Engineering
Closed-loop design of heat-resistant austenitic alloys through iterative machine learning and combinatorial approaches
This PhD project aims to accelerate the discovery of heat-resistant austenitic alloys by integrating machine learning with high-throughput combinatorial experiments. Through iterative design, synthesis, and validation, the project will develop advanced materials for high-temperature reactors, significantly reducing alloy development time and enhancing structural integrity under creep-fatigue conditions.