1
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Jiang Y, Huang Y, Guo H, Zhu H, Chen ZX. Comparative simulations of methanol steam reforming on PdZn alloy using kinetic Monte Carlo and mean-field microkinetic model. J Chem Phys 2024; 161:024701. [PMID: 38980094 DOI: 10.1063/5.0206139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 06/19/2024] [Indexed: 07/10/2024] Open
Abstract
Methanol steam reforming (MSR) is an attractive route for producing clean energy hydrogen. PdZn alloys are extensively studied as potential MSR catalysts for their stability and high CO2 selectivity. Here, we investigated the reaction mechanism using density functional calculations, mean-field microkinetic modeling (MF-MKM), and kinetic Monte Carlo (kMC) simulations. To overcome the over-underestimation of CO2 selectivity by log-kMC, an ads-kMC algorithm is proposed in which the adsorption/desorption rate constants were reduced under certain requirements and the diffusion process was treated by redistributing surface species each time an event occured. The simulations show that the dominant pathway to CO2 at low temperatures is CH3OH → CH3O → CH2O → H2COOH → H2COO → HCOO → CO2. The ads-kMC predicted OH coverage is 2-3 times that of MF-MKM, while they produce similar coverage for other species. Analyses indicate that surface OH promotes the dehydrogenation of CH3OH, CH3O, and H2COOH significantly and plays a key role in the MSR process. The dissociation of water/methanol is the most important rate-limiting/rate-inhibiting step. The CO2 selectivity obtained by the two methods is close to each other and consistent with the experimental trend with temperature. Generally, the ads-kMC results agree with the MF-MKM ones, supporting the previous finding that kMC and MF-MKM predict similar results if the diffusion is very fast and adsorbate interactions are neglected. The present study sheds light on the MSR process on PdZn alloys, and the proposed scheme to overcome the stiff problems in kMC simulations is worthy of being extended to other systems.
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Affiliation(s)
- Yongjie Jiang
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Yucheng Huang
- College of Chemistry and Material Science, Key Laboratory of Functional Molecular Solids, Ministry of Education, Anhui Normal University, Wuhu 241000, China
| | - Hui Guo
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Hong Zhu
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Zhao-Xu Chen
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
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2
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Yokaichiya T, Ikeda T, Muraoka K, Nakayama A. On-the-fly kinetic Monte Carlo simulations with neural network potentials for surface diffusion and reaction. J Chem Phys 2024; 160:204108. [PMID: 38785283 DOI: 10.1063/5.0199240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 05/05/2024] [Indexed: 05/25/2024] Open
Abstract
We develop an adaptive scheme in the kinetic Monte Carlo simulations, where the adsorption and activation energies of all elementary steps, including the effects of other adsorbates, are evaluated "on-the-fly" by employing the neural network potentials. The configurations and energies evaluated during the simulations are stored for reuse when the same configurations are sampled in a later step. The present scheme is applied to hydrogen adsorption and diffusion on the Pd(111) and Pt(111) surfaces and the CO oxidation reaction on the Pt(111) surface. The effects of interactions between adsorbates, i.e., adsorbate-adsorbate lateral interactions, are examined in detail by comparing the simulations without considering lateral interactions. This study demonstrates the importance of lateral interactions in surface diffusion and reactions and the potential of our scheme for applications in a wide variety of heterogeneous catalytic reactions.
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Affiliation(s)
- Tomoko Yokaichiya
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Tatsushi Ikeda
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Koki Muraoka
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Akira Nakayama
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
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3
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Sun S, Higham MD, Zhang X, Catlow CRA. Multiscale Investigation of the Mechanism and Selectivity of CO 2 Hydrogenation over Rh(111). ACS Catal 2024; 14:5503-5519. [PMID: 38660604 PMCID: PMC11036393 DOI: 10.1021/acscatal.3c05939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/26/2024]
Abstract
CO2 hydrogenation over Rh catalysts comprises multiple reaction pathways, presenting a wide range of possible intermediates and end products, with selectivity toward either CO or methane being of particular interest. We investigate in detail the reaction mechanism of CO2 hydrogenation to the single-carbon (C1) products on the Rh(111) facet by performing periodic density functional theory (DFT) calculations and kinetic Monte Carlo (kMC) simulations, which account for the adsorbate interactions through a cluster expansion approach. We observe that Rh readily facilitates the dissociation of hydrogen, thus contributing to the subsequent hydrogenation processes. The reverse water-gas shift (RWGS) reaction occurs via three different reaction pathways, with CO hydrogenation to the COH intermediate being a key step for CO2 methanation. The effects of temperature, pressure, and the composition ratio of the gas reactant feed are considered. Temperature plays a pivotal role in determining the surface coverage and adsorbate composition, with competitive adsorption between CO and H species influencing the product distribution. The observed adlayer configurations indicate that the adsorbed CO species are separated by adsorbed H atoms, with a high ratio of H to CO coverage on the Rh(111) surface being essential to promote CO2 methanation.
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Affiliation(s)
- Shijia Sun
- Kathleen
Lonsdale Materials Chemistry, Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
| | - Michael D. Higham
- Kathleen
Lonsdale Materials Chemistry, Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
- Research
Complex at Harwell, Rutherford Appleton
Laboratory, Harwell, Oxon OX11 0FA, United Kingdom
| | - Xingfan Zhang
- Kathleen
Lonsdale Materials Chemistry, Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
| | - C. Richard A. Catlow
- Kathleen
Lonsdale Materials Chemistry, Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
- Research
Complex at Harwell, Rutherford Appleton
Laboratory, Harwell, Oxon OX11 0FA, United Kingdom
- School
of Chemistry, Cardiff University, Park Place, Cardiff CF10 1AT, United
Kingdom
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4
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Werkovits A, Hollweger SB, Niederreiter M, Risse T, Cartus JJ, Sterrer M, Matera S, Hofmann OT. Kinetic Trapping of Charge-Transfer Molecules at Metal Interfaces. THE JOURNAL OF PHYSICAL CHEMISTRY. C, NANOMATERIALS AND INTERFACES 2024; 128:3082-3089. [PMID: 38414835 PMCID: PMC10895664 DOI: 10.1021/acs.jpcc.3c08262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 02/29/2024]
Abstract
Despite the common expectation that conjugated organic molecules on metals adsorb in a flat-lying layer, several recent studies have found coverage-dependent transitions to upright-standing phases, which exhibit notably different physical properties. In this work, we argue that from an energetic perspective, thermodynamically stable upright-standing phases may be more common than hitherto thought. However, for kinetic reasons, this phase may often not be observed experimentally. Using first-principles kinetic Monte Carlo simulations, we find that the structure with lower molecular density is (almost) always formed first, reminiscent of Ostwald's rule of stages. The phase transitions to the upright-standing phase are likely to be kinetically hindered under the conditions typically used in surface science. The simulation results are experimentally confirmed for the adsorption of tetracyanoethylene on Cu(111) using infrared and X-ray photoemission spectroscopy. Investigating both the role of the growth conditions and the energetics of the interface, we find that the time for the phase transition is determined mostly by the deposition rate and, thus, is mostly independent of the nature of the molecule.
