Toward multiscale modeling of thin-film growth processes using SLKMC


The self-learning kinetic Monte Carlo method has been shown to be suitable for examining the temporal and spatial evolution of adatom islands on the (111) surface of several fcc metals, unbiased by diffusion processes chosen a priori. A pattern-recognition scheme and a diffusion path finder scheme enable collection of a large database of diffusion processes and their energetics. A variety of mechanisms involving single and multiple atoms, and concerted island motion are uncovered in long-time simulations. In this contribution, after reviewing the methodology, we present results comparing the diffusion kinetics of two sets of homo-epitaxial and hetero-epitaxial systems: small (2–8 atom) Pd and Ag islands on the respective (111) surfaces and small Cu islands on Ni(111) and Ni islands on Cu(111). We trace the dominance of concerted motion in Pd/Pd(111) and Ni/Cu(111) and competition among concerted, multiatom and single-atom processes in Ag/Ag(111) and Cu/Ni(111) to the strength of the lateral interaction among adatoms in these systems.

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We would like to acknowledge the computational resources provided by the STOKES facility at the University of Central Florida. We are pleased to acknowledge partial support from NSF grants: CHE-1310327, under which the project was started and MMN-1710306, under which the project was completed.

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Correspondence to Talat S. Rahman.

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Acharya, S.R., Rahman, T.S. Toward multiscale modeling of thin-film growth processes using SLKMC. Journal of Materials Research 33, 709–719 (2018).

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