tap temporal analysis of products · tap – transient response data in contrast to traditional...
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TAPTemporal Analysis of Products
SSITKA Steady State Isotopic Transient
Kinetic Analysis
Modern Methods in Heterogeneous Catalysis
Cornelia Breitkopf, 14.11.2003Universität Leipzig, Institut für Technische Chemie
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Transient methods are a powerful tool for gaining insights into the mechanisms of
complex catalytic reactions.
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Outline
• Microkinetic modeling• Laboratory reactors• Background
Diffusion, mathematics• TAP
System hardware, theory, examples• SSITKA
Theory, examples
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Macrokinetics and Microkinetics
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Kinetic measurements
Complexity of heterogeneously catalyzed reactions –Macrokinetics and Microkinetics
O. Deutschmann, XXXIV. Jahrestreffen Deutscher Katalytiker/ Fachtreffen Reaktionstechnik, Weimar 21.-23.3.2001
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Microkinetic modeling
J.A.Dumesic
„Microkinetic analysis is an examination of catalytic reactions in terms of elementary chemical reactionselementary chemical reactionsthat occur on the catalyst surfacesurface and their relationrelationwith each other and with the surface during acatalytic circle.“
Review article: P. Stoltze
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Microkinetic model development
Surface science studies
Microkinetic model
Reactor model
Comparison of expe-riment and simulation
Tentative surface reaction mechanism
AnalogiesAb initiocalculations
TST, collision theory
Steady-state kinetics
Transient experiments
Optimization of kinetic parameters, sensitivity analysis
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Kinetic measurements
Tasks of laboratory investigations of heterogeneous catalytic processes
o catalyst preparation
o catalyst screening
o activity
o selectivity
o stability
o scale-up
o process optimization
Complex reaction
o species
o reaction mechanism
o reaction kinetics
Laboratory reactors
o microcatalytic pulse r.
o gaschromatographic r.
o single pellet diffusion r.
o catalytic fixed bed r.
o recycle r.
o ( TAP )
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Kinetic investigations
• Steady-state or unsteady-state experiment ?• Quantitative evaluation of kinetic data ?
Constructing of amathematical model
Evaluation of the reaction mechanism
Parameter estimation
How to do…?
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Steady-state experiments
• Most common reaction technique used inheterogeneous catalysis
• Achieved by operation such that temperature,pressure, concentration, and flow rate at anypoint in the reactor is time invariant
• Access to activity, selectivity, reaction order, activation energy
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Steady-state experiments
• Advantages:- Easy to build and operate- Results can be described with mathematical
models based on algebraic equations - Most industrial processes are operated under
steady-state conditions
• Disadvantages:- Provide global kinetic parameters, limited
information on individual reaction steps- Interpretations often based on „simple“
assumptions
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Unsteady-state experiments
• Transient techniques provide information on
- Reaction intermediates (pulse response) (Gleaves 1988)
- Reaction sequence in a multistep reaction (Kobayashi 1975)
- Rate constants of elementary steps (Ertl 1979, Creten 1995)
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Unsteady-state experiments
• Transient techniques provide information on
- Investigation of complex kinetic phenomena(oscillating chemical reactions, hysteresis)that are not observable under steady-state conditions
- Probe of catalyst surfaces that are not easily observed under steady-state conditions (oxidation catalysis) (Haber 1983)
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Unsteady-state experiments
• Disadvantages
- Not easy to build up, expensive
- Main problem: theory is very complex
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Steady-state and transient methods
• measure overall performance
• give integrated picture of reaction system
• have minimum reactor residence time of 1 s
Steady-state methods
Transient methods
• give information on individual steps
• operate in millisecond time regime; resolution increase
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Transient experiments
• Transients are introduced into a system by varying one or more state variables (p, T, c, flow)
- Temperature-programmed experiments temperature change
- Step change experiments concentration change
• Examples:
- Molecular beam experiments pressure change
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TAP – A transient technique
• The key feature which distinguishes it from other pulse experiments is that no carrier gas is used and, gas transport is the result of a pressure gradient.
• At low pulse intensities the total gas pressure is very small, and gas transport occurs via Knudsen diffusion only.
