Phase Transformations in Cu-Zr-X High-Temperature Shape Memory Alloys Studied Using Nanocalorimetry and Materials Simulations

Integrating computational and experimental methods can speed up the discovery process of shape memory alloys and provide a better understanding of the martensitic transformation mechanisms. We use density functional theory (DFT), molecular dynamics (MD), and high-throughput nanocalorimetry to study the Cu-Zr-X high-temperature shape memory alloy system (X= Ni/Co/Hf). Nanocalorimetry shows the martensite-austenite transformation temperature and stability on thermal cycling as a function of composition. DFT and MD are used to map out the martensitic transformation pathways. We found that the martensite-austenite energy difference and transformation temperature are positively correlated, while the martensite-austenite lattice mismatch and transformation hysteresis are negatively correlated. Our results provide a map of the shape-memory properties of Cu-Zr-X, and can be extrapolated to a larger compositional space to search for novel shape memory alloys.