38 research outputs found

    The Kinetic Activation-Relaxation Technique: A Powerful Off-lattice On-the-fly Kinetic Monte Carlo Algorithm

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    Many materials science phenomena, such as growth and self-organisation, are dominated by activated diffusion processes and occur on timescales that are well beyond the reach of standard-molecular dynamics simulations. Kinetic Monte Carlo (KMC) schemes make it possible to overcome this limitation and achieve experimental timescales. However, most KMC approaches proceed by discretizing the problem in space in order to identify, from the outset, a fixed set of barriers that are used throughout the simulations, limiting the range of problems that can be addressed. Here, we propose a more flexible approach -- the kinetic activation-relaxation technique (k-ART) -- which lifts these constraints. Our method is based on an off-lattice, self-learning, on-the-fly identification and evaluation of activation barriers using ART and a topological description of events. The validity and power of the method are demonstrated through the study of vacancy diffusion in crystalline silicon.Comment: 5 pages, 4 figure

    Sampling the diffusion paths of a neutral vacancy in Silicon with quantum mechanical calculations

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    We report a first-principles study of vacancy-induced self-diffusion in crystalline silicon. Starting form a fully relaxed configuration with a neutral vacancy, we proceed to search for local diffusion paths. The diffusion of the vacancy proceeds by hops to first nearest neighbor with an energy barrier of 0.40 eV in agreement with experimental results. Competing mechanisms are identified, like the reorientation, and the recombination of dangling bonds by Wooten-Winer-Weaire process.Comment: 10 pages, 5 figures, accepted for publication in Pysical review

    Physica A

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