A Catalytic Reaction Mechanism for Methane Partial Oxidation at Short

Department of Chemical Engineering and Center for Catalytic Science and Technology, University of Delaware, Newark, Delaware 19716-3110. Ind. Eng. Che...
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Ind. Eng. Chem. Res. 2007, 46, 5310-5324

A Catalytic Reaction Mechanism for Methane Partial Oxidation at Short Contact Times, Reforming, and Combustion, and for Oxygenate Decomposition and Oxidation on Platinum A. B. Mhadeshwar and D. G. Vlachos* Department of Chemical Engineering and Center for Catalytic Science and Technology, UniVersity of Delaware, Newark, Delaware 19716-3110

Hydrogen production from fuel processing and its utilization in fuel cell technology is recognized as a promising route to future power generation. Reliable chemistry models are necessary to improve the hydrogen generation processes via optimal reactor design. With this objective, here, we present a predictive microkinetic model for CH4 (C1) partial oxidation, combustion, and reforming, as well as oxygenate (CH3OH and CH2O) decomposition and oxidation on platinum, consisting of 104 elementary-like steps. A hierarchical multiscale approach is used in the parameter estimation of bottom-up mechanism building. Thermodynamic consistency is ensured in the C1 mechanism. Important kinetic parameters are identified via sensitivity analysis for various experimental systems, using diverse operating conditions, and only a limited number of important kinetic parameters are refined (four for CH4). The C1 mechanism is extensively validated against several additional experimental data and is observed to be fairly predictive (within the uncertainty of measurements in catalyst surface area, temperature, etc.). Analysis shows spatial zones in catalytic methane oxidation at short contact times, viz., an oxidation zone near the reactor entrance, followed by a reforming zone, where mainly steam reforming and, to a lesser extent, dry reforming occur. Thus, methane oxidation follows the indirect pathway (i.e., total oxidation products are first formed), followed by reforming to generate the partial oxidation ones, in agreement with modeled experimental data. CH4 + CO2 f 2CO + 2H2

1. Introduction Natural gas is a multipurpose source of energy; it is mainly utilized in heating, electricity generation, and transportation. Furthermore, it can be converted to syngas, which is a mixture of CO and H2, which is useful in methanol, ammonia, and gasoline production.1 In turn, methanol is an important chemical used in the production of oxygenates, such as formaldehyde, methyl tertiary butyl ether (MTBE), and acetic acid. Furthermore, H2 derived from syngas could be utilized for power generation in fuel cells for vehicular, residential, and portable applications. The commonly used process for conversion of natural gas into syngas is steam reforming:

CH4 + H2O f CO + 3H2 This process is limited from extensive energy input, because of its high endothermicity, coking, blocking of reformer tubes, large reactor and plant sizes, long residence times, and an undesired H2:CO ratio of 3:1 for some applications. Experiments in short contact time reactors2 have demonstrated that the catalytic partial oxidation of methane (CPOX),

CH4 + 0.5O2 f CO + 2H2 could be considered to be an attractive alternative for syngas production. Autothermal reforming of CH4

2CH4 + 0.5O2 + H2O f 2CO + 5H2 (an illustrative stoichiometry is indicated) and dry (CO2) reforming * To whom correspondence should be addressed: Tel.: (302)-8312830. Fax: (302)-831-1048. E-mail address: [email protected].

are also of potential interest. CO produced from these processes is harmful to the catalyst of fuel cells and therefore, water-gas shift (WGS) reaction

CO + H2O f CO2 + H2 is performed to decrease the CO concentration. The preferential oxidation of CO (PROX),

CO + 0.5O2 f CO2 and

H2 + 0.5O2 f H2O is finally performed to decrease the CO concentration to the parts per million (ppm) level, leaving the H2 relatively unaffected. A review of earlier work on CPOX is given in ref 3. Platinum and rhodium are two of the most widely used catalysts in CH4 CPOX. A variety of microkinetic models for fuel (CO, H2, CH4, CH3OH, etc.) oxidation have been proposed in the literature on these catalysts.4-14 However, as demonstrated in our previous papers,3,15,16 these models have numerous shortcomings. To name a few, the rate parameters are not thermodynamically consistent and cannot predict equilibrium limited data, such as WGS and reforming; some mechanisms are tuned against a single type of experimental data and cannot describe multiple data; crucial parameters, such as the effect of adsorbateadsorbate interactions on surface reactions, and many reaction steps are not incorporated in the mechanism. Mechanisms developed for one process may not capture a combination of processes and a change in processes (e.g., CPOX, followed by

10.1021/ie070322c CCC: $37.00 © 2007 American Chemical Society Published on Web 07/11/2007

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reforming or reforming along with WGS). We believe that it is important to develop a mechanism that can simultaneously describe all these processes, to have the best chance of correctly capturing the underlying chemistry. Our recent work has focused on developing predictive microkinetic models for the H2 generation processes previously mentioned, using a hierarchical multiscale approach.17-20 Our approach involves a hybrid parameter estimation methodology, based on experimental data, semiempirical methods, and firstprinciples density functional theory (DFT) techniques, and refines important parameters, identified via sensitivity analysis (SA), via DFT and/or constrained optimization. The approach is a bottom-up procedure, because mechanisms for smaller molecules are developed first, followed by the more-complex molecules or coupling (co-occurrence of various processes or co-feeding) of fuels. Using the hierarchical multiscale approach, a CO-H2 coupling mechanism on platinum was recently published that captures CO oxidation, H2 oxidation, water-promoted CO oxidation at low temperatures, WGS, and PROX.19 In this work, we extend the approach to develop a predictive microkinetic model for CH4 partial oxidation, reforming, combustion, as well as oxygenate decomposition and oxidation on platinum. First, a thermodynamically consistent CH4 (C1) mechanism is developed. Parameter refinement is demonstrated against multiple low- and moderate-pressure experimental data of different types. The mechanism is validated and analyzed against a variety of experiments. Reaction path analysis (RPA) is also presented for selected experimental systems, to understand the underlying pathways. This work presents the first thermodynamically consistent, comprehensive C1 microkinetic model on platinum that is compared to a broad spectrum of processes and experimental conditions. In addition, our analysis provides new insights into various processes, including the long-debated partial oxidation of methane in short contact times. 2. Development of an Initial C1 Mechanism on Platinum 2.1. Reaction Steps and Initial Parameter Estimation. The CO-H2 coupling mechanism, taken from our previous work,19 is shown in Table 1 (reactions R1-R46) and its parameters are not modified here. The C1 mechanism has 58 additional steps, as shown in Table 2, which are identical to the C1 mechanism on rhodium that we recently developed.21 Transitionstate theory (TST) is used to set the initial pre-exponentials (e.g., 1013 s-1 for the desorption steps and 1011 s-1 for the LangmuirHinshelwood (LH)-type reactions), which are based on ref 22. Initial sticking coefficients of the CHx species (CH4, CH3, CH2, CH, and C) and the oxygenates (CH3OH, CH3O, CH2O, HCO, and CH2OH) are set to unity. The molecular heat of chemisorption of CH4 is taken from ref 23, whereas the heats of CHx adsorption are taken from the DFT calculations of ref 24. For the oxygenates, we have considered intermediate values of heats of chemisorption based on various sources, such as surface science experiments, slab- and cluster-based DFT data, and the unity bond index-quadratic exponential potential (UBIQEP) method (which is also known as bond order conservation (BOC) theory)25,26 calculations. The values are summarized in Table 3. Given the heats of chemisorption, the activation energies of all surface reactions are estimated using the UBIQEP method, and the calculated values are shown in Tables 1 and 2. 2.2. Adsorbate-Adsorbate Interactions and Thermodynamic Consistency. Two important features that distinguish this C1 mechanism from previous literature mechanisms are that the

