A Materials Informatics Approach to Refractory High Entropy Alloy Development

Most commercial refractory alloys were designed with high temperature strength and manufacturability prioritized over oxidation resistance. This drives the need for complex and expensive coatings in aggressive service conditions. By lifting classic composition constraints through a high entropy alloying approach, it is possible to achieve improved balance-of-properties in refractory metals. Tailoring properties individually, as required for a specific application or as input for design trades, is also enabled. Here, we review recent work combining high throughput experimental screening, machine learning, and multi-objective optimization to explore a wide refractory alloy composition space. We demonstrate a materials informatics alloy selection process for extreme service conditions where oxidation resistance is prioritized alongside mechanical properties and manufacturability. The general methods presented here can be applied to other applications and highlight the benefits of a materials informatics approach to alloy design.