Machine learning-guided design and development of metallic structural materials

Jinxin Yu, Shengkun Xi, Shaobin Pan, Yongjie Wang, Qinghua Peng, Rongpei Shi, Cuiping Wang, Xingjun Liu
2021 Journal of Materials Informatics  
In recent years, the advent of machine learning (ML) in materials science has provided a new tool for accelerating the design and discovery of new materials with a superior combination of mechanical properties for structural applications. In this review, we provide a brief overview of the current status of the ML-aided design and development of metallic alloys for structural applications, including high-performance copper alloys, nickel- and cobalt-based superalloys, titanium alloys for
more » ... al applications and high strength steel. We also present our perspectives regarding the further acceleration of data-driven discovery, development, design and deployment of metallic structural materials and the adoption of ML-based techniques in this endeavor.
doi:10.20517/jmi.2021.08 fatcat:7r3wdmxgl5dbdmci27me6wvzdy