activation energies are (i) coverage-dependent and (ii) temperature-dependent. Adsorbate-adsorbate interactions between similar species (self-interactions) or different species (crossinteractions) could be important under high coverage conditions and affect the mechanism energetics. The interactions have been extracted from surface science experiments or estimated using DFT calculations. The C1 mechanism, presented in Tables 1 and 2, includes interactions between O*-O*, H*-H*, OH*O*, H2O*-H2O*, H2O*-OH*, and CO*-CO*, whose values are shown in Table 3. Aside from the obvious modification of desorption energies, these interactions affect activation energies of many surface reactions. A mechanism can be enthalpically consistent at only one temperature, despite using UBI-QEP to calculate the activation energies. Therefore, we use statistical mechanics to estimate the temperature dependence of heats of chemisorption based on the changes in degrees of freedom that occur upon adsorption.16,18,19 This temperature dependence is taken into account into the activation energies through the UBI-QEP framework to ensure enthalpic consistency at all temperatures. The formulas for temperature-dependent heats of chemisorption are summarized in Table 3. Next, the deviation between the gas-phase entropies and the overall surface reaction entropies is minimized to ensure entropic consistency of the C1 mechanism for every elementary step. Pre-exponentials and temperature exponents (β; see the modified Arrhenius form in Tables 1 and 2) get adjusted in this step; however, no experimental data fitting is conducted at this stage. Thermodynamic consistency is another unique attribute of our mechanism and can be essential given the importance of equilibrium-limited reforming reactions that can occur in CPOX (see below). 3. Parameter Refinement Using Ultrahigh Vacuum, Low-Pressure, and Moderate-Pressure Experiments With the current level of accuracy of quantum mechanical simulations and the complexity of real catalysts and reactors, truly first-principles quantitative modeling is impossible (an order of magnitude prediction of reaction rates is the best one can hope to achieve for supported catalysts). While we, and others, keep pushing the frontiers of multiscale model development, the refinement of a few pre-exponentials to describe a wide spectrum of processes and conditions quantitatively is highly desirable, so, eventually, these models can be used, in a reasonable time frame, for reactor and catalyst design (what we term as “data injection” into multiscale models27). We prefer to adjust pre-exponentials rather than energetics (unless there is a clear indication for doing so), because, in most cases, the actual catalyst surface area is unfortunately unknown (see captions of figures below); in addition, the temperature changes over a wide range, and the lack of such fitting, provides us with better confidence that we capture energetics reasonably well. With this rationale, the C1 mechanism on platinum is used to model a multitude of experimental systems, including ultrahigh vacuum (UHV) temperature-programmed reaction (TPR) experiments, as well as molecular beam experiments, low-pressure laser-induced fluorescence (LIF) experiments, and moderate-pressure oxidation, as well as reforming experiments. With such diversity in conditions and catalysts, we attempt to fill in the well-known pressure and materials gap. We have used some of these experiments for parameter refinement (targeted experiments) and the remainder for mechanism assessment. Diversity in operating conditions and types of experiments, as well as in sensitivity analysis (SA), are key ingredients for guiding the selection of targeted experiments. The comparison

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Table 1. Surface Reaction Mechanisms for CO Oxidation (R1-R10), H2 Oxidation (R1-R4 and R11-R24), and CO-H2 Coupling (R25-R46) Reactions on Platinuma reaction step

reaction

sticking coefficient (unitless) or pre-exponential (s-1)

temperature exponent, β

activation energy at 300 K for selected reactions (kcal/mol)

Oxygen Adsorption-Desorption Steps 0.766 5.42 × 10-2 -0.796 8.41 × 1012 -2 4.91 × 10 0.250 1.44 × 1013 -0.250

0.0 50.9 - 32θO + f(T) 0.0 85.0 - 16θO + f(T)

CO + * f CO* CO* f CO + * CO2 + * f CO2* CO2* f CO2 + * CO2* + * f CO* + O* CO* + O* f CO2* + *

CO Oxidation on Platinum 1.00 × 100 0.000 5.66 × 1015 -0.500 0.250 1.95 × 10-1 -0.250 3.63 × 1012 0.177 4.18 × 1010 -0.177 2.39 × 1011

0.0 40 - 15θCO + f(T) 0.0 3.6 + f(T) 26.3 + f(θO,θCO,T)b 20.6 + f(θO,θCO,T)

R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24

H2 + 2* f 2H* 2H* f H2 + 2* OH* + * f H* + O* H* + O* f OH* + * H2O* + * f H* + OH* H* + OH* f H2O* + * H2O* + O* f 2OH* 2OH* f H2O* + O* OH + * f OH* OH* f OH + * H2O + * f H2O* H2O* f H2O + * H + * f H* H* f H + *

H2 Oxidation on Platinum 0.858 1.29 × 10-1 -0.001 7.95 × 1012 1.95 × 1012 1.872 6.33 × 1012 0.624 -0.118 9.36 × 1012 -1.049 9.99 × 1012 0.082 4.32 × 1010 0.325 1.70 × 1010 9.99 × 10-1 2.000 1.44 × 1014 2.000 1.162 1.08 × 10-1 12 1.372 2.03 × 10 3.84 × 10-1 1.832 4.37 × 1013 1.890

0.0 19.8 - 6θH + f(T) 27.1 + f(θO,θH,θH2O,T) 8.8 + f(θO,θH,θH2O,T) 17.8 + f(θO,θH,θOH,θH2O,T) 13.5 + f(θO,θH,θOH,θH2O,T) 8.8 + f(θO,θOH,θH2O,T) 22.7 + f(θO,θOH,θH2O,T) 0.0 63.0 - 33θO + 25θH2O + f(T) 0.0 10.0 - 2.5θH2O + 25θOH + f(T) 0.0 62.0 - 3θH + f(T)

R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39 R40 R41 R42 R43 R44 R45 R46

Coupling between CO and H2 Chemistries on Platinum CO2* + H* f CO* + OH* -0.531 6.0 + f(θO,θH,θH2O,θCO,T) 8.03 × 108 CO* + OH* f CO2* + H* 0.531 18.5 + f(θO,θH,θH2O,θCO,T) 1.25 × 109 COOH + * f COOH* 6.34 × 10-2 -0.089 0.0 COOH* f COOH + * 1.12 × 1013 0.089 55.3 + f(T) 8 COOH* + * f CO* + OH* 8.43 × 10 0.024 5.3 + f(θO,θH2O,θCO,T) CO* + OH* f COOH* + * 1.19 × 109 -0.024 19.1 + f(θO,θH2O,θCO,T) COOH* + * f CO2* + H* 0.549 1.0 + f(θH,T) 1.06 × 1011 CO2* + H* f COOH* + * -0.549 2.4 + f(θH,T) 9.45 × 1010 CO* + H2O* f COOH* + H* 0.492 23.7 + f(θH,θOH,θH2O,θCO,T) 1.10 × 1011 COOH* + H* f CO* + H2O* -0.492 5.6 + f(θH,θOH,θH2O,θCO,T) 9.07 × 1010 CO2*+ OH* f COOH* + O* 0.097 26.5 + f(θO,θH2O,T) 5.35 × 1010 COOH* + O* f CO2* + OH* -0.097 7.0 + f(θO,θH2O,T) 1.87 × 1011 CO2* + H2O* f COOH* + OH* -0.031 17.5 + f(θO,θOH,θH2O,T) 8.64 × 1010 COOH* + OH* f CO2* + H2O* 0.031 11.9 + f(θO,θOH,θH2O,T) 1.16 × 1011 HCOO + 2* f HCOO** 1.46 × 10-1 0.201 0.0 HCOO** f HCOO + 2* 4.83 × 1012 -0.201 53.0 + f(T) CO2* + H* f HCOO** -0.422 18.5 + f(θH,T) 1.12 × 1011 HCOO** f CO2* + H* 0.422 0.0 + f(θH,T) 8.96 × 1010 CO2* + OH* + * f HCOO** + O* 0.236 36.8 + f(θO,θH2O,T) 6.17 × 1010 HCOO** + O* f CO2* + OH* + * -0.236 0.0 + f(θO,θH2O,T) 1.62 × 1011 CO2* + H2O* + * f HCOO** + OH* 0.095 25.8 + f(θO,θOH,θH2O,T) 1.02 × 1011 10 HCOO** + OH* f CO2* + H2O* + * -0.095 3.0 + f(θO,θOH,θH2O,T) 9.78 × 10

R1 R2 R3 R4

O2 + 2* f O* 2O* f O2 + 2* O + * f O* O* f O + *

R5 R6 R7 R8 R9 R10

modified bond index for selected reactions

0.8c

a The activation energies are temperature-dependent, according to statistical mechanics (see Table 3).16,18,19 The coverage dependence of the activation energies of various reaction steps is incorporated in our simulations via the UBI-QEP method.25,26 The functions f in the last column indicate the nonlinear dependence of activation energies on specific coverages and on temperature. The reaction rate constant (k) is calculated using the modified Arrhenius form k ) (A/σn-1)(T/To)β exp[-E/(RgT)] or k ) (s/σn)[RgT/(2πM)]1/2(T/To)β exp[-E/(RgT)] (here, A is the pre-exponential, s the sticking coefficient, σ the site density, n the reaction order, β the temperature exponent, E the activation energy, Rg the ideal gas constant, and T the absolute temperature). Modified pre-exponentials that give better agreement with target experiments are shown in italics. b A modified bond index is used in the UBI-QEP formula for the calculation of the forward activation energy, instead of the usual value of 0.5. The backward activation energy is calculated using the forward activation energy and the heat of reaction. c Modified bond index.

