Catalytic Reduction of CO2 Into Hydrogen Using Micro Reactors
Catalysts and Catalytic Reactors, Catalytic Reactor Models_ Fixed Bed Reactors
Transcript of Catalysts and Catalytic Reactors, Catalytic Reactor Models_ Fixed Bed Reactors
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Lecture 7
Catalysts and Catalytic Reactors
Catalytic reactor models: Fixed Bed reactors
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The choice of catalyst is very important
but still largely empirical.
• Most processes use a catalystCatalysts increase the rate of reaction but are unchanged in quantity
and chemical composition at the end of the reaction.
Catalysts for multiple reactions: the catalyst may have different effects
on the rates of the different reactions
Catalysts need to be developed that increase the rate of the desiredreactions relative to the undesired reactions
CATALYSTS
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• The reactions proceeds entirely in the vapour or liquid phase• The catalyst may modify the reaction mechanism by participation in the
reaction but is regenerated in a subsequent step. The catalyst is then free
to promote further reaction
E.g. Production of acetic anhydride
CH3COOH CH2=C=O + H2O acetic acid ketene water
Catalyst : triethyl phosphate
• The catalytic process can beHomogenous
Heterogenous
Biochemical
(i) Homogeneous Catalyst
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• The reaction rate of catalysed reactions is more complex than that
of uncatalysed ones.
• The overall rate of a heterogeneous gas-solid reaction is made up
of a series of physical steps as well as the chemical reaction.Mass transfer of reactant from the bulk gas phase to the external solid surface
Diffusion from the solid surface to the internal active sites Adsorption on solid surface
Activation of the adsorbed reactants
Chemical reaction
Desorption of products
Internal diffusion of products to the external solid surface
Mass transfer to the bulk gas phase
all these steps are rate processes and are temperature dependent rate controlling step : the step that is slower than the others
Heterogeneous Gas-Solid Reaction Rate
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• The optimal performance of the catlayst is obtained by locating the
Dirac Delta catalyst distrubtion so as to maximize the reaction rate by
taking advantage of both temperature and concentration gradients
within the pellet.
• Location of Dirac Delta Function to be optimsed.In practice, step function is used for Dirac Delta Function
the ratio of the observed rate to that which would beobtained if the whole of the internal surface of the pelletwere available to the reagents at the same concentrationsas they have at the external surface
Effectiveness Factor
• Effectiveness factor =
0 1
Less than 5 % of thecharacteristic dimensionof the pellet
(b) Step function.0 1
(a) Dirac delta function.
(Morbidelli, Gavriilidis and Varma (2001) Catalyst Design: Optimal Distributionof Catalyst in Pellets, Reactors and Membranes, Cambridge University Press).
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Solid-catalysed reactions
• Usually, multiple reactions
• The gross flow pattern of fluid through reactor should be
considered
• For parallel reactions
Maintaining the appropriate high or low concentration and temperature levelsof reactants at the catalyst surface
- Encourage the desired reaction
- Discourage the byproduct reaction
• For series reactions
Avoiding the mixing of fluids of different compositions
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Local non-homogeneity of catalyst
• Lowered reactant concentration or change in temperature within the catalyst
pelletsThe concentration and temperature in the interior of catalyst pellets may differ from the
main body of the gas
Different product distribution from that for homogenous system
• Two extremes for local non-homogeneitySurface reaction controls
concentrations of reactant inthe main gas stream
concentrations of reactantat the catalyst surface
Diffusion controls
concentrations of reactant inthe main gas streamconcentrations of reactantwithin the pellets
When the desired reaction is of lower order,operating under conditions of diffusion controlincreases selectivity
The gross flow pattern of f luid through the reactor would be considered
Lowered reactant concentrationfavours the reaction of lower order
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Selectivity for solid catalysed reactions
Optimum selectivity given by Dirac Delta Function
Step function can be used in practice
Need to optimize the location of the step function within the
catalyst pellet
(Morbidelli, Gavriilidis and Varma, (2001) Catalyst Design: Optimal Distribution of Catalyst in Pellets, Reactors and Membranes, Cambridge University Press)
Practical difficulties in producing catalyst pellets with preciselocation of catalyst step function
Deterioration of catalyst performance with time needs to beconsidered
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Temperature Control
• Adiabatic operation leads to the simplest and cheapest reactor
designTemperature control is required for
- Unacceptable temperature rise for exothermic reactions
- Unacceptable temperature fall for endothermic reactions
• Temperature control for adiabatic operationCold shot or hot shot : the injection of cold or hot fresh feed directly into the
reactor
- Temperature control by direct contact heat transfer
- Concentration control of feed material to adjust the rate of reaction
Indirect heat transfer with the reactor: indirect heating or cooling
- Heat transfer takes place inside the reactor or
- Material is taken outside of the reactor to a heat transfer device and returned to the
reactor.