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Affiliation(s)
- Anna Werkovits
- Institute
of Solid State Physics, Graz University of Technology, Petersgasse 16/II, 8010 Graz, Austria
| | - Simon B. Hollweger
- Institute
of Solid State Physics, Graz University of Technology, Petersgasse 16/II, 8010 Graz, Austria
| | - Max Niederreiter
- Institute
of Physics, University of Graz, Universitätsplatz 5, 8010 Graz, Austria
| | - Thomas Risse
- Institut
für Chemie und Biochemie, Freie Universität Berlin, Arminallee 22, 14195 Berlin, Germany
| | - Johannes J. Cartus
- Institute
of Solid State Physics, Graz University of Technology, Petersgasse 16/II, 8010 Graz, Austria
| | - Martin Sterrer
- Institute
of Physics, University of Graz, Universitätsplatz 5, 8010 Graz, Austria
| | - Sebastian Matera
- Theory
Department, Fritz Haber Institute of the
MPG, Faradayweg 4-6, 14195 Berlin-Dahlem, Germany
| | - Oliver T. Hofmann
- Institute
of Solid State Physics, Graz University of Technology, Petersgasse 16/II, 8010 Graz, Austria
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5
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Amini PM, Rouse I, Subbotina J, Lobaskin V. Multiscale modelling of biomolecular corona formation on metallic surfaces. BEILSTEIN JOURNAL OF NANOTECHNOLOGY 2024; 15:215-229. [PMID: 38379931 PMCID: PMC10877083 DOI: 10.3762/bjnano.15.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/16/2024] [Indexed: 02/22/2024]
Abstract
In the realm of food industry, the choice of non-consumable materials used plays a crucial role in ensuring consumer safety and product quality. Aluminum is widely used in food packaging and food processing applications, including dairy products. However, the interaction between aluminum and milk content requires further investigation to understand its implications. In this work, we present the results of multiscale modelling of the interaction between various surfaces, that is (100), (110), and (111), of fcc aluminum with the most abundant milk proteins and lactose. Our approach combines atomistic molecular dynamics, a coarse-grained model of protein adsorption, and kinetic Monte Carlo simulations to predict the protein corona composition in the deposited milk layer on aluminum surfaces. We consider a simplified model of milk, which is composed of the six most abundant milk proteins found in natural cow milk and lactose, which is the most abundant sugar found in dairy. Through our study, we ranked selected proteins and lactose adsorption affinities based on their corresponding interaction strength with aluminum surfaces and predicted the content of the naturally forming biomolecular corona. Our comprehensive investigation sheds light on the implications of aluminum in food processing and packaging, particularly concerning its interaction with the most abundant milk proteins and lactose. By employing a multiscale modelling approach, we simulated the interaction between metallic aluminum surfaces and the proteins and lactose, considering different crystallographic orientations. The results of our study provide valuable insights into the mechanisms of lactose and protein deposition on aluminum surfaces, which can aid in the general understanding of protein corona formation.
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Affiliation(s)
| | - Ian Rouse
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Julia Subbotina
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Vladimir Lobaskin
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
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6
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Yu H, Zhang L, Wang W, Yang K, Zhang Z, Liang X, Chen S, Yang S, Li J, Liu X. Lithium-ion battery multi-scale modeling coupled with simplified electrochemical model and kinetic Monte Carlo model. iScience 2023; 26:107661. [PMID: 37680483 PMCID: PMC10481351 DOI: 10.1016/j.isci.2023.107661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/13/2023] [Accepted: 08/15/2023] [Indexed: 09/09/2023] Open
Abstract
The multi-scale modeling of lithium-ion battery (LIB) is difficult and necessary due to its complexity. However, it is difficult to capture the aging behavior of batteries, and the coupling mechanism between multiple scales is still incomplete. In this paper, a simplified electrochemical model (SEM) and a kinetic Monte Carlo (KMC)-based solid electrolyte interphase (SEI) film growth model are used to study the multi-scale characteristics of LIBs. The single-particle SEM (SP-SEM) is described for macro scale, and a simple and self-consistent multi-particle SEM (MP-SEM) is developed. Then, the KMC-based SEI model is established for micro-scale molecular evolution. And, the two models are coupled to construct the full-cycle multi-scale model. After modeling, validation is performed by using a commercial 18650-type LIB. Finally, the effect of parameters on the SEI model is studied, including qualitative trend analysis and quantitative sensitivity analysis. The growth of SEI film with different particle sizes is studied by MP-SEM coupling simulation.
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Affiliation(s)
- Hanqing Yu
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Lisheng Zhang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Wentao Wang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Kaiyi Yang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Zhengjie Zhang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Xiang Liang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Siyan Chen
- College of Automotive Engineering, Jilin University, Changchun 130022, China
| | - Shichun Yang
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
| | - Junfu Li
- School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, China
| | - Xinhua Liu
- School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
- Dyson School of Design Engineering, Imperial College London, London SW7 2AZ, UK
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7
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Savva GD, Benson RL, Christidi IA, Stamatakis M. Exact distributed kinetic Monte Carlo simulations for on-lattice chemical kinetics: lessons learnt from medium- and large-scale benchmarks. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2023; 381:20220235. [PMID: 37211035 DOI: 10.1098/rsta.2022.0235] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/30/2023] [Indexed: 05/23/2023]
Abstract
Kinetic Monte Carlo (KMC) simulations have been instrumental in multiscale catalysis studies, enabling the elucidation of the complex dynamics of heterogeneous catalysts and the prediction of macroscopic performance metrics, such as activity and selectivity. However, the accessible length- and time-scales have been a limiting factor in such simulations. For instance, handling lattices containing millions of sites with 'traditional' sequential KMC implementations is prohibitive owing to large memory requirements and long simulation times. We have recently established an approach for exact, distributed, lattice-based simulations of catalytic kinetics which couples the Time-Warp algorithm with the Graph-Theoretical KMC framework, enabling the handling of complex adsorbate lateral interactions and reaction events within large lattices. In this work, we develop a lattice-based variant of the Brusselator system, a prototype chemical oscillator pioneered by Prigogine and Lefever in the late 60s, to benchmark and demonstrate our approach. This system can form spiral wave patterns, which would be computationally intractable with sequential KMC, while our distributed KMC approach can simulate such patterns 15 and 36 times faster with 625 and 1600 processors, respectively. The medium- and large-scale benchmarks thus conducted, demonstrate the robustness of the approach, and reveal computational bottlenecks that could be targeted in further development efforts. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.
