Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new sy...Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new systems.Experimental approaches are based on physical intuition and/or expensive trial and error strategies.Most computational methods rely on the availability of sufficient experimental data and computational power.Machine learning(ML)applied to materials science can accelerate development and reduce costs.In this study,we propose an ML method,leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability(i.e.,entropy-forming ability)of disordered metal carbides.展开更多
基金We acknowledge support through the Office of Naval Research ONR-MURI(grant number N00014-15-1-2863)K.K.acknowledges support by the Department of Defense(DoD)through the National Defense Science and Engineering Graduate Fellowship(NDSEG)Program+1 种基金K.K.also acknowledges the financial support of the ARCS Foundation,San Diego ChapterK.S.V.acknowledges the financial generosity of the Oerlikon Group in support of his research group.
文摘Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new systems.Experimental approaches are based on physical intuition and/or expensive trial and error strategies.Most computational methods rely on the availability of sufficient experimental data and computational power.Machine learning(ML)applied to materials science can accelerate development and reduce costs.In this study,we propose an ML method,leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability(i.e.,entropy-forming ability)of disordered metal carbides.
