Long-timescale transformations of self-interstitial atom clusters of Cu using the SEAKMC method; The Effect of setting an activation energy threshold for saddle point searches

早川 頌*; 山本 耀二郎*; 沖田 泰良*; 板倉 充洋; 鈴木 克幸*

Computational Materials Science, 218, p.111987_1 - 111987_10, 2023/02

https://doi.org/10.1016/j.commatsci.2022.111987

On-the-fly kinetic Monte Carlo (kMC), a computational technique for atomistic simulations, has attracted attention because it increases the simulation timescale beyond that of molecular dynamics (MD) simulations while maintaining atomistic fidelity. However, for most kMC methods, when events with high and low activation energies coexist in the event list, trivial events with extremely low activation energies that do not essentially affect the phenomena of interest, so-called flicker events, are frequently selected, making it challenging to observe the key dynamics. In this study, we use Self-Evolving Atomistic kMC (SEAKMC), one of the on-the-fly kMC methods, to model the unstable-to-stable transformations of irregular three-dimensional self-interstitial-atom (SIA) clusters in Cu generated through collision cascade. By setting an activation energy threshold once every five steps, transformations into stable configurations are enhanced. The algorithm renders the simulation timescales one or two orders of magnitude longer than those possible with MD simulations. Further, the probability of transformations into stable configurations is increased by 40 times compared to that of the original SEAKMC method. In addition, we find that the stable configurations obtained by the transformation of the SIA clusters are mostly Frank loops. In summary, this new algorithm for the SEAKMC method helps to resolve the inefficiency of kMC methods resulting from the selection of flicker events and will aid the study of meso-timescale atomistic dynamics.