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      Efficient implementation of Cluster Expansion models in surface Kinetic Monte Carlo simulations with lateral interactions: Subtraction Schemes, Supersites and the Supercluster Contraction

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          Abstract

          While lateral interaction models for reactions at surfaces have steadily gained popularity and grown in terms of complexity, their use in chemical kinetics has been impeded by the low performance of current KMC algorithms. The origins of the additional computational cost in KMC simulations with lateral interactions are traced back to the more elaborate Cluster Expansion Hamiltonian, the more extensive rate updating, and to the impracticality of rate-catalog-based algorithms for interacting adsorbate systems. Favoring instead site-based algorithms, we propose three ways to reduce the cost of KMC simulations: 1. Represent the lattice energy by a smaller Supercluster Hamiltonian without loss of accuracy, 2. employing Subtraction Schemes for updating key quantities in the simulation that undergo only small, local changes during a reaction event, and 3. applying efficient search algorithms from a set of established methods (Supersite Approach). The resulting algorithm is fixed-cost with respect to the number of lattice sites for practical lattice sizes and scales with the square of the range of lateral interactions. The overall added cost of including a complex lateral interaction model amounts to less than a factor 3. Practical issues in implementation due to finite numerical accuracy are discussed in detail, and further suggestions for treating long-range lateral interactions are made. We conclude that, while KMC simulations with complex lateral interaction models are challenging, these challenges can be overcome by modifying the established Variable Step Size Method by employing the Supercluster, Subtraction and Supersite algorithms (SSS-VSSM).

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          Active sites for CO2 hydrogenation to methanol on Cu/ZnO catalysts.

          The active sites over commercial copper/zinc oxide/aluminum oxide (Cu/ZnO/Al2O3) catalysts for carbon dioxide (CO2) hydrogenation to methanol, the Zn-Cu bimetallic sites or ZnO-Cu interfacial sites, have recently been the subject of intense debate. We report a direct comparison between the activity of ZnCu and ZnO/Cu model catalysts for methanol synthesis. By combining x-ray photoemission spectroscopy, density functional theory, and kinetic Monte Carlo simulations, we can identify and characterize the reactivity of each catalyst. Both experimental and theoretical results agree that ZnCu undergoes surface oxidation under the reaction conditions so that surface Zn transforms into ZnO and allows ZnCu to reach the activity of ZnO/Cu with the same Zn coverage. Our results highlight a synergy of Cu and ZnO at the interface that facilitates methanol synthesis via formate intermediates.
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            A graph-theoretical kinetic Monte Carlo framework for on-lattice chemical kinetics

            Existing kinetic Monte Carlo (KMC) frameworks for the simulation of adsorption, desorption, diffusion, and reaction on a lattice often assume that each participating species occupies a single site and represent elementary events involving a maximum of two sites. However, these assumptions may be inadequate, especially in the case of complex chemistries, involving multidentate species or complex coverage and neighboring patterns between several lattice sites. We have developed a novel approach that employs graph-theoretical ideas to overcome these challenges and treat easily complex chemistries. As a benchmark, the Ziff-Gulari-Barshad system is simulated and comparisons of the computational times of the graph-theoretical KMC and a simpler KMC approach are made. Further, to demonstrate the capabilities of our framework, the water-gas shift chemistry on Pt(111) is simulated.
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              Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions.

              Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. More recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.
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                Author and article information

                Journal
                09 August 2019
                Article
                10.1002/jcc.26041
                1908.03526
                3b30e030-a075-403c-b5d5-e86b88dcdffa

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                physics.comp-ph cond-mat.stat-mech physics.chem-ph

                Condensed matter,Mathematical & Computational physics,Physical chemistry
                Condensed matter, Mathematical & Computational physics, Physical chemistry

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