Research Projects

Shape memory and superelastic materials (SMAs) are integral to applications such as actuators, biomedical devices, and energy-efficient technologies, thanks to their unique ability to undergo thermally and mechanically induced reversible martensitic phase transformations. Advances in SMA design, like compositional tuning and microstructural engineering, have pushed boundaries, achieving properties such as ultra-low fatigue, high strength, and tunability in transformation temperatures and hysteresis. However, fundamental questions remain about the mechanisms driving these properties, especially in SMAs with coherent second phases or nanoscale modulations, which exhibit unprecedented fatigue resistance, high strength, and uncharacterstic second order martensitic transformation. This proposal aims to develop a predictive understanding of how nanoscale heterogeneities and engineered second phases influence SMA behavior. By combining atomistic simulations with machine learning, we seek to map energy landscapes and uncover the mechanisms behind second-order transformations, enhanced fatigue resistance, and ultra-low stiffness. The research is structured into three main thrusts: (1) understanding the impact of second-phase properties on martensitic responses, (2) exploring crystal/amorphous nanostructures for high strength fatigue-resistant SMAs, and (3) investigating structural stability and martensitic transformations in composites of non-transforming materials. This framework will guide the design of next-generation SMAs with tailored properties, enabling lightweight, high-performance materials for diverse fields demanding innovation and resilience.