• Pulse residence time under vacuum conditions is much shorter than in conventional pulse experiments. Thus a high time resolution is achievable.
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Microkinetic model development
Surface science studies
Microkinetic model
Reactor model
Comparison of expe-riment and simulation
Tentative surface reaction mechanism
AnalogiesAb initiocalculations
TST, collision theory
Steady-state kinetics
Transient experiments
Optimization of kinetic parameters, sensitivity analysis
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TAP – Features• Extraction of kinetic parameters differs compared to
steady-state and surface science experiments
- Steady-state: kinetic information is extracted from the transport-kinetics data by experimentally eliminating effects of transport
- Surface science: gas phase is eliminated
- In TAP pulse experiments gas transport is not eliminated. The pulse response data provides in-formation on the transport and kinetic parameters.
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TAP – Features
• TAP pulse experiments are state-defining
- Typical pulse contains ≈ 1013 moleculesor 1010 moles
- Example: § sample surface of 10 m2/g § a single pulse would be equivalent to 1/10000 of
the total surface per gram of sample§ conventional pulsed reactor experiments
address approximately 20 % of the surface per pulse
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Background - Diffusion
Transport mechanisms in porous solids
Pore diffusion depending on pore diameter
Λ …mean free path length
w …mean velocity of molecule
wD free Λ=31
MRTdwdD ppKnudsen π
831
31
==
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Background - Diffusion
Characterization of porous structures
• Porosity
• Pore radius, pore diameter• Pore radius distribution, -density
• Specific surface area• Tortuousity factor
kgm
mm 3
3
3
,mass- volume,total
volumepore
p
ppp
r
rpp dr
rHdrhrdrhrH
p
p
)()(;)()(
min,
== ∫
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Background - DiffusionKnudsen diffusion
• mean free path length of molecule > pore diameterΛ …mean free path lengthσ2…molecular cross-sectionV… gas molar volume at p
• NA/V at 298 K : cges ≈ 3.1019 *p (molecules/cm3) (dimension of p 105 Pa)
• mean free path length with typical σ (9-20*10-16 cm2)
ANV
221πσ
=Λ
)(102
nmp
≅Λ
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Background - DiffusionKnudsen diffusion
• Knudsen flow through one zylindrical pore
• For porous solids, the relative pore volume εb and thetortuousity factor τK have to be considered
)01.0,293(1083
26
, MPaKats
mMRTd
D piK
−≈=π
MRTd
D p
K
PiK
eff
πτε 8
3, =
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Background - Mathematics
• Delta function f(x) = δ (x-a)
- functional which acts on elements of a function
- integral
- multiplication with a function f(x)
yxforayxa
yaxdtat
y
x
<<<
<<
=−∫ ,01
)(δ
∫+∞
∞−
=− )()()( afdxaxxf δ
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Background - Mathematics
• Delta function
- graphical representation as „Sprungfunktion“ (limes)
- graphical representation as „Pulsfunktion“
x
u(x-a)
1
a
)(sin)(
1lim)( axnax
axn
−−
=−∞→ π
δ
)()( axdx
axdu−=
−δ
1
x
u(t-a)
a
∫
=−01
)( dtatδ
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Background - Mathematics
• Laplace transformation- aim: transformation of differential and integral
expressions into algebraic expressions- definition
- examplesdttFesf ts )()(
0∫∞
−=
[ ]s
es
dteLsf tsts 111)(00
=−===∞
−∞
−∫
[ ]s
dteeeLsf ttst
−=== ∫
∞−
ααα 1)(
0
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TAP – System hardware
• Injection of a narrow gas pulse into an evacuated microreactor
• Gas pulses travel through the reactor• Gas molecules (reactant and product)
are monitored as a function of time and produce a transient response at the MS
Reaction zoneGas pulse Detector
Simplified schematic of a TAP pulse response experiment
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TAP – System hardware
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TAP – System hardware
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TAP – System hardware
1) High speed pulse valve2) Pulse valve manifold3) Microreactor4) Mass spectrometer5) Vacuum valve6) Manual flow valve7) Mosfet switch
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TAP – Response curves
Typical pulse response experimental outputs
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TAP – Multipulse experiment
• Key features of input:- typical pulse intensity range from 1013 to 1017
molecules/pulse- pulse width 150-250 µs- pulse rates 1-50 s-1
• Key features of output:- different products have different responses- individual product response can change with pulse number
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TAP – Pump probe experiment
• Key features of input:- different reaction mixtures are introduced sequentially from separate pulse valves
• Key features of output:- output transient response spectrum coincides with both valve inputs
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TAP – Transient response data
In contrast to traditional kinetic methods, that measure concentrations, the observable quantity in TAP pulse response experiments is the time dependent gas flowescaping from the outlet of the microreactor.
