experimental and theoretical- gb marin

8/12/2019 Experimental and Theoretical- GB Marin

1/36


2/36

INTRODUCTION

The ultimate goal of chemical kinetics is to unravel the mechanism of a chemical reaction and

to predict the rate of formation of desired and undesired products, both of which are essential

to maximize the energy efficiency and minimize the environmental impact of chemical processes.

Approximately 90% of all chemical processes worldwide (1) make use of catalysts, and there is a

pressing need for more efficient solid catalysts to allow sustainable production of fuels and bulk

chemicals. At present, catalyst development is dominated by experimental research and is focused

mainly on optimization of a given catalyst with respect to given criteria (2). The ability to predicthow the catalysts composition and structure, and hence its physicochemical properties, control

the rate of key steps in the catalytic mechanism is essential to come to a rational design of new

and more efficient catalysts.

Microkinetic models are uniquely suited to identify which (surface) species or surface reac-

tion paths control the observed product spectrum; thus, they provide a tool to define the process

conditions to obtain the maximum yield of the desired product (3). Moreover, microkinetic mod-

els have the unique ability to provide a unified, quantitative understanding of heterogeneously

catalyzed reactions by incorporating knowledge of a series of catalysts obtained from various sur-

face science techniques (46), experimental kinetic studies (7, 8), quantum chemical studies, and

statistical thermodynamics (918). Hence, they have the potential not only to incorporate (10,

11, 1922) but also to develop structure-activity relationships and/or identify catalyst descriptors,which makes them an ideal tool for in silico catalyst design (10, 11, 23). Therefore, kinetic studies

in heterogeneous catalysis now aim mainly to identify the detailed reaction mechanism, develop

an appropriate mathematical description of the influence of the reaction conditions and catalyst

properties on the elementary reaction rates, and determine the unknown parameters in the rate

expressions. Kinetic analysis of the reaction network then allows us to identify which elementary

steps control the reaction rates (2428), how their rates are affected by the reaction conditions,

and the catalyst properties, all of which are crucial to provide guidelines for the design of bet-

ter catalysts (29). To obtain the necessary information and/or to validate rate coefficients and

mechanisms obtained from quantum chemical calculations, steady-state and non-steady-state or

transient kinetic experiments can be used (24).

We begin with a brief survey of the necessary requirements to extract model-free intrinsic re-action rates from dedicated experiments. Comparison of experimentally observed rates with those

obtained based on quantum chemical calculations is often biased by overlooking these necessary

requirements. Next, we illustrate the potential of microkinetic modeling for catalyst design for

three complex acid zeolitecatalyzed reactions taken from our work. Zeolites are microporous,

crystalline, inorganic oxides that are widely used as solid Brnsted acid catalysts in a variety of

chemical processes for the production of fuels, energy carriers, and bulk and fine chemicals. The

catalytic properties of zeolites are related mainly to their structural and compositional character-

istics, such as pore opening, channel and void dimensions, and Si/Al ratio. Typically, zeolites are

excellent catalysts owing to their high surface area, high adsorption capacity, and well-defined

micropores that can induce shape selectivity (3037). Historically, the emphasis on the size and

shape of zeolite voids and their connecting apertures in explaining shape selectivity has led tothe development of zeolite descriptors based on reactions of molecules of different sizes, such

as the constraint index (38) and the spaciousness index (39). These methods provide an indi-

rect assessment of zeolite activity when it is controlled by molecular transport or size exclusion.

Although these methods allow us to screen the immense diversity of shape, size, and connectiv-

ity of voids and pores in hypothetical (106 in number) (4042) and known (102 in number)

(http://www.iza-structure.org/databases/) zeolites, they do not provide insight into how the

564 Reyniers Marin
http://www.iza-structure.org/databases/http://www.iza-structure.org/databases/http://www.iza-structure.org/databases/


3/36

physicochemical properties of the zeolite, such as acid strength and solvation ability of confining

voids, influence zeolite reactivity and selectivity (43). Given that only approximately ten families of

zeolites are commonly applied in industrial processes (44), there is a clear need for a more rational

design of zeolite materials with desired properties for a targeted catalytic reaction. Three different

but complementary approaches for kinetic analysis of zeolite-catalyzed reactions are presented to

illustrate their ability to provide physicochemical insight into the influence of zeolite properties on

the observed product yields under working conditions. We conclude by identifying challenges for

future research that should help to further advance the rational design of heterogeneous catalystsin general and of zeolites in particular.

KINETIC EXPERIMENTS

Experimental Requirements

Usually, experimental kinetic studies are performed in laboratory-scale stirred tank reactors

(STRs) or plug flow reactors (PFRs). Product yields of heterogeneously catalyzed processes per-

formed in these types of reactor not only depend on the rate of the chemical reactions but also

are influenced by physical transport phenomena, such as heat and mass exchange between the

catalyst and the fluid phase (so-called external heat and mass transfer) and heat and mass transportwithin the catalyst pellet, so-called internal transport. To extract intrinsic kinetic information

(i.e., kinetic data that pertain to the chemical reactions only), the typical strategy in experimental

kinetic studies is to eliminate the effects of mass and heat transport as much as possible. Ideally,

the kinetic experiment must fulfill two requirements: isothermicity and uniformity of chemical

composition. In dedicated laboratory setups, this can be accomplished by, for example, diluting

the reactive medium by using special mixing devices, either internally (impellers) or externally by

recirculation. Several experimental and theoretical (4548) diagnostic tools are available to iden-

tify the range of reaction conditions and catalyst particle diameters that allow us to ensure that

in a given reactor configuration the influence of inter- and intraparticle transport on the reaction

rates is eliminated. In so-called intrinsic kinetic studies, these requirements are fulfilled. In the

case of irreducible transport phenomena, the transport regime in the reactor must be well defined,

and its mathematical description must be reliable (24). Failure to comply with these experimental

requirements inevitably produces kinetic data that are biased by ill-defined transport phenomena.

This leads to biased values of fitted rate coefficients and to misleading conclusions when compar-

ing experimentally determined turnover frequencies and/or rate-controlling steps from different

literature sources or with those obtained from ab initiobased kinetic model simulation.

Obtaining Model-Free Kinetic Data

Importantly, in kinetic experiments, the reaction rate can seldom be measured directly. The

experimentally determined characteristic in most experimental kinetic studies is the net rate of

production of a component, Ri, which can be defined as a linear combination of the rates of allthe elementary steps,rj, in which the component is consumed or formed. The coefficients in this

linear combination are the components stoichiometric coefficients, ij, in each of the steps:

Ri=

j

i jrj. 1.

Both continuously stirred tank reactors (CSTRs) and PFRs are used frequently to obtain steady-

state kineticinformation. Steady-state kinetic data areusually related to the rate-controlling step(s)

www.annualreviews.org Heterogeneously Catalyzed Reactions 565


4/36

STEADY-STATE ISOTOPIC TRANSIENT KINETIC ANALYSIS

Steady-State Isotopic Transient Kinetic Analysis (SSITKA) is based on the determination of isotopic labels of a

component in the reactor effluent versus time following a stepwise change in the isotopic labeling of one of the

reactants in the reactor feed. SSITKA can be used to determine the amount and rate of formation of surface species;

in other words, it allows us to characterize the steady state of the catalyst surface under working conditions.

of a complexcatalytic reaction. To obtainkinetic information on theindividual elementary reaction

steps, non-steady-state experiments are required.

Ideally, kinetic information should be obtained in a model-free manner, which means that

during the experimental procedure and the subsequent data processing no bias is introduced

by making assumptions about, for example, the reaction mechanism, the kinetic model, or the

reactor model. Some techniques, such as a combination of CSTR or PFR with isotopic step-

response experiments, allow the model-free determination of formation rates by Steady-State

Isotopic Transient Kinetic Analysis (SSITKA) (49) (see sidebar, Steady-State Isotopic Transient

Kinetic Analysis).

Non-steady-state kinetic data can also be based on the technique of Temporal Analysis of

Product (TAP) (24, 50, 51). The earlier three- and one-zone configurations of the TAP reactor

could not provide model-free kinetic information. In contrast, the Y-procedure (52), a new theo-

retical method for the thin-zone TAP reactor, enables values of reaction rates and, hence, kinetic

coefficients to be obtained from exit flow rates without any assumptions regarding the detailed

kinetic model (see sidebar, Temporal Analysis of Products).

CSTR andPFR experiments areperformedat temperaturesand pressures relevant forindustrial

conditions. For highly exothermic reactions, CSTRs are usually operated at low conversions to

ensure isothermicity. The TAP system can be used in a wide domain of operation conditions;

however, to ensure the Knudsen diffusion regime (i.e., a well-defined transport regime that can

be reliably described mathematically), the preferred window of pressures ranges from 102 to

101 Pa. The latter pressure is the upper boundary of the surface science domain; hence, TAP

experiments provide a bridge between surface science and more traditional applied kinetics.

KINETIC ANALYSIS OF COMPLEX ACIDZEOLITECATALYZED REACTIONS

Three different but complementary approaches for the kinetic analysis of complex acid zeolite

catalyzed reaction networks are presented. All three approaches aim to obtain a quantitative

TEMPORAL ANALYSIS OF PRODUCTS

The main idea of Temporal Analysis of Products (TAP) is to inject a series of narrow gas pulses into one end of a

microreactor and continuously evacuate the other end. The intensity of each pulse is small relative to the amountof catalyst used to ensure that the surface state of the catalyst is not significantly perturbed by each pulse and that

the Knudsen diffusion regime is guaranteed. The change in the composition of the pulsed mixture is monitored

by a precise mass-spectroscopic technique. Upon applying a large series of such narrow pulses, the surface state of

the catalyst can be changed significantly in a controlled manner. Thus, a sequence of infinitesimal steps is used to

produce a finite change of the catalyst activity; hence, the technique can also be named chemical calculus.

