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arXiv 1109.0924cond-mat.mtrl-sciphysics.comp-ph
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非格点动力学蒙特卡罗模拟的非格点模式识别新方法

New off-lattice Pattern Recognition Scheme for off-lattice kinetic Monte Carlo Simulations

Giridhar Nandipati, Abdelkader Kara, Syed Islamuddin Shah, Talat S. Rahman

摘要:

我们报告了一个新的模式识别计划的非格点自学习动力学蒙特卡罗(KMC)方法,是简单和灵活的,它可以适用于所有类型的表面的发展。在该方案中,为了唯一地识别局部环境和涉及一个或多个原子的三维(3D)运动的相关过程,围绕中心原子或引导原子的3D空间被划分成3D矩形框。3D框的尺寸和数量由网格的类型和过程需要被识别的准确度来确定。作为该方法的一个测试,我们提出了应用离格KMC与模式识别方案的3D Cu岛衰变的Cu(100)表面和二维扩散的Cu(111)表面上的Cu单体和二聚体。我们比较的结果和计算效率,在文献中。

英文摘要:

We report the development of a new pattern-recognition scheme for the off- lattice self-learning kinetic Monte Carlo (KMC) method that is simple and flex ible 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, 3D space around a central atom or leading atom is divided into 3D rectangular boxes. The dimensions and the number of 3D boxes are determined by the type of the lattice and by the ac- curacy with which a process needs to be identified. As a test of this method we present the application of off-lattice KMC with the pattern-recognition scheme to 3D Cu island decay on the Cu(100) surface and to 2D diffusion of a Cu monomer and a dimer on the Cu (111) surface. We compare the results and computational efficiency to those available in the literature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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