A Quick Screening of High Yield Strength Points in Single-Phase Co-Cr-Fe-Ni-Mo High Entropy Alloy System Based on Electronegativity, Thermodynamic Calculations and Machine Learning

A method which combines electronegativity different, CALPHAD (CALculation of PHAse Diagrams) and machine learning has been proposed to efficiently screen the high yield strength regions in Co-Cr-Fe-Ni-Mo multi-component phase diagram. Firstly, the single-phase region at a certain annealing temperature is obtained by combining CALPHAD method and machine learning, to avoid the formation of brittle phases. Then high yield strength points in the single-phase region are selected by electronegativity different. The validation experiments indicate this method is effective to predict high yield strength points in the whole compositional space. The method is instructive to property-oriented compositional design for high entropy alloys.