is also classified as qualitative and quantitative, based on the C1 mechanism predictions and the operating conditions. Next, we discuss these target experiments and parameter refinement. 3.1. Parameter Refinement Using UHV TPR Data. Zaera and Hoffman conducted TPR experiments to measure the CH4 desorption rate as a function of the adsorbed methyl iodide on Pt(111).28 The peak temperature did not shift significantly with varying initial coverages, indicating that adsorbate-adsorbate interactions between CH3*-CH3* are not significant under their

conditions. Methyl iodide is assumed to decompose to CH3* on the surface. Simulations using the C1 mechanism indicate that the peak temperature is ∼365 K, whereas the experimental peak temperatures are in the range of ∼290-300 K. H* required in the CH4 formation from CH3* (CH3* + H* f CH4 + 2*; see reaction R56) is generated from the thermal decomposition of CH3* to CH2*:

CH3* + * f CH2* + H*

(R57)

Ind. Eng. Chem. Res., Vol. 46, No. 16, 2007 5313 Table 2. Surface Reaction Mechanisms for C1 Reactions on Platinum (Reactions R47-R82 Mainly Involve CH4 and Reactions R83-R104 Mainly Involve Oxygenate Decomposition)a reaction step

R47 R48 R49 R50 R51 R52 R53 R54 R55 R56 R57

reaction C + * f C* C* f C + * CH + * f CH* CH* f CH + * CH2 + * f CH2* CH2* f CH2 + * CH3 + * f CH3* CH3* f CH3 + * CH4 + 2* f CH3* + H* CH3* + H* f CH4 + 2* CH3* + * f CH2* + H*

R58

CH2* + H* f CH3* + *

R59 R60 R61 R62 R63 R64 R65 R66 R67 R68 R69 R70 R71 R72 R73 R74 R75 R76 R77

CH2* + * f CH* + H* CH* + H* f CH2* + * CH* + * f C*+ H* C* + H* f CH* + * CH3* + O* f CH2* + OH* CH2* + OH* f CH3* + O* CH* + OH* f CH2* + O* CH2* + O* f CH* + OH* C* + OH* f CH* + O* CH* + O* f C* + OH* CH2* + H2O* f CH3* + OH* CH3* + OH* f CH2* + H2O* CH* + H2O* f CH2* + OH* CH2* + OH* f CH* + H2O* C* + H2O* f CH* + OH* CH* + OH* f C* + H2O* CO* + * f C* + O* C* + O* f CO* + * CO* + H* f CH* + O*

R78

CH* + O* f CO* + H*

R79

CO* + H* f C* + OH*

R80

C* + OH* f CO* + H*

R81

2CO* f C* + CO2*

R82

C* + CO2* f 2CO*

R83 R84 R85 R86 R87 R88 R89 R90 R91 R92 R93 R94 R95 R96 R97

CH3OH + * f CH3OH* CH3OH* f CH3OH + * CH3O + * f CH3O* CH3O* f CH3O + * CH2O + * f CH2O* CH2O* f CH2O + * HCO + * f HCO* HCO* f HCO + * CH2OH + * f CH2OH* CH2OH* f CH2OH + * CH3OH* + * f CH3O* + H* CH3O* + H* f CH3OH* + * CH3O* + * f CH2O* + H* CH2O* + H* f CH3O* + * CH2O* + * f HCO* + H*

R98

HCO* + H* f CH2O* + *

R99 R100 R101

HCO* + * f CO* + H* CO* + H* f HCO* + * CH3OH* + * f CH2OH* + H*

R102

CH2OH* + H* f CH3OH* + *

R103 R104

CH2OH* + * f CH2O* + H* CH2O* + H* f CH2OH* + *

sticking coefficient (unitless) or pre-exponential (s-1)

temperature exponent, β

CH4 Oxidation and Reforming on Platinum 1.64 × 10-2 0.156 -0.156 4.30 × 1013 1.35 × 10-2 0.051 -0.051 5.22 × 1013 0.118 4.50 × 10-2 -0.118 1.57 × 1013 -0.099 1.60 × 10-1 0.099 4.42 × 1012 -1 0.154 1.16 × 10 10 -0.154 6.12 × 10 11 0.419 1.11 × 10 1.11 × 1010 10 -0.419 8.99 × 10 8.99 × 109 0.222 5.22 × 1010 -0.222 1.92 × 1011 9.11 ×1010 0.398 -0.398 1.10 × 1011 11 -0.230 1.97 × 10 0.230 5.08 × 1010 11 0.414 1.10 × 10 10 -0.414 9.10 × 10 10 6.37 × 10 0.225 -0.225 1.57 × 1011 8.19 × 1010 0.099 -0.099 1.22 × 1011 0.269 1.81 × 1011 -0.269 5.53 × 1010 0.090 1.04 × 1011 -0.090 9.61 × 1010 2.85 × 1011 0.468 3.51 × 1010 -0.468 3.12 × 1011 0.073 3.12 × 1010 -0.073 3.21 × 1010 3.21 × 109 -0.168 4.97 × 1011 1.99 × 1011 10 0.168 2.01 × 10 8.05 × 109 11 0.393 5.94 × 10 5.94 × 1012 10 -0.393 1.68 × 10 1.68 × 1011 Oxygenates Decomposition on Platinum 0.258 3.34 × 10-1 -0.258 2.11 × 1012 -1 0.054 1.49 × 10 -0.054 4.73 × 1012 -2 0.098 8.77 × 10 -0.098 8.06 × 1012 -2 1.14 × 10 0.096 -0.096 6.21 × 1013 0.233 5.26 × 10-2 -0.233 1.35 × 1013 0.102 7.82 × 1010 -0.102 1.28 × 1011 0.192 1.25 × 1011 -0.192 8.03 × 1010 0.270 7.14 × 1010 1.43 × 1012 -0.270 1.40 × 1011 2.80 × 1012 0.330 7.11 × 1010 1.41 × 1011 -0.330 0.403 8.48 × 1010 1.70 × 1012 11 -0.403 1.18 × 10 2.36 × 1012 11 -0.104 1.14 × 10 0.104 8.77 × 1010

activation energy at 300 K for selected reactions (kcal/mol)

0.0 157.7 + f(T) 0.0 157.1 + f(T) 0.0 91.6 + f(T) 0.0 45.3 + f(T) 9.0 + f(θH,T) 11.3 + f(θH,T) 15.8 + f(θH,T)b

modified bond index for selected reactions

0.4c

13.3 + f(θH,T) 9.0 + f(θH,T) 35.4 + f(θH,T) 31.3 + f(θH,T) 13.2 + f(θH,T) 10.8 + f(θO,θH2O,T) 26.6 + f(θO,θH2O,T) 44.7 + f(θO,θH2O,T) 0.0 + f(θO,θH2O,T) 27.7 + f(θO,θH2O,T) 27.5 + f(θO,θH2O,T) 14.1 + f(θO,θOH,θH2O,T) 12.3 + f(θO,θOH,θH2O,T) 34.0 + f(θO,θOH,θH2O,T) 3.3 + f(θO,θOH,θH2O,T) 15.6 + f(θO,θOH,θH2O,T) 29.3 + f(θO,θOH,θH2O,T) 76.8 + f(θO,θCO,T)b 22.3 + f(θO,θCO,T) 45.8 + f(θH,θO,θCO,T)

0.7c

9.3 + f(θH,θO,θCO,T) 40.7 + f(θH,θO,θCO,θH2O,T) 4.4 + f(θH,θO,θCO,θH2O,T) 48.8 + f(θCO,T) 0.0 + f(θCO,T)

0.0 9.5 + f(T) 0.0 37.0 + f(T) 0.0 12.0 + f(T) 0.0 55.5 + f(T) 0.0 50.0 + f(T) 18.8 + f(θH,T) 4.3 + f(θH,T) 0.0 + f(θH,T) 14.7 + f(θH,T) 3.6 + f(θH,T)b

0.3c

21.0 + f(θH,T) 0.0 + f(θH,θCO,T) 30.8 + f(θH,θCO,T) 8.7 + f(θH,T)b

0.4c

14.6 + f(θH,T) 7.9 + f(θH,T) 2.2 + f(θH,T)

a The activation energies are temperature-dependent, according to statistical mechanics (see Table 3).16,18,19 The coverage dependence of the activation energies of various reaction steps is incorporated in our simulations via the UBI-QEP method.25,26 The functions f in the last column indicate the nonlinear dependence of activation energies on specific coverages and on temperature. The reaction rate constant (k) is calculated using the modified Arrhenius form k ) (A/σn-1)(T/To)β exp[-E/(RgT)] or k ) (s/σn)[RgT/(2πM)]1/2(T/To)β exp[-E/(RgT)] (here, A is the pre-exponential, s the sticking coefficient, σ the site density, n the reaction order, β the temperature exponent, E the activation energy, Rg the ideal gas constant, and T the absolute temperature). Modified pre-exponentials that give better agreement with target experiments are shown in italics. b A modified bond index is used in the UBI-QEP formula for the calculation of the forward activation energy, instead of the usual value of 0.5. The backward activation energy is calculated using the forward activation energy and the heat of reaction. c Modified bond index.

