# Quantifying chemical short-range order in metallic alloys

**Authors:** Killian Sheriff, Yifan Cao, Tess Smidt, Rodrigo Freitas  
**arXiv:** [2311.01545](https://arxiv.org/abs/2311.01545)  
**Date:** 2023-11-02  
**Summary page:** https://www.summarizepaper.com/en/paper/2311.01545v2/

## Key points

- Study focuses on quantifying chemical short-range order (SRO) in metallic alloys
- Metallic alloys often form solid solutions with elements distributed almost randomly on crystal lattice
- SRO concept arises from certain chemical motifs being more prevalent in complex systems like high-entropy alloys
- Authors introduce multiscale method using machine learning to predict and quantify SRO state with atomic resolution
- Predictive model can determine SRO length scale in agreement with experimental measurements and establish correlations with fundamental quantities
- Advancement in understanding solid-solution phases paves way for incorporating SRO into predictive mechanical and thermodynamic models
- Study provides insights into structural properties of metallic alloys and offers framework for optimizing alloy compositions based on SRO characteristics

## Summary

Authors Killian Sheriff, Yifan Cao, Tess Smidt, and Rodrigo Freitas present a study on quantifying chemical short-range order (SRO) in metallic alloys. Metallic alloys often form solid solutions where chemical elements are distributed almost randomly on the crystal lattice. The concept of SRO arises from certain chemical motifs being more prevalent than others in these alloys, particularly in complex systems like high-entropy alloys with multiple elements at high concentrations. To address this issue, the authors introduce a multiscale method that predicts and quantifies the SRO state of an alloy with atomic resolution. This approach incorporates machine learning techniques to bridge the gap between electronic structure calculations and the characteristic length scale of SRO. The result is a predictive model capable of determining the SRO length scale in agreement with experimental measurements while also establishing correlations between SRO and fundamental quantities such as local lattice distortions. By advancing the quantitative understanding of solid-solution phases, this work lays the foundation for incorporating SRO rigorously into predictive mechanical and thermodynamic models. The study not only provides insights into the structural properties of metallic alloys but also offers a framework for further research on optimizing alloy compositions for specific applications based on their SRO characteristics.