| Literature DB >> 22181304 |
Laurent Karim Béland1, Peter Brommer, Fedwa El-Mellouhi, Jean-François Joly, Normand Mousseau.
Abstract
We present a detailed description of the kinetic activation-relaxation technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, k-ART can be applied to complex materials with atoms in off-lattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of k-ART by applying the algorithm to three challenging systems: self-defect annihilation in c-Si (crystalline silicon), self-interstitial diffusion in Fe, and structural relaxation in a-Si (amorphous silicon).Entities:
Year: 2011 PMID: 22181304 DOI: 10.1103/PhysRevE.84.046704
Source DB: PubMed Journal: Phys Rev E Stat Nonlin Soft Matter Phys ISSN: 1539-3755