Understanding long-time vacancy aggregation in iron: a kinetic activation-relaxation technique study

TL;DR

This study uses the kinetic activation-relaxation technique to analyze vacancy diffusion and clustering in bcc iron, revealing diverse mechanisms, pathway-dependent behaviors, and the influence of elastic interactions on kinetics.

Contribution

It introduces the application of k-ART to study vacancy clustering in iron, highlighting pathway effects and elastic interactions on diffusion mechanisms and relaxation times.

Findings

Clustering results agree with experimental estimates.

Pathways significantly affect diffusion and relaxation times.

Long-range elastic interactions influence early-stage kinetics.

Abstract

Vacancy diffusion and clustering processes in body-centered-cubic (bcc) Fe are studied using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo method with on-the-fly catalog building capabilities. For monovacancies and divacancies, k-ART recovers previously published results while clustering in a 50-vacancy simulation box agrees with experimental estimates. Applying k-ART to the study of clustering pathways for systems containing from one to six vacancies, we find a rich set of diffusion mechanisms. In particular, we show that the path followed to reach a hexavacancy cluster influences greatly the associated mean-square displacement. Aggregation in a 50-vacancy box also shows a notable dispersion in relaxation time associated with effective barriers varying from 0.84 to 1.1 eV depending on the exact pathway selected. We isolate the effects of long-range elastic interactions between defects by comparing to simulations where those effects are deliberately suppressed. This allows us to demonstrate that in bcc Fe, suppressing long-range interactions mainly influences kinetics in the first 0.3 ms, slowing down quick energy release cascades seen more frequently in full simulations, whereas long-term behavior and final state are not significantly affected.