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Example of Temperature Control (I)
• Temperature control for adiabatic operation (continued)
Heat carrier : An inert material can be introduced with the reactor feed- to increase the feed CP (mass flowrate multiplied by specific heat capacity)
- to reduce the temperature rise or fall for reactions
When possible, the existing process fluids should be used as heat carriers Product or byproduct recycling as a mean of temperature control should not have
a detrimental effect on the selectivity of the reaction.
Catalyst profiles- Change of the distribution of active material in the catalyst bed or
- Use a different catalyst in different parts of the reactor or
- Use a mixture of catalyst and inert solid to ‘dilute’ the catalyst
Easy to control the rate of reaction in different parts of the bed
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Example of Temperature Control (II)
Lowconcentration
Reactionproceeds
Highconcentration
REACTANTS
CoolingMedium
PRODUCTS
Reactionproceeds
Coolingmedium
Catalyst
Catalystarrangement
with gradient
Better temperaturecontrol
Feedconcentration
Cooling duty
Heat releasefrom the reaction
Reactor inlet Reactor outlet
Tubular Reactor
• Exothermic reaction with non-uniform catalyst performance
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Example of Temperature Control (III)
Tubular reactor
CO + 2H2 CH3OH
CO2 + H2 CO + H2O
REACTANTS
STEAM
CATALYST
BOILEDFEEDWATER
PRODUCTS
• Production of methanol
230 250 270 OC
Gas inlet temp
water temp
4OC
: Exothermic reaction
: Endothermic reaction
Temperature profile is relatively smooth
Cold shot reactor
REACTANTS
CATALYST
PRODUCTS230 250 270 O C
30OC
Significant temperature f luctuations Accidental catalyst overheating and
shortening of catalyst life
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Quenching of Reactor Effluent
• The reactor effluent may need to be cooled rapidly, or quenched , byIndirect heat transfer : conventional heat transfer equipment
Direct heat transfer : mixing with another fluid
e.g. Cooling of gaseous products mixed with a liquid.
The cooling is accomplished by mixing with a liquid that evaporates.
• Reasons to use quenching with direct heat transfer The reaction is very rapid and must be stopped quickly to prevent excessive byproduct formation.
The reactor product cooling would cause excessive fouling in a conventional exchanger.Special materials-of-construction or an expensive mechanical design is required because the
reactor products are so hot or corrosive.
• The liquid used for the direct heat transfer should be easy to separate from the
reactor product.
• Use of extraneous materials for the direct quenching may be used.
But it should not
Create additional separation problemsDegrade the specifications of product purity
Cause additional environmental problems
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Choosing Heat Transfer in the Reactor
HeatCarrier
HeatCarrier
Is AdiabaticOperation
Acceptable ?
Yes
No
Is IndirectHeat Transfer
Feasible ?
Yes
No
Is HighTemperatureor High FluxRequired ?
Yes
No
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• Catalytic degradation can cause a loss of performancePhysical loss
- Homogenous catalysts : generally important
- Heterogenous catalysts : particularly for catalytic fluidized bed reactors
Attrition of the particles causes the catalyst particles to be broken down
Surface deposits
- The formation of deposits on the surface of solid catalysts introduces a physical barrier to the reacting
species.
