Detailed Kinetic Modeling Study of NOx Oxidation and Storage and

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Detailed Kinetic Modeling Study of NOx Oxidation and Storage and Their Interactions over Pt/Ba/Al2O3 Monolith Catalysts Nikola Rankovic,†,‡ Andre´ Nicolle,*,† and Patrick Da Costa‡ IFP, 1 et 4 aVenue de Bois-Pre´au, 92852 Rueil-Malmaison Cedex, France, and UniVersite´ Pierre et Marie Curie - UPMC Paris 6, Laboratoire de Re´actiVite´ de Surface, CNRS UMR 7197, Case 178, 4 Place Jussieu, Tour 54-55, 75252 Paris Cedex 05, France ReceiVed: January 8, 2010; ReVised Manuscript ReceiVed: March 11, 2010

The concept of nitrogen oxide storage-reduction (NSR) is a promising aftertreatment technology for reducing NOx emissions from lean-burn engine exhaust. The present work focuses on the first two steps of the overall NSR mechanism, namely, NO to NO2 oxidation and NOx storage. The governing storage mechanisms are mainly elucidated on the model catalysts such as Pt/Ba/Al2O3. A unique detailed NO oxidation kinetic model over Pt/Al2O3 was conceived based on literature data and validated over a wide range of experimental conditions. This detailed mechanism was then globalized to obtain a Langmuir-Hinshelwood rate expression, which resulted in a reduced CPU cost in reactor computations. The global oxidation model predicts various experimental NO and NO2 profiles well. Further, a detailed kinetic model for NOx storage over Ba/Al2O3 was developed and validated against different experimental data. Finally, the detailed oxidation and storage schemes were successfully coupled and species spillover between the noble metal and the storage material was accounted for. The experimental NO and NO2 profiles obtained from the NOx storage experiments over Pt/Ba/Al2O3 could be reproduced by the detailed coupled model. Reaction pathway analyses and sensitivity studies were performed to provide a more comprehensive insight into the system behavior. 1. Introduction Lean-burn engines providing higher fuel efficiency and lower CO2 emission are becoming a solution preferable to conventionally tuned engines.1 However, when operating at air-to-fuel ratios higher than the stoichiometric one, the reduction of the toxic NOx lean-burn exhaust over a conventional three-way catalyst becomes noticeably less effective. In urban areas, the NOx photochemical pollution induces acid rains, with a negative impact on ecosystems and the infrastructure. The presence of NOx also contributes to the tropospheric ozone formation and the destruction of the stratospheric ozone layer.2 Numerous studies confirm that the exposure to NOx increases the susceptibility to airway infections and impairs lung function, also being harmful for the immune system.3-5 With almost half of all NOx emissions stemming from mobile sources, vehicular emission in the US and the EU has been legislated since the 1990s. The scientific community is in a constant pursuit of more effective deNOx techniques.6 Only a few technological solutions have been commercially applied today, notably selective catalytic reduction (SCR) with urea or hydrocarbons and NOx storage and reduction (NSR). In the mid-1990s, Toyota laboratories introduced the NSR technology over lean NOx traps (LNT).7-9 Today, highperformance LNT adsorber catalysts present a leading choice for reduction of NOx from lean-burn engine exhausts.10 The NSR operating cycle consists of alternating lean phases during which the exhaust NOx are stored over the LNT catalyst with short rich phases during which the stored NOx are reduced to N2. Hence, a NSR catalyst requires NOx sorption sites (alkali * To whom correspondence should be addressed. Telephone: +33 (0) 147526688. Fax: +33 (0) 147527068. E-mail: [email protected]. † IFP. ‡ Universite´ Pierre et Marie Curie.

or alkaline earth metal compounds) and NOx redox sites (noble metals).11 In search for more efficient catalyst formulations and improved engine control solutions, numerous studies have been devoted to the search of better insight into the NSR operating mechanisms. Most of these studies have involved Ba-based storage materials,12-14 but other storage materials (Na-, K-, Mg-, Sr-, Mn-, or Ca-based) have also been investigated.15-18 Precious metals (Pt, Rh, and Pd) are commonly used in a NSR catalyst, playing an important role in the oxidation of NO and in the reduction of the stored NOx.18 The washcoat support is chosen to have a high surface area to disperse the noble metal and the storage compound, most commonly Al2O3, CeO2, ZrO2, MgO, or a mixture of these. A typical model catalyst formulation used for studying the NSR mechanisms is Pt/Ba/Al2O3. Despite the fact that the NSR concept has been known for years now, there is still a lack of knowledge about mechanistic details. Reviewing earlier work, the NSR operating mechanism can be roughly divided into five steps:18 (i) NO oxidation to nitrogen dioxide, (ii) NO or NO2 sorption on the surface of the storage material, giving raise to nitrites or nitrates, (iii) reductant evolution while operating in the rich conditions, (iv) NOx release from stored nitrates or nitrites, and (v) NOx reduction to N2. The NO oxidation over platinum model catalysts has been thoroughly investigated by several research groups, with some of them also focusing on elucidating a kinetic NO oxidation model that would describe the experimental data.19-28 Kinetic studies by Olsson et al.24 indicated that NO oxidation on Pt/ Al2O3 and Pt/Ba/Al2O3 could proceed via both LangmuirHinshelwood and Eley-Rideal mechanisms. Results of Mulla and co-workers19,20 showed that NO2 inhibits the oxidation reaction with a global NO2 order varying from -0.92 for a fresh catalyst to -0.89 for a sintered one. They proposed the molecular oxygen adsorption on platinum to be the ratedetermining step. Harold et al.21 also considered molecular O2

