Syed Islamuddin Shah

Off-lattice pattern recognition scheme for kinetic Monte Carlo simulations

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

Self-diffusion of small Ni clusters on the Ni(111) surface: A self-learning kinetic Monte Carlo study

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, multiatom 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 multiatom processes that are not accessible under SLKMC-I or in short time-scale MD simulations.

Self-learning kinetic Monte Carlo simulations of self-diffusion of small Ag islands on the Ag(111) surface.

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.

Island-size selectivity during 2D Ag island coarsening on Ag(111)

We report on the early stages of submonolayer Ag island coarsening on the Ag(111) surface carried out using kinetic Monte Carlo simulations for several temperatures. Our simulations were performed using a very large database of processes identified by their local environment and whose activation barriers were calculated using the semi-empirical interaction potentials based on the embedded-atom method. We find that during the early stages, coarsening proceeds as a sequence of selected island sizes, creating peaks and valleys in the island-size distribution. This island-size selectivity is independent of initial conditions and results from the formation of kinetically stable islands for certain sizes as dictated by the relative energetics of edge atom detachment/attachment processes together with the large activation barrier for kink detachment. Our results indicate that by tuning the growth temperature it is possible to enhance the island-size selectivity.

Kinetically driven shape changes in early stages of two-dimensional island coarsening: Ag/Ag(111)

In our earlier study of Ag island coarsening on Ag(111) surface using kinetic Monte Carlo (KMC) simulations we found that during early stages coarsening proceeds as a sequence of selected island sizes resulting in peaks and valleys in the island-size distribution.1, and that this selectivity is independent of initial conditions and dictated instead by the relative energetics of edge-atom diffusion and detachment/attachment processes and by the large activation barrier for kink detachment. In this paper we present a detailed analysis of the shapes of various island sizes observed during these KMC simulations and show that selectivity is due to the formation of kinetically stable island shapes which survive longer than non-selected sizes, which decay into nearby selected sizes. The stable shapes have a closed-shell structure one in which every atom on the periphery having at least three nearest neighbors. Our KMC simulations were carried out using a very large database of processes identified by each atom’s unique local environment, the activation barriers of which were calculated using semi-empirical interaction potentials based on the embedded-atom method. PACS numbers: 68.35.Fx, 68.43.Jk,81.15.Aa,68.37.-d 1 ar X iv :1 21 1. 07 40 v1 [ co nd -m at .m tr lsc i] 5 N ov 2 01 2