A scalable parallel Monte Carlo algorithm for atomistic simulations of precipitation in alloys

TL;DR

This paper introduces a scalable Monte Carlo algorithm that enables efficient large-scale atomistic simulations of precipitation phenomena in multicomponent alloys, incorporating structural relaxations and thermal vibrations.

Contribution

It develops the variance-constrained semi-grandcanonical ensemble for scalable, multiphase simulations of alloys, combining Monte Carlo and molecular dynamics methods.

Findings

Successfully simulated Cu precipitation in nanocrystalline Fe

Demonstrated scalability on massively parallel platforms

Provided insights into precipitation mechanisms in alloys

Abstract

We present an extension of the semi-grandcanonical (SGC) ensemble that we refer to as the variance-constrained semi-grandcanonical (VC-SGC) ensemble. It allows for transmutation Monte Carlo simulations of multicomponent systems in multiphase regions of the phase diagram and lends itself to scalable simulations on massively parallel platforms. By combining transmutation moves with molecular dynamics steps structural relaxations and thermal vibrations in realistic alloys can be taken into account. In this way, we construct a robust and efficient simulation technique that is ideally suited for large-scale simulations of precipitation in multicomponent systems in the presence of structural disorder. To illustrate the algorithm introduced in this work, we study the precipitation of Cu in nanocrystalline Fe.