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Table 3. Temperature- and Coverage-Dependent Heats of Chemisorption, Using Statistical Mechanics16,18,19 with the UBI-QEP Methoda

species

heat of chemisorption, Q (kcal/mol)

selected references

temperature dependence,b (Q(To) - Q(T))/(Rg∆T)

O* CO* CO2* H* OH* H2O* COOH* HCOO** (bidentate) C* CH* CH2/ CH3/ CH4 CH3OH* CH3O* CH2O* HCO* CH2OH*

85 - 16θO 40 - 15θCO 3.6 62 - 3θH 63 - 33θO + 25θH2O 10 - 2.5θH2O + 25θOH 55.3 53.0 157.7 157.1 91.6 45.3 5.9 9.5 37.0 12.0 55.5 50.0

Expt,52-55 DFT56,57 Expt,58-60 DFT61-63 Expt,64-68 UBI-QEP,23 DFT69 Expt,70,71 DFT57,72,73 Expt,74,75 DFT72,76,77 Expt,78 DFT57,79 DFT80,81 DFT80 DFT24 DFT24 DFT24 DFT24 UBI-QEP23 Expt,82 DFT83,84 DFT83,84 DFT83,84 DFT83,84 DFT83,84

1.5 2.0 2.0 1.5 2.0 2.5 2.5 3.0 1.5 2.0 2.5 2.5 2.0 2.5 2.5 2.5 2.5 2.5

change in degrees of freedom (DOFs) needed to derive the temperature dependencec -3FT + 3FV -3FT - 2FR + FRR + 4FV -FT - 3FR + 4FV -3FT + 3FV -3FT - 2FR + FRR + 4FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + 6FV -3FT + 3FV -3FT - 2FR + FRR + 4FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV -FT - 3FR + 4FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV -3FT - 3FR + FRR + 5FV

a From refs 25 and 26. The heat of chemisorption, Q(T), decreases as the temperature increases (here, ∆T ) T - T and T ) 300 K). b The generalized o o assumptions to calculate the temperature dependence are as follows. (1) Each translational, rotational, and vibrational degree of freedom (DOF) corresponds to 0.5RgT, 0.5RgT, and RgT, respectively, where Rg is the universal gas constant. (2) Upon adsorption, all translational DOFs are converted into vibrational DOFs. In the case of weakly bound molecules (such as CO2 and CH4), only one translational DOF is lost upon adsorption (the molecule is able to move readily on the surface). (3) All rotational DOFs are converted to vibrational DOFs upon adsorption. For species such as OH*, H2O*, etc., with a vertical axis through the adsorbed atom, one of the gained vibrational DOFs is assumed to be a free, internal rotor (rigid rotor approximation) and counts as 0.5RgT.c FT, FR, and FV denote translational, rotational, and vibrational DOFs. FRR indicates that a vibrational DOF is assumed to be a free, internal rotor. The “minus” and “plus” signs indicate a loss and gain in DOFs, respectively.

Because the activation energy of reaction R57 is much higher than that of reaction R56, reaction R57 is the rate-determining step (RDS) in this experiment. The bond index of reaction R57 is adjusted to 0.4 (0.5 is the usual value used in UBI-QEP) to decrease the activation energies of reaction pair R57-R58 by ∼4 kcal/mol, which is within the typical uncertainty of UBIQEP and first-principles calculations. Similar bond index adjustment has previously been demonstrated for CO oxidation on platinum as well.18 Using the modified bond index, it is observed that the simulated peak temperature is ∼290 K, which is in better agreement with the experiments (not shown). 3.2. Parameter Refinement Using UHV Molecular Beam Data. Walker and King performed molecular beam experiments on Pt(110) under UHV conditions.29 A carbon adlayer was prepared on the platinum surface, using CH4 adsorption and subsequent heating. Titration with gas-phase O2 was performed at different temperatures to measure the CO and CO2 desorption rates. These experiments are included in the qualitative category, because the catalyst used is Pt(110), which could have significantly different energetics and pre-exponentials than those of Pt(111). Nonetheless, the C1 mechanism could be expected to capture the trends observed in the experiments qualitatively. Simulations indicated that, in contradiction with the experiments, negligible CO2 is produced, compared to CO. CO* is produced from

C* + O* f CO* + *

(R76)

Walker and King explained these results using a four-step reaction model,29 with a very small pre-exponential of 24 s-1 and an activation energy of 0 kcal/mol for reaction R76. They mentioned that this pre-exponential is too small, compared to typical values, and some finite activation barrier is expected, instead of zero. Furthermore, the DFT calculations given in refs 24 and 30 indicate that the activation energy of reaction R76 is ∼2 eV (46.1 kcal/mol) on Pt(111). The pre-exponential and UBI-QEP-based activation energy for reaction R76 in our C1 mechanism were ∼3.5 × 1010 s-1 and ∼0.3 kcal/mol, respec-

tively, indicating that the activation energy needs refinement. We have adjusted the bond index of reaction pair R75-R76 to 0.7 (the usual value in UBI-QEP is 0.5), so that the activation energies of reaction pair R75-R76 are increased by ∼22 kcal/ mol, which is an intermediate value between the UBI-QEP and DFT estimates. Simulations with the modified bond index show a better qualitative agreement with the experimental data of Walker and King (not shown); CO2 production is comparable to that of CO. This example demonstrates how first-principles techniques could be used in conjunction with surface science experiments for important parameter refinement. At this point, we would like to note that, although DFT-based activation energies are reported in the literature for several reactions, because of the uncertainty in DFT calculations specific to activation energy estimation and the unavailability of coveragedependent energetics, bond index tuning is attempted only when supported by experiments. 3.3. Parameter Refinement Using Methanol Thermal Decomposition Low-Pressure LIF Data. Next, we focus on the LIF experiments of Zum Mallen and Schmidt on methanol decomposition.14 These researchers measured the CO partial pressure in methanol decomposition on platinum, as a function of temperature, at different inlet methanol pressures. Figure 1a shows the experimental data. The CO production rate increases as the temperature increases and reaches a plateau after a certain temperature. This system is simulated as a continuously stirred tank reactor (CSTR), using the C1 mechanism. It is observed that the CO partial pressure is significantly underpredicted, by an order of magnitude (not shown). A pairwise brute-force SA is performed, with respect to the pre-exponentials, to identify the important reactions contributing to the CO production. In pairwise SA, preexponentials of both the forward and backward reactions are perturbed by the same factor, so that thermodynamic consistency is maintained.31 It is observed that CO production is mainly sensitive to the reactions

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CH3OH* + * T CH2OH* + H* (R101-102) and

CH2O* + * T HCO* + H*

(R97-R98)

A decrease in the pre-exponentials of only these reactions by a factor of 50 results in a significantly better agreement with the experimental data. Typically, the surface reaction preexponentials are considered to be uncertain, within 2 orders of magnitude. A decrease in the important pre-exponentials by a factor of 20 and a small adjustment of bond indices (viz., 0.3 for reaction pair R97-R98 and 0.4 for reaction pair R101R102) provides similar results. Because these changes in the bond indices result in a decrease in the corresponding activation energies by only 2-2.5 kcal/mol, the latter modification is preferred, instead of changing the pre-exponentials by a factor of 50. The modified pre-exponentials are shown in Table 2 in italics. Figure 1a compares the simulations using these modified parameters with the experimental data. The CO partial pressure is quantitatively captured by the C1 mechanism with varying inlet methanol pressure. The onset of reactivity is also in good agreement with the experimental data. We revisit this experiment below in the assessment and analysis section, to understand the dominant chemistry. 3.4. Parameter Refinement Using CH4 Autothermal Reforming Data at Moderate Pressures. The parameter refinement discussed so far is based on UHV and low-pressure experiments. Next, we focus on moderate-pressure experiments to diversify the operating conditions and consider some morepractical processes. It is observed that ignoring the oxygenate decomposition steps (reactions R83-R104) from the C1 mechanism does not have any significant influence on the methane oxidation and reforming experiments. Therefore, they are not considered in the simulations presented hereafter, except for the oxygenate-related experiments in the mechanism assessment section. Furthermore, because gas-phase chemistry does not have an important role at moderate pressures (∼1 atm), the simulations shown hereafter are performed using the C1 surface chemistry only. Souza and Schmal conducted CH4 autothermal reforming experiments on Pt/Al2O3, Pt/ZrO2, and Pt/ZrO2/Al2O3 catalysts to measure the CH4 conversion and H2:CO ratio, as a function of temperature.32 Here, we consider the experimental data only on the first two catalysts to eliminate the effect of interactions between multiple supports. The fixed-bed reactor data is shown in Figures 2a and 2b. The general trend in these experiments is that the CH4 conversion increases and the H2: CO ratio decreases as the temperature increases. Equilibrium calculations using the GASEQ software33 show that these data are not equilibrium-limited. A plug flow reactor (PFR) model is used to simulate these experimental data. Predictions with the C1 mechanism indicate that an adjustment of catalyst area per unit volume of reactor (A/V) results in decent agreement with the experimental data for CH4 conversion in Figure 2a. However, the predicted H2:CO ratio at low temperatures is only ∼3 (not shown), whereas an intermediate value on both the Pt/ Al2O3 and Pt/ZrO2 catalysts is ∼5, indicating that some parameter refinement is necessary. A pairwise brute-force SA, with respect to pre-exponentials, indicates that the H2:CO ratio at low temperatures is mainly dependent on the thermal decomposition of CH3*:

