SLKMC-II study of self-diffusion of small Ni clusters on Ni (111) surface

TL;DR

This study uses an advanced self-learning kinetic Monte Carlo method to analyze how small nickel clusters diffuse on a nickel (111) surface, revealing dominant concerted diffusion mechanisms and providing detailed diffusion coefficients and energy barriers.

Contribution

The paper introduces an improved SLKMC-II simulation approach that includes both fcc and hcp sites, enabling detailed analysis of diffusion processes for small Ni clusters.

Findings

Diffusion primarily occurs via concerted processes.

Diffusion coefficients vary with cluster size and temperature.

New multi-atom processes were identified that previous methods could not access.

Abstract

We studied self-diffusion of small 2D Ni islands (consisting of up to 10 atoms) on Ni (111) surface using a self-learning kinetic Monte Carlo (SLKMC-II) method with an improved pattern-recognition scheme that allows inclusion of both fcc and hcp sites in the simulations. In an SLKMC simulation, a database holds information about the local neighborhood of an atom and associated processes that is accumulated on-the-fly as the simulation proceeds. In this study, these diffusion processes were identified using the drag method, and their activation barriers calculated using a semi-empirical interaction potential based on the embedded-atom method. Although a variety of concerted, multi-atom and single-atom processes were automatically revealed in our simulations, we found that these small islands diffuse primarily via concerted diffusion processes. We report diffusion coefficients for each island size at various tepmratures, the effective energy barrier for islands of each size and the processes most responsible for diffusion of islands of various sizes, including concerted and multi-atom processes that are not accessible under SLKMC-I or in short time-scale MD simulations.