10.1021/jp100192u  2010 American Chemical Society Published on Web 03/29/2010

Study of NOx Oxidation and Storage adsorption to be the rate-determining step when developing a global NO oxidation model. Marques et al.29 performed steadystate experiments and found that the NO and O2 global orders on Pt/SiO2 catalyst were 0.30 and 0.44, respectively. Studies of Fridell et al.30 indicated that the NO oxidation to NO2 is the rate-governing step in the overall storage mechanism. They also suggested that platinum facilitates nitrate decomposition via the spillover from the storage material to the noble metal sites. Findings that platinum decreases nitrate stability is also put forward by James et al.31 Mahzoul et al.32 discerned two platinum sites, close to storage sites and far from storage sites, responsible for NOx storage and NO oxidation, respectively. Forzatti et al.33 identified nitrates as the most abundant surface species upon complete NOx uptake on barium. Density functional theory (DFT) studies34 focusing on the storage mechanism indicate that the storage material lattice oxygen is absorbed by the incoming NO2 molecules, forming a nitrite-nitrate pair. These results are experimentally confirmed by Lunsford and Hess.35 Studies that used more complex gas mixtures (CO2, H2O, and/or hydrocarbon stream) revealed the importance of the competition between carbonate and nitrate formation involved in the storage and release mechanisms.36-38 The most significant attempts to develop a detailed kinetic model for NOx storage can be found in the studies of Olsson et al.,24,25 Forzatti et al.39,40 and Larson et al.41 The importance of chemical kinetic modeling is crucial in terms of developing simulation tools that could predict reactivity and selectivity over an extended range of experimental conditions. In our case, a LNT model is intended for engine aftertreatment system design and control solutions. Employing a predictive software tool instead of doing numerous experimental runs represents an advantage in economic terms. Indeed, kinetic modeling plays a central role in developing new technologies and in the research of an improved catalyst design.42 Most of the kinetic models in literature are limited by validation with data from only one precise experimental setup. To overcome the diversity of models available in the literature, a unique detailed kinetic model for NO oxidation over Pt/Al2O3 formulation is herein developed and validated over a wide range of experimental conditions. Being aware of the importance of such a model in engine control, a globalization methodology that would increase the model robustness and require less CPU requirements for computing the NO oxidation rate is proposed. The second part of the study is dedicated to elucidating and validating a detailed kinetic model for the NOx storage over Ba/Al2O3. Bearing in mind that a typical NSR catalyst consists both of a noble metal and a storage material, the ultimate goal was to examine the possibility of coupling the detailed oxidation and storage submodels and account for species spillover between the two functions. The coupled oxidation-storage model is capable of reproducing experimental data from several sources. Having conceived an accurate oxidation-storage model, an indepth analysis of NOx storage pathways was then performed, followed by rate-of-production and sensitivity analyses. The impact of the synergy between the noble metal and the storage material was also analyzed, and the spillover rate in different storage conditions examined. 2. Modeling 2.1. Reactor Model. The present model has been developed in the AMESim (LMS.IMAGINE.Lab) environment which is based on bond-graph theory. It relies on the exchange of power in a multiphysical system, which is normally the product of an effort variable and a flow variable.43 In the present modeling

J. Phys. Chem. C, Vol. 114, No. 15, 2010 7103 approach, the monolith is split into three phases: bulk gas, reactive surface, and solid phase. It is assimilated to only one mean channel and represented by an association of 0D stirred reactors (CSTR) in series to account for axial dispersion. The monolith model is therefore similar to that of a dispersive instationary plug-flow reactor.44 This multi-0D approach presents a good compromise between CPU performance and physical accuracy. A 0D reactor itself is composed of capacitive and resistive elements. The capacitive element is similar to an open volume where pressure and temperature are deducted from mass and energy balances, whereas the resistive element is used to compute mass and enthalpy flow rates through a channel from the Hagen-Poiseuille pressure drop law.45 The mass balance equation of gaseous species i in a capacitive element is hence

dmi ˙ iout + ωi )m ˙ iin - m dt

(1)

[kg/s]

in which m ˙ in ˙ out represent inlet and outlet mass flux, i and m i respectively, while ωi is the chemical source term due to catalytic reactions. Note that the present model relies on the assumption of a kinetic regime (i.e., no external or internal diffusion limitations). According to the modeling results of Chatterjee,46 this hypothesis is valid at low NO conversions (below 260 °C and over 370 °C). The conversion at temperatures higher than 370 °C is thermodynamically limited. We therefore expect the model to slightly overestimate the NO conversion in the 260-370 °C temperature range. 2.2. Surface Chemistry Model. The proposed model is based on the mean field approximation, with the assumption that the adsorbates are randomly distributed on the surface, which is viewed as being uniform. The site heterogeneity was therefore averaged out by mean rate coefficients.47-49 Surface coverage of adsorbed species i, θi dynamics is described via50,51

dθi ri ) dt Γ

(2)

in which ri is the rate of generation or consumption of species i due to adsorption, desorption, or chemical reaction and Γ is the surface (noble metal) or volume (storage material) site density. Pt site density of 1.7 × 10-5 mol/m2 is calculated by assuming an equidistribution of (100), (110), and (111) crystal planes and using the crystal lattice constant of 0.3923 nm. Considering storage material, the present model uses a site density of crystalline BaO of 3.72 × 104 mol/m3. Equation 3 describes the chemical source terms, ωi:

(

ωi ) SPt

NPt

NΣ+NPt

j)1

k)NPt+1

∑ Vi,jri,j + VΣ ∑

)

Vi,kri,k Mi

[kg/s]

(3)

where SPt stands for active platinum surface, NPt is the number of surface reactions on platinum, VΣ is the active volume of the storage material, NΣ is the number of reactions taking place on the storage material, νi is the corresponding stoichiometric coefficient, and Mi is the molar weight. Molar reaction rates, rj, are described by elementary-step-based reaction mechanisms. Forward reaction rate constants are described via the Arrhenius expression, and the model is conceived so that thermodynamic

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consistency is guaranteed by computing the backward rates via the corresponding thermodynamic constants:52

( )

rj ) Aj exp -

(∏ Ngf

i)1

Ea,j × RT

Nsf

ci

V′i,j

∏ θi

V′i,j

i)1

1 P Keq,j RT

( )

∆Vi,j

Ngb

Nsb

∏ ci ∏ θiV′′ V′′i,j

i)1

i,j

i)1

)

(4)

with Aj being the pre-exponential factor, Ea,j the corresponding activation energy, ci the concentration of the gaseous species i, Keq,i the equilibrium constant, Ng and Ns the number of gasphase and surface species, respectively (index f for forward and b for backward reaction), and ∆ν the difference between gasphase forward (ν′) and backward (ν′′) stoichiometric coefficients. The equilibrium constants are calculated from the corresponding thermodynamic data via

Keq,i )

( ) (

kf,i ∆rHi ∆rSi ) exp exp kb,i R RT

)

(5)

with ∆rSi and ∆rHi representing the reaction entropy and enthalpy, respectively. 2.3. Detailed Kinetic Modeling. The detailed kinetic model for NO oxidation over Pt/Al2O3 and NOx storage on Pt/Ba/ Al2O3 consists of 10 bidirectional elementary-step reactions far from equilibrium, four of which are taking place on platinum, five on the storage material, and one spillover reaction between the noble metal and the storage component. Three gas-phase species and seven surface species are involved. 2.3.1. NO Oxidation oWer Pt/Al2O3. Previous works of Olsson and co-workers24,25 and Harold et al.22 suggest that NO oxidation over Pt/Al2O3 follows the Langmuir-Hinshelwood mechanism. However, other investigations show that NO oxidation over supported Pt catalysts follow an Eley-Rideal type mechanism involving dissociative O2 adsorption and reaction with NO from the gas phase.53 Herein, a mechanism based on the Langmuir-Hinshelwood-Hougen-Watson formalism54,55 and the mean field approximation24,53 is developed. Some studies in literature describe oxygen adsorption by two consecutive steps, molecular adsorption and subsequent dissociation.19,21,56,57 However, following the studies of Olsson et al., the dissociative oxygen adsorption is here described as a single step. The reaction scheme implemented in the AMESim software is described below:

O2 + 2* a 2O*

(R1)

NO + * a NO*

(R2)

NO* + O* a NO2* + *

(R3)

NO2 + * a NO2*

(R4)

where * denotes a platinum site. This scheme corresponds to the global NO oxidation reaction 2NO + O2 ) 2NO2. Pre-exponential factors for adsorption reactions (R1, R2, and R4) are calculated from the corresponding sticking coefficients at zero coverage, S0,i:

