Design of a promoter to enhance the stability of catalysts for hydrocarbon reactions 2

CHAPTER 1
INTRODUCTION

The continuous improvement of computational chemistry algorithms and the ever-
increasing computational resources have brought realistic first principles studies for
industrially relevant catalytic reactions within reach. Theory can be used to help provide
a molecular level understanding of the mechanism of the catalytic reaction and elucidate
the electronic origin of catalyst promotion. Such understanding can lead to optimization
of the industrial process, i.e. selection of improved process conditions, as well as the
design of improved catalysts. Nowadays, the combination of density functional theory
(DFT) calculations, kinetic measurements, and experimental investigations is being
used increasingly for the design of novel/improved catalysts, such as steam reforming
and ammonia synthesis catalysts (Hinneman and Nørskov, 2003; Zhang and Hu, 2002).

Transition metal catalysts such as Fe, Co and Ni are widely used in hydrocarbon
reactions because of the high activity and significantly lower cost in comparison with
precious metal-based catalysts (Zonnevylle

et al., 1990; Joyner

et al., 1988). Especially
Ni based catalysts are commonly used in chemical processes of natural gas activation,
such as steam reforming (SR) and catalytic partial oxidation (CPO) of natural gas
(
Twigg, 1996; Ponec and Bond, 1995). Natural gas is gaining importance as an energy
source and as a raw material for the petrochemical industry. The decreasing supplies of
petroleum and more stringent environmental demands will further strengthen the

1
importance of natural gas. In addition, natural gas conversion into hydrogen for the
efficient production of electricity in fuel cells is attracting widespread research attention.

Its high hydrogen content makes methane a particularly interesting raw material.
Chemisorption and activation of methane on Ni catalysts is of considerable importance
because SR and CPO of methane to produce syngas is the first step in several
industrially important catalytic processes such as production of ammonia (Haber-Bosch),
methanol and higher hydrocarbons (Fischer-Tropsch).

However, coke formation on Ni surfaces is an important technological problem. Ni
catalyzes SR and CPO of methane reactions, but it also catalyzes the formation of
graphitic carbon deposits. Carbon deposition on the catalyst might cause loss of activity,
while growth of filamentous carbon nanotubes can lead to reactor blocking, leading to
regular shutdowns and production losses (Trimm et al., 1981; Reyniers et al., 1994).
Enhancing the stability of Ni based catalysts has therefore been an area of intensive
research, and various promoters have been proposed. One of the oldest proposals is to
introduce trace amount (2 ppm) of H
2
S with the feed gas (Rostrup-Nielsen,

1984). This
method is industrially implemented in the Sulfur Passivated Reforming (SPARG)
Process and was developed by Rostrup-Nielsen. The sulfur selectively poisons the most
active sites of the Ni catalyst, believed to be the step sites, leading to a small loss in the
reforming activity. However, trace amount of sulfur affects the deactivation rate much
more than the reforming rate (Andersen et al., 1987). More recently, promoters such as
Au (Besenbacher et al, 1998; Bengaard et al., 2002), K (Rostrup-Nielsen, 1984), Sn
(Nikolla et al., 2006) and B (Xu and Saeys, 2006) have been proposed and shown to

2
improve the stability of Ni catalysts.

The objective of this thesis is to design a promoter to enhance the stability of Ni-based

catalysts. Thermodynamic and kinetic calculations were carried out to quantify the
stability of different forms of chemisorbed carbon on a Ni catalyst, and to evaluate the
diffusion of carbon atoms from the Ni surface to the first and second subsurface layer
and to the Ni bulk. Boron is found to show similar chemisorption characteristics with
carbon and is proposed to selectively block sites that initiate catalyst deactivation.
Based on this molecular level understanding, boron is proposed as promoter to enhance
the stability of Ni catalysts.
In this thesis, first principles DFT investigations are
combined with experimental validation and optimization to design improved Ni
catalysts.


This thesis is organized as follows. In chapter 2, an overview is given of the state-of-
the-art in first principles based design of metal catalysts. In chapter 3, the theory and the
computational methods used in this work are discussed. In chapter 4, the stability of
different forms of carbon that can exist on a Ni catalyst and the kinetics of carbon
diffusion are addressed, and the effect of boron as a promoter to improve the coking
resistance of Ni catalysts is proposed. A more detailed analysis of the effect of carbon
and boron on the activity of a Ni catalyst is presented in chapter 5. In chapter 6, an
experimental validation of the proposed effect of boron on the stability of a Ni catalyst
during steam methane reforming is presented. Finally, the main conclusions of this work
are summarized in Chapter 7.

