Cao Group

Our research focuses on fundamentally understanding material behaviors under extreme environments, including high stress, elevated temperatures, and radiation flux. To address the timescale challenges inherent in atomistic modeling and understand fundemental mechanisms, we develop computational and modeling algorithms, such as energy landscape sampling , neural network kinstics (NKK) to reveal slow defect kinetics (e.g., vacancy diffusion correlation ). By integrating state-of-the-art electron microscopy with atomistic modeling, we study how defects and microstructures evolve under stress-, radiation-, and time-dependent conditions in heterogeneous, non-equilibrium systems (e.g., short-range ordering , maximum strength , slip banding , strongest size ). This approach enables us to predictively tune atomic-scale mechanisms and develop advanced alloys designed for high-performance nuclear energy and aerospace applications.