Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges

In the design and development of novel materials that have excellent mechanical properties, classification and regression methods have been diversely used across mechanical deformation simulations or experiments. The use of materials informatics methods on large data that originate in experiments or/and multiscale modeling simulations may accelerate materials' discovery or develop new understanding of materials' behavior. In this fast-growing field, we focus on reviewing advances at the intersection of data science with mechanical deformation simulations and experiments, with a particular focus on studies of metals and alloys. We discuss examples of applications, as well as identify challenges and prospects.

Automated summary

The design and development of novel materials with excellent mechanical properties often utilize classification and regression methods in mechanical deformation simulations or experiments. The application of materials informatics on large data can expedite materials discovery and deepen understanding of materials behavior. This review focuses on advances in the intersection of data science with mechanical deformation simulations and experiments, particularly in the study of metals and alloys.