3
References
Andersen, N.T., Topsøe, F., Alstrup, I., and Rostrup-Nielsen, J.R., J. Catal. 104, pp. 454.
1987.
Bengaard, H.S., Nørskov, J.K., Sehested, J., Clausen, B.S., Nielsen, L.P., Molenbroek,
A.M., and Rostrup-Nielsen, J.R., J. Catal. 209, pp. 365. 2002.
Besenbacher, F., Chorkendorff, I., Clausen, B.S., Hammer, B., Molenbroek, A.M.,

Nørskov, J.K., and Stensgaard, I., Science 279, pp. 1913. 1998.
Hinneman, B., and Nørskov, J.K., J. Am. Chem. Soc. 125, pp. 1466. 2003.
Joyner, R.W., Darling, G.R., and Pendry, J.B., Surf. Sci. 205, pp. 513. 1988.
Nikolla, E., Holewinski, A., Schwank, J., and Linic, S., J. Am. Chem. Sci. 128, pp.
11354. 2006.
Ponec, V., and Bond, G.C., Catalysis by Metals and Alloys, Elsevier, New York, 1995.
Reyniers, G.C., Froment, G.F., Kopinke, F.D., and Zimmerman, G., Ind. Eng. Chem. Res.
33(11), pp. 2584. 1994.
Rostrup-Nielsen, J.R., J. Catal. 85, pp. 31. 1984.
Trimm, D.L., Holmen, A., and Lindvag, O., J. Chem. Technol. Biotechnol. 31(6), pp.
311. 1981.
Twigg, M.V., Catalyst Handbook, 2
nd
Ed, Manson Pub., London, 1996.
Xu, J., and Saeys, M., J. Catal. 242, pp. 217. 2006.

Zhang, C.J., and Hu, P., J. Catal. 116, pp. 4281. 2002.
Zonnevylle, M.C., Geerlings, J.J.C., and van Santen, R.A., Surf. Sci. 240, pp. 253. 1990.

4
CHAPTER 2
FIRST PRINCIPLES BASED DESIGN OF METAL
CATALYSTS
2.1 Introduction
Traditionally, heterogeneous catalysis has largely been an experimental field. While this
is still true, the powerful computational resources available today and the continuous
improvement of computational chemistry algorithms and software are providing new
tools for the study and development of catalytic systems. Using well-chosen and
sufficiently accurate quantum chemical calculations, scientists have been able to
provide new insights into reaction pathways, to predict properties of catalysts that have

not been synthesized, and to bring information for a given system from many different
experimental techniques into a coherent picture.

Theory can be used to help provide a molecular level understanding of the reaction
mechanism and elucidate the electronic origin of catalyst promotion. Such
understanding can lead to optimization of industrial processs, i.e. selection of improved
process conditions, as well as the design of improved catalysts. It has been
demonstrated how first principles calculations can provide a detailed understanding of
the elementary steps of catalytic processes. This molecular level insight was used to
construct fundamental kinetic models from first principles for industrially important
reactions (Saeys et al. 2003; Neurock and van Santen, 2000; Neurock et al., 2000).

5
Recently, in particular the Nørskov group has demonstrated how collaboration between
applied catalysis, surface science and theory can lead to the design from first principles
of improved catalyst for established processes such as steam reforming and ammonia
synthesis (Besenbacher et al., 1998; Honkala et al., 2005).

In this chapter, we will review models using first principles computation to represent the
surface of catalysts. Here, results from first principles based computation for several
notable processes which are metal catalyzed such as hydrogenation of olefins and
aromatics, steam reforming, ammonia synthesis and selective catalytic oxidation will be
presented.

2.2 Models of catalytic surface
The choice of an appropriate model to represent a catalytic surface or active site is
important as it can have significant effects on the accuracy of results. Cluster
calculations use a limited number of atoms to model the catalytic surface. These models
are computationally convenient because they employ atomic or molecular orbital basis
sets to satisfy the boundary condition of zero electron density at infinite distance from

the cluster. It is also possible to study low coverage and calculate vibrational
frequencies with cluster calculations. Unfortunately, sufficiently large clusters need to
be used to obtain a reliable representation of the electronic band structure of a catalyst,
especially in the case of a metal. To partly overcome this problem, embedded cluster
models have been proposed, where the central atoms (the active site) are treated with an

6
accurate computational method and the surrounding atoms are treated at a lower, often
semi-empirical level.


