Statistical distribution of thermal vacancies close to the melting point

TL;DR

This paper models the statistical distribution of thermal vacancies in copper near melting, revealing they follow a Gamma distribution and potentially influence homogeneous melting mechanisms.

Contribution

It introduces a novel Gamma distribution model for thermal vacancies near melting, based on molecular dynamics simulations and a new vacancy recognition algorithm.

Findings

Vacancies increase with temperature following Arrhenius' law.

Thermal vacancies follow a Gamma distribution.

Results may aid in understanding homogeneous melting mechanisms.

Abstract

A detailed description of the statistical distribution of thermal vacancies near the melting point is presented, using copper as an example. As the temperature is increased, the average number of thermal vacancies generated by atoms migrating to neighboring sites also increase, according to Arrhenius' law. We present for the first time a model for the distribution of thermal vacancies, which according to our results follow a Gamma distribution. All the simulations are carried out by classical molecular dynamics and the recognition of vacancies is achieved via a recently developed algorithm. Our results could be useful in the further development of a theory explaining the mechanism of homogeneous melting, which seems to be mediated (at least in part) by the accumulation of thermal vacancies near the melting point.