- Most often, the deposits are insoluble or non-volatile. e.g. Coke formation (carbon deposits) in hydrocarbon reactions
suppression by adjustment of feed composition or regeneration by air oxidation at elevated temperatures
Sintering : molecular re-arrangement below the melting point
- Sintering causes a reduction in the effective surface area of catalyst.
- Sintering results from high temperature reaction / poor heat transfer / poor mixing of reactants / catalyst
regeneration at high temperature
Poisoning- Usually impurities in the raw materials or products of corrosion chemically react with or form strong
chemical bonds with the catalyst
Chemical change
- some catalysts can slowly change chemically with a consequent reduction in activity
Catalyst Degradation
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Effects of Catalyst Degradation
• Catalyst degradation is important for :the choice of catalyst
reactor conditions
reactor configuration
• Deterioration in catalyst performance lowers the rate of reaction.
• Increasing the temperature of reactor gradually can be used to compensate for the deterioration in performance.
High temperature can decrease selectivity considerably and often accelerate the catalyst
degradation.
• The reactor configuration must make a provision if degradation is rapid.Use standby capacity or
Removal of catalyst from the bed on a continuous basis
The lost or degraded catalyst implies cost and environmental impacts.
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Types of catalytic reactors: Fixed-bed reactors
•
Major part of catalytic processes carried out in fixed-bed reactors
–
With the exception of catalytic cracking of gas-oil
• Carried out in fluidised beds
–
Typical fixed bed industrial processes include:
Chemical
industry
Petrochemical
Industry
Petroleum refining
Steam reforming Ethylene oxide Catalytic reforming
CO conversion Ethylene
dichloride
isomerization
Synthesis: Vinyl acetate polymerization
Sulfuric Acid butadiene hydrodesulfurisation
Methanol Maleic anhydride hydrocracking
Oxo cyclohexane
ammonia styrene
hydrodealkylation
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Technical innovations•
Fixed-bed reactors are large capacity units – To address high market demands – Made possible by progress in both technical and fundamental areas
•
Introduction of better materials of construction – E.g. centrifugal cast 25% Cr 20% Ni steel tubes to increase operating T’s and
throughput
• Better design of reactor internals to improve the rate of uniformity of heatremoval
– By molten salts
• Better design techniques allowing construction of multi-bar reactors withapprox 20,000 tubes of large diametre.
•
Modification of auxiliary equipment increase the capacity of establishedprocesses such as ammonia synthesis – Centrifugal compressors
• Flow pattern modifications – Use of radial flow reactors to reduce pressure drop and enhance recycle capacity
of compressor
• Use combinations of small catalyst particles to enhance heat transfer and oflarge catalyst particles to limit pressure drop
• Design of improved control scheme
•
Development of new catalysts and modifications of existing ones – Formulation of stable low P methanol synthesis catalyst
– Introduction of low T CO shift catalyst
• Availability of more reliable kinetic data and physicochemical data – Advanced experimental design techniques
– Improved methods in data analysis
• Improved reactor models
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Fixed-bed reactor models
• Principles of general models
–
Models of variable complexity –
Required degree of sophistication depends on specific process• Kinetic reaction scheme• Sensitivity to perturbing operating conditions
–
Both macroscale and microscale issues• Microscale deal with catalyst particles and sites• Macroscale mainly determined by hydrodynamics
–
Plug flow enough or more accurate?
• Model classification in two big categories: –
Pseudohomogeneous models:• Do not expliciltly account for the presence of catalyst
–
Heterogeneous models:• Separate conservation equations for fluid and catalyst
–
Models can be 1-D or 2-D• 2-D models account for variations in radial dimension
– Mixing in axial directions to account for non-ideal flow conditionscan be included
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1-D pseudo-homogeneous model
• Concentration and T gradients only occur in axial
direction• Overall transport mechanism: plug flow
• Conservation equations:
– S.S. and single rxn in tube:
•
I.Cs: at z=0, C A=C A0, T=T0, pt=pt0
•
dp is the equivalent particle diameter, us the superficialvelocity, !g the gas density, U the overall heat transfercoefficient, dt the internal tube diameter, Tr the ambient T, !B the catalyst bulk density and f the friction factor
p
s g t
r
t
B A P g s
B A A s
d
u f
dz
dp
T T d
U Hr
dz
dT cu
r
dz
C ud
2
)(4
)(
!