566 Reyniers Marin


5/36

BOTTOM-UP APPROACH TO KINETIC ANALYSIS

In the Bottom-Up Approach to kinetic analysis, a detailed analysis of the observed product distribution ove

a broad range of reaction conditions is complemented with kinetic fingerprinting and reaction path analysis to

resolve the so-called minimal reaction network. Subsequently, thermodynamic-consistent Langmuir-Hinshelwood

Hougen-Watson-type rate equations are constructed that contain both kinetic and catalyst descriptors. The catalys

descriptors that reflect the effect of the catalyst on the stability of intermediates and transition states are identifiedbased on a kinetic analysis of the experimental observations and enable a physicochemical interpretation of th

influence of the catalyst properties.

understanding of the influence of the zeolite properties, such as Si/Al ratio (i.e., number and

strength of acid sites) and framework structure, on its catalytic behavior under working conditions.

The liquid-phase alkylation of benzene with 1-octene over a series of Y zeolites (22, 53) ex-

emplifies the Bottom-Up Approach (see sidebar, Bottom-Up Approach to Kinetic Analysis). Al-

ternatively, in the Top-Down Approach, insight into the chemistry of the catalytic process is

translated into chemical rules that are implemented as algorithms in computer codes, allowing us

to generate detailed reaction networks consisting of several thousands of elementary steps (27, 28,5456). This approach is illustrated for the catalytic cracking of hydrocarbons over a series of Y

and ZSM-5 zeolites (21, 57, 58) (see sidebar, Top-Down Approach to Kinetic Analysis).

In the third approach, molecular modeling is used to construct a minimal reaction network

for ethanol dehydration to ethylene over H-FAU, H-MOR, H-ZSM-5, and H-ZSM-22 together

with their corresponding kinetic coefficients (59, 60). Comparing simulated and experimentally

observed product yields over a broad range of reaction conditions then allows us to identify

important elementary steps that are missing from the network and/or must be found/calculated

more accurately by, for example, molecular dynamics.

Bottom-Up Approach: Liquid-Phase Alkylation of Benzene with 1-Octene

Alkylation of benzene with linear long-chain alkenes is used to synthesize linear alkyl benzenes

(LABs) as building blocks for the production of detergents. Conventional processes are based on

highly corrosive acid catalysts, such as aluminum trichloride and hydrofluoric acid (61). Therefore,

an efficient, recyclable, and environmentally friendly solid-acid catalyst is highly desired (62

64). Among various zeolites tested, Y zeolites have been shown to be suitable catalysts for the

alkylation of benzene with long-chain olefins because they combine two important features: strong

TOP-DOWN APPROACH TO KINETIC ANALYSIS

In the Top-Down Approach to kinetic analysis, a detailed reaction network is automatically generated a priori base

on so-called reaction rules. The advantage of this approach is that all surface intermediates are explicitly accounte

for and no a priori reaction pathways are assumed. Databases, based either on experiment or on quantum chemica

calculations for model components, provide values for kinetic descriptors. If unavailable, estimates of kinetic and/o

catalyst descriptors can be obtained by regression of experimental data. Numerical integration or kinetic Mont

Carlo simulations then allow us to evaluate the relative importance of various reaction paths and the effect of catalys

properties on the product yields and to define optimal values for catalyst descriptors.



6/36

Table 1 Properties of the Y zeolites used in the liquid-phase alkylation of benzene with 1-octene

CBV712 CBV720 CBV760

Bulk Si/Al ratio 6 13 30

Framework Si/Al ratio 21.2 26.2 75.8

Acid site concentration (mol kg1) 0.69 0.62 0.24

Al (IV) concentration (mol kg1) 0.75 0.61 0.22

BET surface area (m2 g1) 730 780 720

Micropore volume (cm3 g1) 0.25 0.27 0.25

Mesopore volume (cm3 g1) 0.15 0.16

Unit cell size, ao(nm) 24.36 24.34 24.25

Total Al per unit cell 28.2 13.7 6.2

Framework Al per unit cell 8.6 7.1 2.5

acidic character and the ability to accommodate large molecules, such as alkylbenzenes, inside

their pores (65, 66). De Almeida et al. (65) reported that the selectivity to 2-phenyldodecane

increased with increasing acid strength in the alkylation of benzene with 1-dodecene over Y

zeolites performed in a batch-slurry reactor. However, Y zeolites are prone to deactivation, and

operation in batch mode does not allow us to exclude the influence of coke deposition on theproduct distribution. Hence, Cruciun et al. (53) studied, as a model reaction, the liquid-phase

alkylation of benzene with 1-octene over three commercial Y zeolites with bulk Si/Al ratios of 6,

13, and 30 (seeTable 1) in a Robinson-Mahoney reactor operating in a continuous-flow (CSTR)

mode. This allowed extrapolation to zero time-on-stream and thus enabled evaluation of the

influence of reaction conditions and acid properties on activity and selectivity in the absence of

deactivation. Temperatures ranged from 343 K to 373 K, benzene/1-octene feed molar ratios

ranged from 1 to 10, and 1-octene conversions were between 10% and 99%.

Definition of the minimal reaction network: kinetic fingerprinting and reaction path anal-

ysis. Representative profiles of conversion versus site time (molH+mol1-octene1

s) and selectivityversus 1-octene conversion are shown in Figure 1. Clearly, the catalytic activity per acid site

increases with increasing Si/Al ratio, indicating that the acid strength is important in determining

the reactivity, whereas the selectivities are not affected. Also, for all catalysts, the experimental

data indicate that product selectivities are not influenced by temperature.

Two main groups of components were obtained as reaction products: octene isomers

(2-octene, 3-octene, and 4-octene) and phenyloctanes (2-phenyloctane, 3-phenyloctane, and 4-

phenyloctane). Traces of di-alkylated benzenes were observed at low benzene-to-1-octene molar

feed ratios only. Branched octene isomers were not observed, indicating that the octene isomers

result from double-bond migration. As illustrated in Figure 2, kinetic fingerprinting using the

delplot technique (67) revealed that, when the feed consists of only 1-octene and benzene, 2-octene

and 2-phenyloctane are the only primary products, whereas 3-octene and 3-phenyloctane are sec-

ondary products and 4-octene and 4-phenyloctane are tertiary products. Hence, intramolecular

hydride shifts could be discarded as elementary steps in the reaction network because their occur-

rence would allow for the formation of all the reaction products as primary products. Therefore,

we can conclude that the formation of octene isomers occurs through a sequence of consecutive

protonation-deprotonation steps. Intermolecular hydride shift reactions could be eliminated as

well from the minimal reaction network because octane, octadienes, and components derived from

them are not observed under the mild conditions investigated.

568 Reyniers Marin


7/36

00

20

20

40

40

60

60

80

CBV712 6

CBV720 13

CBV760 30

Si/Al

80

100

100

0 20 40 60 80 100

1-Octeneconversion(%)

NH+/Fo,1-oct(s)

0

20

40

60

80

100

Selectiv

ity(%)

Selectivity(%)

1-Octene conversion (%)

0 20 40 60 80 100


0

10

20

30

40

2-Phenyloctane

3-Phenyloctane

2-Octene

3-Octene

4-Octene Phenyloctane4-Phenyloctane

a

b c

Figure 1

(a) Conversion of 1-octene as a function of site time and ( b) octene isomer distribution and (c) phenyloctaneisomer distribution as a function of conversion over three Y zeolite catalysts at 373 K and a benzene/1-octenefeed molar ratio of 5. Experimental points and model simulations ( lines) shown (adapted from Reference 53).

Figure 2a,balso illustrates that, although double-bond isomerization is faster compared with

benzene alkylation, the internal equilibrium distribution of the octenes is not reached. Conse-

quently, the double-bond isomerization and the alkylation take place on a comparable timescale;

hence, the two processes must be described as occurring simultaneously rather than as two con-

secutive, decoupled processes.

From the high values of the equilibrium coefficients (K= 109M1) for the formation of

phenyloctanes from benzene and octenes, we can conclude that the alkylation is practically

irreversible at the experimental conditions investigated. Hence, the minimal reaction network

shown inFigure 3could be presented for the alkylation of benzene with octenes over Y zeolites.

The underlying mechanism is of the EleyRideal type, with benzene reacting from the liquid

phase and olefins reacting as adsorbed species on the surface of the catalyst. EleyRideal-type

mechanisms have been proposed previously for the alkylation of benzene over large pore zeolites,

such as Y and beta (68, 69). Also, preliminary isothermal model discrimination allowed us to

eliminate models considering benzene adsorption (22).

Although the nature of the protonated hydrocarbon species in zeolite catalyststhat is, whether

they are carbenium ions or alkoxidesis the subject of ongoing investigation (7074), the mech-

anism is formulated based on carbenium ion chemistry that is assumed to occur on the catalyst

surface because the expressions for the rate equations of the elementary steps do not depend on



8/36

0

20

40

60

80

100

Selectivity(%)

2-Octene

3-Octene

4-Octene

2-Octene

3-Octene

4-Octene

2-Phenyloctane

3-Phenyloctane

4-Phenyloctane

2-Phenyloctane

3-Phenyloctane

4-Phenyloctane

0

5

10

15

20

25

Selectivity(%)

0

0.5

1

1.5

2

2.5

0 20 40 60 80 100


Select

ivity/conversion

0

0.05

0.1

0.15

0.2

0.25

0 20 40 60 80 100


Select

ivity/conversion

0 20 40 60 80 100


0 20 40 60 80 100


Figure 2

First-order (top) and second-order (bottom) delplot method charts for octene isomers ( left) and phenyloctanes(right) for data over CBV760 at 343 K and benzene-1-octene molar feed ratio of 5. Markers indicateexperimental data, and solid lines are added to guide the eye. Dotted lines correspond to theoreticalselectivities calculated for equilibrium between octene isomers, respectively, between 2-, 3-, and4-phenyloctane isomers (adapted from Reference 53).

the nature of the intermediates involved, and hence, the kinetic model is independent of the nature

of the reactive intermediates.

