Off-Lattice Kinetic Monte Carlo Methods

Trochet, Mickaël; Mousseau, Normand; Béland, Laurent Karim; Henkelman, Graeme

doi:10.1007/978-3-319-42913-7_29-2

Cited by 6 publications

(8 citation statements)

References 74 publications

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“…Adaptive KMC methods, which automatically construct reaction mechanisms on-the-fly during the simulation can help alleviate this problem. , The adaptive KMC method leverages on automated saddle point searches using, for example, the dimer method, metadynamics, , and high temperature MD simulations. Adaptive KMC methods are also suitable for enabling higher fidelity off-lattice simulations, which are crucial for studying lattice reconstructions. , …”

Section: First-principles-based Microkinetic Modeling For Heterogeneo...mentioning

confidence: 92%

“…However, we envision that KMC simulations that treat the dynamics of the catalyst surface as kinetic events on the same level as the chemical transformations of reaction intermediates will help yield significant insights into the interplay between the dynamic catalyst surface and adsorbates. While adapting on-lattice methods to treat lattice reconstructions may be initially cost-effective, it will be necessary to gradually move toward more computationally intensive off-lattice methods to accommodate the wide range of possible particle transformations and reconstructions in real catalytic processes. , …”

Section: First-principles-based Microkinetic Modeling For Heterogeneo...mentioning

confidence: 99%

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Computational Methods in Heterogeneous Catalysis

2020

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The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

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Section: First-principles-based Microkinetic Modeling For Heterogeneo...mentioning

confidence: 92%

Section: First-principles-based Microkinetic Modeling For Heterogeneo...mentioning

confidence: 99%

Computational Methods in Heterogeneous Catalysis

2020

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“…AMC-KMC works well with and without time scale separation and has been implemented in the software package EON for off-lattice (adaptive or OTF) KMC simulations. 43,[166][167][168][169][170][171] However, a downside of this approach is that the matrix operations can become computationally intensive when dealing with large Markov matrices (i.e., large superbasins). Moreover, the method does not explicitly specify how to group states to form a superbasin.…”

Section: Treating Event Frequency Disparitymentioning

confidence: 99%

“…The so-called off-lattice or adaptive KMC approach could in principle be useful for this purpose. 170 However, its implementation is currently computationally too expensive. A boost to solve this challenge could also be provided by integrating machine learning approaches into the 1p-KMC-based multiscale modeling framework.…”

Section: Future Challengesmentioning

confidence: 99%

Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges

Pineda

Stamatakis

2022

The Journal of Chemical Physics

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Kinetic Monte Carlo (KMC) simulations in combination with first-principles-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length and time-scales over which heterogeneous catalysis unfolds. First-principles KMC (1p-KMC) simulations provide accurate insights into reactions over surfaces, a vital step towards the rational design of novel catalysts. In this perspective article, 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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“…Several KMC methods are available and are implemented depending on the investigated time and space scales. Atomistic kinetic Monte Carlo (AKMC) methods monitor the positions of all atoms on the lattice [8][9][10] or over the space [11,12]. The variant method is commonly known as object kinetic Monte Carlo (OKMC), rather simulate diffusing entities like defect-solute clusters [13].…”

Section: Introductionmentioning

confidence: 99%

Absorption kinetics of vacancies by cavities in Aluminum: numerical characterization of sink strengths and first-passage statistics through Krylov subspace projection and eigenvalue deflation

Kaur,

Athènes,

Creuze

2021

Preprint

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Modeling the microstructural evolution of metal and alloys, specifically under irradiation, is essential to predict the aging properties of materials. Many models are based on a transition rate matrix describing the jump frequencies of defects and involve a master equation governing the time evolution of a state probability vector. Here, we present non-stochastic numerical techniques to characterize the motion of individual defects migrating over long distances prior to recombining or being absorbed by another defect, resorting to the theory of absorbing Markov chains. These important events are fully determined by their first-passage time distribution to distant locations, no-passage distribution ,and walker fluxes to the sinks. We show that these functions can be efficiently computed using a method combining Krylov subspace projection and eigenvalue deflation. For a model system describing the absorption of a vacancy by a cavity in aluminum, the use of a small Krylov subspace deflated by the unique eigenmode corresponding to the quasi-stationary distribution is sufficient to capture the kinetics of the defect absorption faithfully. This method can be used in kinetic Monte Carlo simulations to perform stochastic non-local moves or in cluster dynamics simulations to compute sink strengths.

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Off-Lattice Kinetic Monte Carlo Methods

Cited by 6 publications

References 74 publications

Computational Methods in Heterogeneous Catalysis

Computational Methods in Heterogeneous Catalysis

Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges

Absorption kinetics of vacancies by cavities in Aluminum: numerical characterization of sink strengths and first-passage statistics through Krylov subspace projection and eigenvalue deflation

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