contact or in supplying them to the soluble catalyst, enzyme or cell). This is

particularly important for non-premixed feeds.

We need to assess the scale of the smallest turbulent eddies in the system which is

determined by the amount of energy dissipated per unit mass of the system. For

example

2.02

molecular diffusivity

S11

All reactions with R > O(1 second ) will not cause transport limitations.

Reactors with large can be considered in maximum mixedness condition2

s

D

kD

1

5

232

1010

10

mOk 10:SolutionWater

Only reactions with R > 105(s) will not cause transport limitations.

For most systems mixing and reaction occur simultaneously and proper micromixing

model is needed.

Proper treatment of this topic is not available in most standard reaction engineering

text. References and related notes can be obtained upon request.

s

D

KD

4

8

222

1010

10

Example:

mOk 100:Solution ViscousHighly

S12

o

batch

batchFS

AAA

A

o

AA

CCtRdt

dC

dttEtCC

0where

..

1. Segregated Flow – All fluid elements remain segregated by

age on their sojourn through the system and elements of

different ages mix only at the exit.

Two extreme micromixing models are:

0

solvingby obtained0..

d

dC

CC

dttE

ER

d

dC

CC

A

AA

t

A

A

AA

o

MM

2. Maximum Mixedness – All fluid elements of same life

expectancy are together at all times.

S13

Micromixing EffectA P 1st order

k1

2A S 2nd orderk2

k2CA0/k1 = 0.5

Reactions:

System: CSTR, = 48 min; Exponential RTD

Laboratory System: 1 L vessel, 1500 rpm

Large System: 5000 gallon vessel; 300 rpm

Selectivity in the Lab.: CP/CS = 98 at XA= 0.98

Selectivity in the Large Unit: CP/CS = 15 at XA= 0.98+

Model Predictions:

Maximum Mixedness Flow: CP/CS = 100

Segregated Flow: CP/Cs = 4.5

t

S14

Key issues associated with selection and scale-up of reactors for

homogeneous reactions

Developing sufficient knowledge of molecular level events to propose mechanism and establish reaction pathways, key reactions and their parameters.

Determining optimal ideal flow pattern and maintaining the same flow pattern (same and with scale-up).

Avoiding bypassing and stagnancy with scale-up.

Maintaining same level of micromixing with scale-up is needed but hard as power dissipated per unit volume decays with scale and affects micromixing adversely.

Maintaining adequate heat transfer rate with scale-up is difficult as heat evolved by reaction volume and heat removed surface. With scale-up in general S/V is reduced which may lead to problems unless corrective steps are taken.

Control of temperature, pressure, pH etc. becomes more difficult with increased scale.

Homogenous catalyst or soluble enzyme recovery, a cinch in the lab, becomes a major chore in large units.

Solvent separation is a problem.

t2

Heterogenize the system whenever possible, do not use solvents unless

absolutely necessary!S15

The objective in multiphase reactor selection and design is to minimize

the manufacturing costs in producing the desired marketable product.

For conversion cost-intensive processes one must achieve both high

volumetric productivity and high product concentration.

lumereactor vo -

weightmolecular -

rate productionmolar -

typroductivi c volumetri-

3

3

mV

kmolkg

hkmolF

hmkgm

p

p

v

For recovery cost intensive processes (e.g. often encountered in

biotechnology) one must achieve high product concentration cp(kg/m3).

ionconcentratmolar 3

mkmolc

Cc

p

ppp

In either case proper reactor selection is required since reactor type and

performance affects significantly the whole process.

VFm ppv

S16

)T,C(R)C(L bbb

j

bbjjRbh )T,C(R)H()C(Lj

transport;kineticsf

00 P,C,T

P,C,T

feed, Q

product, Q

Reactor performance determines the number of separation units and their load and

hence profoundly affects process economics and profitability.

Pattern

Mixing; Rates;

Variables Operating

andInput

ePerformanc

Reactorf

-Conversion - Flow Rates - Kinetics - Macro

-Selectivity - Inlet Conc. & Temp. - Transport - Micro

-Production Rate - Heat Removal

LHS RHS

Volume

Reactor

RateReaction

Averaged Volume

Rate

Production

S17

In heterogeneous systems the volume averaged reaction

rate (volumetric productivity) is a function of:

Molecular scale – kinetics and rate forms

Single particle (single eddy) scale effects on diffusion and

reaction in the particle, specific phase interfacial area

effect on inter-phase mass and heat transfer

Reactor scale effect via contacting pattern and phase RTD

influence on the average rate and via flow regime effect on

phase holdups and inter-phase transport coefficients.