The outlet flow is measured with a MS (QMS) that detects individual components of the flow with great sensitivity.
The composition of the flow provides information on the types of chemical transformation in the microreactor.
The time dependence of the flow contains information on gas transport and kinetics.
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TAP – Theory
Goal
• Interpretation of pulse response data- determine typical processes- find parameters for these processes- develop a model
• Analyzation of experiments that provide parameters of diffusion, irreversible adsorption or reaction and reversible reaction
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TAP – General models
Currently there are three basic models in application based on partial-differential equations.
- One-zone-model- Three-zone-model- Thin-zone-model
The mathematical framework for the one-zone-model was first published in 1988 (Gleaves).
Basic assumptions of one-zone-model:- catalyst and inert particle bed is uniform- no radial gradient of concentration in the bed- no temperature gradient (axial or radial)- diffusivity of each gas is constant
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TAP – Gas transport model
The gas transport is the result of Knudsen diffusion.
An important characteristic of this tranport process is that the diffusivities of the individual components of a gas mixture are independent of the presssure or the compositionof the mixture.
2
22
1
11 T
MD
TM
D ee =De,i …effective Knudsen diffusivityMi …molecular weight Ti …temperature 1,2 …gas 1, gas 2
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TAP – Transport model
2
2
zCD
tC A
eAA
b ∂∂
=∂
∂ε
(1) Diffusion only case –Mass balance for a non-reacting gas A transported by Knudsen diffusion
CA … concentration of gas A (mol/cm3)DeA … effective Knudsen diffusivity of
gas A (cm2/s)t … time (s)z … axial coordinate (cm)εb … fractional voidage of the packed
bed in the reactor
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TAP – Transport model
initial conditions: 0 ≤ z ≤ L , t = 0 , A
NC
b
pAzA ε
δ=
boundary conditions: z = 0 ,
z = L ,
0=∂
∂z
CA
0=AC
The equation can be solved using different sets of initial and boundary conditions that correspond to different physical situations.
NpA … number of moles of gas A in one pulseA … cross-sectional area of the reactor (cm2)L … length of the reactor (cm)
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TAP – Transport model
The gas flow at the reactor exit FA (mol/s) is described by
LzA
eAA zCDAF =∂
∂=
and the gas flux (mol/cm2 s) by
AFA=AFlux
To solve for the gas flow it is useful to express initial and boundary conditions in terms of dimensionless parameters.
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TAP - Transport model
Use of dimensionless parameters
… dimensionless axial coordinate
… dimensionless concentration
… dimensionless time
Lz
=ξ
LANCC
bPA
AA ε
=
2LDt
b
eA
ετ =
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TAP – Transport model
2
2
ξτ ∂∂
=∂
∂ AA CC initial conditions: 0 ≤ ξ ≤ 1 , t = 0 , ξδ=AC
boundary conditions: ξ = 0 ,ξ = 1 ,
0=∂
∂ξ
AC
0=AC
Dimensionless form of mass balance
Solution:- analytical a) method of separation of variables
b) Laplace transformation- numerical for more complex problems
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TAP – Transport model
Method of separation of variables:
solution for dimensionless concentration
( ) ( )τππξτξ 22
0)5.0(exp)5.0(cos2),( +−+= ∑
∞
=
nnCn
A
solution for dimensionless flow rate
( ) ( )τππξπξ
τξτξ 22
0)5.0(exp)5.0(sin)12(),(),( +−++=
∂∂
−= ∑∞
=
nnnCFn
AA
dimensionless flow rate at the exit (ξ=1)
( )τππ 22
0)5.0(exp)12()1( +−+−= ∑
∞
=
nnFn
nA
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TAP – Transport model
( )τππ 22
0)5.0(exp)12()1( +−+−= ∑
∞
=
nnFn
nA
Expression for the dimensionless exit flow rate as a function of dimensionless time
Standard diffusion curve
For any TAP pulse response experiment that involves only gas transport, the plot of the dimensionless exit flow rateversus dimensionless time will give the same curveregardless the gas, reactor length, particle size, or reactor temperature.