Kinetic analysis: definition of catalyst descriptors. Asexplainedinearlierwork(53),theratioof

the initial selectivities (i.e., in the limit of zero 1-octene conversion) of 2-octene to 2-phenyloctane

is related to the ratio of the rate coefficient for the deprotonation step leading to the formation of

2-octene to the rate coefficient for alkylation leading to 2-phenyloctane ( Scheme 1).

Considering the benzene concentrations used in the kinetic experiments, the observed higher

initial selectivity for 2-octene as compared with that for 2-phenyloctane indicates that the rate

coefficient for deprotonation is higher than the rate coefficient for alkylation. Because the selec-

tivity of the primary products, 2-octene and 2-phenyloctane, is independent of temperature, we

can conclude that the activation energy for the deprotonation step leading to 2-octene is similar

to that for the alkylation step leading to 2-phenyloctane, as illustrated in the enthalpy diagram in

Figure 4, and that entropy favors double-bond isomerization over alkylation.

A change in acid strength can lead to a change in the protonation enthalpy of the olefins and the

phenyloctanes. Because Hiso(liq)between the olefins is independent of the catalyst, it follows from

570 Reyniers Marin


9/36

+ + +

+++

+ H+ + H+ + H+

+

H+

+

H+

+

H+

+

H+

+

+

+

1

7 8 9

2 3 4 5 6

10 11 12

Figure 3

Reaction network of elementary steps for the alkylation of benzene with octenes over ultrastable Y zeolites (22).

thermodynamic considerations that the effect of the catalyst on the protonation of the octenes canbe captured by the introduction of a single cat(Hpr,O), where catpresents a change in going

from one catalyst to another. Hence,cat(Hpr,O) can be seen as an average measure of the effect

of the catalyst on the stability of the intermediate octyl carbenium ions.

Also, activation energies of the elementary steps could be affected by a change in catalyst.

However, the observation that product selectivities are not affected by the catalyst indicates that

the effect on the activation energies for deprotonation and alkylation is similar; in other words,

catEa,al k = catEa,depr,O, 2.

indicating that the stability of all transition states (smaller ones for protonation/deprotonation

and larger ones for alkylation) are influenced to the same extent by the zeolite. By applying the

EvansPolanyi principle (75), the change in activation energy of the alkylation step can be relatedto the enthalpy change of the surface alkylation step, catHalk, as follows:

catEa,al k = al k catH al k. 3.

Given thatHr(liq) is independent of the catalyst, thermodynamic considerations allow us to

expresscatHalkas

catHal k = catHp r,Ph e O catHpr,O. 4.



10/36

+

+

+

kpr,0

kdepr,1

kdepr,2

kalk

kpr,0

H+

+ H+

+

H+R 0

2PO

kalkKpr,0CtC0

1octC0

b

1 + Kiso, I+ Kpr,0C0

1oct+ Kpr,0C0

b

=kalkkpr

R 02O

kdepr,2

Kpr,0

CtC0

1oct

1 + Kiso,I+ Kpr,0C0

1oct+ Kpr,0C0

b

=kalkkpr

S 02PO

S 02O

kalkC0

b

kdepr,2=

Scheme 1

Initial reaction scheme and initial rate equations.

Because the transition states for deprotonation and alkylation are similarly influenced by the

catalyst, the extent to which the intermediate phenyloctane arenium ions are influenced likely is

the same as that for the octyl carbenium ions; in other words, it can be assumed that

catHpr,PheO= catHpr,O = catHpr. 5.

Enthalpy

Reaction coordinate

Ea,pr

Hpr,O

Ea,alk

Ea,de-pr,2

2C+8ads

2C=8

Ea,alk Ea,de pr,2

2PhO

2PhO+ads

1C=8

Hpr,PO

Hr

Figure 4

Energy diagram for the alkylation of benzene with octenes over a Y zeolite.

572 Reyniers Marin


11/36


12/36

0.250.1

0.08

0.06

0.04

0.02

0

20

1

3

5

740

6080

100

Total C+8 2-C+8

0.2

0.15

Fractionalcoverage()

Acidityd

ifferenc

e(kJ/m

ol)Sitetime(s)

0.1

0.05

0

a0.15

0.1

0.08

0.06

0.04

0.02

0

20

1

3

5

740

6080

100

0.12

0.09


Acidityd

ifferenc

e(kJ/m

ol)Sitetime(s)

0.06

0.03

0

b

0.080.1

0.08

0.06

0.04

0.02

0

20

1

3

5

740

6080

100

3-C +8 4-C+8

0.06

0.04


Acidityd

ifferenc

e(kJ/m

ol)Sitetime(s)

0.02

0

c0.08

0.1

0.08

0.06

0.04

0.02

0

20

1

3

5

740

6080

100

0.06

0.04


Acidityd

ifferenc

e(kJ/m

ol)Sitetime(s)

0.02

0

d

Figure 6

Model prediction for acid site coverage at 373 K and feed benzeneto-1-octene ratio of 5:1 as a function of the acid strengthrelatedparameter,Hpr, and the variation of the coverage with the site time: (a) total octyl carbenium ion coverages, (b) 2-octyl cationcoverages, (c) 3-octyl cation coverages, and (d) 4-octyl cation coverages (22).

and to 26 kJ mol1 for CBV712. Thus, on CBV760, the protonation steps occur more easily

than on the other two Y zeolites. This results in a higher coverage of octyl carbenium ions on the

surface of CBV760, which in turn leads to higher alkylation rates. The fractional site coverage of

the various octyl carbenium ions, for different values ofcatHpr, is illustrated inFigure 6as a

function of site time.

Physicochemical significance ofcatHpr. To interpret the physicochemical significance of

catHprin terms of zeolite properties, the thermodynamic cycle presented in Figure 7 is fre-

quently used (43, 7981) because the protonation enthalpy of, for example, an octene can then be

expressed asHpr= DPE+PAo l e f + Es ta b , 10

withDPE(deprotonation energy of the zeolite) defined as the energy required to remove a proton

from the solid acid (increases for weaker acids), implying that acid strength differences reflect

differences in stability between the protonated zeolites (ZO-H) and their conjugate bases (ZO).

In general, acidityincreases withincreasing polarity of theZO-H bond andwith increasing stability

of the conjugate base (i.e., with increasing ability of the conjugate base to accept and delocalize

574 Reyniers Marin


13/36

H

H+

+

+

Hprot

PA1-octene

Estab

DPE

AlSi Si

O O

AlSi Si

O O

AlSi Si

O O

AlSi Si

O O

Figure 7

Thermodynamic cycle explaining the contribution of the zeolite deprotonation energy (DPE), the alkeneproton affinity, and the stabilization energy (Estab) owing to confinement of the free-gas-phase carbenium ionin the zeolite to the protonation enthalpy of the olefin.

the negative charge).PAo l e f is the proton affinity of the olefin, andEs ta bis the stabilization energy

owing to confinement of the free-gas-phase octyl carbenium ion in the zeolite. The extent to

which guest molecules are solvated by confinement in the zeolite frame depends on one hand on

the structure and composition of the zeolite and on the other hand on the size, shape, functional

groups, and charge of the guest molecule. These factors determine the number and nature of host-

guest interactions, such as, for instance, the weak induced-dipole interactions between alkanes and

the Brnsted acid site (43, 82, 83), H-bonding interactions between the hydrogen of the hydroxyl

group in alcohols and framework oxygens (84, 85), long-range electrostatic interaction between

charged species and the zeolite conjugate base, and van der Waals interactions (8486). Attractive

van der Waals interactions between the zeolite framework atoms and polarizable electron clouds

of the guest molecule typically increase when the confining space becomes smaller, up to the pointwhere Pauli repulsion takes over and the interaction becomes repulsive (i.e., sterical hindrance

comes into play). In general, Estabcan be decomposed into a long-range electrostatic interaction

energy,Eelec, and stabilizing van der Waals interactions, EvdW. Similar equations can be written

for the protonation of the phenyloctanes and also for the activation energies.

Hence,catHprcan be rewritten as

c atHpr= c atDPE+c atEs ta b = c atDPE+c atEelec+c atEvd W, 11.



14/36

because the proton affinity of the olefin is independent of the catalyst and cancels out. catDPE

represents the difference in acid strength between two zeolites, whereascatEstab represents the

difference in solvation ability of the considered confined species between the two zeolites. Clearly

these two factors can contribute to the value ofcatHpr. Recently, it was suggested that the

main factor responsible for activity differences between dealuminated Y zeolites is differences in

solvation ability, catEstab, whereas differences in the Brnsted acid strength would play only a

minor role (43, 80). Thus, activity differences among dealuminated Y zeolites were attributed to

changes in the effective size of the supercages owing to the presence of varying amounts of extraframework alumina. An increase in activity over dealuminated Y zeolites would then be related to

increased van der Waals interaction in supercages with smaller void space. If so, then the effect

of a change in catalyst is expected to be more pronounced on the more bulky confined hydro-

carbon species. However, as discussed above, in benzene alkylation, experimental observations

indicate that intermediates and transition states, which strongly differ in size and shape, are all

affected to the same extent in going from one Y zeolite to the other. Hence, for a given confined

hydrocarbon species, differences in van der Waals interactions with the large supercages of the

Y zeolites can be neglected; in other words, for a given intermediate, catEvdW =0. Given that

the charge on the intermediates (i.e., octyl carbenium ions and protonated phenyloctanes) is not

expected to change significantly in going from one Y zeolite to the other, Eelecis not expected to

change significantly for a given hydrocarbon species; in other words, for a given intermediate,catEelec= 0. Our analysis thus indicates that activity differences in benzene alkylation are mainly

related to acidity differences between the Y zeolites, in agreement with recent theoretical (87, 88)

and experimental studies on protolytic and catalytic cracking (89) and previous work on hydro-

cracking (20, 23).

