Yifan (Henry) Cao

Yifan (Henry) Cao is a PhD candidate working at the frontier of a new materials science field: high- entropy alloys (HEAs). HEAs offer valuable traits, such as high strength and fracture resistance. As a MathWorks Fellow, Henry will be expanding a new method he has developed to optimize machine learning interatomic potentials (MLP) in cross-scale atomistic simulations, thereby predicting HEA
properties with greater efficiency than current methods. Although HEAs are created by mixing many chemical elements, local chemical ordering (LCO), the prominent mechanism underlying many of these properties, remains poorly understood. Henry’s research seeks to close that knowledge gap. Two MathWorks tools will play a central role in the project: Simulink, which will enable the development of a well-rounded MLP training set, and MATLAB, which will be used to extract physically important features and plot relevant data obtained from HEA cross-scale simulations. Henry also plans to explore potential applications of these tools in mesoscale, atomic, and quantum mechanics modeling approaches.