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Affiliation(s)
- Giannis D Savva
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
| | - Raz L Benson
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
| | - Ilektra-Athanasia Christidi
- Research Software Development Group, Advanced Research Computing Centre, University College London, Gower Street, London WC1E 6BT, UK
| | - Michail Stamatakis
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
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8
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Kouroudis I, Gößwein M, Gagliardi A. Utilizing Data-Driven Optimization to Automate the Parametrization of Kinetic Monte Carlo Models. J Phys Chem A 2023. [PMID: 37421601 DOI: 10.1021/acs.jpca.3c02482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2023]
Abstract
Kinetic Monte Carlo (kMC) simulations are a popular tool to investigate the dynamic behavior of stochastic systems. However, one major limitation is their relatively high computational costs. In the last three decades, significant effort has been put into developing methodologies to make kMC more efficient, resulting in an enhanced runtime efficiency. Nevertheless, kMC models remain computationally expensive. This is in particular an issue in complex systems with several unknown input parameters where often most of the simulation time is required for finding a suitable parametrization. A potential route for automating the parametrization of kinetic Monte Carlo models arises from coupling kMC with a data-driven approach. In this work, we equip kinetic Monte Carlo simulations with a feedback loop consisting of Gaussian Processes (GPs) and Bayesian optimization (BO) to enable a systematic and data-efficient input parametrization. We utilize the results from fast-converging kMC simulations to construct a database for training a cheap-to-evaluate surrogate model based on Gaussian processes. Combining the surrogate model with a system-specific acquisition function enables us to apply Bayesian optimization for the guided prediction of suitable input parameters. Thus, the amount of trial simulation runs can be considerably reduced facilitating an efficient utilization of arbitrary kMC models. We showcase the effectiveness of our methodology for a physical process of growing industrial relevance: the space-charge layer formation in solid-state electrolytes as it occurs in all-solid-state batteries. Our data-driven approach requires only 1-2 iterations to reconstruct the input parameters from different baseline simulations within the training data set. Moreover, we show that the methodology is even capable of accurately extrapolating into regions outside the training data set which are computationally expensive for direct kMC simulation. Concluding, we demonstrate the high accuracy of the underlying surrogate model via a full parameter space investigation eventually making the original kMC simulation obsolete.
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Affiliation(s)
- Ioannis Kouroudis
- Department of Electrical and Computer Engineering, Technical University of Munich, Hans-Piloty-Strasse 1/III, 85748 Garching bei München, Germany
| | - Manuel Gößwein
- Department of Electrical and Computer Engineering, Technical University of Munich, Hans-Piloty-Strasse 1/III, 85748 Garching bei München, Germany
| | - Alessio Gagliardi
- Department of Electrical and Computer Engineering, Technical University of Munich, Hans-Piloty-Strasse 1/III, 85748 Garching bei München, Germany
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9
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Razdan NK, Lin TC, Bhan A. Concepts Relevant for the Kinetic Analysis of Reversible Reaction Systems. Chem Rev 2023; 123:2950-3006. [PMID: 36802557 DOI: 10.1021/acs.chemrev.2c00510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
The net rate of a reversible chemical reaction is the difference between unidirectional rates of traversal along forward and reverse reaction paths. In a multistep reaction sequence, the forward and reverse trajectories, in general, are not the microscopic reverse of one another; rather, each unidirectional route is comprised of distinct rate-controlling steps, intermediates, and transition states. Consequently, traditional descriptors of rate (e.g., reaction orders) do not reflect intrinsic kinetic information but instead conflate unidirectional contributions determined by (i) the microscopic occurrence of forward/reverse reactions (i.e., unidirectional kinetics) and (ii) the reversibility of reaction (i.e., nonequilibrium thermodynamics). This review aims to provide a comprehensive resource of analytical and conceptual tools which deconvolute the contributions of reaction kinetics and thermodynamics to disambiguate unidirectional reaction trajectories and precisely identify rate- and reversibility-controlling molecular species and steps in reversible reaction systems. The extrication of mechanistic and kinetic information from bidirectional reactions is accomplished through equation-based formalisms (e.g., De Donder relations) grounded in principles of thermodynamics and interpreted in the context of theories of chemical kinetics developed in the past 25 years. The aggregate of mathematical formalisms detailed herein is general to thermochemical and electrochemical reactions and encapsulates a diverse body of scientific literature encompassing chemical physics, thermodynamics, chemical kinetics, catalysis, and kinetic modeling.
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Affiliation(s)
- Neil K Razdan
- Department of Chemical Engineering and Materials Science, University of Minnesota─Twin Cities, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States
| | - Ting C Lin
- Department of Chemical Engineering and Materials Science, University of Minnesota─Twin Cities, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States
| | - Aditya Bhan
- Department of Chemical Engineering and Materials Science, University of Minnesota─Twin Cities, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States
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10
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Savva GD, Benson RL, Christidi IA, Stamatakis M. Large-scale benchmarks of the time-warp/graph-theoretical kinetic Monte Carlo approach for distributed on-lattice simulations of catalytic kinetics. Phys Chem Chem Phys 2023; 25:5468-5478. [PMID: 36748393 DOI: 10.1039/d2cp04424b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Motivated by the need to perform large-scale kinetic Monte Carlo (KMC) simulations, in the context of unravelling complex phenomena such as catalyst reconstruction and pattern formation, we extend the work of Ravipati et al. [S. Ravipati, G. D. Savva, I.-A. Christidi, R. Guichard, J. Nielsen, R. Réocreux and M. Stamatakis, Comput. Phys. Commun., 2022, 270, 108148] in benchmarking the performance of a distributed-computing, on-lattice KMC approach. The latter, implemented in our software package Zacros, combines the graph-theoretical KMC framework with the Time-Warp algorithm for parallel discrete event simulations, and entails dividing the lattice into subdomains, each assigned to a processor. The cornerstone of the Time-Warp algorithm is the state queue, to which snapshots of the simulation state are saved regularly, enabling historical KMC information to be corrected when conflicts occur at subdomain boundaries. Focusing on three model systems, we highlight the key Time-Warp parameters that can be tuned to optimise performance. The frequency of state saving, controlled by the state saving interval, δsnap, is shown to have the largest effect on performance, which favours balancing the overhead of re-simulating KMC history with that of writing state snapshots to memory. Also important is the global virtual time (GVT) computation interval, ΔτGVT, which has little direct effect on the progress of the simulation but controls how often the state queue memory can be freed up. We also find that pre-allocating memory for the state queue data structure favours performance. These findings will guide users in maximising the efficiency of Zacros or other distributed KMC software, which is a vital step towards realising accurate, meso-scale simulations of heterogeneous catalysis.