! !
!
="
""#"=
="
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1-D pseudo-homogeneous model (contd)Heat transfer coefficient
• Overall heat transfer coefficient
– ai =heat transfer coefficient on the bed side (kJ/m2soC)
–
au= heat transfer coefficient, transfer medum side (kJ/m2soC)
– Ab= heat exchanging surface, bed side (m2)
– ! = heat conductivity of the wall (kJ/m-hr oC)
– Au= heat exchanging surface, heat transfer medium
side (m2) – Am= log mean of Ab and Au (m
2)
u
b
um
b
i A
A
a A
Ad
aU
111++=
!
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1-D pseudo-homogeneous model (contd)Pressure drop
•
Pressure drop equation for flow through packed beds: –
Ergun 1952
–
Bed of connecting parallel channels with hydraulic radius R h= " / # v• " = void fraction
•
# v = surface solid per m3 bed
–
Equivalent particle diameter, d p, diameter of sphere with the samesurface area per unit volume as actual particle, Sv = # v / (1- " )
–
So d p=6 (1- " ) / # v –
Ergun proposed:
• "=1.75 and b=150
• Handley and Heggs (1968) derived: "=1.24 and b=368
•
Hicks (1970) found that Ergun’s equation is limited to Re / (1- " ) < 500 – Handley and Heggs’ equation to 1000 < Re / (1- " ) < 5000
!"
#$%
& '++
'=
Re
)1(13
(
(
( ba f
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1-D pseudo-homogeneous model
with axial mixing
•
Mixing in the axial direction – Due to turbulence and presence of packing
– Accounted by superimposing an effectivetransport mechanism
•
On overall transport by plug flow
–
Flux due to this mechanism analogous toFick’s law for mass transfer, Fourier’s law forheat transfer
• Proportionality constants effective diffusivities,conductivities
• They implicitly contain the effect of the velocityprofile
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1-D pseudo-homogeneous model
with axial mixing (contd)
• Steady-state mass balance for component A:
• Energy equation:
• The b.c.s used in general are:
02
2
=!! B A
A
s
A
ea r
dz
dC u
dz
C d D " #
( ) 0)(42
2
=!!"!+! r t
B A P g sea T T d
U r H dz
dT cudz
T d # # $
L z for dz
dT
dz
dC
z for dz
dT T T cu
z for dz
dC DC C u
A
ea p s g
Aea A A s
===
=!=!
=!=!
0
0)(
0)(
0
0
" #
$
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1-D pseudo-homogeneous model
with axial mixing (contd)
•
Two-point boundary value problem•
Effect of axial dispersion for heat and mass onconversion – Negligible when bed depth > 50 particle diameters
–
More accurately, for monotonically decreasing rate:•
Axial dispersion negligible when:
–
Addition of axial mixing leads to the possibility of steadystate multiplicity for adiabatic case
ha
p g sw
p B A
ma
s
p B A
Pe
cuT T
d r H
PeC u
d r
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2-D pseudo-homogeneous model
•
1-D models neglect resistance to heat and mass transferin radial direction
–
Predict uniform temperatures, conversions in cross-section
–
Problem for rxns with high heat effects
• 2-D model here uses effective transport concept
–
In r-direction –
Effective diffusivity non-isotropic
• Radial component different from axial component
• Based on flow characteristics
–
Effective conductivity #e decreases strongly near the wall
• Can consider #e
constant away from wall and introduce newcoefficient for heat transfer near the wall
w
er W Rw
dr
dT T T a !