Whether the physical origin ofcatHpris related to a change in acid strength, to a change in

van der Waals interactions, or to a combination of both factors is of less importance if the interest

remains restricted to modeling the effect of the catalyst on the product yields because both factors

are captured by the same catalyst descriptor. However, to suggest targets for synthesis strategies

that would enable us to tune the zeolite properties, a clear distinction between these two factors

is needed. This requires first-principles methods that enable us to assess the contribution of

dispersive interactions to the thermodynamics of adsorbed species and transition states in zeolites

Top-Down Approach: Catalytic Cracking of Hydrocarbons

Catalytic cracking of hydrocarbons over a solid acid catalyst is one of the most important oil

refining processes, and high-performance catalysts are needed to ensure optimal use of feed and

energy resources. In fluid catalytic cracking (FCC), dealuminated Y zeolites and H-ZSM-5 are

mainly used as catalysts.

Although catalytic cracking of hydrocarbons proceeds via a complex reaction mechanism, the

thousands of reactions that occur can be grouped into a limited number of elementary reaction

families, including protolytic scission, (de)protonation, -scission/alkylation, hydride transfer,

and isomerization reaction steps. Hence, a kinetic analysis based on the automated generation of

a detailed reaction network is ideally suited to evaluate the influence of reaction conditions and

catalyst properties on the product yields.

Detailed reaction network generation. Various algorithms and techniques are in use for the

automated generation of complex chemistries, and several excellent reviews on the topic are avail-

able (27, 28, 5456). We used a computer algorithm in which species are represented by vec-

tors and reactions are implemented as operations on Boolean relation matrices (90, 91). Specific

576 Reyniers Marin


15/36

Table 2 Summary of the detailed generated reaction network for catalytic cracking of

2,2,4-trimethylpentane

Hydrocarbon species Elementary reaction steps

35 Alkanes 179 Protolytic scissions

78 Hydride transfers

94 Alkenes 137 Protonations

102 Carbenium ions 88 Hydride shifts

36 Methyl shifts

193 PCP-isomerizations

21 -Scissions

6 Alkylations

161 Deprotonations

231 Total 899 Total

reaction rules for each elementary reaction family are defined; hence, all possible reaction path-

ways, intermediates, and products are generated starting from a specified feed molecule. Known

kinetic coefficients can be provided from databases based on kinetic experiments or on quantum

chemical calculations for model components. Missing kinetic and/or catalyst descriptors can be fit-

ted to kineticexperimentsusing model molecules.A summary of theresultingdetailed reaction net-

work for 2,2,4-trimethylpentane is given inTable 2 to illustrate that even during cracking of a sin-

gle molecule a huge number of elementary reactions occur simultaneously: In total, 899 reactions

consisting of 179 protolytic scissions, 78 hydride transfers, 137 protonations, 88 hydride transfers,

36 methyl shifts, 193 PCP-isomerizations, 21 -scissions, 6 alkylations, and 161 deprotonations

between 231 species consisting of 35 alkanes, 94 alkenes, and 102 alkylcarbenium ions occur (21).

Kinetic and catalyst descriptors. The effect of the catalyst properties on the product yields was

evaluated for the cracking of two model hydrocarbons, 2,2,4-trimethylpentane (57) and methylcy-

clohexane (58), over a series of commercially available Y and MFI zeolites with varying Si/Al ratios.The properties of the catalysts used and the experimental conditions investigated are provided in

Supplemental Tables 2and3. Dedicated kinetic experiments were performed in a reactor that

operates gradientlessly at high conversion because of the use of external recirculation (92).

Representative profiles of conversion versus site time (molH+ mol1-octene1 s) and selectivity

versus conversion are shown in Figures 8 and 9. At equal conditions, the site time yields obtained

when cracking 2,2,4-trimethylpentane over the MFIs are a factor 34 lower than over the FAUs,

whereas for methylcyclohexane the site time yields are similar, showing that the lower activity

displayed by MFI for cracking of 2,2,4-trimethylpentaneresults fromreactant diffusionlimitations.

As illustrated inFigure 9, a unique relationship was found between the product selectivities

and conversion within a given framework type, independent of the Si/Al ratio of the zeolite.

This is valid for FAU as well as for MFI and for methylcyclohexane cracking as well as for

2,2,4-trimethylpentane cracking. Changing the framework alters the product selectivity versus

conversion profile owing to shape selectivity.

The main reaction route on FAU in 2,2,4-trimethylpentane cracking was found to be hydride

transfer followed by-scission leading to mainly C4 species, whereas on MFI protolytic scission

it is responsible for the formation of high amounts of C1C3 species, pointing toward the occur-

rence of transition-state shape selectivity hampering the bimolecular hydride transfer reaction.

Reactant shape selectivity can be ruled out because the kinetic diameter of 2,2,4-trimethylpentane


Supplementa
http://www.annualreviews.org/doi/suppl/10.1146/annurev-chembioeng-060713-040032http://www.annualreviews.org/doi/suppl/10.1146/annurev-chembioeng-060713-040032


16/36

80

60

40

20

00 50 100 150 200

C

onversion[mol%]

Site time [mol H+s mol1]

80

60

40

20

00 50 100 150 200

C

onversion[mol%]


80

60

40

20

00 25 50 75 100

C

onversion[mol%]


80

60

40

20

00 20 40 60 80

C

onversion[mol%]


a i-Octane b Methylcyclohexane

CBV500

CBV720

CBV760

LZ-Y20

Y62

CBV3020E

CBV5524G

CBV8014

Figure 8

Conversion of (a) i-octane and (b) methylcyclohexane on five FAU zeolites (top) and three MFI zeolites (bottom) as a function of the sitetime at 748 K and 7 kPa partial pressure. Solid lines represent trend lines obtained by fitting the data series to a logarithmic curve(adapted from References 57 and 58).

is 0.62 nm (93), whereas the effective catalytic pore size of MFI at 573 K lies between 0.662

and 0.727 nm and increases to 0.764 nm at 643 K (94). In methylcyclohexane cracking on FAU,

methylcyclohexane isomerization, followed by ring opening and subsequent cracking, is the main

reaction pathway, whereas on MFI, protolytic scission followed by cracking is predominant,

indicating that here too the bimolecular hydride transfer reaction is hampered and transition-state

shape selectivity is operative.

So far, only a fewkinetic models that explicitly account for the effect of the catalyst acidityon the

product yields have been reported (95107). To the best of our knowledge, only one microkinetic

modeling study accounting for the effect of transition-state shape selectivity in hydroconversion

ofn-octane on the Pt-H-ZSM-22 zeolite has been reported (108).

We have used the single-event microkinetic modeling approach (20, 23) to describe the con-

version of the hydrocarbons based on carbenium ion chemistry that is assumed to occur on the

catalyst surface (see sidebar, Single-Event Microkinetic Modeling Approach).

To account for the effect of variations in acidity on the observed catalytic behavior, a change

in protonation enthalpy, catHpr, referenced to LZ-Y20 is sufficient because the absence of

selectivity differences when cracking alkanes or cycloalkanes on FAU or MFIzeolites indicates that

each reaction pathway is affected in the same way by a change in acid strength; in other words, all

transition states and surface intermediates are affected to the same extent. This results in a change

in activation energy of the so-called initiation reactions (i.e., protonation and protolytic scission),

whereas the activation energies of the surface reactions and deprotonations remain unaffected by

the zeolite acid strength. A variation in protonation enthalpy of 29 kJ mol1 was found for the

578 Reyniers Marin


17/36

SINGLE-EVENT MICROKINETIC MODELING APPROACH

In the single-event microkinetic modeling approach, the global symmetry numbers of the reactant and transition

state are factored out from the rate coefficient and calculated from statistical thermodynamics, leading to th

so-called single-event rate coefficient, k:

k =react gl

gl

k,

in which react gl and

glare the global symmetry numbers of the reactant and the transition state, respectively

The single-event rate coefficient, k, is assumed to depend only on the reaction family and the type of carbenium

ions (primary, secondary, or tertiary) involved. These assumptions allow for a drastic reduction in the number o

adjustable parameters to be fitted to the experimental data.

five faujasites (21), whereas for the three MFI zeolites, a variation in protonation enthalpy of 10 kJ

mol1 was found (109).

To describe the effect of transition-state shape selectivity on the rates of hydride transfer of

gas-phase alkanes and cycloalkanes when cracking methylcyclohexane on MFI, it was sufficient to

40

30

20

MFI

MFI

MFI

MFI

FAU

FAU FAU

MFI

FAU

FAU

10

0

Selectivity[mol%]

0 20 40 60 80

Conversion [mol%]

CBV500

CBV720

CBV760

LZ-Y20

Y62

CBV3020E

CBV5524G

CBV8014

60

45

30

15

0

Selectivity[mol%]

0 20 40 60 80

Conversion [mol%]

80

60

40

20

0

Selectivity[mol%]

0 20 40 60 80

Conversion [mol%]

50

30

40

20

10

0

Selectivity[mol%]

0 20 40 60 80

Conversion [mol%]

a Ethylene b Propane

c Propylene d Isobutane

Figure 9

Representative product selectivities as a function of methylcyclohexane conversion on five FAU zeolites and three MFI zeolites at748 K and 7 kPa partial pressure. The solid lines represent trend lines obtained by fitting all FAU and MFI data to a second-orderpolynomial curve (adapted from References 57 and 58).



18/36

PROTOLYTIC CRACKING

Protolytic cracking is a monomolecular reaction and involves proton transfer from the zeolite to a C-C or C-H

of a physisorbed alkane. Assuming equilibrium for the physisorption step, the relationship between the observed

cracking rate, the intrinsic protolytic cracking rate coefficient, and the physisorption enthalpy and entropy can be

expressed as

r= kKph ysp i

and

r= Aexp

EaRT

e xp

S0ph ys

R

e xp

H0ph ys

R

p i.

This leads to

Ecomp =Ea +H0ph ys

and

Acomp = A+

S0ph ys

R

for the composite activation energy,Ecomp, and the composite preexponential factor,Acomp.

introduce a single shape-selectivity descriptor in the model:

Ea,MFI,ht f =Ea,FAU,ht f+c atEa,h f t. 12

On MFI, an increase in activation energy of hydride transfer of 10 kJ mol1 relative to FAU

was found (109), reflecting that in MFI, Pauli repulsion comes into play; in other words, sterical

hindrance between the hydride transfer transition state and the zeolite wall becomes important in

the smaller MFI voids. The entropic contributions were assumed to be similar for both frameworktypes. Narasimhan et al. (108) also reported that the effect of shape selectivity in ZSM-22 can be

captured by a change in activation energy only.

