Accelerated Nuclear Materials and Fuel Qualification by Adopting a First to Failure Approach

Physics-based multi-scale modeling was coupled with deep, recursive, and transfer learning approaches to accelerate nuclear materials research and qualification of high- entropy alloys. Applying AI to combinatorial-based materials research enables subsequent analysis to focus on a limited number of candidates predicted to have the necessary materials properties for the application.