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TAP – Transport model
+−+−= ∑
∞
=2
22
02 )5.0(exp)12()1(
LDtnn
LD
NF
b
eA
n
n
b
eA
pA
A
επ
επ
Due to initial condition the surface area under SDC is equal to unity – flow rate in dimensional form
An important property of this dimensional dependence is that its shape is independent on the pulse intensity if the process occurs in the Knudsen regime.
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TAP – Transport model
+−+−= ∑
∞
=2
22
02 )5.0(exp)12()1(
LDtnn
LD
NF
b
eA
n
n
b
eA
pA
A
επ
επ
Characteristics of standard diffusion curve
… peak maximum
… corresponding height
… „fingerprint“ for Knudsen regime
eA
bpp D
Lt2
61,
61 ε
τ ==
2, 85.1,85.1L
DHFb
eAppA ε
==
31.0, ≈= ppppA tHF τ
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TAP – Transport model
a) Standard diffusion curve showing key time characteristics and the criterion for Knudsen diffusion
b) Comparison of standard curve with experimental inert gas curve over inert packed bed
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TAP – Transport + adsorption model
AabvsA
eAA
b CkSazCD
tC )1(2
2
εε −−∂
∂=
∂∂
(2) Diffusion + irreversible adsorption
(adsorption is first order in gas concentration)
as … surface concentration of active sites (mol/cm2 of catalyst)
ka … adsorption rate constant (cm3 of gas/mol s)
Sv … surface area of catalyst per volume of catalyst (cm-1)
θA … fractional surface coverage of A
AaA Ck
t=
∂∂θ
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+−+−−= ∑
∞
=2
22
0
´2 )5.0(exp)12()1()exp(
LDtnntk
LD
NF
b
eA
n
na
b
eA
pA
A
επ
επ
TAP - Transport + adsorption model
Flow rate FA at reactor exit
(2) Diffusion + irreversible adsorption
b
abvsa
kSakε
ε )1(´ −=with
Exit flow curve for diffusion+irreversible adsorption - is smaller than SDC by a factor of exp(-ka´t)- is always placed „inside“ the SDC (fingerprint)
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TAP - Transport + adsorption model
Exit flow curve for the diffusion+irreversible adsorption case
Comparison of irreversible adsorption curves with standard diffusion curve(A) ka=0 (SDC), (B) ka=3 (C) ka=10
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(3) Diffusion + reversible adsorption
Mass balances- for component A in gas phase
)()1(2
2
AdAabvsA
eAA
b kCkSazCD
tC
θεε −−−∂
∂=
∂∂
AdAaA kCk
tθ
θ−=
∂∂
- for component A on the catalyst surface
kd …desorption rate constant (s-1)
TAP – Transport and adsorption model
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TAP - Transport + adsorption model
Exit flow curve for the diffusion+reversible adsorption case
Comparison of reversible adsorption curves with standard diffusion curve(A) ka=0 (SDC), (B) ka=20, kd=20 (C) ka=20, kd=5
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TAP – Transport, adsorption, reaction
(3) Diffusion + reversible adsorption + irreversible reaction
)()1(2
2
AdAAaAbvsA
eAA
b kCkSazCD
tC
θεε −−−∂
∂=
∂∂
ArAdAAaAA kkCk
tθθ
θ−−=
∂∂
)()1(2
2
BdBBaBbvsB
eBB
b kCkSazCD
tC
θεε −−−∂
∂=
∂∂
BdBBdBArB kCkkt
θθθ
+−=∂
∂
A(gas) B(gas)
A(ads) B(ads)kr
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TAP – Transport, adsorption, reaction
(3) Diffusion + reversible adsorption + irreversible reaction
The initial and boundary conditions used in the transport-only case can be applied to the transport+reaction case as well.
