Designing High-Entropy Alloys With Low Stacking Fault Energy Through Interpretable Machine Learning

Today's article comes from the MGE Advances journal. The authors are Nie et al., from Northwestern Polytechnical University, in China. In this paper they're showcasing a pipeline that can hunt for new metals with specific physical properties. It screens through a massive set of candidate compositions, and narrows those down to a handful of promising alloys.