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Affiliation(s)
- Giannis D Savva
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK. .,Theory and Simulation of Materials (THEOS), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Raz L Benson
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
| | - Ilektra A Christidi
- Research Software Development Group, Advanced Research Computing Centre, University College London, Gower Street, London, WC1E 6BT, UK
| | - Michail Stamatakis
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
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11
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Dietze EM, Grönbeck H. Ensemble Effects in Adsorbate-Adsorbate Interactions in Microkinetic Modeling. J Chem Theory Comput 2023; 19:1044-1049. [PMID: 36652690 PMCID: PMC9933425 DOI: 10.1021/acs.jctc.2c01005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Adsorbates on a surface experience lateral interactions that result in a distribution of adsorption energies. The adsorbate-adsorbate interactions are known to affect the kinetics of surface reactions, which motivates efforts to develop models that accurately account for the interactions. Here, we use density functional theory (DFT) calculations combined with Monte Carlo simulations to investigate how the distribution of adsorbates affects adsorption and desorption of CO from Pt(111). We find that the mean of the average adsorption energy determines the adsorption process, whereas the desorption process can be described by the low energy part of the adsorbate stability distribution. The simulated results are in very good agreement with calorimetry and temperature-programmed desorption experiments and provide a guideline of how to include adsorbate-adsorbate interactions in DFT-based mean-field kinetic models.
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12
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Lee CH, Pahari S, Sitapure N, Barteau MA, Kwon JSI. DFT–kMC Analysis for Identifying Novel Bimetallic Electrocatalysts for Enhanced NRR Performance by Suppressing HER at Ambient Conditions Via Active-Site Separation. ACS Catal 2022. [DOI: 10.1021/acscatal.2c04797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Chi Ho Lee
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
- Texas A&M Energy Institute, College Station, Texas77843, United States
| | - Silabrata Pahari
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
- Texas A&M Energy Institute, College Station, Texas77843, United States
| | - Niranjan Sitapure
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
- Texas A&M Energy Institute, College Station, Texas77843, United States
| | - Mark A. Barteau
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
- Texas A&M Energy Institute, College Station, Texas77843, United States
| | - Joseph Sang-Il Kwon
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
- Texas A&M Energy Institute, College Station, Texas77843, United States
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13
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14
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Deimel M, Prats H, Seibt M, Reuter K, Andersen M. Selectivity Trends and Role of Adsorbate–Adsorbate Interactions in CO Hydrogenation on Rhodium Catalysts. ACS Catal 2022. [DOI: 10.1021/acscatal.2c02353] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Martin Deimel
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstraße 4, 85747 Garching, Germany
| | - Hector Prats
- Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, UK
| | - Michael Seibt
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstraße 4, 85747 Garching, Germany
| | - Karsten Reuter
- Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Mie Andersen
- Aarhus Institute of Advanced Studies, Aarhus University, 8000 Aarhus C, Denmark
- Center for Interstellar Catalysis, Department of Physics and Astronomy, Aarhus University, 8000 Aarhus C, Denmark
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15
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Gößwein M, Kaiser W, Gagliardi A. Local Temporal Acceleration Scheme to Couple Transport and Reaction Dynamics in Kinetic Monte Carlo Models of Electrochemical Systems. J Chem Theory Comput 2022; 18:2749-2763. [DOI: 10.1021/acs.jctc.1c01010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Manuel Gößwein
- Department of Electrical and Computer Engineering, Technical University of Munich, Karlstraße 45, 80333 Munich, Germany
| | - Waldemar Kaiser
- Department of Electrical and Computer Engineering, Technical University of Munich, Karlstraße 45, 80333 Munich, Germany
- Computational Laboratory for Hybrid/Organic Photovoltaics (CLHYO), Istituto CNR di Scienze e Tecnologie Chimiche “Giulio Natta” (CNR-SCITEC), 06123 Perugia, Italy
| | - Alessio Gagliardi
- Department of Electrical and Computer Engineering, Technical University of Munich, Karlstraße 45, 80333 Munich, Germany
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16
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Pineda M, Stamatakis M. Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges. J Chem Phys 2022; 156:120902. [DOI: 10.1063/5.0083251] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Kinetic Monte Carlo (KMC) simulations in combination with first-principles (1p)-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length scales and time scales over which heterogeneous catalysis unfolds. 1p-KMC simulations provide accurate insights into reactions over surfaces, a vital step toward the rational design of novel catalysts. In this Perspective, we briefly outline basic principles, computational challenges, successful applications, as well as future directions and opportunities of this promising and ever more popular kinetic modeling approach.
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Affiliation(s)
- M. Pineda
- Thomas Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, United Kingdom
| | - M. Stamatakis
- Thomas Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, United Kingdom
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17
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Li J, Maresi I, Lum Y, Ager JW. Effects of surface diffusion in electrocatalytic CO 2 reduction on Cu revealed by kinetic Monte Carlo simulations. J Chem Phys 2021; 155:164701. [PMID: 34717370 DOI: 10.1063/5.0068517] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Kinetic Monte Carlo (KMC) methods are frequently used for mechanistic studies of thermally driven heterogeneous catalysis systems but are underused for electrocatalysis. Here, we develop a lattice KMC approach for electrocatalytic CO2 reduction. The work is motivated by a prior experimental report that performed electroreduction of a mixed feed of 12CO2 and 13CO on Cu; differences in the 13C content of C2 products ethylene and ethanol (Δ13C) were interpreted as evidence of site selectivity. The lattice KMC model considers the effect of surface diffusion on this system. In the limit of infinitely fast diffusion (mean-field approximation), the key intermediates 12CO* and 13CO* would be well mixed on the surface and no evidence of site selectivity could have been observed. Using a simple two-site model and adapting a previously reported microkinetic model, we assess the effects of diffusion on the relative isotope fractions in the products using the estimated surface diffusion rate of CO* from literature reports. We find that the size of the active sites and the total surface adsorbate coverage can have a large influence on the values of Δ13C that can be observed. Δ13C is less sensitive to the CO* diffusion rate as long as it is within the estimated range. We further offer possible methods to estimate surface distribution of intermediates and to predict intrinsic selectivity of active sites based on experimental observations. This work illustrates the importance of considering surface diffusion in the study of electrochemical CO2 reduction to multi-carbon products. Our approach is entirely based on a freely available open-source code, so will be readily adaptable to other electrocatalytic systems.
