Machine learning assisted design of new ductile high-entropy alloys: Application to Al-Cr-Nb-Ti-V-Zr system

Abstract

The search for new high-entropy alloys (HEAs) with desired properties is an urgent problem that is hardly solvable experimentally due to the extremely large number of possible alloy compositions. Here we address developing data-driven machine learning models (DDML) to predict the ductility of HEAs