Aads ) S0,i




RT 2πMi

[m/s]

(6)

Note that the Motz-Wise correction58 is not accounted for here. The parameter values used for modeling are shown in Table 1. Literature data on the sticking coefficient for oxygen on a Pt(111) surface at 27 °C vary from 0.054 to 0.07.59-62 It was therefore decided to use the sticking coefficient of 0.064 proposed by Yeo et al.61 Exploiting the temperature-programmed desorption (TPD) data, Olsson et al. reported the activation energy for O2 dissociative adsorption to be 30.4 kJ/mol. The enthalpy of O2 adsorption (-192.0 kJ/mol) agrees well with the range of values proposed in the literature.24,50 The same goes for the entropy of adsorption, since our value (-206 J/(molK)) is comparable with the entropy calculations of Olsson et al. derived from transition-state theory. The oxygen desorption enthalpy, ∆rH1 is dependent on oxygen coverage, and this is taken into account by using a coverage-dependent adsorption enthalpy:63

∆rH1(θ) ) ∆rH1,0(1 + R1θO*)

[kJ/mol]

(7)

where ∆rH1,0 is the adsorption enthalpy for zero coverage, R1 is a constant, and θO* is the coverage of oxygen on Pt. The value of R1 is fitted to 0.047. Values assumed by the sticking coefficient for NO adsorption on Pt at 27 °C vary between 0.82 and 0.9.28,63-65 Here, the value proposed by King et al.65 is chosen (0.87). Most of the literature references consider both NO and NO2 adsorption on Pt as being nonactivated.24,28,46,65-67 The enthalpy of adsorption is slightly different from those determined by Gorte et al.68 (-105 to -140 kJ/mol according to the different crystal planes). The entropy value is close to one used by Olsson et al. (-157 vs 150 J/(mol K)). The NO2 sticking coefficient of 0.97 agrees well with literature data.28,67 The enthalpy and entropy values for NO2 adsorption are close to those reported in previous studies.24,65 The enthalpy of NO2 adsorption, ∆rH4, also varies with oxygen coverage according to

∆rH4(θ) ) ∆rH4,0(1 + R4θO*)

[kJ/mol]

(8)

where the value of the inhibition coefficient R4 is optimized to 0.074. The kinetic data for the surface reaction (R3) are calculated from thermodynamics and consequently optimized to predict the experimental conversion. 2.3.2. NOx Storage on Pt/Ba/Al2O3. We now focused on developing a submodel describing the NOx storage on Ba/Al2O3. Forzatti and co-workers40,69-71 suggested that the storage could proceed through two parallel routes, a nitrite route where NO is oxidized on Pt and directly stored in nitrites which are consequently oxidized into nitrates, and a nitrate route where NO2 formed on Pt would spillover on Ba sites to form nitrates and gaseous NO. Harold et al.22 assumed that NOx storage proceeds via the disproportionation of NO2. The disproportionation mechanism that would account for the stoichiometric ratio observed during the NOx storage (1 mol of NO released for 3 mol of NOx stored) is also proposed by Cant and Patterson.72 Epling and Al Harbi73 have shown that NSR trapping materials are generally more effective in trapping NO2 than NO, which has also been confirmed by in situ Fourier transform infrared (FTIR) spectra.74 After extensive screening of literature data and analyzing the microkinetic model proposed by Olsson et

Study of NOx Oxidation and Storage

J. Phys. Chem. C, Vol. 114, No. 15, 2010 7105

∆rH9(θ) ) ∆rH9,0(1 + R9θΣ-NO2NO3)

TABLE 1: Kinetic and Thermodynamic Parameters for NO Oxidation reaction R1 R2 R3 R4 a

S0 or A (mol/m2s) 0.064a 0.87a 7 × 1013 0.97a

b

Ea (kJ/mol)

∆rH (kJ/mol)

∆rS (J/(mol K))

30.4 0.0 101.0b 0.0

-192.0b -100.0b 36.9b -115.0b

-206b -157b 39b -160b

Sticking coefficient (unitless). b Value fitted in this work.

al.24 and adopted by Forzatti et al.,39 the mechanistic model described below was chosen:

O2 + 2Σ a 2Σ-O

(R5)

NO2 + Σ a Σ-NO2

(R6)

NO + Σ-O a Σ-NO2

(R7)

NO2 + Σ-O a Σ-NO3

(R8)

NO2 + Σ-NO3 a Σ-NO2NO3

(R9)

NO2* + Σ-NO3 a Σ-NO2NO3 + *

(R10)

DFT studies of Broqvist et al.75 and Tutuianu et al.76 support the idea of multiple storage sites on barium (oxide, hydroxide, and carbonate). Epling et al. observed the inhibition of NOx storage in presence of CO2 and H2O,38 mechanistically elucidated by Forzatti et al.33 and Lindholm et al.77 Several models taking into account the coexistence of different barium species have also been developed.78,79 In the present model, barium storage sites are considered as equivalent (denoted Σ) regardless of their chemical nature. The validity of the present model is therefore limited to water- and CO2-free experimental conditions. Since NOx storage requires an oxidation step from NO2 to nitrate, several oxidizing agents have been proposed: (i) lattice oxygen associated to the catalyst (support or storage material); (ii) O2 from the gas stream; (iii) NO2.18 We consider stream O2 oxidizing the surface of the storage material (R5). In situ Raman spectra80 confirm the formation of BaO2 when BaO is exposed to oxygen. NO2 chemisorption on storage material leads to the formation of the intermediate species Σ-NO2 which is subsequently oxidized to Σ-NO3, a precursor for the subsequent barium nitrate (Σ-NO2NO3) formation (R9). Other studies also revealed the effect of the proximity between Pt and BaO on NOx uptake and hence the importance of the spillover between the noble metal and the storage component.24,81,82 To account for this phenomenon, the bidirectional spillover reaction R10 is included. The values of the kinetic and thermodynamic parameters for reactions R5-R10 are listed in Table 2. Most of the activation energy, enthalpy, and entropy values are calculated from previous work of Olsson et al.24 and subsequently optimized for our model, while it was chosen to express pre-exponential factors independently from washcoat mass so that the model could be used to reproduce different experimental setups regardless of the washcoat mass and the storage material percentage. Therefore, the pre-exponential factors are expressed in s-1 for the adsorption reactions R5-R9 or in mol/(m2 s) for the surface spillover reaction (R10). The surface nitrate formation (R9) enthalpy is coverage-dependent:

[kJ/mol]

(9)

where θΣ-NO2NO3 denotes surface nitrates coverage and the value of the constant R9 is fitted to 0.091. Following the same formalism, the activation energy and enthalpy of the spillover also depend on oxygen-platinum coverage and nitrate coverage, respectively. Values of linear constants accounting for coverage dependences are 0.212 and 0.344. 2.4. Global NO Oxidation Model. The development of a NOx trap model is intended for the optimization of catalyst volume, loading, and operating strategy (alternating lean and rich cycles).83 Aiming to reduce the number of parameters and calculations used in the oxidation model, and hence optimize the CPU requirements, we performed a study in which the microkinetic model was used to determine NO, O2, and NO2 global orders. For this purpose, the initial oxidation rates were calculated in a differential monolith reactor (i.e., monolith volume and Pt loading were decreased, so that NO conversion remains lower than 15%).29 Literature approaches to global NO oxidation over Pt/Al2O3 modeling consist in introducing a power law expression of the type:

rNO,ox ) kapp[NO]R[O2]β[NO2]γ(1 - η)