S18

As a reminder consider the diffusional effects on the rate in a porous particle with

uniformly deposited active catalyst in pores

sApparticleA RR

p

p

p

h

tan

Conditions Surface

Outside Particle

at Evaluated Rate

Factor

essEffectiven Particle

Particle of

VolumePer Unit

Rate Average

Where typically

pWith Thiele modulus

p

p

p

R

Dp

S

V

2

True kinetics, activation energy is observed. Doubling catalyst activity doubles the rate.

Rate independent of Sp/Vp

1 -

0.1 -

0.01 -

0.001 -

10-4 -

0.01 0.1 1.0 10 100 1000

| | | |

p

p

SAparticleAp RR 0

2

11

n

A

p

p

eA

p

particleAp SSC

V

SDkCR

Approximately ½ E observed. Reduced order

2121

1

.loadingcatalst ,activitycatalyst ;

p

p

partAS

VR

S19

Now one must also consider inter-phase transport

ppsAAAps VRCCSksb

ppvps

A

bulkApartobsA

VkSk

CRR b

110

And for first order reaction one gets

The denominator contains the sum of external resistance and internal +

kinetic resistance.

Of course we need the rate per unit reactor volume so

Clearly how much catalyst we packed in (bed voidage B) affect also

volumetric productivity.

Finally flow pattern will affect how (-RA)bulk is averaged and flow pattern

affects transport coefficient ks.

2

11

n

A

p

p

eA

p

particleAp SSC

V

SDkCR

Approximately ½ E observed. Reduced order

2121

1

.loadingcatalst ,activitycatalyst ;

p

p

partAS

VR

bulkAoBreactobsA RR 1

S20

1 :REACTION PlBgA

Gas Limiting Reactant (Completely Wetted Catalyst)

pvBpsBl

A

g

H

g

BvoA

slp

a

g

B

sBpv

Av

kakaK

H

A

AkR

sreactmmol

AAa

AH

Aa

sreactmmol

sreactmmolAk

scatmmolAk

A

1

1111

:. RATE (APPARENT) OVERALL

k:solid-Liquid -

K:liquid-Gas -

lumereactor vounit per

. RATE TRANSPORT

lumereactor vounit per

.1 : CATALYST IN RATE

olumecatalyst vunit per

.: RATE KINETIC

3

s

11

3

3

3

S21

A System Approach to Multiphase

Reactor Selection

Process Requirements

• Maximum selectivity

• Maximum conversion

• Maximum productivity

• Stable

• Easy scale-up

• Operability

Environmental Constraints

• Minimum pollution

Why System Approach?

• Number of configurations extremely large

• Limits to intuitive decision making

• Innovations are possible

Reactor Type

&

Contacting Pattern?

Economics

Reactants Products

S22

Multiphase Reactor Selection Methodology

I. Volume / Interfacial Area for the Phases

~ dp for gas-solid systems

~ b for gas-liquid systems

~dp and b for G-L-S systems

II. Contacting & Flow Pattern

a) RTD for each phase (PF, backmixed)

b) Co – Counter – Cross current?

c) Split addition

Product removal in situ, etc.

III. Flow Regime

Homogeneous

Churn turbulent

Dense phase riser (air lift)

Dilute phase riser (spray) S23

Example: Recovery of Oil From Oil Shale

Process Requirements (Wish List)

• Maximize “oil” recovery (99%+)

• Scale-up to mega-size units ( 500 kg/s feed)

• Minimize reactor volume

• Handle fines well

>200 G-S Reactor Configurations possible!After Krishna (1989) S24

S25

Shell’s SPHER 3

Bed Concept

Chevron’s STB

(staged turbulent bed)

S26

Decisions to be made:

I. Particle Size

II. Contacting Pattern

III. Gas-Solid Fluidization Regime

a. Overall contacting flow pattern of gas and solid phases:

b. RTD of each phase:

Krishna (1992), Adv. Chem. Eng. S27

Kinetics & Transport Phenomena

Affecting Process Performance

Oil Shale Pyrolysis

Wallman et al (1980), AIChE Meeting, San Francisco S28

Large throughputs minimize reactor

Volume need small residence times need particles in

range I need plug flow of solids

Residence time required for heating up of particle to

95% of Tg = 482°C

Residence time required for isothermal backmixed reactor

(174 min)

Conversion of kerogen 99%

Residence time required for isothermal plug flow reactor

(8 min)

S29

Desired product (heavy oil) yield improved with

small particle size (dp < 2mm).

In grinding shale to make 2mm particles fines

may be formed too.