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Affiliation(s)
- Jinghan Li
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ilaria Maresi
- Fung Institute, University of California Berkeley, Berkeley, California 94720, USA
| | - Yanwei Lum
- Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), 138632, Singapore
| | - Joel W Ager
- Joint Center for Artificial Photosynthesis, Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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18
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Wang Y, Kalscheur J, Su YQ, Hensen EJM, Vlachos DG. Real-time dynamics and structures of supported subnanometer catalysts via multiscale simulations. Nat Commun 2021; 12:5430. [PMID: 34521852 PMCID: PMC8440615 DOI: 10.1038/s41467-021-25752-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 08/18/2021] [Indexed: 02/08/2023] Open
Abstract
Understanding the performance of subnanometer catalysts and how catalyst treatment and exposure to spectroscopic probe molecules change the structure requires accurate structure determination under working conditions. Experiments lack simultaneous temporal and spatial resolution and could alter the structure, and similar challenges hinder first-principles calculations from answering these questions. Here, we introduce a multiscale modeling framework to follow the evolution of subnanometer clusters at experimentally relevant time scales. We demonstrate its feasibility on Pd adsorbed on CeO2(111) at various catalyst loadings, temperatures, and exposures to CO. We show that sintering occurs in seconds even at room temperature and is mainly driven by free energy reduction. It leads to a kinetically (far from equilibrium) frozen ensemble of quasi-two-dimensional structures that CO chemisorption and infrared experiments probe. CO adsorption makes structures flatter and smaller. High temperatures drive very rapid sintering toward larger, stable/metastable equilibrium structures, where CO induces secondary structure changes only.
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Affiliation(s)
- Yifan Wang
- Department of Chemical and Biomolecular Engineering, 150 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States
- Catalysis Center for Energy Innovation (CCEI), RAPID Manufacturing Institute, and Delaware Energy Institute (DEI), 221 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States
| | - Jake Kalscheur
- Department of Chemical and Biomolecular Engineering, 150 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States
- Catalysis Center for Energy Innovation (CCEI), RAPID Manufacturing Institute, and Delaware Energy Institute (DEI), 221 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States
| | - Ya-Qiong Su
- School of Chemistry, Xi'an Key Laboratory of Sustainable Energy Materials Chemistry, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China
- Laboratory of Inorganic Materials and Catalysis, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands
| | - Emiel J M Hensen
- Laboratory of Inorganic Materials and Catalysis, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands.
| | - Dionisios G Vlachos
- Department of Chemical and Biomolecular Engineering, 150 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States.
- Catalysis Center for Energy Innovation (CCEI), RAPID Manufacturing Institute, and Delaware Energy Institute (DEI), 221 Academy St., University of Delaware, Newark, Delaware, DE, 19716, United States.
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19
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Chen Z, Liu Z, Xu X. Coverage-Dependent Microkinetics in Heterogeneous Catalysis Powered by the Maximum Rate Analysis. ACS Catal 2021. [DOI: 10.1021/acscatal.1c01997] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Zheng Chen
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Zhangyun Liu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
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20
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Abstract
KIMERA is a scientific tool for the study of mineral dissolution. It implements a reversible Kinetic Monte Carlo (KMC) method to study the time evolution of a dissolving system, obtaining the dissolution rate and information about the atomic scale dissolution mechanisms. KIMERA allows to define the dissolution process in multiple ways, using a wide diversity of event types to mimic the dissolution reactions, and define the mineral structure in great detail, including topographic defects, dislocations, and point defects. Therefore, KIMERA ensures to perform numerous studies with great versatility. In addition, it offers a good performance thanks to its parallelization and efficient algorithms within the KMC method. In this manuscript, we present the code features and show some examples of its capabilities. KIMERA is controllable via user commands, it is written in object-oriented C++, and it is distributed as open-source software.
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21
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Ding C, Weng J, Shen T, Xu X. The enhanced extended phenomenological kinetics method to deal with timescale disparity problem among different reaction pathways. J Comput Chem 2020; 41:2115-2123. [PMID: 32618018 DOI: 10.1002/jcc.26374] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 05/29/2020] [Accepted: 06/02/2020] [Indexed: 11/10/2022]
Abstract
Kinetic Monte Carlo method can provide valuable mechanistic insights for catalytic systems. Nonetheless, it suffers from the notorious problem of timescale disparity due to the existence of the complex catalytic network that consists of fast events and slow events. Previously, we have proposed the extended phenomenological kinetics (XPK) method that effectively deals with the timescale disparity problem between diffusion and reaction. However, it remains a great challenge to simulate systems with timescale disparity among different reaction pathways, which is important when selectivity is the major concern. In this study, we implement the enhanced XPK method to address this problem. The new algorithm works by identifying states connected through fast transitions and compressing them into a "superstate" when the chosen states satisfy a local steadystate condition. This state compression algorithm simplifies the reaction network by concealing the fast transitions. The accuracy and efficiency of the algorithm are demonstrated by two model systems: selective catalytic hydrogenation and selective catalytic decomposition. The enhanced XPK method is expected to be beneficial to the kinetic simulations of catalytic systems, especially those with complex reaction networks.
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Affiliation(s)
- Chen Ding
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai, China
| | - Jingwei Weng
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai, China
| | - Tonghao Shen
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai, China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai, China
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22
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Ravipati S, d'Avezac M, Nielsen J, Hetherington J, Stamatakis M. A Caching Scheme To Accelerate Kinetic Monte Carlo Simulations of Catalytic Reactions. J Phys Chem A 2020; 124:7140-7154. [PMID: 32786994 DOI: 10.1021/acs.jpca.0c03571] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Kinetic Monte Carlo (KMC) simulations have been instrumental in advancing our fundamental understanding of heterogeneously catalyzed reactions, with particular emphasis on structure sensitivity, ensemble effects, and the interplay between adlayer structure and adsorbate-adsorbate lateral interactions in shaping the observed kinetics. Yet, the computational cost of KMC remains high, thereby motivating the development of acceleration schemes that would improve the simulation efficiency. We present an exact such scheme, which implements a caching algorithm along with shared-memory parallelization to improve the computational performance of simulations incorporating long-range adsorbate-adsorbate lateral interactions. This scheme is based on caching information about the energetic interaction patterns associated with the products of each possible lattice process (adsorption, desorption, reaction etc.). Thus, every time a reaction occurs ("ongoing reaction"), it enables fast updates of the rate constants of "affected reactions", i.e., possible reactions in the region of influence of the "ongoing reaction". Benchmarks on KMC simulations of NOx oxidation/reduction, yielded acceleration factors of up to 20, when comparing single-thread runs without caching to runs on 16 threads with caching, for simulations with a cluster expansion Hamiltonian that incorporates up to 8th-nearest-neighbor interactions.