Initial condition t = 0 , CA = 0
Inlet boundary condition )(,0 1,1, t
zC
Dz AeA δ=
∂∂
−=
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TAP – Transport, adsorption, reaction
(3) Diffusion + reversible adsorption + irreversible reaction
)(1,1, t
zC
D AeA δ=
∂∂
−
The inlet flux is respresented by a delta function. With this combination, analytical solutions in the Laplace-domain can be easily derived when the set of differential equations that describe the model is linear.
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TAP – Characteristic values
Use of dimensionless parameters
eA
baa D
Lkk2
´ ε= dimensionless apparent adsorption
rate constant
b
abvsa
kSakε
ε )1(´ −=
ka´ contains:
- the kinetic characteristics of the active site (ka)- the structural characteristics of the whole
catalytic system b
bvs Saε
ε )1( −
with
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TAP – Extended models
Three-zone-model
Additional boundary conditions between the different zones have to be applied
catalystinert inert
zone 1 zone 2 zone 3
pulse outcome to QMS
Evaluation of curve shapes and „fingerprints“ are basicly the same as for the one-zone-model
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TAP – Theory
Moment-based quantitative description of TAP-experiments
• idea behind: observed TAP data consist of a set of exit flow rates versus time dependencies
• analytical solutions in integral form can be usually obtained
• analysis of some integral characteristics (moments) of the exit flow rate
• moments reflect important primary features of the observations
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TAP – Theory - Moments
• moment Mn of the exit flow rate (i.e. not of concentration)
n…order of moment
• representation in dimensionless form
dttFtMt
nn )(
0∫=
)/(with 2
0 eAbA
nn DL
tdFmε
τττ == ∫∞
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TAP – Theory - Moments
Application to TAP experiments:- for irreversible adsorption / reaction
DaI … Damköhler number I
- mean dimensionless residence time
eA
baI
I DLkDa
DaXm
2´
0 withcosh
11 ε==−=
[ ]Dif
n I
n Ires
DanBnA
DanBnA
mm
ττ
∑
∑∞
=
∞
=
+
+==
0
0
0
1
)()(
)()(
)12()1()( +−= nnnA22)5.0()( π+= nnB
Ae
bDif D
L
,
2ετ =
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TAP - Examples
Mechanism and Kinetics of the Adsorption and Combustionof Methane on Ni/Al2O3 and NiO/Al2O3 (Dewaele et al. 1999)
- Supported Ni catalysts for steam reforming of natural gasto synthesis gas
- Combination of TPR with single pulse experiments
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TAP - ExamplesSelective oxidation of n-butane to maleic anhydride (MA)
over vanadium phosphorous oxide (VPO) (Gleaves et al. 1997)
• important heterogeneous selective oxidation• complex reaction (electron transfer, fission of C-H-bonds,
addition of oxygen, ring closure)• literature: (VO)2P2O7-lattice as active-selective phase, but it
is not clear how the lattice supplies the oxygen- possible involvation of oxygen adspecies adsorbed on
vanadium surface sites- possible involvation of bulk oxygen- possibly other crystal phases are active
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TAP - ExamplesSelective oxidation of n-butane to maleic anhydride (MA)
over vanadium phosphorous oxide (VPO)
• Steady-state kinetic studies yielded different rate expressions and kinetic parameters – this may be related to differences in c. composition, c. structure, c. oxydation state, etc. no unique information
• Aim of TAP investigations:Relate changes in kinetic dependencies to changes inthe catalyst
• How to do ? Systematic alteration of the state of the catalyst and measuring kinetic dependencies
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TAP - ExamplesSelective oxidation of n-butane to maleic anhydride (MA) over
vanadium phosphorous oxide (VPO)
Kinetics of n-butane conversion over VPO in the absence of gas phase oxygen
- n-butane curve lies completelywithin the generated diffusion curve irreversible process
- initial step is irreversible (fissure of CC or CH bond)
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TAP - ExamplesSelective oxidation of n-butane to maleic anhydride (MA) over
vanadium phosphorous oxide (VPO)
Kinetics of n-butane conversion on oxygen-treated VPO
- values of apparent activationenergy is strongly dependenton the VPO oxidation state
- decreasing number of active centers
- TAP + Raman: V4+ V5+Arrhenius plots for pulsed n-butane conversion over an oxygen-treated VPO catalyst sample as a function of oxidation state
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TAP - ExamplesN-Butane Isomerization on Sulfated Zirconia Catalysts(SPP-1091, Acid-Base Catalyzed Alkane Activation)
0.0 0.1 0.2 0.3 0.4 0.5
0.0
0.2
0.4
0.6
0.8
1.0
reference helium 100 °C 150 °C 200 °C 250 °C
height
nor
malized
cur
ve
time [s]
0.0 0.1 0.2 0.3 0.4 0.5
0.0
0.2
0.4
0.6
0.8
1.0
100 °C 150 °C 200 °C 250 °C
h.n.