"
#$%
&'=' ( )(
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2-D pseudo-homogeneous model (contd)
• Mass balance for single component A
• Energy balance
•
B.C.s
•
Note that (Der )s=$Der and #er based on superficial flow velocity
0)1
()(2
2
=!!+ B A
A
s
A A
ser r
dz
dC u
dr
dC
r dr
C d D "
( ) 01
2
2
=!"+"##$
%&&'
(+ B A P g ser r H
dz
dT cu
dr
dT
r dr
T d ) ) *
z Rr at T T a
dr
dT
z r at dr
dT
z Rr and r at dr
dC
Rr z at T T
Rr z at C C
W R
er
w
A A
!=""=
!==
!===
##==
##==
,)(
,00
,0,00
0,00,0
0
0
$
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1-D heterogeneous model
accounts for interfacial gradients •
Very rapid rxns with high heat effects
– Need to distinguish between conditions in the fluid and
on catalyst surface
•
Even inside catalyst
–
Can have 1-D or 2-D models• Steady state mass and energy balances for single rxn:
–
For fluid:
–
For solid:
)(4)(
)(
r
t
s
sv f P g s
s
sv g A
s
T T d
U T T ah
dz
dT cu
C C ak dz
dC u
!!!=
!=!
"
)()(
)(
T T ahr H
C C ak r
s
sv f A B
s
sv g A B
!="!
!=
#
#
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1-D heterogeneous model
accounts for interfacial gradients (contd)
•
B.Cs: at z=0, C=C0 and T=T0• k g =mass transfer coefficient from gas to solid interface
• # v =external particle surface area per unit volume
•
hf =heat transfer coefficient for film surrounding particle
• Most likely interfacial gradient to occur is
temperature gradient•
Compared to the corresponding pseudo-homogeneous 1-D model – Fluid/solid intrerface can lead to multiplicity of steady
states
•
Heat produced in the catalyst: sigmoidal curve•
Heat removed by the fluid through the film: straight line – 3 steady states arise from their intersections
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1-D Heterogeneous model accounting for
interfacial and intraparticle gradients
• When resistance to mass and heat transfer inside particleis important
–
Rate or rxn not uniform throughout particle
–
Equations describing concentration and temperature gradients
inside particle are needed
–
Steady state mass and energy balances for single rxn become:
• Fluid:
•
Solid:
)(4)(
)(
r
t
s
sv f P g s
s
sv g A
s
T T d
U T T ah
dz
dT cu
C C ak dz
dC u
!!!=
!=!
"
0),()(
0),(
2
2
2
2
=!"+##$
%&&'
(
="##$%
&&'(
s s A s
se
s s A s
se
T C r H d
dT
d
d
T C r d
dC
d
d D
) *
* * *
+
) *
* * *
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1-D Heterogeneous model accounting for
interfacial and intraparticle gradients
(contd)•
B.Cs: C=C0 T=T0 at z=0
• A single particle is considered not whole solid
•
The shape of particle also determines values for De and #e
•
Set ODEs describing intra-particle gradients need to be integrated at
each computational node of the fluid – Computationally tedious
•
Even with strongly exothermic rxns particle practically isothermal
– Main resistance inside the pellet to mass transfer
2)(
2)(
00
p se
s
s f
p se
s
s g
s s
d at
d
dT T T h
d at
d
dC DC C k
at d
dT
d
dC
=!=!
=!=!
===
" "
#
" "
" " "
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1-D Heterogeneous model accounting for
interfacial and intra-particle gradients Effectiveness factor
•
When gradients occur inside particle use effectiveness factor %
–
Multiplies rxn rates at particle surface conditions
• To account for rate actually experienced when conditions insideparticle are different
•
System then becomes:
–
Fluid:
–
Solid:
•
Effectiveness factor depends on Thiele modulus f and needs to becomputed at each computational node
)(4)(
)(
r
t
s
sv f P g s
s
sv g A
s
T T d
U T T ah
dz
dT cu
C C ak dz
dC u
!!!=
!=!
"
)(),()(
)(),(
T T ahT C r H
C C ak T C r
s
sv f s s A B
s
sv g s s A B
!="!
!=
# $
$#