However, Bhan et al. (110) recently emphasized the important role of the activation entropy

in protolytic cracking of alkanes in zeolites (see sidebar, Protolytic Cracking).

Earlier studies on protolytic cracking reported a similar intrinsic activation energy for pro-

tolytic scission on all zeolites, and observed differences in catalytic activity were explained by

differences in physisorption enthalpies between zeolites. Bhan et al. (110) pointed out that at typi-

cal protolytic cracking conditions, differences in physisorption enthalpies alone cannot account for

the observed differences in activity and selectivity among different zeolite framework types owing

to the compensation effect between adsorption enthalpy and entropy. Differences in activity were

attributed to differences in intrinsic preexponential factors as well as differences in intrinsic activa-

tion energies. From a dispersion-corrected periodic density functional theory (DFT-D) study of

adsorption equilibrium coefficients ofn-alkanes in various zeolites, De Moor et al. (83) concluded

that changes in monomolecular cracking activity with carbon number and with zeolite framework

cannot be attributed solely to changes in the physisorption equilibrium coefficient. Given that

reported intrinsic activation energies are rather independent of the zeolite and the length of the

alkane (43, 111115), these authors concluded that the intrinsic preexponential factors, and thus

the intrinsic activation entropies, also play an important role. In addition, Iglesia and coworkers

580 Reyniers Marin


19/36


20/36

hydrogenation are similar in size, shape, and composition, and it is reasonable to assume that they

are solvated to the same extent within a given confining space. Hence,

rEa,8 = rEa,12 = (PAC-C PAC-H), 19

indicating that the difference in activation energy between cracking and hydrogenation is inde-

pendent of the zeolite environment. Given the observed difference in cracking-to-hydrogenation

ratio between 8-MR and 12-MR sites in MOR, entropy differences induced by confinement of

the two transition states in the different surrounding voids clearly can play a role in explaining theobserved product yields; in other words,

rSa,8 = (SstabTSC-C,8 SstabTSC-H,8) = rSa,8 = (SstabTSC-C,12 SstabTSC-H,12). 20

To explain the observed selectivity behavior with varying fractions of 8-MR sites in MOR

Gounder & Iglesia (43, 110, 115) thus emphasized the dominant role of entropy in the stabiliza-

tion of adsorbed species and transition states within different confining spaces in a given zeolite

when competing reactions proceed via transition states of similar size, shape, and composition;

therefore, differences in the enthalpy factors more or less cancel out in Equations 17 and 18.

The effect of the surrounding environment (8-MR or 12-MR sites) on a given reaction (i.e.,

the shape-selectivity effect) can, however, also be interpreted using the expressions

s it eEa,C-C = s it e DPE+ (EstabTSC-C,12 EstabTSC-C,8) (Hf ys,12 Hf ys,8) 21.

and

s it eEa,C-H = s it e DPE+ (EstabTSC-H,12 EstabTSC-H,8) (Hf ys,12 Hf ys,8), 22

because thePAterm cancels out from the equations. Usually, van der Waals contributions in the

physisorbed alkanes and transition states are similar; hence,

s it eEa,C-C = s i te DPE+s it eEelecTSC-C 23

and

s it eEa,C-H = s it e DPE+s it eEelecTSC-H. 24

In the particular case considered (i.e., competing reactions of a given alkane in differently shapedsurroundings in a given zeolite with a given Si/Al ratio but in which the protons on the 8-MR sites

have been selectively replaced by monovalent sodium ions), it can be expected that the 8-MR and

12-MR sites have more or less equal strength and that the long-range electrostatic stabilization of

the charged transition states by the MOR framework is rather similar too.

Inthemoregeneralcase(i.e.,foragivenreactioninadifferentzeoliteframeworkwithadifferent

Si/Al ratio), Equation 23 or 24, together with its counterpart for the intrinsic activation entropy,

clearly shows that, in principle, changes in the intrinsic activation energy and/or entropy of a given

reaction occurring on sites that are located in a different zeolite framework with a different Si/Al

ratio can be induced by differences in long-range electrostatic stabilization between the zeolites,

but also by differences in acid strength. Moreover, differences in physisorption enthalpy and

entropy of thealkane in thedifferentconfining spaces can be expected to contribute to the observed

shape-selectivity effect as well. Thus, in general, depending on the particular reaction and on the

particular zeolite frameworks under consideration, one or the other factor can become dominant

in determining enthalpy and/or entropy contributions to explain shape-selectivity effects.

Moreover, Tranca et al. (116) recently reported on a molecular mechanicsMonte Carlo study

of adsorption of light alkanes in H-ZSM-5, which suggested that the physisorption entropy sig-

nificantly depends on temperature. At typical cracking temperatures (700 K), the calculated alkane

adsorption entropy was found to be significantly less negative than at the temperatures usually

582 Reyniers Marin


21/36


22/36

AlO O

HO

H

AlO

O O

O

O O

O

H

OH

O

EtOHg

D1D2

M1

C1

M2

Ethoxy Etheneads

DEEads

DEEg

DEEg

EtOHg

EtOHg

H2Og

H2Og

Al

H

Al

HAl

O O

H

Al

O

H

O

O

AlO

H

O

O

H

HO

AlO O

O

HH

H

AlO O

O

HH

Al

H

O

H

Al

O O

H

EtOHg

EtOHg

EtOHg

H2C = CH2

H2C = CH2

H2C = CH2g

H2C = CH2g

1

2

3 4

5

6

7 8

9

10

11

Figure 10

Reaction network of elementary steps for the zeolite-catalyzed dehydration of ethanol (adapted from Reference 59). Therate-determining step along each reaction path is indicated in red. For the quasi-equilibrated steps, forward and backward arrows are

indicated, whereas only the forward arrow is indicated for the rate-determining step along each reaction path. For all elementary steps,forward and backward steps have been considered explicitly in the microkinetic simulations.

hydrocarbons, also occurs, even on these monofunctional acid catalysts. And at temperatures

above 473 K, the higher hydrocarbons constitute the dominant products (118). In analogy with

the methanol-to-gasoline process, a hydrocarbon pool mechanism has been suggested to explain

the production of the higher hydrocarbons (125).

Because the number of elementary reaction steps involved in ethanol dehydration remains

limited, it is feasible to compute thermodynamics and kinetics for all elementary steps in various

types of zeolites using quantum chemical calculations. Therefore, we have chosen ethanol

dehydration as a probe reaction to obtain a basic understanding of the influence of the zeolite

properties on its reactivity and selectivity behavior in bioalcohol conversion over various types of

zeolites using a first-principles-based microkinetic modeling approach. Relevant thermodynamic

and kinetic parameters for the elementary steps involved in ethanol dehydration over H-FAU, H-

MOR, H-ZSM-5, and H-ZSM-22 were obtained from static dispersioncorrected periodic DFT-

D calculations at 0 K and statistical thermodynamics and fed to a microkinetic model to investigate

the influence of reaction conditions and zeolite properties on reactivity and product selectivity (59,

60). The reaction scheme considered in the microkinetic modeling is illustrated in Figure 10,

584 Reyniers Marin


23/36

Table 3 Elementary steps and the three reaction paths for the assumed mechanism for the

dehydration of ethanola

Step Elementary step A B C

1 C2H5OH(g)+M1 1 1 0

2 M1 M2 1 0 0

3 M2 Ethoxy+ H2O(g) 1 0 0

4 Ethoxy Etheneads 1 0 0

5 EtheneadsEthene(g)+ 1 0 16 M1 +C2H5OH(g) D1 0 1 0

7 D1 D2 0 1 0

8 D2 DEEads+ H2O(g) 0 1 0

9 DEEadsDEE(g)+ 0 1 1

10 DEEads A = r2 C1 0 0 1

11 C1 Etheneads +C2H5OH(g) 0 0 1

Path A C2H5OH(g) Ethene(g) + H2O(g)

Path B 2 C2H5OH(g) DEE(g) + H2O(g)

Path C DEE(g) Ethene(g) + C2H5OH(g)

aThe rate-determining step along each reaction path is indicated in red. For the quasi-equilibrated steps, forward andbackward arrows are indicated, whereas only the forward arrow is indicated for the rate-determining step along each path.

For all elementary steps, forward and backward steps have been considered explicitly in the microkinetic simulations.

and an overview of the three reaction paths is given in Table 3. Kinetic experiments were

performed over H-ZSM-5 in a broad range of conditions and were used for validation purposes.

Our periodic DFT-D calculations indicate that the monomolecular pathway (see Path

A in Table 3) occurs via an intermediate chemisorbed monomer M1 (step 1) that rear-

ranges to a physisorbed monomer M2 (step 2), which undergoes water elimination to form

surface-bound ethoxide (step 3). The water elimination from M2 occurs through activation

of the alcohol C-O bond by the zeolite proton for attack of the carbon atom by the

aluminum-bound oxygen adjacent to the acid site, resulting in a [CH 3CH2OH2]+ cationic

transition state. This mechanism is consistent with the secondary kinetic isotopic effects measured

for ethylene synthesis rates using C2D5OH, which implies that the kinetically relevant step

involves the cleavage of the CO bond via a carbenium-ion-like transition state (123). Other

mechanisms were found to be significantly more activated. Ethoxide is then decomposed

into physisorbed ethene (Ethene) (step 4) that desorbs with regeneration of the active site

(step 5).

