Off-lattice Pattern Recognition Scheme for Kinetic Monte Carlo

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 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, 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 central atom moving to a neighboring vacant box accompanied by the motion of any other atom or atoms in its sur-rounding boxes. As a test of this method we apply it to 3D Cu island decay on the Cu(100) surface and to 2D diffusion of a Cu monomer and a dimer on the (111) surface, and results and computational efficiency to those available in the literature. 1