Crystal Nucleation in Al-Ni Alloys: an Unsupervised Chemical and Topological Learning Approach

TL;DR

This study uses large-scale molecular dynamics and unsupervised topological learning to analyze crystal nucleation pathways in Al-Ni alloys, revealing composition-dependent polymorph selection and ordering processes.

Contribution

It introduces an unsupervised topological learning approach to elucidate atomic-scale nucleation mechanisms in Al-Ni alloys, a novel application in this context.

Findings

Nucleation begins with chemical ordering followed by bond-orientational ordering.

Different alloy compositions exhibit distinct nucleation pathways and polymorphs.

Al50 Ni50 favors a single-step B2 short-range order nucleation, while Al25 Ni75 shows a step-wise L12 phase formation.

Abstract

Crystallization represents a fundamental process engendering solidification of a material and determines its microstructure. Driven by complex phenomena at the atomic scale, its understanding for alloys still remains elusive. The present work proposes a large scale molecular dynamics simulation study of the homogeneous crystal nucleation pathways of prototypical undercooled Al-Ni binary alloys. An unsupervised topological learning analysis shows that the nucleation sets in first from a chemical ordering, followed by a bond-orientational ordering of the underlying crystal phase. Our results indicate also a different polymorph selection that depends on composition. While the nucleation pathway of Al50 Ni50 displays a single step with the emergence of B2 short-range order, a step-wise nucleation toward the L12 phase is seen for Al25 Ni75 . The influence of the nucleation of pure Al and Ni counterparts is further discussed.