Kinetic activation-relaxation technique

Laurent Karim Béland, Peter Brommer, Fedwa El-Mellouhi, Jean François Joly, Normand Mousseau

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80 Citations (Scopus)

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).

Original languageEnglish
Article number046704
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume84
Issue number4
DOIs
Publication statusPublished - 17 Oct 2011

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ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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