Off-lattice pattern recognition scheme for kinetic Monte Carlo simulations

    Authors

    G. Nandipati; A. Kara; S. I. Shah;T. S. Rahman

    Comments

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    Abbreviated Journal Title

    J. Comput. Phys.

    Keywords

    Self learning; Off lattice; Kinetic Monte Carlo; Pattern recognition; Surface diffusion; Thin film growth; EPITAXIAL-GROWTH; MOLECULAR-DYNAMICS; DIFFUSION; SURFACES; CU(100); GE; CU; Computer Science, Interdisciplinary Applications; Physics, Mathematical

    Abstract

    We report the development of a pattern-recognition scheme for the off-lattice self-learning kinetic Monte Carlo (KMC) method, one that is simple and flexible enough that it can be applied to all types of surfaces. In this scheme, to uniquely identify the local environment and associated processes involving three-dimensional (3D) motion of an atom or atoms, space around a central atom is divided into 3D rectangular boxes. The dimensions and the number of 3D boxes are determined by the accuracy with which a process needs to be identified and a process is described as the central atom moving to a neighboring vacant box accompanied by the motion of any other atom or atoms in its surrounding boxes. As a test of this method to we apply it to examine the decay of 3D Cu islands on the Cu(100) and to the surface diffusion of a Cu monomer and a dimer on Cu(111) and compare the results and computational efficiency to those available in the literature. (C) 2012 Elsevier Inc. All rights reserved.

    Journal Title

    Journal of Computational Physics

    Volume

    231

    Issue/Number

    9

    Publication Date

    1-1-2012

    Document Type

    Article

    Language

    English

    First Page

    3548

    Last Page

    3560

    WOS Identifier

    WOS:000302501500004

    ISSN

    0021-9991

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