Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration

no code implementations • 4 Mar 2020 • Sen Liu, Branden B. Kappes, Behnam Amin-ahmadi, Othmane Benafan, Xiaoli Zhang, Aaron P. Stebner

Machine learning (ML) is shown to predict new alloys and their performances in a high dimensional, multiple-target-property design space that considers chemistry, multi-step processing routes, and characterization methodology variations.

BIG-bench Machine Learning Feature Engineering +1