Figure 2.1. Three approaches and examples for modeling chemisorption and reactivity
on surfaces. (Left) cluster approach, maleic anhydride on Pd; (center) embedding
scheme: ammonia adsorption in a zeolite cage; (right) periodic slab model: maleic
anhydride adsorption on Pd(111). (Neurock, 2003)


On the other hand, slab models use periodic boundary conditions to model extended
surfaces. In these models, the surface is represented by a unit cell which is repeated in 3
dimensions. The slab models avoid the electronic structure artifacts that sometimes
trouble cluster calculations. Typically, the unit cell consists of a two-dimensional
rectangular cluster of about 10 atoms and 3-5 atom layer thickness with a large vacuum
layer on top of it, resulting in a model consisting of an infinite 2D slab of 3-5 layer
thickness, separated from the next slab by a vacuum layer of 1-2 nanometer. To study
low coverage adsorption using periodic slabs, very large unit cells are required. The slab
models require the use of periodic basis sets to match the boundary conditions, and
often plane waves are used. The convergence can however be slow, depending on the

7
size of the plane wave basis set. The three approaches are illustrated in Figure 2.1.

2.3 Hydrogenation of olefins and aromatics
The adsorption of ethene (Fahmi and van Santen, 1996; Shen et al., 1999; Watwe et al.,
1998), ethyne (Watwe et al., 1998; Clotet and Pacchioni, 1996; Medlin and Allendorf,
2003), propene (Valcarcel et al., 2002a), propyne (Valcarcel et al., 2002b), cyclohexene
(Saeys, 2002), cyclohexadiene (Saeys, 2002; Saeys and Reyniers, 2002), and benzene
(Mittendorfer and Hafner 2001; Saeys et al., 2002) on various transition metals (Ni, Pd,
Pt) has been studied from first principles. Reaction path studies have been carried out
for gas phase hydrogenation of ethene (Pallassana et al., 1999; Pallassana and Neurock,
2000; Neurock and van Santen, 2000; Neurock et al., 2000), ethyne (Sheth et al., 2003),
and benzene (Saeys, 2002; Saeys et al., 2003; Morin et al., 2003). Most of the results
reported are based on the most thermodynamically stable (111) facet. However, a few
studies also employ the (100) and (110) facets. These ideal surfaces are mostly studied
with periodic slabs with a few employing cluster models.

Ethene hydrogenation has been studied in the greatest detail, in particular by Neurock et
al A series of DFT calculations was performed by Neurock et al. to help elucidate the
nature of the active sites, understand the kinetics and establish the source of the
structure insensitivity. The results indicate that the basic mechanism follows the ideas
proposed by Horiuti and Polanyi (1934). At low or moderate coverages, hydrogen adds
via a classical homogeneous catalyzed reductive-elimination step that involves

8
hydrogen insertion into a metal carbon bond to subsequently form an ethyl intermediate
(Neurock and van Santen, 2000; Neurock et al., 2000). The three-center (Pd-C-H)
transition state involves breaking of the metal-hydrogen and metal-carbon bonds. The
transition state is early along the reaction path whereby there is still a strong interaction
between hydrogen and the metal as well as the carbon and the metal. The C-H bond is
still quite long. The resulting transition state structure is consistent with results found
for homogeneously catalyzed hydrogenation.

The ethyl intermediate that forms reacts in a very similar way to yield ethane. The
transition state to ethane is remarkably similar to that for ethyl. In fact, most of the
hydrogenation reactions that have been examined in the literature are quite similar. The
important point is that the active surface complex involves only one or perhaps two
metal atoms. This is likely one of the reasons hydrogenation reactions are structure
insensitive. Subsequent calculations over the Pd(100) surfaces have been performed
yielding barriers similar to that on Pd(111).

