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

TL;DR

This paper introduces a new flexible pattern-recognition scheme for off-lattice kinetic Monte Carlo simulations, enabling accurate identification of local atomic environments across various surfaces, demonstrated through Cu surface decay and diffusion studies.

Contribution

A novel off-lattice pattern-recognition method that can be applied to all surface types, improving identification of atomic processes in kinetic Monte Carlo simulations.

Findings

Effective in identifying local environments for 3D atomic motion

Applied successfully to Cu island decay and diffusion

Achieved comparable or improved computational efficiency

Abstract

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.