CH3* + * T CH2* + H*

(R57-R58)

Figure 1. (a) Predictions of the C1 mechanism against the LIF experiments of Zum Mallen and Schmidt14 for methanol thermal decomposition on a platinum foil. The operating conditions include a reactor volume of 0.4 L, a catalyst foil area of 0.51 cm2, and a residence time of 4 s. Simulations with pure methanol at four different pressures are shown. Rate parameters of the C1 mechanism are adjusted to capture the experimental data (see text). (b) Dominant coverages at a methanol pressure of 0.2 Torr.

Figure 2. Predictions of the C1 mechanism against the fixed-bed CH4 autothermal reforming experiments of Sousa and Schmal,32 showing the effect of temperature on (a) the methane conversion and (b) the syngas ratio. The equilibrium calculations, shown by dotted lines, are performed using the GASEQ software.33 The operating conditions include a pressure of 1 atm, a reactor diameter of 0.6 cm, a bed length of 0.45 cm, an adjusted catalyst area per unit volume of 8000 cm-1, and an inlet flow rate of 200 cm3/min. The inlet composition is 20% CH4, 5% O2, 10% H2O, and 65% helium. These experimental data are used as a target in the optimization of the C1 mechanism rate parameters (see text).

The pre-exponentials of reaction pair R57-R58 are decreased by a factor of 10 to improve the C1 mechanism predictions. Such adjustment is crude; however, a rigorous optimization of the pre-exponentials is not done, to retain flexibility of the C1 mechanism and to avoid the incorporation of experimental uncertainties in mechanism parameters. For example, the experimental uncertainty in the H2:CO ratio could be large at low conversions at low temperatures. The modified parameters are shown in Table 2 in italics, and Figures 2a and 2b show the C1 mechanism predictions using these modified parameters. The H2:CO ratio at low temperatures (∼748 K) is significantly improved to ∼5. Both model responsessviz, the CH4 conversion

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Figure 3. Predictions of the C1 mechanism against the monolith CH4 CPOX reactor experiments of Tornianen et al.34 The operating conditions include a pressure of 1.4 atm, a reactor volume of ∼2.3 cm3, a reactor length of 1 cm, a catalyst area of ∼255.1 cm2, and an inlet flow rate of 4 L/min at STP (note that the inlet velocity changes with temperature). The feed includes 5% air, and the remainder is CH4 and O2. Rate parameters of the C1 mechanism are modified to capture all model responses (viz, CH4 conversion, CO selectivity, and H2 selectivity in this experiment; see text).

and the H2:CO ratiosare captured reasonably well by the C1 mechanism. The UHV TPR predictions discussed in section 3.1 are slightly deteriorated by the changes in the pre-exponentials of reaction pair R57-R58 (the peak temperature shifts to ∼320 K), but this is definitely outweighed by the gain in the predictions of autothermal reforming. 3.5. Parameter Refinement Using CH4 CPOX Data at Moderate Pressures. The last set of experimental data used for parameter refinement are CH4 CPOX experiments of Torniainen et al.34 These researchers conducted CH4 CPOX experiments in a platinum-coated ceramic monolith reactor to measure CH4 conversion and syngas selectivity, as a function of temperature. Figure 3 shows the experimental data. Using a PFR model to simulate these experiments, it is observed that the C1 mechanism captures the CH4 conversion well, but the CO selectivity is significantly underpredicted (by ∼25%) and the H2 selectivity is significantly overpredicted (by ∼10%15%) (not shown). Following the parameter refinement approach, a pairwise brute force SA is performed, with respect to the pre-exponentials of the C1 mechanism. The CO selectivity is mainly dependent on the reactions

CO* + H* T C* + OH*

(R79-R80)

2CO* T C* + CO2*

(R81-R82)

CH4 + 2* T CH3* + H*

(R55-R56)

and

The H2 selectivity is dependent on reaction pair R79-R80 only, whereas CH4 conversion is controlled by these three reactions, as well as

CO* + H* T CH* + O*

(R77-R78)

The pre-exponentials of reaction pairs R79-R80 and R81R82 are tuned to predict the CO and H2 selectivities, whereas, because the reaction pair R77-R78 only affects the CH4 conversion, its pre-exponentials are used to adjust the CH4 conversion predictions. Overall, the pre-exponentials of reaction pairs R77-R78 and R79-R80 are decreased by a factor of 10 and 2.5, respectively, whereas those of reaction pair R81-R82 are increased by a factor of 10. The modified parameters are shown in Table 2 in italics. Figure 3 shows the simulation

predictions using the C1 mechanism with these modified parameters. It is observed that the mechanism predictions are in decent agreement with the experimental data, with a significant improvement in the predicted syngas selectivity. 3.6. Summary. Overall, we have adjusted a total of 10 parameters (4 bond indices and 6 pre-exponentials) of the C1 mechanism, based on several experiments ranging from UHV to low pressures to moderate pressures. Of these 10 adjusted parameters, 4 are associated with oxygenates, which do not influence the CH4 chemistry. Furthermore, 2 of the remaining adjusted parameters are relevant to UHV conditions, which are not so much of practical interest. In essence, with an adjustment of only 4 parameters, it is possible to develop a fairly predictive C1 mechanism on platinum using the methods outlined previously. In the next sections, we assess and analyze the performance of the C1 mechanism against a variety of additional experiments, which were not considered in parameter refinement. These experiments primarily include low-pressure oxygenate decomposition and moderate-pressure oxygenate oxidation, CH4 CPOX, combustion, dry reforming, as well as steam reforming. Given that the catalyst surface area and reactor temperature are often not reported or a single temperature (e.g., exit) is measured (which is subject to uncertainty), some preliminary uncertainty analysis, with respect to these parameters, is occasionally performed to investigate their effect on model prediction and to avoid attributing all differences in the data to kinetic parameters. A more-comprehensive uncertainty analysis will be the subject of future work. 4. Assessment and Analysis of the C1 Mechanism for Oxygenate Decomposition and Oxidation 4.1. Oxygenate Decomposition on Platinum. Papapolymerou and Schmidt performed LIF experiments to measure the CO production rate, as a function of temperature, at different inlet formaldehyde pressures.35 The experimental data are shown in Figure 4a. The CO production rate increases as a function of increasing temperature and reaches a plateau after a certain temperature. A CSTR model is used to simulate the LIF system. Performance of the C1 mechanism is also shown in Figure 4a, where the predictions are normalized with the experimental data at 1150 K and 0.1 Torr. It is evident that the agreement between the C1 mechanism predictions and the experimental data is good, especially the onset of activity in the lowtemperature region (for the sake of clarity, comparisons at 0.2 and 0.03 Torr are not shown). Coverages based on the C1 mechanism simulations are shown in Figure 4b, at a formaldehyde pressure of 0.5 Torr. At low temperatures, CH* is the dominant species, whereas vacancies dominate after the onset of activity. We have performed RPA for this system at 400 and 600 K, which shows that CH2O is adsorbed on the surface and gets converted to HCO* and CH2OH*. However, the formation and decomposition of CH2OH* is close to partial equilibrium, making HCO* formation the dominant decomposition path. HCO* then decomposes to CO*, which finally desorbs. At low temperatures, a very small amount of CO* is converted to C* through reaction R81 (2CO* T C* + CO2*) and results in CH* formation on the surface through reaction R62 (C* + H* T CH* + *). At higher temperatures, most of the CO* desorbs, leading to negligible CH* formation and vacancies on the surface. Coverages in the methanol decomposition LIF experiment (see Figure 1b) are similar to those for the formaldehyde decomposition experiment. Unfortunately, coverages are not