Ethene hydrogenation was examined on well-defined model Pd(111) surface. At low
coverage, the predicted intrinsic activation barriers for ethene and ethyl hydrogenation
are quite similar at 72 and 71 kJ/mol, respectively. The π-bound intermediate (ethene
sits atop a single metal atom) is first converted to the di-σ-species (ethene binds parallel
to one of the bridge metal-metal forming two σ-metal-carbon bonds) before it reacts
with hydrogen. At higher surface coverages, the activation barriers for hydrogenation
are reduced by the repulsive interactions between neighboring hydrocarbon and

9
hydrogen intermediates. The higher coverages lead to the population of π-bound ethene
states that provide a hydrogenation path which has a lower activation barrier at 36
kJ/mol (Neurock and van Santen, 2000; Neurock et al., 2000). The reaction from the π -
bound state proceeds through a "slip-type" mechanism that was proposed in the
homogeneous literature. The only difference here is that the availability and
participation of other surface metal atoms that can assist the reaction on the surface. The
transition state takes place over two metal atoms to form a more “five-center like”
intermediate. The classical homogeneous slip mechanism takes place over one metal
atom to form a “four-center” transition state.

Quantum chemical simulations can provide critical information on the nature of the
active sites, the bonding, and the activation, reaction energy for individual steps. This is

only part of the picture with regard to catalytic performance. A more complete analysis
requires elucidating the formation and consumption of all reactants, intermediates, and
products along with simulating the full set of possible reaction steps to establish what
actual controls the outcome. The Monte Carlo (MC) simulation enables to explicitly
include the atomic surface structure and track the dynamics associated with atomic
transformations in the adsorbate surface layer including surface diffusion. A
representative snapshot of the surface at some instant in time for ethene hydrogenation
over Pd is shown in Figure 2.2. The simulation of ethene hydrogenation over Pd in a
continuous flow reactor system nicely matches those found experimentally. The
apparent activation energy was calculated to be 40 kJ/mol which is within the range of
30-40 kJ/mol reported for fixed-bed experimental systems in the literature (Davis and

10
Boudart, 1991). In addition, by changing the partial pressures of ethene and hydrogen
we find partial reaction orders for hydrogen to be 0.65 to 0.85 and partial reaction
orders of ethene to be –0.4 to 0.0. These are consistent with the experimental values of
0.7 to 0.9 for hydrogen and –0.2 to 0.0 for ethene.

Heterogeneous catalytic reactions which take place over one- or two-metal-atom centers
such as hydrogenation and dehydrogenation resemble analogous homogeneous systems
and tend to be structure insensitive. Alloys can be used in order to improve the
selectivity of these reactions to specific products by shutting down unwanted paths that
lead to byproduct formation. The turn over frequency (TOF) for these reactions,
however, does not change appreciably with changes in structure or surface composition.
For hydrogenation, this is due to a balance between lower hydrogen surface coverages
which decrease the rate and more weakly bound hydrocarbon intermediates which
increase the rate (Mei et al., 2003).

By calculating the adsorption energies, activation barriers and overall energies on model
PdAu surfaces, Neurock and co-authors (Mei et al., 2003; Neurock and Mei, 2002) were

able to simulate the kinetics over different PdAu alloys and surface ensembles. The
simulation results clearly demonstrate that the reaction is insensitive to the addition of
gold regardless of the composition, and specific atomic arrangement of gold. There is
little change in the turnover frequency on a per palladium atom basis (Neurock and Mei,
2002). A more thorough analysis shows that gold reduces the number of sites to adsorb
and activate hydrogen. This decrease in the surface coverage of hydrogen will act to

11
lower the rate. On the other hand, the presence of gold weakens the metal-hydrogen and
metal-carbon bonds to increase the rate of reaction. These two factors tend to
compensate each other and the activity remains essentially the same (Mei et al., 2003).
This is consistent with the experimental results by Davis and Boudart (1991), who show
that the TOF for ethene hydrogenation was changed less than a factor of 2 by increasing
Au to 40% in the Pd/Au alloy. The two important points in this system are that the
reaction occurs over one to two metal atom centers and that the reaction environment
near the active site is important.

Benzene adsorption and hydrogenation was studied in detail by Saeys et al. (2002;
2003). A fundamental kinetic model was constructed from first principles for the
hydrogenation of benzene over a Pt catalyst by using theory to probe the elementary
steps for this process over a Pt(111) surface. Cluster density functional theory
calculations were used to gain fundamental insight in the reaction mechanism and to
obtain reasonable values for thermodynamic and kinetic parameters. In combination
with a limited number of laboratory scale experiments, a fundamental kinetic model
was constructed, which can be implemented in mathematical reactor models for the
simulation of industrial units.



