Kinetic activation-relaxation technique.

نویسندگان

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

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).

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عنوان ژورنال:
  • Physical review. E, Statistical, nonlinear, and soft matter physics

دوره 84 4 Pt 2  شماره 

صفحات  -

تاریخ انتشار 2011