Accelerated prediction of chemical short-range order via lattice distortion in multi-principal element alloys

Abstract

The chemical short-range order (CSRO) in multi-principal element alloys (MPEAs) critically influences their microstructural and various properties. Conventional density functional theory (DFT)-based Monte Carlo (MC) simulations, though accurate, are computationally expensive and limited to small-scale systems. This study introduces a novel local-lattice-distortion (LLD)-based MC framework as a computationally efficient alternative for predicting CSRO. By replacing energy-based acceptance criteria with LLD reduction as the metric for atomic swaps, our method achieves computational speeds over two orders of magnitude faster than DFT-based methods while maintaining accuracy. Validated on six representative face-centered cubic and body-centered cubic MPEAs, the framework reveals a strong correlation between LLD and CSRO. Its scalability enables applications in large-scale simulations and high-throughput studies, providing actionable insights into the LLD-CSRO relationship. This methodology offers a transformative tool for advancing the design and optimization of MPEAs with tailored properties.