Microstructurally-driven Framework for Optimization of In-core Materials

This research will develop a methodology that relies on mechanism-informed machine learning models, rapid ion irradiation and creep testing techniques, and advanced characterization coupled with automated image analysis to enable reactor developers to quickly understand the complex linkage between alloy composition, thermomechanical processing, the resulting microstructure, and swelling and creep behavior. This project will (1) develop and demonstrate a high-potential methodology for rapid development of future in-core materials and (2) provide critically important information on alloy design for optimized swelling and creep behavior to the advanced reactor development community.