S30

III. Flow

Regime

Selection

Tree

II. Contacting

Flow Pattern

Selection

Tree

I. Particle

Size

Selection

Tree

S31

Wilkins et al (1981), 2nd World Congress, Montreal

To reduce oil degradation, must remove oil as soon as

formed in situ product removal

S32

A. Counter-Current Contacting

B. Co-Current Contacting

C. Cross-Current Contacting

Reactor volume requirement need plug flow of solids

Rapid oil removal cross flow for gas S33

Proper fluidization regime should now be chosen to

accommodate:

• Desired particle size (small)

• Desired solids holdup (large)

• Desired contacting pattern (solids-plug flow, gas short

contact time)

• Excellent heat transfer

S34

The “Ideal” Reactor:

Multi-Stage Cross-Current Fluidized Bed

Meets the criteria:

• Small particles

• Plug flow of solids

• Short vapor residence time (cross-flow)

• Good mixing and heat transfer

• Scale-up possible – study one train

Shell Shale Retorting Process

(Shell Research)Krishna (1992) S35

For Shale ExamplePossible Reactor Combinations

regimes

onfluidizati

pattern

contacting

solid-gas

range

size

particle

1955133

• Sequential design making leads to success without brute force

evaluation of all options.

Choice of wish list effects final result. Add:

Choice should be based on known technology

Moving bed reactor

S36

This example illustrates how consideration of all

scales leads to successful reactor selection

It also teaches that in situ separation when

possible is of high value and can sometimes be

achieved by:

Catalytic distillation

Selective adsorption or absorption

Membrane separation

Other means (e.g. dynamic reactor operation, etc.)

Think Out of the Box!

S37

Clearly is determined by transport limitations and by

reactor type and flow regime.

Improving only improves if we are not already transport

limited.

Our task in catalytic reactor selection, scale-up and design is to

either maximize volumetric productivity, selectivity or product

concentration or an objective function of all of the above. The key

to our success is the catalyst. For each reactor type considered

we can plot feasible operating points on a plot of volumetric

productivity versus catalyst concentration.

vm

aS

vm

maxvm

maxx x

maxxmaxvm

aS

ionconcentratcatalyst

activity specific

3

reactorm

catkgx

hcatkg

PkgSa

S38

Chemists or biochemists need to improve Sa and together with engineers work on

increasing maxx .

Engineers by manipulation of flow patterns affect maxvm .

In Kinetically Controlled Regime

vm aSx,

maxx limited by catalyst and support or matrix loading capacity for cells or

enzymes

In Transport Limited Regime

vm pp

a xS ,

2/10 p

Mass transfer between gas-liquid, liquid-solid etc. entirely limit vm and set maxvm .

Changes in ,aS do not help; alternating flow regime or contact pattern may help!

Important to know the regime of operation

S39

Schematic of Bubble Column Type of

Photo Reactors (Commercially Used)

A train of bubble columns (sparged reactors) through which liquid

toluene and chlorinated products flow in series while chlorine is added

into each column and hydrogen is removed from the column.

Typical selectivity to benzyl chloride: 90% But Toluene conversion is

less than 30%. Can one do better?S40

Schematic of Photo Reactive Distillation SystemConfigured into a Semi-Batch Model

Allows in situ product removal

and toluene recycle.

Selectivity to benzyl chloride: 96% + up to toluene conversion of 98%.

Z. Xu (1998) S41

PROBLEMProduction of herbicide intermediate, aryl

amino-alcohol (AA) via hydrogenation of

aryl nitro-alcohol (NA)

Reaction System: complex

Current Reactor: semi-batch dribbling liquid reactor with

suspended catalyst slurry

DISADVANTAGES: Low volumetric productivity

Poor selectivity

Catalyst filtration and separation

problems

Pressure limitations (due to shaft)

Khadilkar et al., AIChE J., 44(4), 912 (1998)

Khadilkar et al., AIChE J., 44(4), 921 (1998) S42

Reaction Network

S43

Conclusions Liquid trickling flow pattern is preferable to a suspended

catalyst mixed slurry to obtain the desired yield and productivity of Amino Alcohol.

Yield improvement is observed with decreasing feed concentration, liquid flow rate and temperature due to suppression of NA decomposition and subsequent side reactions.

Productivity of AA is a complex function of flow, feed concentration and temperature with optimal productivity being determined by the level of acceptable by-product concentrations.

Laboratory trickle bed performance data is shown to be an effective means to obtain the network kinetic parameters by proposing a plausible mechanism and optimizing the reactor model generated data. This is particularly effective in cases where conventional slurry and basked methods are rendered ineffective by the dominance of side reactions.

S44

References

1. Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Reactors – Revisited”, Chem. Eng. Science, 541, 1975-1995 (1999).

2. Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Catalytic Reactors: A Perspective on Current Knowledge and Future Trends”, Catalysis Reviews, 44(11), 123-246 (2002).

3. Levenspiel, Octave, Chemical Reaction Engineering, 3rd

Edition, Wiley, 1999.

4. Tranbouze, P., Euzen, J.P., “Chemical Reactors – From Design to Operation”, IFP Publications, Editions TECHNIP, Paris, France (2002).

S45