time [s]
Pulses of n-butane
over inert material over SZ
τ [s] at 100 °C: 0.107 0.500
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TAP - ExamplesN-Butane Isomerization over Sulfated Zirconia Catalysts
(SPP-1091, Acid-Base Catalyzed Alkane Activation)
Influence of sulfation - pulses of n-butane
SZ, calcined unsulfated precursor, inert
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
0.0
0.2
0.4
0.6
0.8
1.0
BS-1 BSV-1 Ref. Ref.
h.n.
time [s]
-1 0 1 2 3 4 5 6 7 8
0.0
0.2
0.4
0.6
0.8
1.0
BS-1 BSV-1 Ref. Ref.
h.n.
time [s]
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TAP - ExamplesN-Butane Isomerization over Sulfated Zirconia Catalysts
(SPP-1091, Acid-Base Catalyzed Alkane Activation)
Activation plots for active SZ, inactive SZ, industrial reference
at begin of reaction
1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7-2.4
-2.2
-2.0
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
BS-1 BS-2 BSMln
τre
s
1000/T [1/K]
EAkt (BS-1) ≈ EAkt (BS-2) at beginning
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TAP - ExamplesN-Butane Isomerization over Sulfated Zirconia Catalysts
(SPP-1091, Acid-Base Catalyzed Alkane Activation)
Variation of activation state through switch between vacuum and atmospheric flow conditions at 150 °C
0.0 0.2 0.4 0.6 0.8 1.0
-0.0010.0000.0010.0020.0030.0040.0050.0060.0070.0080.0090.0100.0110.0120.0130.014
pulsing before flow after 1 min flow after 2 min flow after 3 min flow after 4 min flow after 10 min flow after 20 min flow after 60 min flowin
tens
ity o
f am
u 43
time [s]
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SSITKA
Steady State Isotopic TransientKinetic Analysis
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SSITKA - Theory• Initially developed by Happel 1978, Bennett 1982 and
Biloen 1983• Determination of kinetics and catalyst surface reaction
intermediates in situ• The technique is based upon the detection of isotopic
labels in the reactor effluent species versus time following a switch (step change) in the isotopic labeling of one of the reactant species in the reactor feed.
• Isothermic and isobaric conditions !• Reactant and product concentrations remain undisturbed
during step change !Steady-state reaction conditions are maintained under
isotopic-transient operation
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SSITKA - TheoryReview article: Shannon, Goodwin 1995
Typical reaction system for SSITKA experimentation
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SSITKA - Theory
• The step-input response is a statistical distribution representing the probability that an isotopic label remains adsorbed on the catalyst surface or appears in the effluent stream with time.
Typical normalized isotopic-transient responses
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SSITKA - Theory
• Characteristic values- Step-input response of the product for the new isotopic
label
- Step-decay response of the old isotopic label (prior to switch)
- Relationship
- Inert-tracer transient response for determination of gas-phase holdup
)(* tF Pm
)(tF Pm
)(1)( * tFtF Pm
Pm −=
)(tF Im
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SSITKA - Theory
• In SSITKA, it is common to consider the catalyst surfaceto be composed of a system of interconnected pools, also termed compartments, where each pool represents a homogeneous or well-mixed subsystem within the reaction pathway.
