Abstract
We present a mixed-lattice atomistic kinetic Monte-Carlo algorithm (MLKMC) that integrates a rigid-lattice AKMC approach with the kinetic activation-relaxation technique (k-ART), an off-lattice/self-learning AKMC. This approach opens the door to study large and complex systems adapting the cost of identification and evaluation of transition states to the local environment. To demonstrate its capacity, MLKMC is applied to the problem of the formation of a C Cottrell atmosphere decorating a screw dislocation in α-Fe. For this system, transitions that occur near the dislocation core are searched by k-ART, while transitions occurring far from the dislocation are computed before the simulation starts using the rigid-lattice AKMC. This combination of the precision of k-ART and the speed of the rigid-lattice makes it possible to follow the onset of the C Cottrell atmosphere and to identify interesting mechanisms associated with its formation.
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