12

Figure 2.2. Representative kinetic Monte Carlo simulation snapshot for ethene
hydrogenation over Pd. (Hansen and Neurock, 2000)


H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
HH
H
H
H
H

H
H
*
*
*
*
*
*
*
**
*
*
*
H
H
H
H
H
H
H
H
H
H
H
*
74
72
77
89
104

87

Figure 2.3. Overview of the different reaction paths for benzene hydrogenation. The
dominant reaction path is indicated in boldface. The hydrogenation activation energies
for every step along the dominant reaction path are indicated. The energy values are
given in kJ/mol. (Saeys, 2002)

13
Benzene adsorption energies at the different sites of Pt(111) surface were calculated.
Benzene adsorbs at the hollow as well as the bridge sites on the Pt(111) surface (Saeys
et al. 2002). Thermodynamics considerations and comparison of the calculated spectra
with the experimental ones revealed that adsorption at the bridge site is preferred at low
coverage, while adsorption at hollow site becomes more important at higher coverage.
Benzene hydrogenation follows a Horiuti-Polanyi type mechanism. Several reaction
paths can be suggested (Figure 2.3). A reaction path analysis based on DFT calculations
indicates that there is a dominant reaction path, along which the activation energy of
every elementary step is at least 15 kJ/mol lower than along an alternative path (Saeys,
2002; Saeys et al. 2003). The dominant reaction path is shown in bold in Figure 2.3.
Along the dominant reaction path, the addition of the fifth hydrogen to benzene to form
the adsorbed cyclohexyl intermediate has the highest activation barrier at 104 kJ/mol
and may likely be the rate determining step (Saeys, 2002).

A Langmuir-Hinshelwood-Hougen-Watson rate expression was constructed from the
first principles based reaction path analysis with the addition of the fifth hydrogen atom
as the rate-determining step. Only the coverage dependent hydrogen adsorption
enthalpy was regressed to accurately model laboratory scale data for the hydrogenation
of toluene over a Pt catalyst. The optimized hydrogen adsorption enthalpy of –62
kJ/mol is consistent with the value from experimental and theoretical studies of high
coverage hydrogen adsorption.

14
2.4 Ammonia synthesis
The synthesis of NH
3
is probably the most studied reaction in heterogeneous catalysis.
The best elementary metal catalysts, such as Ru and Fe were discovered in large-scale
screening experiments almost 100 years ago (Haber, 1966; Bosch, 1966; Mittasch, 1950)
and the nature of the rate-determining step for Fe-based catalysts, N
2
dissociation, was
pinpointed as early as 1934 (Emmett and Brunauer, 1933; 1934). Since 1995, this
process has been studied in great detail on Ru catalysts by Nørskov and co-workers
using periodic DFT calculations. His group's research, recently in collaboration with
Haldor Topsøe A/S, has led to a detailed understanding of the elementary steps and the
origin of catalyst promotion, as well as to the design of a new, improved catalyst.

The starting point to the design of an ammonia catalyst is the volcano-shaped relation
between the ammonia synthesis activity of different catalysts and their nitrogen
adsorption energy shown in Figure 2.4. The transition state for N
2
dissociation is late
and resembles adsorbed atomic nitrogen (Jacobsen et al., 2002), and thus trends in the
nitrogen dissociative chemisorption energy are strongly correlated with the reaction
barrier and with the overall rate of reaction (Logadóttir et al., 2001). The volcano shape
of the plot in Figure 2.4 implies that there is an optimum for the nitrogen adsorption
energy. For metals on which nitrogen is relatively weakly bound, an increase in the
endothermicity of nitrogen chemisorption and a lower coverage of adsorbed atomic
nitrogen implies a high of the transition state energy and thus a lower rate of reaction.