(10)

in which kapp is an apparent kinetic constant and η is an approach to equilibrium factor.19,20,57,84 For Mulla et al.,19 values of global NO, O2, and NO2 orders on a fresh Pt/Al2O3 catalyst are respectively 1.09, 0.86, and -0.85. Harold et al.21 based their global model on the microkinetic analysis, presuming O2 adsorption on Pt to be a rate-determining step and developing a corresponding rate expression. 3. Results and Discussion 3.1. Reactor Model. Figure 1 illustrates the comparison between the AMESim 0D and the theoretical CSTR residence time distribution (RTD) values. This comparison is made in the TABLE 2: Kinetic and Thermodynamic Parameters for NOx Storage reaction

A (s-1 or mol/ (m2 s) (see text)

Ea (kJ/mol)

∆rH (kJ/mol)

∆rS (J/(molK))

R5 R6 R7 R8 R9 R10

1.63 × 104 a 3.85 × 107 a 2.54 × 106 a 5.69 × 104 a 1.15 × 106 a 85a

68.6 31.0a 0.0 0.0 19.1a 53.0a

-128.3 -158.5 -150.0a -135.5a -213.4 -133.4

-226 -169 -150a -137 -189 -150

a

Value fitted in this work.

Figure 1. Comparison of the residence time distribution (RTD) for an ideal CSTR reactor (line) and the AMESim computations (O).

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experimental setup taken from Olsson et al.24 (stepwise signal of 680 ppm NO2 in N2 carrier gas at 350 °C, space velocity of 87 000 h-1, and mean residence time τ ) 0.018 s). The theoretical RTD is calculated via85

1 t exp τ τ

( )

E(t) )

(11)

[1/s]

In order to account for the reactor macromixing properties, several 0D components were assembled in series. Attention was then turned to calculating the number of 0D components required for modeling each experimental condition. For this purpose, we first calculate the axial Peclet number (i.e., the ratio of the flow convection rate and the flow diffusion rate):

uL Peax ) Dax

u2dt2 192Dm

[m2 /s]

(13)

with dt denoting the monolith channel diameter and Dm the molecular binary diffusion coefficient. The value of Dm is for this purpose computed from the GRI Mech 3.0 transport properties database.87 Once the value of the axial Peclet number had been obtained, it was used to calculate the RTD of a continuous dispersive piston reactor model, via85

( ) (

Peax(τ - t)2 1 Peax E(t) ) exp 2 πτt 4τt

)

[1/s]

(14)

We matched these values to the RTD of the assembly of N continuously stirred tank reactors in series, calculated as85

N E(t) ) τ

()

N

( Ntτ )

tN-1 exp -

(N - 1)!

Olsson et al.24 NO conc (ppmv) O2 conc (vol %) volumetric flow rate (mL/min) monolith length (mm) monolith diameter (mm) open section ratio CPSI monolith channel size (mm) axial Peclet number Pt active surface (m2) temperature profile

Harold et al.21

Chatterjee46

600 8 2600

482 5 3000

500 1 or 10 3000

15

15

25

12.34

17

20

0.6 413 1×1

0.8 400 1.1 × 1.1

0.8 400 1×1

72

82

137

0.05

3.5

0.07

ramp 25-500 °C, isothermal conditions ramp 150-550 °C, 5 °C/min (100-500 °C) 5 °C/min

(12)

in which u is the gas velocity, L the reactor length, and Dax the axial diffusion coefficient. Dax is evaluated using Taylor’s correlation proposed by Aris:86

Dax ) Dm +

TABLE 3: Different Experimental Setups for NO Oxidation over Pt/Al2O3

[1/s]

(15)

and hence, the number N of 0D components we needed in order to model the macromixing in the reactor was determined. 3.2. Detailed Kinetic Modeling. 3.2.1. NO Oxidation oWer Pt/Al2O3. The detailed kinetic model for NO oxidation over Pt/ Al2O3 has been validated against experimental results from three different setups. The experimental conditions, monolith details and corresponding references are presented in Table 3. Measured and calculated outlet NO and NO2 concentrations for each of the three experimental conditions are illustrated in Figure 2. Each of the studied experimental conditions was characterized by a relatively high Peclet number, close to a plug-flow configuration. Accounting for axial dispersion effects would therefore require a large number of CSTR reactors in series. However, Olsson et al. suggest to describe their monolith reactor as a series assembly of 15 components. We also observed that the smaller number of elements compared to that based on the Peclet number does not significantly influence species outlet mole fraction. Hence, to minimize CPU cost, all the other

reactors were modeled by a series association of 10 tanks. Noticeably, for the experimental conditions of Olsson et al., the rate of NO2 production is overestimated within a narrow temperature range (285-365 °C). This could be explained by the diffusion limitations, which become important as the conversion reaches the maximum. This hypothesis is in agreement with the NO oxidation results of Chatterjee.46 Therefore, accounting for the diffusion limitations should decrease the reaction rates in the mid-temperature range. The number of Pt sites that Olsson et al. reported from CO TPD measurements is 3.8 × 10-3 mol/(kg of catalyst), corresponding to 0.054 m2 of exposed Pt surface area (based on the area of a Pt site of 8 × 10-20 m2/atom).88 The surface obtained when fitting the experimental data (0.050 m2) agrees well with their experimental findings. 3.2.2. NOx Storage oWer Ba/Al2O3. With the concise NO oxidation route in hand, focus was then placed on experimental data on NOx storage over Ba/Al2O3 model catalysts in a monolith reactor setup. For the model validation, the experimental setup and NOx storage results at 350 and 400 °C of Olsson et al.24 were used (Table 4). It should be pointed out that the model validation is limited to experimental data presenting the detailed experimental setup and catalyst characterization (such as volumetric gas flow, monolith dimensions, or washcoat mass). Since only few papers on NOx storage over monolith catalysts provide complete reactor information, the storage model is only validated at 350 and 400 °C in the experimental conditions of Olsson et al.24 NO, NO2, and NOx outlet concentrations in the storage experiments compared to the model predictions are presented in Figure 3. 3.2.3. NOx Storage oWer Pt/Ba/Al2O3. Having worked out the viable detailed kinetic model of NO oxidation over Pt/Al2O3 and NOx storage over Ba/Al2O3, the feasibility of coupling these two models in order to reproduce the storage over a model Pt/ Ba/Al2O3 catalyst was then studied. The synergy of these two functions includes a spillover reaction (R10) that is taken into account. The coupled model is validated against two different experimental conditions (Table 5): Olsson et al.24 (direct NO2 inlet) and Harold et al.21 (NO oxidation + NOx storage). Experimental and calculated outlet profiles for storage experiments are illustrated in Figure 4. One of the notable features of the coupled Pt-Ba system is the fact that the presence of the storage material influences the noble metal dispersion. This effect has been already discussed in the literature18,24,89 and explained by the physical hindrance of Pt caused by the storage material (particularly Ba(NO3)2) or by an increase of the platinum electronic density by the alkaline-