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Figure 4. Assessment of the C1 mechanism against the formaldehyde thermal decomposition LIF experiments of Papapolymerou and Schmidt.35 The operating conditions include a reactor volume of 0.4 L, a catalyst wire diameter of 0.019 cm, a catalytic wire length of 9 cm, and a residence time of 4 s. Pure formaldehyde is used in the inlet, at five different pressures. (Predictions at 0.2 and 0.03 Torr are not shown for clarity.) (a) Model predictions normalized against the experimental CO production rate under sample conditions of 0.1 Torr and 1150 K; the C1 mechanism captures the experimental data qualitatively at all pressures, without any adjustment of the rate parameters. (b) Dominant coverages at a formaldehyde pressure of 0.5 Torr.

experimentally measured in most reaction studies; therefore, a direct comparison of model predictions to the data is impossible at this stage, but is highly desirable for model assessment and should be the subject of future experimental work. RPA for the methanol decomposition experiment indicates that, upon adsorption, CH3OH* decomposes to CH2OH* via C-H cleavage, which, in turn, creates CH2O*. CH3OH* decomposition to CH3O* is not preferred, because of a high activation energy of this step. Recent DFT work of Gokhale et al.36 also indicates that methanol undergoes C-H scission rather than the O-H scission. Overall, the methanol and formaldehyde decomposition paths could be schematically presented as +*

+*

+*

+*

CH3OH(g) 98 CH3OH* 9 8 CH2OH* 9 8 CH2O* 9 8 -H* -H* -H* +*

HCO* 9 8 CO* 9 8 CO(g) -H* -* 4.2. Methanol Oxidation on Platinum. Atmosphericpressure methanol oxidation experiments were performed by Chantaravitoon et al., using a fixed-bed reactor.37 A minute fraction of methanol (1200 ppm) was oxidized in oxygen and helium, using a Pt/Al2O3 catalyst to measure the methanol conversion, as a function of temperature. Predictions of the C1 mechanism using a PFR model are shown in Figure 5a. With only a single adjustment of A/V, the methanol conversion data are predicted reasonably well by the C1 mechanism. CO2 and H2O are predicted to be the main products. Coverage analysis indicates that O* is the dominant surface species (θO ≈ 0.99), which is expected, given the high concentration of oxygen in the gas phase. To understand the overall pathways, RPA is conducted at 333 K and is shown in Figure 5b. CO* is produced from the sequential dehydrogenation of CH3OH* and is oxidized to CO2* using O*. The H* that is produced

Figure 5. (a) Assessment of the C1 mechanism against the fixed-bed methanol combustion experiments of Chantaravitoon et al.37 Operating conditions include a pressure of 1 atm, a reactor diameter of 1.2 cm, a reactor volume of 0.78 cm3, an adjusted catalyst area per unit volume (A/ V) of 500 cm-1, and an inlet flow rate of 260 cm3/min. The inlet feed is comprised of 1200 ppm CH3OH and 21% O2, balanced by helium. The C1 mechanism captures the methanol oxidation data fairly well. (b) Dominant paths in the overall methanol oxidation. Because of the presence of excess O2, complete oxidation products are observed in the simulations.

also gets oxidized to form H2O*, which desorbs. The overall total oxidation reaction is given as

CH3OH + 1.5O2 f CO2 + 2H2O We have also examined the effect of additional O*-assisted and OH*-assisted oxygenates dehydrogenation reactions (not shown in Table 2). It is observed that the OH*-assisted dehydrogenation reactions are important at only low temperatures, such as 293-303 K. Under these conditions, CO* is predicted to be the most abundant reaction intermediate (MARI). At moderate temperatures, O* becomes the MARI and, mainly, the decomposition reactions dominate. Because of a sudden change in MARI from 293 to 308 K, nonmonotonic behavior is observed in methanol conversion. Because the experimental uncertainty at low temperatures and low conversions is high, we do not include the O*-assisted and OH*-assisted dehydrogenation reactions for any C1 predictions, but realize that more experimental data and DFT-based rate parameters could help in the development of a more-reliable microkinetic model for methanol oxidation on platinum. 5. Assessment and Analysis of the C1 Mechanism for CH4 CPOX: Direct Versus Indirect Oxidation 5.1. Performance of the C1 Mechanism. Many groups have conducted kinetic experiments for CH4 CPOX. One data set was shown in Figure 3. Here, we focus on the experiments of Wolf et al., who used a fixed-bed reactor with a Pt/MgO catalyst.38 These researchers used a high gas velocity and small catalyst particles to suppress the external and internal massand heat-transfer limitations. The gas mixture of CH4/O2 was

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Figure 6. Assessment of the C1 mechanism against the fixed-bed methane CPOX experimental data of Wolf et al.,38 showing the exit mole fractions corresponding to (a) reactants, (b) C-products, and (c) H-products. The operating conditions include a pressure of 1 bar, a temperature of 1003 K, a reactor diameter of 0.6 cm, an adjusted catalyst area per unit volume of A/V ) 10 000 cm-1, and an inlet flow rate of 16.7 cm3/s at STP (note that the inlet velocity changes with temperature). The catalyst weight varies over a range of 0.01-0.2 g, resulting in a range of contact time of 0.061.3 ms. The modified contact time (W/FSTP, in units of g s/cm3), plotted on the x-axis, is defined as the ratio of catalyst weight to inlet flow rate at STP. The inlet feed is comprised of 2% CH4, 1.8% O2, and 96.2% N2. The experimental data is well-captured by the C1 mechanism without any rate parameter adjustment.

Figure 7. Assessment of the C1 mechanism against the experimental data of Wolf et al.38 at 1123 K. Other operating conditions are the same as those given in Figure 6. Good agreement is observed between experimental data and the C1 mechanism predictions.

significantly diluted with N2 (96.2%) to ensure a constant axial temperature within the catalyst bed (temperature variation ≈ 30 °C). The experimental data of product distribution, as a function of a modified contact time (catalyst weight/inlet flow rate at STP, W/FSTP), is shown in Figures 6 and 7 at 1003 and 1123 K, respectively. Such data are useful, in terms of mechanism assessment, because the variation with contact time, in the absence of diffusion and temperature gradients, or for a large Peclet number, could be viewed as spatially resolved data along the reactor length. The C1 mechanism is used to simulate these experiments with a PFR model and an A/V value adjusted at one point. It is evident that the species mole fraction profiles are well-captured by the C1 mechanism. The oxygen consump-

tion location (or contact time) and its shift with temperature are also well-predicted. Obviously, a more stringent model assessment will require input of the catalyst surface area and detailed analysis of transport effects. Such studies will be reported in a forthcoming publication. 5.2. Is Methane CPOX on Platinum Direct or Indirect? The issue of indirect versus direct CH4 CPOX has been discussed to a great extent in the literature for several catalysts. Specific to platinum, the experiments in monoliths and the corresponding simulations of Hickman and Schmidt9 have supported the idea of a direct oxidation path. This idea was proposed based on the high syngas selectivities that were observed with short residence times; however, one realizes that the conclusion has been reached indirectly, and their mechanism was not developed to capture the combustion and reforming data properly. In fact, we have determined that, in several instances, these earlier mechanisms do not predict non-CPOX data. de Smet et al.39 observed CO, CO2, and H2O as primary products at catalyst temperatures in the range of 1030-1200 K, CH4/O2 ratios in the range of 1.8-5, and oxygen conversions in the range of 9%-46%. Therefore, the formation of total oxidation products has also been monitored, under certain operating conditions. Using a temporal analysis of products (TAP-2) reactor, Fathi et al.40 observed that the CO and H2 signals reach their maxima long after the CO2 and H2O signals. However, the authors did not support the idea of secondary reforming. Instead, it was suggested that total oxidation occurs in the presence of oxygen, but when surface and gas-phase oxygen are depleted, surface carbon is selectively oxidized to CO, using subsurface oxygen diffusing from the bulk to the surface. On a similar note, Hofstad et al.41 have suggested that the oxygen available on a rhodium surface, as well as the spillover of oxygen from the support to the metal, can affect the formation of partial or total oxidation products. Transient studies that have been reported in refs 42-44 do not support the hypothesis of a direct reaction pathway on Rh/γ-Al2O3 catalysts. Our simulations on rhodium and, herein, on platinum, in conjunction with recent spatially resolved data,45 alleviate some of the debate in support of the indirect oxidation paths. Two interesting observations can be made from Figures 6 and 7. First, CH4 consumption continues, even after the oxygen is completely consumed, indicating the possibility of a reforming reaction downstream. Second, CO2 and H2O are the major products at short contact times (or short reactor lengths), whose concentrations decrease after complete oxygen consumption, leading to CO and H2. The experimental data on Pt/MgO in Figures 6 and 7, as well as our simulations, indicate that the CO is completely oxidized to CO2. Overall, it seems that the experiments and simulations follow indirect syngas formation. To delineate the dominant reaction paths better, first, we show the dominant surface coverages at selected operating conditions (a contact time of 1 × 10-3 g s/cm3 and a temperature of 1123 K) shown in Figure 8. Clearly, there is a change in the MARI from O* at the reactor front to CH* toward its end. Accordingly, we define (at least) two regions along the reactor length (or versus contact time): an oxidation zone near the entrance of the reactor, where oxygen is abundant on the surface, followed by a reforming zone, where oxygen consumption is complete. Using the C1 mechanism, we calculated ratios of gas-phase species production rates (desorption minus adsorption) to the methane consumption rate (adsorption minus desorption), under the same operating conditions. Figure 9 shows the ratios of such rates along the reactor length. In the oxidation zone, it is evident