In the bimolecular path (see Path B in Table 3), an additional ethanol molecule coadsorbs

with M1 to form a chemisorbed dimer D1 (step 6), in which the proton is shared between the two

ethanol molecules. Rearrangement of D1 to thephysisorbed dimer D2 (step 7) is required for water

elimination to generate chemisorbed diethyl ether (DEE) (step 8). Diethyl ether then desorbs

from the zeolite (step 9) with regeneration of the acid site. The bimolecular elimination toward

DEE involvesactivationoftheC-Obondofonealcoholmoleculebythezeoliteprotonforattack

of its carbon atom by the OH of the other alcohol molecule, leading to a [C2H5OHC2H5

H2O]+ cationic transition state. The second ethanol molecule in the transition state functions as

a solvating agent to stabilize the carbenium-ion-like C2H5+ fragment (80, 123, 126). Reaction of

M1 or M2 with gas-phase ethanol via an Eley-Rideal mechanism was found to be significantly

more activated.



24/36

Table 4 Rate coefficients (s1) at 473 K of the rate-determining step along the monomolecular,

the bimolecular, and the consecutive path in the dehydration of ethanol over zeolites H-FAU,

H-MOR, H-ZSM-5, and H-ZSM-22

H-FAU H-MOR a H-ZSM-5 H-ZSM-22

Reaction k (s1) k (s1) k (s1) k (s1)

M2 Ethoxy+ H2O(g) 2.1 102 7.3 102 1.0 3.6 101

D2 DEE + H2O(g) 3.7 102 7.3 101 2.4 102 8.0 104

DEE C1 1.2 104 2.6 105 5.3 104 2.6 105

a12-MR channels.

In the consecutive path (see Path C inTable 3), a very late and loose transition state is formed

via attack of the -hydrogen of adsorbed diethyl ether by the aluminum-bound oxygen adjacent to

the acid site, leading to simultaneous C-H and C-O bond scission and resulting in physisorbed

ethylene and ethanol (step 10). Desorption of ethanol (step 11) and ethylene (step 5) then restores

the acid site. Several other mechanisms for the consecutive path were investigated and found to

be significantly more activated.

Microkinetic simulations in a broad range of conditions revealed that steps 3, 8, and 10 are therate-determiningsteps alongthe monomolecular, bimolecular, and consecutivepaths,respectively.

All other reaction steps were found to be quasi-equilibrated. Rate coefficients at 473 K for these

rate-determining steps are provided in Table 4. As expected from the values of the rate coef-

ficients, Figure 11 shows that at 473 K, over the four zeolites, diethyl ether is the dominant

reaction product and, hence, that the bimolecular path is by far the dominant reactant path. Also,

the 10-MR zeolites, H-ZSM-5 and H-ZSM-22, are found to be much more reactive than the

12-MR zeolites, H-MOR and H-FAU (60). H-MOR, H-ZSM-5, and H-ZSM-22 have higher

DPEvalues (i.e., lower acid strengths) in comparison with H-FAU, but they provide higher sta-

bilization energies owing to confinement of the bimolecular transition state in the zeolite pores.

Among the four zeolites, H-ZSM-5 and especially H-ZSM-22 effectively stabilize the cationic

transition state by exerting larger dispersive, hydrogen-bonding and/or electrostatic interactions

than H-FAU and H-MOR, leading to significantly higher reactivity, by several orders of magni-

tude, of H-ZSM-5 and H-ZZSM-22 (seeFigure 12).

As illustrated in Supplemental Figure 1, a good agreement between simulated and exper-

imental conversions on H-ZSM-5 is obtained at temperatures ranging from 470 K to 520 K.

However, with increasing conversion, a systematic underprediction of the ethylene selectivity and

overprediction of the diethyl ether selectivity can be noticed. Analysis of the surface coverages

(seeSupplemental Figure 2) revealed that at higher conversion, adsorbed diethyl ether becomes

the most abundant surface intermediate, indicating that the observed deviation with the experi-

mental data most likely results from an underestimation of the preexponential of step 8 (i.e., the

rate-determining step of the consecutive path) and/or the occurrence of a reaction step for the

conversion of diethyl ether to ethylene and ethanol that has not been considered yet in the current

reaction network.

Because we have calculated the entropic contributions based on the harmonic oscillator approx-

imation, in view of the rather late and loose transition state of reaction 8, the approximation likely

performs poorly for the calculation of the activation entropy of this step. For loosely bonded

complexes in zeolites where there are many soft degrees of freedom, entropy losses calculated

based on the harmonic oscillator approximation are overestimated (117, 127). Therefore, the cal-

culated free-energy barrier of step 8 could be too high owing to the use of the harmonic oscillator

586 Reyniers Marin

Supplemental Material
http://www.annualreviews.org/doi/suppl/10.1146/annurev-chembioeng-060713-040032http://www.annualreviews.org/doi/suppl/10.1146/annurev-chembioeng-060713-040032


25/36

00 1 2 3 4

10

20

30

Conversion(%)

Site time (NH+/FEtOH,0)

H-ZSM-22

H-MOR

H-ZSM-5

H-FAU

00 1 2 3 4

10

20

30

D

EEyield(%)


H-ZSM-22

H-MOR

H-ZSM-5H-FAU

0 1 2 3 4

C2H4yield(%)


H-ZSM-22

H-MOR

H-ZSM-5

H-FAU

0

0.4

0.2

0.6

0.8

1

a

b c

Figure 11

(a) Simulated ethanol conversion and (b) diethyl ether and (c) ethylene yield as a function of site time over H-FAU (Si/Al = 47),H-MOR (Si/Al = 95), H-ZSM-5 (Si/Al = 95), and H-ZSM-22 (Si/Al = 35) at 473 K and inlet partial pressure of ethanol of 10 k

approximation. An increase of the preexponential of step 8 with a factor 10, corresponding to a

decrease in activation entropy of approximately 20 J mol1K1 (in the order of the accuracy that

can be expected from the harmonic oscillator approximation), results in very good agreement withthe experimental data, as shown in Figure 13. However, further exploration of the free-energy

surface using more advanced, ab initio dynamic simulations is needed to identify possible missing

steps in the network and/or to obtain a more accurate calculation of reaction free-energy barriers.

CONCLUSIONS AND FUTURE OUTLOOK

Chemical kinetics seeks to unravel the reaction mechanism at the molecular level and to provide a

quantitative description of the reaction rates. Undoubtedly, microkinetic models are indispensable

for chemical process optimization and design. In addition, their ability to incorporate a wealth of

knowledge available from surface science and operando studies, experimental kinetic studies, and

quantum chemistry makes them an ideal tool in the design of high-performance catalysts. In this

review, we have presented three alternative but complementary approaches for the kinetic analysis

of zeolite-catalyzed reactionsto illustratethepotentialof microkinetic modeling forrational design

of zeolite catalysts with improved activity and selectivity.

Although first-principles calculations can already provide valuable insights into the reaction

mechanism and help to unravel the influence of the catalyst properties on the kinetics of individual

elementary steps, full-fledged, first-principles-based microkinetic simulations remain out of



26/36

H-FAU 7.0

6.3

5.6

4.9

4.2

3.5

2.8

2.1

1.4

0.7

0.0

H-MOR (12-MR)

H-ZSM-5 H-ZSM-22

H-FAU H-MOR

H-ZSM-5 H-ZSM-22

Hydrogenbonding

Ele

ctrostaticpotential(eV)

Ecomp,ZeOH Estab,ZeOH DPE + PA

Ecomp,H-FAU Estab,H-FAU+ DPE + PA

catEcomp= Ecomp,ZeOH Ecomp,H-FAU

Ecomp= Estab,ZeOH Estab,H-FAU

Hads,D2

DPEPA

Estab= EvdW+ Estab,DFT

Estab,vdW= Ecomp,vdW DPE PA

Estab,DFT= Ecomp,DFT DPE PA

Estab

TSB

D2

Ecomp

Ea,8

ZeO+ [C2H5OH---C2H5---H2O](g)

ZeOH + 2C2H5OH(g)

ZeO+ H+2C2H5OH(g)

kJ/mol Ecomp DPE Estab Estab,vdW Estab,DFT (Ecomp) (DPE) (Estab) (Estab,vdW) (Estab,DFT)

H-FAU 60 1,181 462 71 391 0 0 0 0 0

H-MOR 63 1,211 495 83 412 3 30 33 13 20

H-ZSM-5 100 1,210 531 97 434 40 29 69 27 42

H-ZSM-22 109 1,210 540 111 429 49 29 78 41 37

O1

O1

O1

O1

O2

O2 O2

O2C1

C1C1

C1

C3

C3 C3

C3C4

C4C4

C4

C2

C2C2

C2

Figure 12

Thermodynamic cycle (top) explaining the dispersion (EvdW) and long-range electrostatic (EDFT) contribution to the stabilizationenergy (Estab) (middle) of transition state TSB(bottom left) of the rate-determining step of the bimolecular reaction path (reaction 8 inFigure 10) owing to confinement in H-FAU (Si/Al = 47) and 12-MR channels of H-MOR (Si/Al = 95), H-ZSM-5 (Si/Al = 95), andH-ZSM-22 (Si/Al = 35). Deprotonation energies are calculated using QMPot(MP2//B3LYP:GULP). Electrostatic potential ( bottomright) for TSBmapped on a plane that crosses the O1, C1, and O2atoms. The atoms of the acid site do not belong to the plane and arenot shown (adapted from Reference 59).

reach in the foreseeable future. However, the traditional trial-and-error experimental approach

to heterogeneous catalyst design has become far too expensive and time consuming. From the

three approaches presented in this review, suggesting targets for synthesis strategies that enable

us to tune the zeolite properties clearly will require a very close intertwinement of first-principles

theoretical and experimental kinetic studies. In particular, systematic joined experimental and

theoretical studies on adsorption and reaction of various hydrocarbons and oxygenates over

588 Reyniers Marin


27/36

Conversio

n/selectivity

Temperature (K)

100

80

60

40

20

0470 480 490 500 510 520

X (%)

S-DEE (%)

S-C2H4(%)

Figure 13

Ethanol conversion (X), diethyl ether (S-DEE), and ethylene (S-C2H4) selectivity as a function oftemperature at space time Wcat/FEtOH,0 = 6.5 kg s mol

1 and PEtOH,0 = 24 kPa over H-ZSM-5.