Study of NOx Oxidation and Storage

J. Phys. Chem. C, Vol. 114, No. 15, 2010 7107 TABLE 4: Experimental Conditions for NOx Storage over Ba/Al2O3 Olsson et al.24 NO2 conc (ppmv) volumetric flow (mL/min) monolith length (mm) monolith diameter (mm) open section ratio CPSI monolith channel size (mm) axial Peclet number Ba active volume (m3) temperature profile

680 2600 15 12.34 0.6 413 1×1 79 6.10 × 10-10 350 or 400 °C

by Olsson et al. are globally well simulated, except that the NO signal is underestimated at the beginning of the storage experiment. This finding incites one to think that the catalyst support plays an important role in NO2 oxidation to nitrites when the inlet gas stream contains NO2 only. This observation is in accordance with the FTIR spectroscopy results of Fridell and Westerberg,90 who showed the formation of nitrates upon exposure of Al2O3 to NO2. Another explanation that would account for the lower quality of prediction at the beginning of the storage is the fact that our model does not describe nitrite formation. Doubtlessly, in situ FTIR spectra have shown that the storage at low exposure time preferably leads to nitrite formation while higher exposure time gives rise to surface nitrate species.40 Note also that the accuracy of our model appears to be as good as the one presented by the authors themselves.24 Moreover, the fractional coverages on the storage material peak are 0.65 for Σ-NO2 and 0.15 for Σ-NO3, versus 0.58 and 0.05,

Figure 2. Measured and calculated NO and NO2 outlet concentrations for different experimental conditions. (a) Olsson et al.:24 600 ppm NO, 8% O2 in N2, 25-500 °C, 5 °C/min. (b) Harold et al.:21 482 ppm NO, 5% O2 in N2, stationary points. (c) Chatterjee:46 500 ppm NO, 1% O2 in N2, 150-550 °C, 5 °C/min. (d) Chatterjee: 500 ppm NO, 10% O2 in N2, 150-550 °C, 5 °C/min. (2) Experimental NO2 concentration, (b) experimental NO concentration, (thick line) calculated NO2 concentration, (thin line) calculated NO concentration.

earth oxide. When the inlet gas contains NO2 alone, the Pt surface does not seem to play an important role, and the species outlet mole fractions are barely sensitive to this parameter. On the other hand, if the inlet gas is a mixture of NO and O2, platinum dispersion has a significant impact on the species outlet profiles. Experimental data of Harold et al. suggest that the Pt particle size increases when Ba is present, which could account for the fact that the Pt surface used in our fit decreases from 3.5 m2 (Pt/Al2O3) to 0.04 m2 (Pt/Ba/Al2O3), corresponding, respectively, to 3.71 and 2.63% Pt. Experimental results obtained

Figure 3. Measured and calculated NO, NO2, and NOx concentration as a function of storage time over a Ba/Al2O3 catalyst (680 ppm NO2 in N2).24 (a) Storage at 350 °C; (b) storage at 400 °C. (2) Experimental NO2 concentration, (b) experimental NO concentration, (O) experimental NOx (NO + NO2) concentration, (thick solid line) calculated NO2 concentration, (thin solid line) calculated NO concentration, (dashed line) calculated NOx concentration.

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TABLE 5: Experimental Conditions and Monolith Properties Used for the Validation of the Coupled NO oxidation-NOx Storage Model NO conc (ppmv) NO2 conc (ppmv) O2 conc (vol %) volumetric flow (mL/min) monolith length (mm) monolith diameter (mm) open section ratio CPSI monolith channel size (mm) axial Peclet number Pt active surface (m2) Ba active volume (m3) temperature profile

Olsson et al.24

Harold et al.21

0 680 0 2600 15 12 0.6 413 1×1 79 8 × 10-4 1.40 × 10-9 350 °C

528 0 5 3000 13 17 0.8 400 1.1 × 1.1 72 0.04 4.41 × 10-9 90-500 °C, stationary profile

respectively, for the authors’ model. In conclusion, additional experimental data would be required to fully assess the respective performance of both models. We also pursued rate-of-production analysis in the operating conditions of Olsson et al. (storage 680 ppm NO2 in N2 at 350 °C over Pt/Ba/Al2O3). Storage reaction rate values are illustrated in Figure 5. Reaction rate analysis shows that the molecular NO2 adsorption on the storage material (R6) dominates in the beginning of the storage (upon the peak NO formation). As the surface becomes saturated in Σ-NO2, the latter one begins to decompose, releasing gaseous NO and creating the oxidized barium surface species (Σ-O) involved in the subsequent oxidation of Σ-NO2 to Σ-NO3. The oxidized intermediate species Σ-NO3 then reacts with the freshly incoming gaseous NO2 to form nitrate. Comparing the rate values obtained in the

Figure 5. Storage reaction rates as function of time (680 ppm NO2 in N2 at 350 °C over Pt/Ba/Al2O3). (a) Rates in the 1st 0D storage component; (b) rates in the 15th 0D component. (thick solid line) NO2 adsorption on Σ rate, (thin solid line) NO desorption rate, (dashed line) Σ-NO2 oxidation rate, (dashed-dotted line) nitrate formation rate.

Figure 6. Spillover net rate as function of time in the storage conditions of Olsson et al24 (solid line); spillover rate temperature dependence in the storage conditions of Harold et al21 (dashed line).

Figure 4. Experimental and calculated profiles for NOx storage over a Pt/Ba/Al2O3 model catalyst. (a) Experimental setup of Olsson et al.24 (680 ppm NO2 in N2 at 350 °C); (b) Harold et al.21 (528 ppm NO + 5% O2). (2) Experimental NO2 concentration, (b) experimental NO concentration, (O) experimental NOx (NO + NO2) concentration, (thick solid line) calculated NO2 concentration, (thin solid line) calculated NO concentration, (dashed line) calculated NOx concentration.

first and the 15th 0D component in series, one also remarks that the model accounts for the axial evolution of reaction rates. Negative net spillover rate values reveal the dominance of the backward reaction, indicating a tendency to decompose nitrates formed on the storage material to yield NO2 adsorbed on platinum (Figure 6). The spillover evolution in the storage experiments of Harold et al.21 was also followed. Concerning the temperature dependency of the spillover step, we observed an increase in the nitrate decomposition rate that reaches its maximum at 374 °C and then decreases to zero (Figure 6). However, superposing the outlet profiles with and without the spillover reaction did not result in any significant change. In order to identify the

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θNO ) K2xNOθv

(17)

θNO2 ) K4xNO2θv

(18)

where Ki represents the equilibrium constant of step i and θv is the vacant site fraction. Each adsorption equilibrium constant is computed from the detailed model thermodynamic data. We can now consider the vacant site coverage to be

