High entropy alloys (HEAs) contain multiple principal elements in high concentrations and can have outstanding mechanical, chemical, and functional properties beyond conventional alloys. Fabrications of HEAs using additive manufacturing (AM) can produce geometrically complex products and potentially enhance the properties of HEAs due to the special processing features. However, it is not straightforward to achieve these properties reliably due to the complex HEAs composition and the extreme AM processing conditions.

Our long-term objective is to utilize state-of-the-art integrated computational materials engineering (ICME) tools, including physics-informed machine learning (ML) and iterative experimental feedback, to discover the novel chemical compositions and optimized processing parameters for AM- fabricated HEAs to achieve unprecedented mechanical properties such as high-strength, high ductility, and high fatigue resistance. In this project, specific HEAs systems will be fabricated by AM to demonstrate our capability to achieve this objective.