Experimental data are indicated with their 95% confidence interval. Model simulations were obtained byadjusting (see text) the ab initiocalculated preexponential of reaction 11 in Figure 10.

well-defined and well-characterized zeolites are needed to unravel the physicochemical origin of

the shape-selectivity effect of zeolites and to obtain quantitative insight into the effect of zeolite

properties on their catalytic behavior under working conditions.

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings that

might be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

This work was carried out using the Stevin Supercomputer Infrastructure at Ghent University and

is supported by the Long-Term Structural Methusalem Funding from the Flemish Government

and the Interuniversity Attraction Poles Programme Belgian State Belgian Science Policy.

LITERATURE CITED

1. Bartholomew CH, Farrauto RJ. 2005. Fundamentals of Industrial Catalytic Processes. 2nd ed. New York:

Wiley-AIChE

2. Keil FJ. 2013. Complexities in modeling of heterogeneous catalytic reactions. Comput. Math. Appl.65:167497

3. Marin GB, ed. 2007.Chemical Engineering Kinetics.Adv. Chem. Eng. 32. London: Academic

4. Ertl G. 2009.Reactions at Solid Surfaces. New York: Wiley & Sons

5. Chorkendorff I, Niemantsverdriet JW. 2003. Concepts of Modern Catalysis and Kinetics. Weinheim: Wiley-

VCH

6. Campbell CT. 1989. Studies of model catalysts with well-defined surfaces combining ultrahigh-vacuum

surface characterization with medium-pressure and high-pressure kinetics.Adv. Catal.36:154



28/36

7. Dumesic JA, Rudd DF, Aparicio LM, Rekoske JE, Trevino AA. 1993.The Microkinetics of Heterogeneous

Catalysis. Washington, DC: Am. Chem. Soc.

8. Masel RI. 2001.Chemical Kinetics and Catalysis. New York: Wiley-Intersci.

9. Bell AT,Head-Gordon M. 2011. Quantum mechanical modeling of catalyticprocesses.Annu. Rev. Chem.

Biomol. Eng.2:45377

10. Salciccioli M, Stamatakis M, Caratzoulas S, Vlachos DG. 2011. A review of multiscale modeling of

metal-catalyzed reactions: mechanism development for complexity and emergent behavior. Chem. Eng.

Sci.66:431955

11. Nrskov JK, Bligaard T, Rossmeisl J, Christensen CH. 2009. Towards the computational design of solidcatalysts.Nat. Chem.1:3746

12. Hansen N, Keil FJ. 2013. Multiscale approaches for modeling hydrocarbon conversion reactions in

zeolites.Chem. Ing. Tech. 85:41319

13. Sabbe MK, Reyniers MF, Reuter K. 2012. First-principles kinetic modeling in heterogeneous catalysis

an industrial perspective on best-practice, gaps and needs.Catal. Sci. Technol.2:201024

14. van Santen RA, Sautet P, eds. 2009.Computational Methods in Catalysis and Material Science. Weinhem,

Ger.: Wiley-VCH

15. van Santen RA, Neurock M. 2006. Molecular Heterogeneous Catalysis: A Conceptual and Computational

Approach. Weinheim, Ger.: Wiley-VCH

16. Smit B. 2008. Molecular simulations of zeolites: adsorption, diffusion, and shape selectivity.Chem. Rev.

108:412584

17. Kim J, Smit B. 2012. Efficient Monte Carlo simulations of gas molecules inside porous materials.J. Chem. Theory Comput. 8:233643

18. Gubbins KE,Liu YC,Moor JD, Palmera JC. 2011. The role of molecular modeling in confined systems

impact and prospects.Phys. Chem. Chem. Phys.13:5885

19. Cheng J, Hu P. 2008. Utilization of the three-dimensional volcano surface to understand the chemistry

of multiphase systems in heterogeneous catalysis. J. Am. Chem. Soc.130:1086869

20. Martens GG, Marin GB, Martens JA, Jacobs PA, Baron GV. 2000. A fundamental kinetic model for

hydrocracking of C8to C12alkanes on Pt/US-Y zeolites.J. Catal.195:25367

21. Van Borm R, Reyniers MF, Marin GB. 2012. Catalytic cracking of alkanes on FAU: single-event mi-

crokinetic modeling including acidity descriptors. AIChE J.58:220215

22. Craciun I, Reyniers MF, Marin GB. 2012. Liquid-phase alkylation of benzene with octenes over Y

zeolites: kinetic modeling including acidity descriptors. J. Catal.294:13650

23. Thybaut JW, Marin GB, Baron GV, Jacobs PA, Martens JA. 2001. Alkene protonation enthalpy de-termination from fundamental kinetic modeling of alkane hydroconversion on Pt/H-(US)Y-zeolite.

J. Catal. 202:32439

24. Marin GB, Yablonsky GS. 2011. Kinetics of Chemical Reactions: Decoding Complexity . Weinheim, Ger.

Wiley-VCH

25. Uhe A, Kozuch S, Shaik S. 2010. Automatic analysis of computed catalytic cycles. J. Comput. Chem.

32:97885

26. Stegelmann C, Andreasen A, Campbell CT. 2009. Degree of rate control: how much the energies of

intermediates and transition states control rates.J. Am. Chem. Soc.131:807782

27. Green WH. 2007. Predictive kinetics: a new approach for the 21st century. In Chemical Engineering

Kinetics, ed. GB Marin, pp. 150. Adv. Chem. Eng. 32. London: Academic

28. Vinu R, Broadbelt LJ. 2012. Unraveling reaction pathways and specifying reaction kinetics for complex

systems.Annu. Rev. Chem. Biomol. Eng.3:295429. Campbell CT. 2004. Towards tomorrows catalysts.Nature432:28283

30. Cejka J, Corma A, Zones S, eds. 2010.Zeolites and Catalysis. Weinheim, Ger.: Wiley-VCH (2 volumes)

31. Corma A. 1997. From microporous to mesoporous molecular sieve materials and their use in catalysis

Chem. Rev.97:2373420

32. Corma A. 2003. State of the art and future challenges of zeolites as catalysts.J. Catal.216:298312

33. Cundy CS, Cox PA. 2003. The hydrothermal synthesis of zeolites: history and development from the

earliest days to the present time. Chem. Rev.103:663701

590 Reyniers Marin


29/36

34. Cejka J, Mintova S. 2007. Perspectives of micro/mesoporous composites in catalysis.Catal. Rev. Sci. Eng.

49:457509

35. Davis ME. 2002. Ordered porous materials for emerging application.Nature417:81321

36. Weisz PB, Frilette VJ. 1960. Intracrystalline and molecular-shape-selective catalysis by zeolite salts.

J. Phys. Chem.64:382

37. Weisz PB, Frilette VJ, Maatman RW, Mower EB. 1962. Catalysis by crystalline aluminosilicates II.

Molecular-shape selective reactions. J. Catal.1:30712

38. Martens JA, Tielen M, Jacobs PA, Weitkamp J. 1984. Estimation of the void structure and pore dimen-

sions of molecular-sieve zeolites using the hydroconversion of normal-decane.Zeolites4:9810739. Weitkamp J, Ernst S, Kumar R. 1986. The spaciousness index: a novel test reaction for characterizing

the effective pore width of bifunctional zeolite catalysts.Appl. Catal.27:20710

40. Deem MW, Pophale R, Cheeseman PA, Earl DJ. 2009. Computational discovery of new zeolite-like

materials.J. Phys. Chem. C113:2135360

41. Pophale R, Cheeseman PA, Deem MW. 2011. A database of new zeolite-like materials. Phys. Chem.

Chem. Phys.13:1240712

42. Treacy MMJ, Rivin I, Balkovsky E, Randall KH, Foster MD. 2004. Enumeration of periodic tetrahedral

frameworks. II. Polynodal graphs.Microporous Mesoporous Mater.74:12132

43. Gounder R, Iglesia E. 2013. The catalytic diversity of zeolites: confinement and solvation effects within

voids of molecular dimensions. Chem. Commun.49:3491509

44. Niwa M, Katada N, Okumura K. 2010.Characterization and Design of Zeolite Catalysts. Berlin: Springer-

Verlag45. Berger RJ, Stitt EH, Marin GB, Kapteijn F, Moulijn JA. 2001. Eurokin. Chemical reaction kinetics in

practice.CATTECH5:3660

46. Mears DE. 1971. Diagnostic criteria for heat transport limitations in fixed bed reactors.J. Catal. 20:127

31

47. Mears DE. 1971. Tests for transport limitations in experimental catalytic reactors.Ind. Eng. Chem. Proc.

Des. Dev.10:54147

48. Berger RJ, Kapteijn F, Moulijn JA, Marin GB, De Wilde J, et al. 2008. Dynamic methods for catalytic

kinetics.Appl. Catal. A342:328

49. Shannon SL, Goodwin JG. 1995. Characterization of catalytic surfaces by isotopic-transient kinetics

during steady-state reaction.Chem. Rev.95:67795

50. Gleaves JT, Ebner JR, Kuechler TC. 1988. Temporal analysis of products (TAP)a unique catalyst

evaluation system with submillisecond time resolution.Catal. Rev. Sci. Eng. 30:4911651. Gleaves JT, Yablonsky GS, Phanawadee P, Schuurman Y. 1997. TAP-2: an interrogative kinetics ap-

proach.Appl. Catal. A160:5588

52. Yablonsky GS, Constales D, Gleaves JT. 2002. Multi-scale problems in the quantitative characterization

of complex catalytic materials.Syst. Anal. Model. Simul.42:114366

53. Craciun I, Reyniers MF, Marin GB. 2007. Effects of acid properties of Y zeolites on the liquid-phase

alkylation of benzene with 1-octene: a reaction path analysis. J. Mol. Catal. A Chem. 277:114

54. Ranzi E, Dente M, Goldaniga A, Bozzano G, Faravelli T. 2001. Lumping procedures in detailed kinetic

modeling of gasification, pyrolysis, partial oxidation and combustion of hydrocarbon mixtures. Prog.