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Affiliation(s)
- Srikanth Ravipati
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom
| | - Mayeul d'Avezac
- Research Software Development Group, Research IT Services, University College London, Torrington Place, London WC1E 6BT, United Kingdom
| | - Jens Nielsen
- Research Software Development Group, Research IT Services, University College London, Torrington Place, London WC1E 6BT, United Kingdom
| | - James Hetherington
- Research Software Development Group, Research IT Services, University College London, Torrington Place, London WC1E 6BT, United Kingdom
| | - Michail Stamatakis
- Thomas Young Centre and Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom
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23
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Kaiser W, Gößwein M, Gagliardi A. Acceleration scheme for particle transport in kinetic Monte Carlo methods. J Chem Phys 2020; 152:174106. [PMID: 32384840 DOI: 10.1063/5.0002289] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Kinetic Monte Carlo (kMC) simulations are frequently used to study (electro-)chemical processes within science and engineering. kMC methods provide insight into the interplay of stochastic processes and can link atomistic material properties with macroscopic characteristics. Significant problems concerning the computational demand arise if processes with large time disparities are competing. Acceleration algorithms are required to make slow processes accessible. Especially, the accelerated superbasin kMC (AS-kMC) scheme has been frequently applied within chemical reaction networks. For larger systems, the computational overhead of the AS-kMC is significant as the computation of the superbasins is done during runtime and comes with the need for large databases. Here, we propose a novel acceleration scheme for diffusion and transport processes within kMC simulations. Critical superbasins are detected during the system initialization. Scaling factors for the critical rates within the superbasins, as well as a lower bound for the number of sightings, are derived. Our algorithm exceeds the AS-kMC in the required simulation time, which we demonstrate with a 1D-chain example. In addition, we apply the acceleration scheme to study the time-of-flight (TOF) of charge carriers within organic semiconductors. In this material class, time disparities arise due to a significant spread of transition rates. The acceleration scheme allows a significant acceleration up to a factor of 65 while keeping the error of the TOF values negligible. The computational overhead is negligible, as all superbasins only need to be computed once.
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Affiliation(s)
- Waldemar Kaiser
- Department of Electrical and Computer Engineering, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
| | - Manuel Gößwein
- Department of Electrical and Computer Engineering, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
| | - Alessio Gagliardi
- Department of Electrical and Computer Engineering, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
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24
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Cao XM, Shao ZJ, Hu P. A fast species redistribution approach to accelerate the kinetic Monte Carlo simulation for heterogeneous catalysis. Phys Chem Chem Phys 2020; 22:7348-7364. [PMID: 32211648 DOI: 10.1039/d0cp00554a] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The first-principles kinetic Monte Carlo (kMC) simulation has been demonstrated as a reliable multiscale modeling approach in silico to disclose the interplay among all the elementary steps in a complex reaction network for heterogeneous catalysis. Heterogeneous catalytic systems frequently contain fast surface diffusion processes of some adsorbates while the elementary steps in it would be much slower than those in fast diffusion. Consequently, the kMC simulation for these systems is easily trapped in the sub-basins of a super basin on a potential energy surface due to the continuous and repeated sampling of these fast processes, which would significantly increase the total accessible simulation time and even make it impossible to get the reasonable simulation results using the kMC simulation. In this work, we present an improved fast species redistribution (FSR) method for the kMC simulation to overcome the stiffness problem resulting from the low-barrier surface diffusion to accelerate the heterogeneous catalytic kMC simulation. Taking CO oxidations on Pt(111) and Pt(100) as examples, we demonstrate that the FSR approach can properly reproduce the results of an equivalent first-principles microkinetic model simulation with more reasonable reaction rates. The improved kMC simulation based on the FSR method can accurately incorporate the effect of the fast diffusion of species on the surface and provide several orders of magnitude of acceleration compared to the standard kMC simulation.
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Affiliation(s)
- Xiao-Ming Cao
- Key Laboratory for Advanced Materials, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P. R. China.
| | - Zheng-Jiang Shao
- Key Laboratory for Advanced Materials, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P. R. China.
| | - P Hu
- Key Laboratory for Advanced Materials, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P. R. China. and School of Chemistry and Chemical Engineering, The Queen's University of Belfast, Belfast BT9 5AG, UK
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25
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Liu J, Tan L, Huang L, Wang Q, Liu Y. Kinetic Monte Carlo Modeling for the NO-CO Reaction Mechanism on Rh(100) and Rh(111). LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2020; 36:3127-3140. [PMID: 32075370 DOI: 10.1021/acs.langmuir.9b03720] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The NO-CO reaction on Rh(100) and Rh(111) is a prototypical catalytic system with various practical applications, including the treatment of automotive gas exhausts. With parameters derived from first-principles calculations, the Brønsted-Evans-Polanyi (BEP) relation for the reaction steps of NO-CO on Rh(100) and Rh(111) surfaces is fitted, which is more accurate and practical for the calculation of the effect of interaction between adsorbates on activation energy compared to the basic BEP relation. Further, a kinetic Monte Carlo (kMC) model for the NO-CO reaction systems on Rh(100) and Rh(111) is constructed for the exploration of the system's reaction mechanism. Besides the temperature and pressure, the coverage and activation sites are essential factors for reaction kinetic of the NO-CO reaction system. Our results are beneficial for designing more efficient, economical, and environmentally friendly next-generation catalysts.
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Affiliation(s)
- Jiangyue Liu
- Department of Chemistry, Zhejiang University, Hangzhou 310027, People's Republic of China
| | - Lu Tan
- Department of Chemistry, Zhejiang University, Hangzhou 310027, People's Republic of China
| | - Liangliang Huang
- School of Chemical, Biological & Materials Engineering, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Qi Wang
- Department of Chemistry, Zhejiang University, Hangzhou 310027, People's Republic of China
| | - Yingchun Liu
- Department of Chemistry, Zhejiang University, Hangzhou 310027, People's Republic of China
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26
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Dynamic vs static behaviour of a supported nanoparticle with reaction-induced catalytic sites in a lattice model. Sci Rep 2020; 10:2882. [PMID: 32076083 PMCID: PMC7031362 DOI: 10.1038/s41598-020-59739-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 02/03/2020] [Indexed: 11/08/2022] Open
Abstract
Modern literature shows a rapidly growing interest to the supported nanocatalysts with dynamic behaviour under reaction conditions. This new frontier of heterogeneous catalysis is recognized as one of the most challenging and worthy of consideration from all possible angles. In this context, a previously suggested lattice model is used to get an insight, by means of kinetic Monte Carlo, into the influence of the mobility of reaction-induced catalytic sites of a two-dimensional supported nanoparticle on the system behaviour. The results speak in favour of feasibility of dynamic nanocatalysts with self-organized structures capable of robust functioning. This approach, from the macroscopic end, is believed to be a useful complement to ever developing experimental and first principle approaches.