• A seperate pool is assumed to exist for each uniqueadsorbed reaction-intermediate species or type of catalytically active site.
• It is assumed that there is essentially no mixing or holdup time associated with each pool or within the reaction pathway except for the residence time of a reaction-intermediate species adsorbed on the catalyst surface.
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SSITKA - Theory
Catalyst-surface model showing the isotopic distributionbetween n pools in series following an isotopic switch, R à*R, at the reaction volume inlet
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SSITKA - Theory
Catalyst-surface mechanistic models, transientresponses, and kinetic parameters
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SSITKA - Theory
Catalyst-surface mechanistic models, transientresponses, and kinetic parameters
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SSITKA – Kinetic parameters
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SSITKA - ExamplesSelective NO reduction over Co-ZSM-5
(Sadovskaya et al. 2001)
• SCR of NO with CH4 in the presence of excess oxygen • Controversial discussion of formation mechanism of
surface NOx species • IR investigation in presence of O2 showed bands for
nitrite and nitrate complexes and for NOxδ+
• Focus on formation of adsorbed NOx species in absence and presence of oxygen, but in absence of methane by using doubly labeled nitric oxide
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SSITKA - ExamplesSelective NO reduction over Co-ZSM-5
(Sadovskaya et al. 2001)
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SSITKA - ExamplesSelective NO reduction over Co-ZSM-5
(Sadovskaya et al. 2001)
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SSITKA - ExamplesSelective NO reduction over Co-ZSM-5
(Sadovskaya et al. 2001)
• Cobalt mononitrosyls, NOxδ+ species, nitrite complexes
have average lifetimes of 0.1, 1, and 100 s• Observation in agreement with DRIFT • Concentration of mononitrosyls was found proportional to
NO content in feed gas; no saturation• NOx
δ+ species approached maximum coverage within the same concentration range; only part of cobalt active species participate in NOx
δ+ species formation
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SSITKA - ExamplesSelective NO reduction over Co-ZSM-5
(Sadovskaya et al. 2001)
• Rate of gaseous NO2 formation comparable with nitrite formation and substantially lower than that of NOx
δ+
formation• Conclusion: NOx
δ+ can not originate from NO2 formation but formed in two sequential steps (i) molecular oxygen adsorption and (ii) NO reaction with oxidized surface sites
• Rate of oxygen exchange within NOxδ+ lower than their
formation indicating that the two oxygens are nonequivalent
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Kinetic modeling
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Way down South in the land of cottonWhere good mints juleps are not forgottenAn old farmer sits on his plantationThinking up problems to astound the nationLindemann and Hinshelwood can stand it no moreWhile Smith and Carberry have run for the doorNow there is one as he told it to meAnd I give it to you, completely for freeWe know kinetics is a staid sort of sportIf reaction order is all there´s to reportSo we´ve studied about reactor designIn detail and elegance quite so fineMixing models have been disussedWhere proper equations are a mustAge distributions become important hereAn intricate analysis, it is clearNow this is the question to give you fitsAn excellent chance to test your witsOf these distributions there are many it´s sureDerived from a theory assuredly most pure
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Residence time, internal, and exit ageAll we owe to Danckwerts, that clever sageWhat are they, please, a clear explanationCombining words with an appropriate equationRelationships between them are almost horrendousA discussion of this would be simply tremendousWhen you´ve written all this consider you´re doneNow wasn´t that all just good clean funIf you did what was aked, and that I hopeThen with chemical reactors you´re able to copeOne final thing I must now sayOf the light of knowledge a final rayReaction kinetics is in a messIn spite of Eyring and ArrheniusAlas, was it ever thus so
The more we learn, the less we know !
John B. Butt
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SSITKA• Happel J. J. Chem. Eng. Sci. 33 (1978), 1567.• Bennett CO. ACS Symposium Series Washington 1982, Vol. 178, 1.• Biloen PJ. J. Mol. Cat. 21 (1983) 17.• Bennett CO. Adv. Catal. 44 (2000) 329.• Sadovskaya EM, Suknev AP, Pinaeva LG, Goncharov VB, Bal´zhinimaev BS,
Chupin C, Mirodatos C. J. Catal. 201 (2001) 159-168.
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