Experimental, detailed, and global kinetic reaction model for NO oxidation over platinum/alumina catalysts

Wentworth, Travis; Loya, Sudarshan; Depcik, Christopher; Stagg-Williams, Susan M.

doi:10.1007/s11144-015-0935-z

Cited by 5 publications

(2 citation statements)

References 54 publications

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“…29,30 However, the NO oxidation mechanism and its transferability from surfaces to nanoparticles remain unresolved. 31 It is known that the greatest TOFs of this reaction occur over the close-packed Pt(111) facets of supported particles. 29,30 Moreover, it has been recognized that, during reaction conditions, oxygen (denoted as O) dominates the Pt surface, and high O coverages have been observed to account for NO oxidation activity.…”

Section: B No Oxidation and No 2 Reduction On Pt(111)mentioning

confidence: 99%

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Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

Pineda

Stamatakis

2017

The Journal of Chemical Physics

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Assessment of mean-field microkinetic models for CO methanation on stepped metal surfaces using accelerated kinetic Monte Carlo The Journal of Chemical Physics 147, 152705 (2017) Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

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Section: B No Oxidation and No 2 Reduction On Pt(111)mentioning

confidence: 99%

“…In our analysis, the catalytic reaction proceeds via the following steps: 19,22,31,32 (10) (11) (12) with * and O * denoting a vacant adsorption site and adsorbed oxygen atoms, respectively. The last reaction denotes diffusion of O * between neighboring adsorption sites.…”

Section: B No Oxidation and No 2 Reduction On Pt(111)mentioning

confidence: 99%

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

Pineda

Stamatakis

2017

The Journal of Chemical Physics

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Improved emissions conversion of diesel oxidation catalyst using multifactor impact analysis and neural network

Peng

2023

Energy

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Optimization of diesel oxidation catalyst for enhanced emission reduction in engines

Peng,

Ye,

Kang

2024

Energy

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Experimental, detailed, and global kinetic reaction model for NO oxidation over platinum/alumina catalysts

Cited by 5 publications

References 54 publications

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

Improved emissions conversion of diesel oxidation catalyst using multifactor impact analysis and neural network

Optimization of diesel oxidation catalyst for enhanced emission reduction in engines

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