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27
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Chutia A, Thetford A, Stamatakis M, Catlow CRA. A DFT and KMC based study on the mechanism of the water gas shift reaction on the Pd(100) surface. Phys Chem Chem Phys 2020; 22:3620-3632. [PMID: 31995067 DOI: 10.1039/c9cp05476f] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We present a combined density functional theory (DFT) and Kinetic Monte Carlo (KMC) study of the water gas shift (WGS) reaction on the Pd(100) surface. We propose a mechanism comprising both the redox and the associative pathways for the WGS within a single framework, which consists of seven core elementary steps, which in turn involve splitting of a water molecule followed by the production of an H-atom and an OH-species on the Pd(100) surface. In the following steps, these intermediates then recombine with each other and with CO leading to the evolution of CO2, and H2. Seven other elementary steps, involving the diffusion and adsorption of the surface intermediate species are also considered for a complete description of the mechanism. The geometrical and electronic properties of each of the reactants, products, and the transition states of the core elementary steps are presented. We also discuss the analysis of Bader charges and spin densities for the reactants, transition states and the products of these elementary steps. Our study indicates that the WGS reaction progresses simultaneously via the direct oxidation and the carboxyl paths on the Pd(100) surface.
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Affiliation(s)
- Arunabhiram Chutia
- School of Chemistry, Brayford Pool, University of Lincoln, Lincoln, LN6 7TS, UK. and UK Catalysis Hub, RCaH, Rutherford Appleton Laboratory, Didcot, OX11 OFA, UK
| | - Adam Thetford
- UK Catalysis Hub, RCaH, Rutherford Appleton Laboratory, Didcot, OX11 OFA, UK and Department of Chemistry, University of Manchester, UK and Department of Chemistry, University College London, Gordon Street, London, WC1H 0AJ, UK.
| | - Michail Stamatakis
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - C Richard A Catlow
- UK Catalysis Hub, RCaH, Rutherford Appleton Laboratory, Didcot, OX11 OFA, UK and Department of Chemistry, University College London, Gordon Street, London, WC1H 0AJ, UK. and Cardiff Catalysis Institute, School of Chemistry, Cardiff University, Cardiff, CF10 3AT, UK
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28
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Adsorption of CO and desorption of CO2 interacting with Pt (111) surface: a combined density functional theory and Kinetic Monte Carlo simulation. ADSORPTION 2020. [DOI: 10.1007/s10450-020-00202-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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29
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Huš M, Grilc M, Pavlišič A, Likozar B, Hellman A. Multiscale modelling from quantum level to reactor scale: An example of ethylene epoxidation on silver catalysts. Catal Today 2019. [DOI: 10.1016/j.cattod.2019.05.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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30
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Mechanistic study of site blocking catalytic deactivation through accelerated kinetic Monte Carlo. J Catal 2019. [DOI: 10.1016/j.jcat.2019.08.029] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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31
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Martin P, Manzano H, Dolado JS. Mechanisms and Dynamics of Mineral Dissolution: A New Kinetic Monte Carlo Model. ADVANCED THEORY AND SIMULATIONS 2019. [DOI: 10.1002/adts.201900114] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Pablo Martin
- Building Technologies Division TecnaliaParque Tecnológico de BizkaiaAstondo Bidea, Edificio 700 CP 48160 Derio Bizkaia Spain
| | - Hegoi Manzano
- Department of Condensed Matter PhysicsUniversity of the Basque Country UPV/EHUBarrio Sarriena s/n 48940 Leioa Bizkaia Spain
| | - Jorge S. Dolado
- Materials Physics Center ‐ Centro de Física de Materiales CSIC‐UPV/EHUPaseo Manuel de Lardizabal, 5 20018 San Sebastian Spain
- Donostia International Physics CenterPaseo Manuel Lardizabal 3 20018 San Sebastián Spain
- Faculty of Civil Engineering and GeosciencesDelft University of TechnologyStevinweg 1 2628 CN Delft The Netherlands
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32
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Affiliation(s)
- Mikkel Jørgensen
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Henrik Grönbeck
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
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33
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Matera S, Schneider WF, Heyden A, Savara A. Progress in Accurate Chemical Kinetic Modeling, Simulations, and Parameter Estimation for Heterogeneous Catalysis. ACS Catal 2019. [DOI: 10.1021/acscatal.9b01234] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Sebastian Matera
- Fachbereich Mathematik and Informatik, Freie Universität, 14195 Berlin, Germany
| | - William F. Schneider
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Andreas Heyden
- Department of Chemical Engineering, University of South Carolina, Columbia, South Carolina 29208, United States
| | - Aditya Savara
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
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34
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Jørgensen M, Grönbeck H. Selective Acetylene Hydrogenation over Single-Atom Alloy Nanoparticles by Kinetic Monte Carlo. J Am Chem Soc 2019; 141:8541-8549. [DOI: 10.1021/jacs.9b02132] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Mikkel Jørgensen
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Henrik Grönbeck
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
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35
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Andersen M, Panosetti C, Reuter K. A Practical Guide to Surface Kinetic Monte Carlo Simulations. Front Chem 2019; 7:202. [PMID: 31024891 PMCID: PMC6465329 DOI: 10.3389/fchem.2019.00202] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/15/2019] [Indexed: 11/26/2022] Open
Abstract
This review article is intended as a practical guide for newcomers to the field of kinetic Monte Carlo (KMC) simulations, and specifically to lattice KMC simulations as prevalently used for surface and interface applications. We will provide worked out examples using the kmos code, where we highlight the central approximations made in implementing a KMC model as well as possible pitfalls. This includes the mapping of the problem onto a lattice and the derivation of rate constant expressions for various elementary processes. Example KMC models will be presented within the application areas surface diffusion, crystal growth and heterogeneous catalysis, covering both transient and steady-state kinetics as well as the preparation of various initial states of the system. We highlight the sensitivity of KMC models to the elementary processes included, as well as to possible errors in the rate constants. For catalysis models in particular, a recurrent challenge is the occurrence of processes at very different timescales, e.g., fast diffusion processes and slow chemical reactions. We demonstrate how to overcome this timescale disparity problem using recently developed acceleration algorithms. Finally, we will discuss how to account for lateral interactions between the species adsorbed to the lattice, which can play an important role in all application areas covered here.