θv )

1

(19)

1 + √K1xO2 + K2xNO + K4xNO2

Assuming reaction R3 to be the rate-determining step, the rate of NO oxidation is Figure 7. Results of the sensitivity analysis for the NOx storage on Pt/Ba/Al2O3 during which pre-exponential factors were successively increased for 10%. The normalized sensitivity coefficients (NSCs) correspond to the relative changes in the outlet concentration. They are calculated at 38 s (peak NO outlet concentration) in the conditions of Olsson et al.24

rNO,ox ) kfθNOθO - kbθNO2θv ) kfK2√K1xO2 -

(1 + √K1xO

2

parameters showing the biggest impact on the simulation results, a sensitivity analysis (Figure 7) was performed, giving insight into the most relevant kinetic factors. For this purpose, the preexponential factors were successively increased compared to the original mechanism and the impact on the outlet NO and NO2 concentrations was observed. The results of the sensitivity studies in the conditions of Olsson et al. showed that the outlet concentrations are mainly sensitive to NO2 adsorption on the storage material, while NO and NO2 oxidation on the storage material, as well as the oxygen adsorption on Pt have less of an impact on the system. Other reactions do not have much influence on the system outlet. 3.3. Global NO Oxidation Model. As the present detailed model performs fairly well over a wide range of operating conditions, we can globalize it confidently in order to minimize the number of computed variables and hopefully increase model robustness. The analysis of the initial oxidation rates in a differential reactor provides values of NO, O2, and NO2 global orders for the 220-480 °C temperature range. They range from 0.64 to 1.05 for NO, 0.35 to 0.78 for O2, and -1.86 to -2.22 for NO2. The negative order with the respect to NO2 accounts for the inhibited reaction rate in the presence of NO2, as previously observed by Mulla et al.19 on Pt/Al2O3 and Kro¨cher et al.27 on Pt/SiO2 catalyst. With this information in hand, a global rate law can now be postulated, based on the proposed microkinetic sequence. As supported by global orders analysis, the surface reaction R3 is considered as the rate-limiting step. This statement that the overall reaction is limited by the oxidation of adsorbed NO on Pt R3 is in agreement with previous assumptions of Disselkamp et al.91 and Harold et al.22 The adsorption reactions R1, R2, and R4 can therefore be considered to be in thermodynamic equilibrium, and the corresponding surface coverages are written as follows:

θO ) √K1xO2θv

(16)

1 Kx Keq 4 NO2

+ K2xNO + K4xNO2

)2

(20)

with kf and kb denoting the global forward and backward kinetic constants, respectively, and Keq being the global equilibrium constant. The microkinetic analysis confirms the findings of Harold et al.21 that chemisorbed O* is the predominant species on the surface over a wide temperature range (175-400 °C). However, it was decided not to neglect NO and NO2 surface coverage. The comparison of the global oxidation model with the experimental NO oxidation data of Olsson et al.,24 Harold et al.,21 and Chatterjee46 is illustrated in Figure 8. Even if only the conversion at low temperature oxidation in Olsson’s conditions is predicted correctly, global predictions are in overall good agreement with the experimental results. Lower calculated NO conversion at temperatures below 250 °C in the conditions of Olsson et al. could be explained by the model’s tendency to overestimate the low temperature oxygen coverage on platinum, thus predicting stronger reaction rate inhibition. Compared to the detailed model computations, the global model gains about 10% CPU time. Note that in this case the size of the scheme to be globalized is relatively small (four bidirectional reactions) and that the reduction of CPU cost would be more pronounced when globalizing larger schemes. 4. Conclusions In summary, we present the first in a series of topics dedicated to understanding and modeling of NOx trap operation. This work required an extensive screening of literature data in order to sort out the NO oxidation experiments on Pt/Al2O3 model catalysts in monolith reactors. After a review of existing studies on NO oxidation, a unique detailed kinetic model was conceived, capable of reproducing experimental data obtained in different operating conditions. Based on the assumption of kinetic limitation, the present model overestimates NO conversion in the 260-370 °C temperature range. Attention was then turned to developing a global oxidation model, which could be more easily implemented in a reactor model. For this purpose, the detailed kinetic model was used to determine global NO, O2, and NO2 orders and calculate the adsorption constants. The global model was also capable of reproducing results from several experimental setups. The detailed NOx storage mechanism was based on previous literature work and adjusted to fit

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Rankovic et al. Acknowledgment. The authors thank Drs. Millet and Mauviot as well as Ms. Leistner and Mr. Berthout for fruitful discussions. References and Notes

Figure 8. Comparison of the global NO oxidation model predictions with experimental data. (a) Conditions of Olsson et al.24 (600 ppm NO, 8% O2 in N2, 25-500 °C, 5 °C/min); (b) Harold et al.21 (482 ppm NO, 5% O2 in N2, stationary data); (c) Chatterjee46 (500 ppm NO, 1% O2 in N2, 150-550 °C, 5 °C/min). (2) Experimental NO2 outlet concentration, (line) calculated NO2 outlet concentration.

the experimental data for NOx storage over Ba/Al2O3 in the 350-400 °C temperature range. The subsequent coupling of the oxidation and storage mechanisms provided a model that reproduced the storage data for a Pt/Ba/Al2O3 model catalyst with sufficient accuracy. For better insight into the storage mechanism, rate-of-production and sensitivity studies were performed. Future work will focus on the development of a fixed-bed reactor model in the LMS.IMAGINE.Lab environment, as well as coupling the global NO oxidation model to the detailed storage mechanism. Work is underway to expand the validity of the present model at low temperature and on different support formulations (CeO2, ZrO2), and to account for the influence of the support on the kinetics, more varied operating conditions (influence of CO2 and H2O), and hydrothermal aging. Besides NO oxidation and NOx storage models, kinetic models for CO and hydrocarbon oxidation and nitrate reduction/NOx release during the rich phase are also being developed.

