Machine learning assisted modelling and design of solid solution hardened high entropy alloys

High entropy alloys (HEAs) are considered as a way to unlock the unlimited potentials of materials during material design, where solid solution hardening (SSH) is one of the major contributors to their excellent mechanical properties. In this work, machine learning (ML) is applied for modelling SSH in HEAs, and a ML system is established for designing solid solution hardened HEAs. The ML-SSH model is built by considering critical factors in SSH theories and parameters associated with the atomic environment and interactions in HEAs as input features, and is demonstrated to be superior to physical SSH models in terms of hardness prediction. The effects of charge transfer and short range order (SRO) and local composition fluctuations on SSH in HEAs are confirmed using feature engineering approaches. Furthermore, two physical models are modified by introducing charge transfer to enhance their accuracy. Finally, an alloy design system is built by combining the ML-SSH model and ML models for single solid solution phase prediction, achieving good agreement with the experimental results of FeNiCuCo and CrMoNbTi families. The non-equiatomic counterparts with 28.3% and 8.8% hardness values higher than their equiatomic counterparts of FeNiCuCo and CrMoNbTi families respectively are discovered. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

In this study, a machine learning model was used to predict solid solution hardening in High Entropy Alloys (HEAs) by considering critical factors and parameters associated with atomic environment. The model outperformed physical models in predicting hardness. The effects of charge transfer, short range order, and local composition fluctuations on solid solution hardening in HEAs were confirmed through feature engineering, leading to the discovery of non-equiatomic counterparts with significantly higher hardness values.