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Affiliation(s)
- Mie Andersen
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Garching, Germany
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36
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Shen TH, Xu X. The XPK package: A comparison between the extended phenomenological kinetic (XPK) method and the conventional kinetic Monte Carlo (KMC) method. CHINESE J CHEM PHYS 2019. [DOI: 10.1063/1674-0068/cjcp1901013] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Tong-hao Shen
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Laboratory for Computational Physical Science, Department of Chemistry, Fudan University, Shanghai 200438, China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Laboratory for Computational Physical Science, Department of Chemistry, Fudan University, Shanghai 200438, China
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37
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Ji J, Lu Z, Lei Y, Turner CH. Mechanistic insights into the direct propylene epoxidation using Au nanoparticles dispersed on TiO2/SiO2. Chem Eng Sci 2018. [DOI: 10.1016/j.ces.2018.06.064] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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38
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Jørgensen M, Grönbeck H. MonteCoffee: A programmable kinetic Monte Carlo framework. J Chem Phys 2018; 149:114101. [DOI: 10.1063/1.5046635] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Affiliation(s)
- Mikkel Jørgensen
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Henrik Grönbeck
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
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39
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Savara A, Sutton JE. SQERT-T: alleviating kinetic Monte Carlo (KMC)-stiffness in transient KMC simulations. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2018; 30:295901. [PMID: 29882745 DOI: 10.1088/1361-648x/aacb6d] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Lattice based kinetic Monte Carlo (KMC) is often used for simulating the dynamics of systems at a supramolecular scale, based on molecular scale transitions. A common challenge in KMC simulations is rapid 'back-and-forth' reactions, which dominate the events executed during simulations and inhibit the ability for simulations to reach longer time scales. Such processes are fast frivolous processes (FFPs) and are one manifestation of a phenomenon referred to as KMC-stiffness. Here, an algorithm for staggered quasi-equilibrium rank-based throttling geared towards transient kinetics (SQERT-T) is presented. Within the SQERT-T methodology, a pace-restrictor reaction and an FFP floor are utilized along with throttling of the process transition rate constants to accelerate the KMC simulations while still retaining sufficient time resolution for sampling of the data. KMC simulations were performed for CO oxidation over RuO2(1 1 0) and over RuO2(1 1 1), and the results were compared to experimental data obtained using RuO2 powders. The experiments and simulations were for transient conditions: the system was subjected to a temperature program which included temperatures in the range of 363 to 453 K. The timescales that were achieved during the KMC simulations in this study would not have been accessible without KMC acceleration, and were enabled by the use of SQERT-T.
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Affiliation(s)
- Aditya Savara
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States of America
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40
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Andersen M, Plaisance CP, Reuter K. Assessment of mean-field microkinetic models for CO methanation on stepped metal surfaces using accelerated kinetic Monte Carlo. J Chem Phys 2018; 147:152705. [PMID: 29055323 DOI: 10.1063/1.4989511] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
First-principles screening studies aimed at predicting the catalytic activity of transition metal (TM) catalysts have traditionally been based on mean-field (MF) microkinetic models, which neglect the effect of spatial correlations in the adsorbate layer. Here we critically assess the accuracy of such models for the specific case of CO methanation over stepped metals by comparing to spatially resolved kinetic Monte Carlo (kMC) simulations. We find that the typical low diffusion barriers offered by metal surfaces can be significantly increased at step sites, which results in persisting correlations in the adsorbate layer. As a consequence, MF models may overestimate the catalytic activity of TM catalysts by several orders of magnitude. The potential higher accuracy of kMC models comes at a higher computational cost, which can be especially challenging for surface reactions on metals due to a large disparity in the time scales of different processes. In order to overcome this issue, we implement and test a recently developed algorithm for achieving temporal acceleration of kMC simulations. While the algorithm overall performs quite well, we identify some challenging cases which may lead to a breakdown of acceleration algorithms and discuss possible directions for future algorithm development.
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Affiliation(s)
- Mie Andersen
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstr. 4, D-85747 Garching, Germany
| | - Craig P Plaisance
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstr. 4, D-85747 Garching, Germany
| | - Karsten Reuter
- Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstr. 4, D-85747 Garching, Germany
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41
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Chen Z, Wang H, Su NQ, Duan S, Shen T, Xu X. Beyond Mean-Field Microkinetics: Toward Accurate and Efficient Theoretical Modeling in Heterogeneous Catalysis. ACS Catal 2018. [DOI: 10.1021/acscatal.8b00943] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Zheng Chen
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - He Wang
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Neil Qiang Su
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Sai Duan
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Tonghao Shen
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai, Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, People’s Republic of China
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42
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Hareli C, Caspary Toroker M. Water Oxidation Catalysis for NiOOH by a Metropolis Monte Carlo Algorithm. J Chem Theory Comput 2018; 14:2380-2385. [DOI: 10.1021/acs.jctc.7b01214] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Chen Hareli
- Department of Materials Science and Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Maytal Caspary Toroker
- Department of Materials Science and Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
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43
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Hoffmann MJ, Bligaard T. A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies. J Chem Theory Comput 2018; 14:1583-1593. [PMID: 29357239 DOI: 10.1021/acs.jctc.7b00683] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Mean-field microkinetic models in combination with Brønsted-Evans-Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the "fruit fly" example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants. As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate-adsorbate interactions have a significant influence on the mixing of the adsorbates.
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Affiliation(s)
- Max J Hoffmann
- Department of Chemical Engineering , Stanford University , Stanford , California 94305 , United States.,SUNCAT Center for Interface Science and Catalysis, SLAC , National Accelerator Laboratory , 2575 Sand Hill Road , Menlo Park , California 94025 , United States
| | - Thomas Bligaard
- Department of Chemical Engineering , Stanford University , Stanford , California 94305 , United States.,SUNCAT Center for Interface Science and Catalysis, SLAC , National Accelerator Laboratory , 2575 Sand Hill Road , Menlo Park , California 94025 , United States
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44
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Turner CH, Ji J, Lu Z, Lei Y. Analysis of the propylene epoxidation mechanism on supported gold nanoparticles. Chem Eng Sci 2017. [DOI: 10.1016/j.ces.2017.09.018] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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45
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Núñez M, Robie T, Vlachos DG. Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling. J Chem Phys 2017; 147:164103. [DOI: 10.1063/1.4998926] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- M. Núñez
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
| | - T. Robie
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
| | - D. G. Vlachos
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
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46
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Jørgensen M, Grönbeck H. Scaling Relations and Kinetic Monte Carlo Simulations To Bridge the Materials Gap in Heterogeneous Catalysis. ACS Catal 2017. [DOI: 10.1021/acscatal.7b01194] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Mikkel Jørgensen
- Department of Physics and
Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Henrik Grönbeck
- Department of Physics and
Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden
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