Kinetic Activation Relaxation Technique

TL;DR

The paper introduces the kinetic Activation-Relaxation Technique (k-ART), a self-learning off-lattice kinetic Monte Carlo method that efficiently models complex materials with elastic deformations and off-lattice atomic positions.

Contribution

It presents a novel off-lattice, self-learning KMC algorithm combining topological classification and ART nouveau for unbiased transition state sampling.

Findings

Successfully applied to self-defect annihilation in c-Si

Demonstrated self-interstitial diffusion in Fe

Showed structural relaxation in amorphous silicon

Abstract

We present a detailed description of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo 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).