(1) Roy, S.; Baiker, A. Chem. ReV. 2009, 109, 4054–4091. (2) Crutzen, P. J. Q. J. R. Meteorol. Soc. 1970, 96, 320–325. (3) Kattan, M.; Gergen, P. J.; Eggleston, P.; Visness, C. M.; Mitchell, H. E. J. Allergy Clin. Immunol. 2007, 120, 618–624. (4) Kraft, M.; Eikmann, T.; Kappos, A.; Kunzli, N.; Rapp, R.; Schneider, K.; Seitz, H.; Voss, J. U.; Wichmann, H. E. Int. J. Hyg. EnViron. Health 2005, 208, 305–318. (5) Olaru, D.; Powell, J. Air Pollut. Model. Its Appl. XIX 2008, 717– 718. (6) Webb, C. C.; Weber, P. A.; Thornton, M. J. SAE Tech. Pap. Ser. 2004, 2004-01-0585. (7) Matsumoto, S. Catal. Today 1996, 29, 43–45. (8) Takahashi, N.; Shinjoh, H.; Iijima, T.; Suzuki, T.; Yamazaki, K.; Yokota, K.; Suzuki, H.; Miyoshi, N.; Matsumoto, S.; Tanizawa, T.; Tanaka, T.; Tateishi, S.; Kasahara, K. Catal. Today 1996, 27, 63–69. (9) Miyoshi, N.; Matsumoto, S.; Katoh, K.; Tanaka, T.; Harada, J.; Takanashi, N.; Yokota, K.; Sugiura, M.; Kasahara, K. SAE Tech. Pap. Ser. 1995, 950809. (10) Shinjoh, H.; Takahashi, N.; Yokota, K.; Sugiura, M. Appl. Cataly., B 1998, 15, 189–201. (11) Alkemade, U. G.; Schumann, B. Solid State Ionics 2006, 177, 2291– 2296. (12) Epling, W. S.; Kisinger, D.; Everest, C. Catal. Today 2008, 136, 156–163. (13) Kim, D. H.; Chin, Y. H.; Muntean, G.; Yezerets, A.; Currier, N.; Epling, W.; Chen, H. Y.; Hess, H.; Peden, C. H. F. Ind. Eng. Chem. Res. 2007, 46, 2735–2740. (14) Roedel, E.; Urakawa, A.; Kureti, S.; Baiker, A. Phys. Chem. Chem. Phys. 2008, 10, 6190–6198. (15) Lesage, T.; Saussey, J.; Malo, S.; Hervieu, M.; Hedouin, C.; Blanchard, G.; Daturi, M. Appl. Catal., B 2007, 72, 166–177. (16) Verrier, C.; Kwak, J. H.; Kim, D. H.; Peden, C. H. F.; Szanyi, J. Catal. Today 2008, 136, 121–127. (17) Lesage, T.; Verrier, C.; Bazin, P.; Saussey, J.; Malo, S.; Hedouin, C.; Blanchard, G.; Daturi, M. Top. Catal. 2004, 30-31, 31–36. (18) Epling, W. S.; Campbell, L. E.; Yezertes, A.; Parks, J. E. Catal. ReV.-Sci. Eng. 2004, 46, 163–245. (19) Mulla, S. S.; Chen, N.; Cumaranatunge, L.; Blau, G. E.; Zemlyanov, D. Y.; Delgass, W. N.; Epling, W. S.; Ribeiro, F. H. J. Catal. 2006, 241, 389–399. (20) Mulla, S. S.; Chen, N.; Delgass, W. N.; Epling, W. S.; Ribeiro, F. H. Catal. Lett. 2005, 100, 267–270. (21) Bhatia, D.; McCabe, R. W.; Harold, M. P.; Balakotaiah, V. J. Catal. 2009, 266, 106–119. (22) Muncrief, R. L.; Khanna, P.; Kabin, K. S.; Harold, M. P. Catal. Today 2004, 98, 393–402. (23) Olsson, L.; Blint, R.; Fridell, E. Ind. Eng. Chem. Res. 2005, 44, 3021–3032. (24) Olsson, L.; Persson, H.; Fridell, E.; Skoglundh, M.; Andersson, B. J. Phys. Chem. B 2001, 105, 6895–6906. (25) Olsson, L.; Fridell, E.; Skoglundh, M.; Andersson, B. Catal. Today 2002, 73, 263–270. (26) Olsson, L.; Fridell, E. J. Catal. 2002, 210, 340–353. (27) Despres, J.; Elsener, M.; Koebel, M.; Krocher, O.; Schnyder, B.; Wokaun, A. Appl. Catal., B 2004, 50, 73–82. (28) Hauptmann, W.; Votsmeier, M.; Gieshoff, J.; Vlachos, D.; Drochner, A.; Vogel, H. Top. Catal. 2009, 52, 1925–1928. (29) Marques, R.; Darcy, P.; Da Costa, P.; Mellotte´e, H.; Trichard, J. M.; Dje´ga-Mariadassou, G. J. Mol. Catal. A: Chem. 2004, 221, 127–136. (30) Fridell, E.; Skoglundh, M.; Johansson, S.; Westerberg, B.; Troncrona, A.; Smedler, G. Studies in Surface Science and Catalysis - Catalysis and AutomotiVe Pollution Control IV, Proceedings of the Fourth International Symposium (CAPoC4); Elsevier: Amsterdam, The Netherlands, 1998; Vol. 116, pp 537-547. (31) James, D.; Fourre´, E.; Ishii, M.; Bowker, M. Appl. Catal., B 2003, 45, 147–159. (32) Mahzoul, H.; Brilhac, J. F.; Gilot, P. Appl. Catal., B 1999, 20, 47– 55. (33) Lietti, L.; Forzatti, P.; Nova, I.; Tronconi, E. J. Catal. 2001, 204, 175–191. (34) Broqvist, P.; Gro¨nbeck, H.; Fridell, E.; Panas, I. Catal. Today 2004, 96, 71–78. (35) Hess, C.; Lunsford, J. H. J. Phys. Chem. B 2002, 106, 6358–6360. (36) Balcon, S.; Potvin, C.; Salin, L.; Tempe`re, J. F.; Dje´ga-Mariadassou, G. Catal. Lett. 1999, 60, 39–43.

