The Governing Council of the University of Toronto

Published purpose

High entropy alloys (HEAs) are a new class of metallic materials that contain five or more metals in equimolar or near-equimolar ratios, which have higher strength, ductility, fracture toughness, and catalytic activity compared to traditional alloys that are made by solution hardening, precipitation hardening, and grain refinement. Considering that there are 75 stable elements that are not toxic, radioactive or noble gases, millions of new alloy systems are possible. The main goal of this Project is to develop and apply machine learning techniques for discovery, design and development of HEAs with desired properties for high-temperature structural, and catalytic applications. This Project will speed up the exploitation of the subtle relationships between the composition and properties of materials, and machine learning (ML) will help screen candidate HEAs that have desired mechanical and functional properties. In this Project, candidate materials will be synthesized and optimized, with the research team intending to design and develop new HEAs for high-temperature structural applications (e.g. in gas turbine), and functional applications (e.g. catalysts for CO2 reduction to methane and methanol).