Energy Combust. Sci.27:99139

55. Clymans PJ,Froment GF.1984.Computer-generationof reaction paths andrate equations in thethermal

cracking of normal and branched paraffins.Comput. Chem. Eng.8:13742

56. Vandewiele NM, Van Geem KM, Reyniers MF, Marin GB. 2012. Genesys: kinetic model constructionusing chemo-informatics.Chem. Eng. Sci.207:52638

57. Van Borm R, Aerts A, Reyniers MF, Martens JA, Marin GB. 2010. Catalytic cracking of 2,2,4-

trimethylpentane on FAU, MFI, and bimodal porous materials: influence of acid properties and pore

topology.Ind. Eng. Chem. Res. 49:681523

58. Van Borm R, Reyniers MF, Martens JA, Marin GB. 2010. Catalytic cracking of methylcyclohexane on

FAU, MFI, and bimodal porous materials: influence of acid properties and pore topology. Ind. Eng.

Chem. Res.49:1048695



30/36

59. Nguyen CM, Reyniers MF, Marin GB. 2012.Reactions of bioalcohols in H-FAU, H-MOR, H-ZSM-5 and

H-ZSM-22. Presented at AIChE Annu. Meet., Pittsburgh, PA

60. Nguyen CM, Alexopoulos K, Reyniers MF, Marin GB. 2013. Ab initio based microkinetic modelling of

ethanol dehydration in zeolites. Presented at EuropaCat XI, Sept. 16, Lyon, France

61. Berna JL, Cavalli L, Renta C. 1995. A life-cycle inventory for the production of linear alkylbenzene

sulphonates in Europe.Tenside Surfactants Deterg.32:12227

62. Corma A, Garcia H. 2003. Lewis acids: from conventional homogeneous to green homogeneous and

heterogeneous catalysis.Chem. Rev.103:430766

63. Yadav GD, Siddiqui MINI. 2009. UDCaT-5: a novel mesoporous superacid catalyst in the selectivesynthesis of linear phenyldodecanes by the alkylation of benzene with 1-dodecene.Ind. Eng. Chem. Res.

48:108039

64. Clark JH. 1999. Green chemistry: challenges and opportunities.Green Chem.1:18

65. De Almeida JLG, Dufaux M, Ben Taarit Y, Naccache C. 1994. Effect of pore-size and aluminum content

on the production of linear alkylbenzenes over HY, H-ZSM-5 and H-ZSM-12 zeolites: alkylation of

benzene with 1-dodecene.Appl. Catal. A Gen. 114:14159

66. Cao Y, Kessas R, Naccache C, Ben Taarit Y. 1999. Alkylation of benzene with dodecene. The activity and

selectivity of zeolite type catalysts as a function of the porous structure. Appl. Catal. A Gen.184:23138

67. Bhore NA, Klein MT, Bischoff KB. 1990. The delplot technique: a new method for reaction pathway

analysis.Ind. Eng. Chem. Res. 29:31316

68. Smirniotis PG,RuckensteinE. 1995. Alkylation of benzene or toluenewith MeOH or C2H4over ZSM-5

or zeolite: effect of the zeolite pore openings and of the hydrocarbons involved on the mechanism ofalkylation.Ind. Eng. Chem. Res. 34:151728

69. Namuangruk S, Pantu P, Limtrakul J. 2004. Alkylation of benzene with ethylene over faujasite zeolite

investigated by the ONIOM method.J. Catal.225:52330

70. Rosenbach N Jr, dos Santos APA, Franco M, Mota CJA. 2010. The tertbutyl cation on zeolite Y: a

theoretical and experimental study.Chem. Phys. Lett.485:12428

71. Boronat M, Corma A. 2008. Are carbenium and carbonium ions reaction intermediates in zeolite-

catalyzed reactions?Appl. Catal. A336:210

72. Tuma C, Sauer J. 2005. Protonated isobutene in zeolites: Tert-butyl cation or alkoxide?Angew. Chem.

Int. Ed. 44:476971

73. Haw JF. 2002. Zeolite acid strength and reaction mechanisms in catalysis. Phys. Chem. Chem. Phys.

4:543141

74. Haouas M, Fink G, Taulelle F, Sommer J. 2010. Low-temperature alkane C-H bond activation by

zeolites: an in situ solid-state NMR H/D exchange study for a carbenium concerto. Chemistry16:9034

39

75. van Santen RA, Neurock M, Shetty SG. 2010. Reactivity theory of transition-metal surfaces: a Brnsted-

Evans-Polanyi linear activation energy-free-energy analysis. Chem. Rev.110:200548

76. Rozanska X, van Santen RA, Demuth T, Hutschka F, Hafner J. 2003.A periodic DFT studyof isobutene

chemisorption in proton-exchanged zeolites: dependence of reactivity on the zeolite framework structure

J. Phys. Chem. B 107:130915

77. Boronat M, Viruela PM, Corma A. 2004. Reaction intermediates in acid catalysis by zeolites: prediction

of the relative tendency to form alkoxides or carbocations as a function of hydrocarbon nature and active

site structure.J. Am. Chem. Soc.126:33009

78. Nguyen CM, De Moor BA,Reyniers MF,Marin GB. 2012. Isobutene protonation in H-FAU, H-MOR

H-ZSM-5, and H-ZSM-22.J. Phys. Chem. C116:1823649

79. Macht J, Carr RT, Iglesia E. 2009. Consequences of acid strength for isomerization and eliminationcatalysis on solid acids.J. Am. Chem. Soc.131:655465

80. Carr RT, Neurock M, Iglesia E. 2011. Catalytic consequences of acid strength in the conversion of

methanol to dimethyl ether. J. Catal.278:7893

81. Macht J, Carr RT, Iglesia E. 2009. Functional assessment of the strength of solid acid catalysts.J. Catal.

264:5466

82. De Moor BA, Reyniers MF, Sierka M, Sauer J, Marin GB. 2008. Physisorption and chemisorption of

hydrocarbons in H-FAU using QM-Pot(MP2//B3LYP) calculations. J. Phys. Chem. C112:11796812

592 Reyniers Marin


31/36

83. De Moor BA, Reyniers MF, Gobin OC, Lercher JA, Marin GB. 2011. Adsorption of C2-C8n-alkanes

in zeolites.J. Phys. Chem. C115:120419

84. Nguyen CM, Reyniers MF, Marin GB. 2010. Theoretical study of the adsorption of C1C4 primary

alcohols in H-ZSM-5.Phys. Chem. Chem. Phys.12:948193

85. Nguyen CM, Reyniers MF, Marin GB. 2011. Theoretical study of the adsorption of the butanol isomers

in H-ZSM-5.J. Phys. Chem. C115:865869

86. Nguyen CM, De Moor BA, Reyniers MF, Marin GB. 2011. Physisorption and chemisorption of lin-

ear alkenes in zeolites: a combined QM-Pot(MP2//B3LYP:GULP)-statistical thermodynamics study.

J. Phys. Chem. C115:238314787. Chu Y, Han B, Fang H, Zheng A, Deng F. 2012. Influence of acid strength on the reactivity of alkane

activation on solid acid catalysts: a theoretical calculation study. Microporous Mesoporous Mater.151:241

49

88. Niwa M, Suzuki K, Morishita N, Sastre G, Okumura K, Katada N. 2013. Dependence of cracking

activity on the Brnsted acidity of Y zeolite: DFT study and experimental confirmation. Catal. Sci.

Technol.8:191927

89. Almutairi SMT, Mezari B, Filonenko GA, Magusin PCMM, Rigutto MS, et al. 2013. Influence of ex-

traframework aluminum on theBrnsted acidity andcatalytic reactivity of faujasite zeolite. ChemCatChem

5:45266

90. Feng W, Vynckier E, Froment GF. 1993. Single event kinetics of catalytic cracking.Ind. Eng. Chem. Res.

32:29973005

91. Vynckier E, Froment GF. 1991. Modeling of the kinetics of complex processes based upon elementarysteps. In Kinetic and Thermodynamic Lumping of Multicomponent Mixtures, Vol. 10, ed. G Astaritra, SI

Sandler, pp. 13161. Amsterdam: Elsevier Sci.

92. BeirnaertHC, Vermeulen R, FromentGF. 1994. A recycle electrobalance reactor for thestudy of catalyst

deactivation by coke formation. Stud. Surf. Sci. Catal. 88:97112

93. Funke HH, Argo AM, Falconer JF, Noble RD. 1997. Separations of cyclic, branched, and linear hydro-

carbon mixtures through silicalite membranes.Ind. Eng. Chem. Res. 36:13743

94. Webster CE, Drago RS, Zerner MC. 1999. A method for characterizing effective pore sizes of catalysts.

J. Phys. Chem. B103:124249

95. Costa C, Lopes JM, Lemos F, Ramoa Ribeiro F. 1999. Activityacidity relationship in zeolite Y. Part 3.

Application of Brnsted type equations.J. Mol. Catal. A Chem. 144:23338

96. Costa C, Dzikh IP, Lopes JM, Lemos F, Ramoa Ribeiro F. 2000. Activityacidity relationship in zeolite

ZSM-5. Application of Brnsted-type equations.J. Mol. Catal. A Chem. 154:19320197. Lemos F, Lemos MANDA, Wang X, Ramos Pinto R, Borges P, et al. 2002. Analysis and modelling

of multi-site acid catalysts. In Principles and Methods for Accelerated Catalyst Design and Testing, ed. EG

Derouane, V Parmon, F Lemos, F Ramoa Ribeiro, pp. 21743. Dordrecht, Neth.: Kluwer Acad. Publ.

98. Borges P, Ramos Pinto R, Lemos MANDA, Lemos F, Vedrine JC, et al. 2005. Activityacidity rela-

tionship for alkane cracking over zeolites: n-hexane cracking over HZSM-5. J. Mol. Catal. A Chem.

229:12735

99. Borges P, Ramos Pinto R, Oliveira P, Lemos MANDA, Lemos F, et al. 2009. Contributions for the

study of the

experimental and theoretical- gb marin

Documents