Self-Learning Kinetic Monte Carlo Simulations Of Self-Diffusion Of Small Ag Islands On The Ag(111) Surface

Keywords

Ag island diffusion; self-diffusion; self-learning kinetic Monte Carlo

Abstract

We studied self-diffusion of small two-dimensional Ag islands, containing up to ten atoms, on the Ag(111) surface using self-learning kinetic Monte Carlo (SLKMC) simulations. Activation barriers are calculated using the semi-empirical embedded atom method (EAM) potential. We find that two- to seven-atom islands primarily diffuse via concerted translation processes with small contributions from multi-atom and single-atom processes, while eight- to ten-atom islands diffuse via single-atom processes, especially edge diffusion, corner rounding and kink detachment, along with a minimal contribution from concerted processes. For each island size, we give a detailed description of the important processes, and their activation barriers, responsible for its diffusion.

Publication Date

1-20-2016

Publication Title

Journal of Physics Condensed Matter

Volume

28

Issue

2

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1088/0953-8984/28/2/025001

Socpus ID

84950241794 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84950241794

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