|About this Abstract
||3rd World Congress on High Entropy Alloys (HEA 2023)
||Deciphering the Strength-vs-ductility Trade-off for High-entropy Alloys with AI-driven Fully ab Initio-based Material Modeling
||Max Hodapp, Ivan Novikov, Olga Kovalyova, Alexander Shapeev, Franco Moitzi, Oleg Peil
|On-Site Speaker (Planned)
In this talk, we present a novel Bayesian multi-objective optimization framework that fully automatically predicts multicomponent refractory alloys with Pareto-optimal strength-vs-ductility ratios. Our framework involves predictive material models as objective functions that are fed with ab initio-based data exclusively, coming from efficient CPA calculations or atomistic simulations using machine-learned interatomic potentials, allowing for a screening over the whole alloy space at an acceptable cost. More broadly, our framework is neither limited to two objectives nor to specific mechanical properties, and, therefore, we anticipate that it also enables us to accelerate the discovery of new materials with exotic properties for various other applications. Further, we outline how magnetism can be brought into the game so that our methodology would allow for screening over a much larger space of (magnetic and non-magnetic) alloys than the space that can currently be approached with state-of-the-art methods.
||Planned: Metallurgical and Materials Transactions