Study of NOx Oxidation and Storage (37) Kobayashi, T.; Yamada, T.; Kayano, K. SAE Tech. Pap. Ser. 1997, 970745. (38) Epling, W. S.; Parks, J. E.; Campbell, G. C.; Yezerets, A.; Currier, N. W.; Campbell, L. E. Catal. Today 2004, 96, 21–30. (39) Scotti, A.; Nova, I.; Tronconi, E.; Castoldi, L.; Lietti, L.; Forzatti, P. Ind. Eng. Chem. Res. 2004, 43, 4522–4534. (40) Castoldi, L.; Lietti, L.; Nova, I.; Matarrese, R.; Forzatti, P.; Vindigni, F.; Morandi, S.; Prinetto, F.; Ghiotti, G. Alkaline- and alkaline-earth oxides based Lean NOx Traps: Effect of the storage component on the catalytic reactivity. Chem. Eng. J. 2009, doi:10.1016/j.cej.2009.10.065. (41) Larson, R. S.; Pihl, J. A.; Kalyana Chakravarthy, V.; Toops, T. J.; Daw, C. S. Catal. Today 2008, 136, 104–120. (42) Tomasic, V. Catal. Today 2007, 119, 106–113. (43) Paynter, H. M. Analysis and Design of Engineering Systems; MIT Press: Cambridge, MA, 1961. (44) Depcik, C.; Assanis, D. Prog. Energy Combust. Sci. 2005, 31, 308– 369. (45) Mauviot, G.; Le Berr, F.; Raux, S.; Perretti, F.; Malbec, L. M.; Millet, C. N. Oil Gas Sci. Technol. 2009, 64, 285–307. (46) Chatterjee, D. Detaillierte Modellierung von Abgaskatalysatoren. Ph.D. Dissertation, Ruprecht-Karls Universitat, Heiderlberg, 2001. (47) Raimondeau, S.; Aghalayam, P.; Mhadeshwar, A. B.; Vlachos, D. G. Ind. Eng. Chem. Res. 2003, 42, 1174–1183. (48) Deutschmann, O. Interactions between transport and chemistry in catalytic reactors. Habilitation Thesis, Fakultat fur Chemie der RuprechtKarls-Universitat Heidelberg, 2001, pp 5-24. (49) Coltrin, M. E.; Kee, R. J.; Rupley, F. M. Surface Chemkin (Version 4. 0): A Fortran Package for Analyzing Heterogeneous Chemical Kinetics at a Solid-Surface - Gas-Phase Interface; Sandia National Laboratories Report, SAND90-8003B, 1990. (50) Koop, J.; Deutschmann, O. Appl. Catal., B 2009, 91, 47–58. (51) Thormann, J.; Maier, L.; Pfeifer, P.; Kunz, U.; Deutschmann, O.; Schubert, K. Int. J. Hydrogen Energy 2009, 34, 5108–5120. (52) Mhadeshwar, A. B.; Wang, H.; Vlachos, D. G. J. Phys. Chem. B 2003, 107, 12721–12733. (53) Crocoll, M.; Kureti, S.; Weisweiler, W. J. Catal. 2005, 229, 480– 489. (54) Froment, G. F.; Hosten, L. Catalysis; Springer-Verlag: Berlin, 1981; p 97. (55) Froment, G. F.; Bischoff, K. B. Chemical Reactor Analysis and Design; Wiley: New York, 1979; p 765. (56) Kromer, B. R.; Cao, L.; Cumaranatunge, L.; Mulla, S. S.; Ratts, J. L.; Yezerets, A.; Currier, N. W.; Ribeiro, F. H.; Delgass, W. N.; Caruthers, J. M. Catal. Today 2008, 136, 93–103. (57) Weiss, B. M.; Iglesia, E. J. Phys. Chem. C 2009, 113, 13331– 13340. (58) Motz, H.; Wise, H. J. Chem. Phys. 1960, 32, 1893–1894. (59) Elg, A. P.; Eisert, F.; Rose´n, A. Surf. Sci. 1997, 382, 57–66. (60) Campbell, C. T.; Ertl, G.; Kuipers, H.; Segner, J. Surf. Sci. 1981, 107, 220–236. (61) Yeo, Y. Y.; Vattuone, L.; King, D. A. J. Chem. Phys. 1997, 106, 392–401. (62) Rinnemo, M.; Deutschmann, O.; Behrendt, F.; Kasemo, B. Combust. Flame 1997, 111, 312–326. (63) Wartnaby, C. E.; Stuck, A.; Yeo, Y. Y.; King, D. A. J. Phys. Chem. 1996, 100, 12483–12488.

J. Phys. Chem. C, Vol. 114, No. 15, 2010 7111 (64) Kinnersley, A. D.; Darling, G. R.; Holloway, S. Surf. Sci. 1997, 377-379, 567–571. (65) Fiorin, V.; Borthwick, D.; King, D. A. Surf. Sci. 2009, 603, 1360– 1364. (66) Chatterjee, D.; Deutschmann, O.; Warnatz, J. Faraday Discuss. 2001, 119, 371–384. (67) Bartram, M. E.; Windham, R. G.; Koel, B. E. Surf. Sci. 1987, 184, 57–74. (68) Gorte, R. J.; Schmidt, L. D.; Gland, J. L. Surf. Sci. 1981, 109, 367– 380. (69) Nova, I.; Castoldi, L.; Prinetto, F.; Santo, V. D.; Lietti, L.; Tronconi, E.; Forzatti, P.; Ghiotti, G.; Psaro, R.; Recchia, S. Top. Catal. 2004, 3031, 181–186. (70) Nova, I.; Castoldi, L.; Lietti, L.; Tronconi, E.; Forzatti, P.; Prinetto, F.; Ghiotti, G. J. Catal. 2004, 222, 377–388. (71) Forzatti, P.; Castoldi, L.; Nova, I.; Lietti, L.; Tronconi, E. Catal. Today 2006, 117, 316–320. (72) Cant, N. W.; Patterson, M. J. Catal. Today 2002, 73, 271–278. (73) Al Harbi, M.; Epling, W. Catal. Lett. 2009, 130, 121–129. (74) Sedlmair, C.; Seshan, K.; Jentys, A.; Lercher, J. A. J. Catal. 2003, 214, 308–316. (75) Broqvist, P.; Panas, I.; Gronbeck, H. J. Phys. Chem. B 2005, 109, 9613–9621. (76) Tutuianu, M.; Inderwildi, O. R.; Bessler, W. G.; Warnatz, J. J. Phys. Chem. B 2006, 110, 17484–17492. (77) Lindholm, A.; Currier, N. W.; Fridell, E.; Yezerets, A.; Olsson, L. Appl. Catal., B 2007, 75, 78–87. (78) Gangwal, V. R.; Scholz, C. M. L.; De Croon, M. H. J. M.; Schouten, J. C. Chem. Eng. Sci. 2007, 62, 5167–5175. (79) Scholz, C. M. L.; Gangwal, V. R.; De Croon, M. H. J. M.; Schouten, J. C. J. Catal. 2007, 245, 215–227. (80) Xie, S.; Mestl, G.; Rosynek, M. P.; Lunsford, J. H. J. Am. Chem. Soc. 1997, 119, 10186–10191. (81) Cant, N. W.; Liu, I. O. Y.; Patterson, M. J. J. Catal. 2006, 243, 309–317. (82) Kwak, J.; Kim, D.; Szailer, T.; Peden, C.; Szanyi, J. Catal. Lett. 2006, 111, 119–126. (83) Ahmadinejad, M.; Watling, T. C.; York, A. P. E.; Walker, A. P.; Chen, H. Y.; Hess, H. S.; Cox, J. P. SAE Tech. Pap. Ser. 2006, 200, 601– 3445. (84) Cao, L.; Ratts, J. L.; Yezerets, A.; Currier, N. W.; Caruthers, J. M.; Ribeiro, F. H.; Delgass, W. N. Ind. Eng. Chem. Res. 2008, 47, 9006–9017. (85) Schweich, D. Ge´nie de la re´action chimique; Tec & Doc Lavoisier ed.: Paris, 2001; p 142. (86) Aris, R. Proc. R. Soc. London 1956, 235A, 67–77. (87) Smith, G. P.; Golden, D. M.; Frenklach, M.; Moriarty, N. W.; Eiteneer, B.; Goldenberg, M.; Bowman, C. T.; Hanson, R. K.; Song, S.; Gardiner, W. C., Jr.; Lissianski, V. V.; Qin, Z. http://www.me.berkeley.edu/ gri_mech/. (88) Andersson, J. R. Structure of Metallic Catalysts; Academic Press: London, 1975; p 296. (89) Olsson, L.; Fridell, E. J. Catal. 2002, 210, 340–353. (90) Westerberg, B.; Fridell, E. J. Mol. Catal. A: Chem. 2001, 165, 249– 263. (91) Disselkamp, R. S.; Tonkyn, R. G.; Chin, Y. H.; Peden, C. H. F. J. Catal. 2006, 238, 1–5.

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