Determining the Optimal Phase-Change Material via High-Throughput Calculations

TL;DR

This paper introduces a high-throughput computational approach to identify optimal phase-change materials by predicting compositions that minimize interface strain, thereby aiding experimental synthesis and improving material performance.

Contribution

A novel computational method using first-principles calculations to determine ideal alloy compositions for phase-change materials, streamlining discovery and optimization.

Findings

Validated method on known phase-change material

Predicted ideal composition matches experimental data

Potential to reduce mechanical failure in applications

Abstract

The discovery and optimization of phase-change and shape memory alloys remain a tedious and expensive process. Here a simple computational method is proposed to determine the ideal phase-change material for a given alloy composed of three elements. Using first-principles calculations, within a high-throughput framework, the ideal composition of a phase-change material between any two assumed phases can be determined. This ideal composition minimizes the interface strain during the structural transformation. Then one can target this ideal composition experimentally to produce compounds with low mechanical failure rates for a potentially wide variety of applications. Here we will provide evidence of the effectiveness of our calculations for a well-known phase-change material in which we predict the ideal composition and compare it to experimental results.