For metals on which nitrogen is strongly bound, however, an increase in the strength of


15

Figure 2.4. Calculated turnover frequencies for ammonia synthesis as a function of the
adsorption energy of nitrogen for various transition metals and alloys. (Jacobsen et al.,
2002)


Figure 2.5. The calculated potential energy diagram for NH
3
synthesis from N
2
and H
2

over Ru(0001) (dashed curve) and stepped Ru(0001) (solid curve). (Honkala et al., 2005)


16
the metal-nitrogen interaction leads to increased nitrogen surface coverage (site
blocking) and thus to a decreased catalytic activity. The net result of these two effects is
a volcano plot in which a maximum in the ammonia synthesis rate versus nitrogen
chemisorption energy relationship is observed (Figure 2.4). The optimal catalyst thus
has a low dissociation barrier, but does not bind nitrogen too strongly. The optimal pure
metals are Os, Ru and Fe. However, Ru and Os are very expensive and thus
commercially less attractive compared to the third, Fe. Fe is sensitive to surface
blocking (too strong nitrogen bonding), whereas Ru has a low sticking coefficient for
N

2
(Egeberg et al., 2001). At higher conversions, Ru becomes a far better catalyst than
Fe, since it is less sensitive to self-poisoning by adsorbed N and NH (Logadóttir et al.,
2001).

As indicated in Figure 2.4, a combination of Mo (which binds N too strongly) with Co
(which binds N too weakly) should be close to optimum. Jacobsen et al. (2002)
identified CoMo as a potential high-activity alloy catalyst by simple interpolation
between the corresponding pure-metal components on the volcano curve (Figure 2.4).
Then, they confirmed with first principles DFT calculations that nitrogen does, in fact,
have the required intermediate chemisorption energy on CoMo surfaces. They also
calculated that the N
2
dissociation energy on this alloy is intermediate between the
dissociation energies on the pure metal components. Finally, they used a Co
3
Mo
3
N
catalyst to demonstrate experimentally that this alloy has an ammonia synthesis activity
comparable to that of the best industrial catalysts (Jacobsen et al., 2002; Boisen et al.,
2002).

17
The maximum of the volcano curve is also sensitive to the reaction conditions
(Jacobsen et al., 2002). At higher NH
3
partial pressures, a catalyst with a lower N-
binding energy is preferred, to prevent site blocking. As illustrated, the catalytic activity
is function only of the N-binding energy. Since it is possible to design catalysts with the

optimal binding energy it is possible to optimize the ammonia process. In this way a
link between DFT and catalyst selection and reactor design can be established (Jacobsen
et al., 2002).

Logadóttir and Nørskov (2003) provided a complete description of the reaction pathway
on both flat and stepped Ru(0001) (Figure 2.5). The calculations show that step sites on
the surface are much more reactive than the terrace sites. The intermediates in the
reaction are bound stronger to the active sites located at steps than on flat terraces.
Based on these results, they suggested that the reaction mainly occurs at the step sites
and N
2
dissociation is the rate-determining step in the reaction over a Ru(0001) surface.
They calculated the activation barrier for N
2
dissociation to be 183 kJ/mol on Ru(0001)
and 39 kJ/mol on the stepped surface. Note that the heat adsorption is incorporated. This
difference in activation energy (Dahl et a., 1999) leads to a 9 orders of magnitude
difference in rate at 500 K. This extreme surface sensitivity of N
2
dissociation was also
found in surface science experiments (Dahl et al., 2000). The active sites for N
2

dissociation are therefore only the step site or the defects and have a relatively low
surface concentration.



18

2.5 Steam reforming
In the steam reforming process, hydrocarbons such as methane are converted to CO and
H
2
over nickel catalysts. The dissociative adsorption of methane and the adsorption and
dehydrogenation of various CH
x
species on Ni(111) were studied in detail (Kratzer et al.,
1996; Watwe et al., 2000; Yang and Whitten, 1992; Michaelides and Hu, 2000) using
first principles DFT calculations. The dissociative adsorption of CH
4
is the rate-limiting
step of the steam reforming process (Besenbacher et al., 1998). The breaking of the C-H
bond in the adsorption of CH
4
occurs on top of a Ni atom, with a barrier of about 100
kJ/mol. Based on a combination of DFT calculations and experimental studies a very
detailed mechanistic picture and a complete potential energy diagram of steam
reforming including graphite formation on a Ni catalyst has been presented (Figure 2.6)
(Bensgaard et al., 2002). Two types of active site were found: a more active one
associated with step/defect sites and a less active one associated with closed-packed
facets. On closed-packed Ni terrace surface, a barrier of about 100 kJ/mol for methane
activation was reported while a less 88 kJ/mol barrier was calculated for the Ni(211)
surface (Abild-Pedersen et al., 2005). Graphite nucleation is however also initiated at
step sites. Promoters S, and Au preferentially bind to the step sites and block the sites
where graphite formation is initiated, but also reduce the rate of the steam reforming
process. If 50% step sites are blocked by S, the barrier at the Ni(211) steps increase
from 88 kJ/mol to 125 kJ/mol (Abild-Pedersen et al., 2005). An optimized catalyst will
have enough amounts of promoters that graphite formation is effectively blocked, while

19
the fast reaction channel for methane activation is still open.