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Figure 8. Axial profiles of surface coverages of dominant species at 1123 K and W/FSTP ) 1 × 10-3 g s/cm3 for the conditions given for Figure 7. The MARI changes from O* to CH* along the reactor length. Figure 10. Schematic representation of the species production/consumption pathways, using the C1 mechanism for the conditions given for Figure 7 at 1123 K (a) in the oxidation zone (sample W/FSTP ) 5 × 10-4 g s/cm3) and (b) in the reforming zone (sample W/FSTP ) 1 × 10-3 g s/cm3). Dominant paths are shown with solid lines, whereas dashed lines indicate alternate paths that are less important but not negligible. In the oxidation zone, O*assisted CHx dehydrogenation is observed along with CO* oxidation. On the other hand, thermal decomposition of CHx dominates in the reforming zone, along with CO formation from steam and CO2 reforming, without any CO2 formation.

To understand the underlying chemistry, we conducted RPA at two selected operating conditions (a contact time of 5 × 10-4 g s/cm3, where oxygen consumption is incomplete, and a contact time of 1 × 10-3 g s/cm3, where oxygen consumption is complete) for the conditions corresponding to Figure 7. Figure 10 shows the dominant paths from reactants to products. As shown in Figure 10a (oxidation zone, short contact time), CHx dehydrogenation mainly happens via the oxygen-assisted route, rather than via the thermal or hydroxyl-assisted routes. Instead of producing C*, CH* is converted to CO* via the reaction Figure 9. Surface-chemistry-based ratios of species production rates to CH4 consumption rate, using the C1 mechanism for the conditions given for Figure 7 at 1123 K and W/FSTP ) 1 × 10-3 g s/cm3. In the oxidation zone, the rate ratios correspond to the stoichiometry of the total oxidation of methane. Downstream from the oxidation zone, steam reforming dominates.

that CH4 is completely oxidized to CO2 and H2O, which is consistent with the stoichiometry of complete combustion:

CH4 + 2O2 f CO2 + 2H2O In the reforming zone, CH4, H2O, and CO2 are consumed to produce CO and H2. There are three different overall reactions that could happen in the reforming zone, which are given as follows:

steam reforming: CH4 + H2O f CO + 3H2 dry reforming: CH4 + CO2 f 2CO + 2H2 and

forward or reverse WGS: CO + H2O T CO2 + H2 The ratios of reaction rates in Figure 9 in the reforming zone are similar to those of the steam reforming. However, some small contribution from dry reforming or WGS also occurs. Because any one of these three reactions is a linear combination of the other two, we cannot assess which reactions occur in the reforming zone, solely based on the information of Figure 9.

CH* + O* f CO* + H*

(R78)

CO2* is produced via CO* oxidation by O* and it subsequently desorbs. The recombination of H* and O* ultimately results in H2O production. In comparison, as shown in Figure 10b (reforming zone, long contact time), CHx dehydrogenation is mainly thermal and proceeds all the way to produce C*. H2O and CO2, which are produced in the oxidation zone, readsorb on the surface. H2O* causes OH* formation, and CO* formation occurs mainly via two reactions, viz,

C* + OH* f CO* + H*

(R80)

C* + CO2* f 2CO*

(R82)

and

Because the conversion from C* to CO* occurs using OH* (generated from gas-phase H2O) and CO2* (generated from gasphase CO2), we can infer that steam reforming and dry reforming reactions happen in the reforming zone. Furthermore, using the information in Figure 9, we also deduce that steam reforming dominates over dry reforming by at least a factor of 3. On the other hand, if CO2* were consumed by H* or if CO* had reacted primarily with OH* or H2O*, the reverse WGS or the WGS reaction would have been the contributing pathway. Because the experimental data of ref 34 in Figure 3 is also CH4 CPOX, but with a different diluent concentration (only 3.95% versus 96.2% in Figures 6 and 7), it is interesting to check the conclusions regarding direct versus indirect pathways of methane oxidation. Analysis for the reaction rate ratios and

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Figure 11. Mole fraction profiles using the C1 mechanism for the conditions of Figure 3, corresponding to an inlet CH4:O2 ratio of 1.8:1: (a) reactants, (b) C-products, and (c) H-products. The decrease in methane mole fraction, even after complete oxygen consumption and the simultaneous decrease in H2O mole fraction, indicate that steam reforming occurs. The decrease in CO2 after complete oxygen consumption suggests some CO2 reforming.

RPA (not shown) indicate the same production-consumption pathways as those in Figures 10a and 10b. Figure 11 shows the mole fraction profiles along the reactor length at selected operating conditions of Figure 3. The profiles resemble closely the experimental data shown in Figures 6 and 7, indicating that the underlying chemistry is unaffected by the diluent concentration. Furthermore, RPA for the autothermal reforming experiments of ref 32 in Figure 2 is also similar to that in Figures 10a and 10b. At the front of the reactor, where oxygen is present, oxygen-assisted paths dominate and CO2 is produced. On the other hand, toward the exit of the reactor, where oxygen conversion is complete, adsorption of H2O results in steam reforming to produce CO. However, no dry (CO2) reforming is observed, because of the excess H2O. We should caution the reader that details of the paths may be dependent on, and vary to some extent with, different operating conditions, as already mentioned previously, regarding the role of dry reforming. Based on this analysis, it can be concluded that, for the conditions analyzed here, CH4 CPOX on platinum is determined to be indirect, where total oxidation products are formed first, followed by steam and dry reforming reactions that produce the partial oxidation products CO and H2. Our recent work on rhodium indicated that, after oxygen consumption is complete, steam reforming of methane produces hydrogen and more CO.

Figure 12. (a) Assessment of the C1 mechanism against the fixed-bed methane complete oxidation experiments of Wierzba and Depiak.46 The operating conditions include a pressure of 1 atm, a reactor length of 5 cm, an adjusted catalyst area per unit volume of A/V ) 220 cm-1, and an inlet velocity of 100 cm/s. The inlet feed is comprised of a lean CH4/air mixture with an equivalence ratio of 0.35, corresponding to 3.5% CH4, 20.3% O2, and 76.2% N2. The C1 mechanism captures the temperature effects on methane conversion fairly well, without any rate parameter adjustment. (b) RPA-based dominant paths in overall methane oxidation. O*-assisted dehydrogenation paths dominate due to the high oxygen content in the inlet, leading to total oxidation products.

equilibrium CH4 conversion under these conditions is ∼100% and, hence, the C1 mechanism captures the kinetics of CH4 oxidation. CO2 and H2O are observed as the major products, with negligible selectivity to the partial oxidation products CO and H2. To understand the important pathways, RPA is performed at 723 K and is shown in Figure 12b. Overall, the oxidation process is the same as that shown in Figure 10a, which is a characteristic of an oxidation zone on platinum. O* dominates the surface under all conditions. 6.2. Ignition of CH4/Air Mixtures on Platinum. The ignition temperature is an important characteristic of a fuel/oxidizer system, because it represents the minimum temperature to which the fuel must be heated to start the chemistry. Here, we validate the C1 mechanism to check its predictions for CH4/air ignition data. Veser et al. measured the ignition temperatures of various CH4/air mixtures in a stagnation point flow reactor using a platinum foil.47 Figure 13 shows the experimental ignition temperatures as a function of the equivalence ratio. The ignition

6. Additional Assessment of the C1 Mechanism for CH4 Oxidation 6.1. Complete Oxidation of Fuel-Lean Mixtures on Platinum. Wierzba and Depiak studied CH4 oxidation on platinum using a fixed-bed reactor.46 Using external electrical heating, the catalyst bed was maintained at a uniform temperature (to within (5 °C). Very lean CH4/air mixtures (equivalence ratio of φ ) 0.35) were used in these experiments. The experimental data of fuel conversion versus temperature is shown in Figure 12a. The CH4 conversion increases significantly at intermediate temperatures, which is a process typically known as light off or ignition. Figure 12a also shows the performance of the C1 mechanism using a PFR model. The agreement between simulations and the experimental data is impressive, provided that only the A/V value is adjusted at one point. Note that the

Figure 13. Assessment of the C1 mechanism versus the CH4 ignition temperature, as a function of equivalence ratio (inlet composition), using data from Veser et al.47 The operating conditions include a pressure of 1 atm, a residence time of ∼2 s, in inlet flow rate of 3 L/min, and an adjusted catalyst area per unit volume of A/V ) 0.1 cm-1. The decrease in ignition temperature with increasing equivalence ratio is captured reasonably well by the C1 mechanism.

