Materials informatics for the screening of multi-principal elements and high-entropy alloys

Abstract

The identification of high entropy alloys is challenging given the vastness of the compositional space associated with these systems. Here the authors propose a supervised learning strategy for the efficient screening of high entropy alloys, whose hardness predictions are validated by experiments.