Figure 2.6. Energies for the species on Ni(211) and Ni(111). All energies are relative to
CH
4
and H
2
O in the gas phase and calculated using the results for the individual species.
(Bengaard et al., 2002)



Figure 2.7. Conversion of n-butane as a function of time during steam reforming in a
3% n-butane-7% hydrogen-3% water in helium mixture at a space velocity of 1.2h
-1
.
The dashed curve shows the n-butane conversion for the Ni and the solid curve is for

20
the Au/Ni supported catalyst. (Besenbacher et al. 1998)
Graphite formation is clearly a problem during steam reforming over nickel and leads to
catalyst deactivation. The Ni surface binds C too strongly, which leads to graphite
formation (Besenbacher et al., 1998; Bengaard et al., 2002). As a possible solution to
this problem, Besenbacher et al. (1998) considered a gold-doped nickel catalyst. Au was
found to substantially improve stability of Ni catalysts under n-butane steam reforming
(Figure 2.7). They also performed theoretical calculations for methane steam reforming.
They calculated the energy barriers of methane activation, when 0.25 ML of Au was
substitutionally alloyed into the Ni surface layer. The barrier increased by 38 kJ/mol

(compared with pure Ni) for methane activation over Ni atoms with two Au neighbors.
Extensive surface characterization confirmed that a stable Au/Ni surface alloy could
exist under in situ reaction conditions and that the catalyst could effectively catalyze the
reforming reaction without substantial graphite formation.

2.6 Selective catalytic oxidation
A microkinetic model for ethene epoxidation was derived by Linic and Barteau (2003a
and 2003b) using surface science experiments and DFT calculations. Theory was used
to study the various possible reaction paths. It was found ethene adsorbs on top of an
oxygen atom to form a surface oxametallacycle intermediate. This intermediate reacts to
form ethene oxide. The surface oxametallacycle was also observed under UHV
conditions using high-resolution electron energy loss spectroscopy (HREELS) and an
intermediate with an almost identical vibrational fingerprint appeared during steady
state catalytic experiments. The activation energy of dissociative O
2
adsorption and the

21
oxygen-silver bond strength are strongly coverage-dependent. From the reaction path
analysis a microkinetic model was constructed. The activation energies and the pre-
exponential factors were obtained from DFT. The proposed kinetic model suggests that
in steady state catalytic process the dissociative adsorption of O
2
and the reaction of
weakly adsorbed ethene with oxygen-covered sites is the potential rate determining
steps. The resulting rate law is said to agree with experimental observations.

The chemistry of the oxametallacycle intermediate was found to control the selectivity
of silver epoxidation catalysis (Linic and Barteau, 2003b). The selectivity of the
epoxidation process is determined by the difference in the rate coefficients for the two

reaction paths. The difference in Gibbs free energy of activation is calculated to be 1.2
kJ/mol in favor of acetaldehyde formation. This indicates that the selectivity to ethane
oxide will predict selectivity of 40 % at 400-500 K.

The calculations of Linic and Barteau correspond to a clean silver surface at rather low
coverages, which is far from the catalytically relevant conditions. Linic and Barteau
argue that dissociatively adsorbed atomic oxygen is the reactive species, using
experimental data. Recently, Li at al. (2003) and Gajdos et al. (2003) have carried out
detailed calculations for different oxygen adsorption states, including subsurface
adsorption, and for varying coverages, taking into account temperature and pressure
effects (Li et al., 2003), to provide a comprehensive picture of the behavior of oxygen
on silver and to obtain insight in the function of silver as an oxidation catalyst. These
studies have led to the identification of other possibly active oxygen species. It seems

22
that at conditions typical for epoxidation, a thin silver-oxidelike structure is most stable
(Li et al., 2003), in contrast to the dissociatively adsorbed oxygen atoms suggested by
Linic and Barteau. Such studies indicate the importance of understanding the surface
structure under catalytically relevant conditions.