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Figure 15. (a) Assessment of the C1 mechanism against the fixed-bed methane steam reforming experiments of Hegarty et al.50 The operating conditions include an assumed pressure of 1 atm, a reactor diameter of 0.4 cm,85 a reactor length of 6.4 cm, an inlet flow rate of 130 cm3/min, and an adjusted catalyst area per unit volume of A/V ) 1000 cm-1. The inlet feed includes CH4:H2O:H2:N2, in the proportion of 1:2.64:3.6:0.46. Equilibrium calculations using the GASEQ software33 are also shown. The temperature effects on steam reforming are well-captured by the C1 mechanism. (b) RPA-based dominant pathways for steam reforming at 923 K.

Figure 14. Assessment of the C1 mechanism against the fixed-bed methane CO2 reforming experimental data of Gustafson and Walden49 for (a) temperature effects and (b) composition effects. The experimental data at 1123 K in panel b is close to equilibrium predictions, according to the equilibrium calculations performed using the GASEQ software.33 The operating conditions include a pressure of 1 atm, a reactor diameter of 1 in., an assumed reactor length of 3 cm, an inlet flow rate of 486 cm3/min at STP (note that the inlet velocity changes with temperature), and an adjusted catalyst area per unit volume of A/V ) 10 000 cm-1. The inlet CO2:CH4 feed ratio in panel a is 0.9:1. Decent agreement is observed between the experimental data and the C1 mechanism predictions. (c) Dominant reaction paths in CO2 reforming of methane for conditions given in panel a, at 873 K; the reverse Boudouard reaction has an important role in CO2 reforming.

temperature decreases as the CH4 concentration increases. A CSTR model is used to simulate this system, along with a twoparameter continuation algorithm to solve for the ignition temperature, as a function of the inlet composition.48 With an adjustment of the A/V value, the C1 mechanism is able to capture the ignition data reasonably well. Coverage analysis indicates that, for fuel-lean mixtures, O* is the dominant species on platinum prior to ignition, whereas after ignition, there is a shift to vacant surface sites. For fuel-rich mixtures, similar behavior is observed, except that CH* coverage is also nonnegligible after ignition. Because CH4 adsorption is activated, increasing the CH4 fraction assists the oxidation process, leading to a reduction of the ignition temperature. 7. Assessment and Analysis of the C1 Mechanism for CH4 Reforming In this section, the C1 mechanism is validated against additional reforming experimental data. One of the data sets is similar to the equilibrium conditions and shows the importance of thermodynamic consistency of the C1 mechanism. 7.1. Dry (CO2) Reforming of Methane on Platinum. Gustafson and Walden investigated the temperature and composition effects in the CO2 reforming of methane in a fixed-

bed reactor.49 The experimental data on a Pt/Al2O3 catalyst are shown in Figures 14a (temperature effects) and 14b (composition effects). Using the GASEQ software,33 it is observed that the CO2 reforming data in Figure 14b is similar to equilibrium conditions. Therefore, the data in Figure 14b could be useful to validate the thermodynamic consistency of the C1 mechanism on platinum. In comparison, data in Figure 14a is not equilibrium limited, especially at low temperatures. Results using a PFR model are shown in Figures 14a and 14b. The change in mole fractions of major species is well-captured by the C1 mechanism, as shown in Figure 14a, indicating that the C1 mechanism can predict temperature effects in dry reforming. Only A/V is adjusted at one point in these simulations. Furthermore, good agreement between the close to equilibrium experimental data and the model predictions in Figure 14b indicate that the C1 mechanism is thermodynamically consistent. This example illustrates the importance of thermodynamic consistency of surface reaction mechanisms. RPA for a selected temperature of 873 K is shown in Figure 14c. C* is formed from the sequential thermal dehydrogenation of CHx species on the surface. Upon CO2 adsorption, the reverse Boudouard reaction,

C* + CO2* f 2CO*

(R82)

occurs to form CO*, which desorbs. H* atoms abstracted from CHx species result in associative H2 desorption. The reverse Boudouard reaction was also determined to be important in our recent work on CO2 reforming on rhodium.21 7.2. Steam Reforming of Methane on Platinum. The final assessment of the C1 mechanism is examined against the steam reforming experiments of Hegarty et al.50 These researchers measured CH4 conversion in a fixed-bed reactor using a Pt/ ZrO2 catalyst. Figure 15a shows the experimental data. Equilibrium calculations using the GASEQ software33 show that the experimental data is not equilibrium-limited. The system is modeled as a PFR with an adjusted A/V. Predictions of the C1

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mechanism, shown in Figure 15a, are in decent agreement with the experimental data and indicate that the C1 mechanism also works reasonably well for steam reforming. The main gas-phase products are H2, CO, and CO2. RPA for steam reforming, shown in Figure 15b, indicates that the sequential thermal dehydrogenation of CHx species on the surface results in C*, which is oxidized to CO* by OH*:

C* + OH* f CO* + H*

(R80)

H2O adsorption is crucial to generate this OH*, as well as to convert CO* to CO2* (which, in this case, is undesirable) via the CO-H2 coupling chemistry, which is given as

CO* + H2O* f COOH* + H*

(R33)

COOH* + * f CO2* + H*

(R31)

and

Clearly, the WGS reaction occurs under these conditions. In our recent work on WGS on platinum, reaction R33 was shown to be the rate-determining step,51 and this example also emphasizes the importance of CO-H2 coupling chemistry in steam reforming.

In the bigger picture, this C1 mechanism could be utilized for the modeling and optimization of fuel processing reactors and operating conditions. From our experience in mechanism development, it becomes clear that, to develop a next generation of more-reliable microkinetic models, aside from theoretical advances, one requires minimal experimental requirements, namely (i) spatially resolved experimental data, (ii) accurate temperature profiles, and (iii) data for various pathways and processes generated in the same reactor with the same catalyst. The first requirement is essential to understand pathways, because the exit composition is easily predicted, even with qualitatively incorrect mechanisms. The second requirement was revealed from our work, where we have determined that changes by even 50 °C have a profound effect on the predictions. The third one underscores the importance of knowing the active surface area and residence time and how these are linked to catalyst synthesis conditions, variables that are often not reported, and variables that are adjusted in a model at the expense of increased parameter uncertainty. We will address some of these issues in future work. Acknowledgment This work was supported in part by the donors of the Petroleum Research Fund, administered by the American Chemical Society.

8. Conclusions A predictive CH4 (C1) mechanism is developed on platinum, using a hierarchical multiscale approach. Parameters are estimated using literature experimental data, semiempirical calculations, and literature density functional theory (DFT) calculations. The semiempirical unity bond index-quadratic exponential potential (UBI-QEP) framework, along with statistical mechanics and constraints-based optimization, are applied to ensure thermodynamic consistency in the C1 mechanism. Selected important parameters are refined using different types of experimental data from ultrahigh vacuum (UHV) conditions to atmospheric pressure. Essentially, with an adjustment of only four important parameters, the C1 mechanism predicts CH4 partial oxidation, combustion, steam reforming, and dry reforming. In addition, oxygenate decomposition and oxidation on platinum has been described, but further assessment of these submechanisms is desirable. Dominant pathways from reactants to products of these processes are identified. In the catalytic partial oxidation of methane (CPOX) at short contact times, different spatial zones are observed: an oxidation zone, where oxygen dominates on the surface, followed by a reforming zone, where oxygen conversion is complete. Methane is completely oxidized in the oxidation zone via the reaction

CH4 + 2O2 f CO2 + 2H2O whereas steam reforming reactions, e.g.,

CH4 + H2O f CO + 3H2 and, to a lesser extent, some CO2 reforming reactions, e.g.,

CH4 + CO2 f 2CO + 2H2 happen in the reforming zone to produce CO and H2, which suggests that methane oxidation follows an indirect pathway. In the case of steam reforming, the water-gas shift (WGS) reaction seems to have a role (at least under the simulated conditions).

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ReceiVed for reView March 2, 2007 ReVised manuscript receiVed April 29, 2007 Accepted May 23, 2007 IE070322C