| Abstract Scope |
The design of refractory complex concentrated alloys (RCCAs) is challenged by an immense compositional space and a fundamental duality between global stoichiometry and local chemical environments. This talk discusses a multi-scale framework developed for a model RCCA system (MoNbTaTi) that bridges electronic structure, atomistic representations, and autonomous discovery.
I first examine the critical role of local stoichiometry in promoting high yield strength, tracing its origin to a transition from metallic to covalent-like bonding. Building on this understanding, I introduce metrics to quantify local chemical complexity and demonstrate how short-range order alters material property distributions. Finally, I will present a multi-objective Bayesian optimization workflow that navigates antagonistic property relationships to identify compositions with optimized high-temperature stability and resilient deformation mechanisms under dynamic shock loading. This integrated approach provides a robust pathway for the autonomous design of high-performance refractory materials. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. |