23
2.7 References
Bengaard, H.S., Nørskov, J.K., Sehested, J., Clausen, B.S., Nielsen, L.P., Molenbroek,
A.M., and Rostrup-Nielsen, J.R., J. Catal. 209, pp. 365. 2002.
Besenbacher, F., Chorkendorff, I., Clausen, B.S., Hammer, B., Molenbroek, A.M.,
Nørskov, J.K., and Stensgaard, I., Science 279, pp. 1913. 1998.
Boisen, A., Dahl, S., and Jacobsen, C.J.H., J. Catal. 208, pp. 180. 2002.
Bosch, C., Nobel Price lecture 1931, in Nobel Lecture, Chemistry pp. 1922-1941.
Elsevier, Amsterdam, 1966
Clotet, A., and Pacchioni, G., Surf. Sci. 346, pp. 91. 1996.

Dahl, S., Logadóttir, A., Egeberg, R.C., Larsen, J.H., Chorkendorff, I., Tornqvist, E.,
and Nørskov, J.K., Phys. Rev. Lett. 83, pp. 1814. 1999.
Dahl, S., Tornqvist, E., and Chorkendorff, I., J. Catal. 192, pp. 381. 2000.
Davis, R., and Boudart, M., Catal. Sci., Technol.
1, pp. 129. 1991.
Egeberg, R.C., Dahl, S., Logadóttir, A., Larsen, J.H., and Nørskov, J.K., and
Chorkendorff, I., Surf. Sci. 491, pp. 183. 2001.
Emmett, P.H., and Brunauer, S., J. Am. Chem. Soc. 55, pp. 1738. 1933.
Emmett, P.H., and Brunauer, S., J. Am. Chem. Soc. 56, pp. 35. 1934.
Fahmi, A., and van Santen, R.A., J. Phys. Chem. 100, pp. 5676. 1996.
Gajdos, M., Eichler, A., and Hafner, J., Surf. Sci. 531, pp. 272. 2003.
Haber, F., Nobel Price lecture 1918, in Nobel Lecture, Chemistry pp. 1901-1921.
Elsevier, Amsterdam, 1966
Hansen, E.W., and Neurock, M., J. Catal. 196, pp. 241. 2000.

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Honkala, K., Hellman, A., Remedeiakis, I.N., Logadóttir, A., Carlsson, A., Dahl, S.,
Christensen, C.H., and Norskov, J.K., Science, 307, pp. 555. 2005.
Horiuti and M. Polanyi, Trans. Faraday Soc.
30, pp. 1164. 1934.
Kratzer, P., Hammer, B., and Nørskov, J.K., J. Chem. Phys. 105, pp. 5595. 1996.
Jacobsen, C.J.H., Dahl, S., Boisen, A., Clausen, B.S., Topsoe, H., Logadóttir, A., and
Nørskov, J.K., J. Catal. 205, pp. 382. 2002.
Li, W.X., Stampfl, C., and Scheffler, M., Phys. Rev. Lett. 90, pp. 256102. 2003.
Linic, S., and Barteau, M.A., J. Catal. 214, pp. 200. 2003a.
Linic, S., and Barteau, M.A., J. Am. Chem. Soc. 125, pp. 4034. 2003b.
Logadóttir, A., and Nørskov, J.K., J. Catal. 220, pp. 273. 2003.
Logadóttir, A., Rod, T.H., Nørskov, J.K., Hammer, B., Dahl, S., Jacobsen, C.J.H., J.
Catal. 197, pp. 229. 2001.
Medlin, J.W., and Allendorf, M.D., J. Phys. Chem. B 107, pp. 217. 2003.

Mei, D.H., Hansen, E.W., and Neurock, M., J. Phys. Chem. B 107, pp. 798. 2003.
Michaelides, A., and Hu, P., J. Chem. Phys. 112, pp. 8120. 2000.
Mittasch, A., Adv. Catal. 2, pp. 81. 1950.
Mittendorfer, F., and Hafner, J., Surf. Sci. 472, pp. 133. 2001.
Morin, C., Simon, D., and Sautet, P., J. Phys. Chem. B 107, pp. 2995. 2003
Neurock, M., Pallassana, V., and van Santen, R.A., J. Am. Chem. Soc. 122, pp. 1150.
2000.
Neurock, M., and van Santen, R.A., J. Phys. Chem. B 104, pp. 11127. 2000.
Neurock, M., and Mei, D.H., Top. Catal. 20, pp. 5. 2002.
Neurock, M., J. Catal. 216, pp. 73. 2003.

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