Computational Design and Experimental Validation of Ductile Refractory Metal-Based High Entropy Materials

The vast design space of high entropy materials allows the tuning of designer materials with enhanced properties. The subset of high entropy materials consisting of refractory metals with a body centered cubic (BCC) structure are known to maintain a high yield strength at elevated temperatures. However, just tailoring refractory metal-based high entropy materials to be strong and BCC stable is insufficient and ductility, which is challenging to model, must be incorporated into any alloy design process. Ductility models are compared with experimental compression and elongation data to determine which model accurately predicts ductility in refractory metal-based high entropy materials. Through analytical calculations, we investigate high entropy alloys from the Hf-Mo-Nb-Ta-Ti-V-W-Zr element palette to identify ductile candidates and understand which compositional combinations, with varying entropy, lead to novel properties. The design strategy is then expanded to rapidly explore the space of high order non-equiatomic refractory metal-based high entropy materials by leveraging machine learning and high-performance computing capabilities. Selected compositions predicted to maintain high strength, BCC phase stability and acceptable ductility are manufactured and tested to validate the search for refractory metal-based high entropy materials with designer properties. Prepared by LLNL under Contract DE-AC52-07NA27344.