This review summarizes the development of Ti-based high-entropy and multi-principal element shape memory alloys (SMAs), with a particular focus on TiZrHfCoNiCu, TiHf(Zr)Ni(Pt)Pt, and TiPd-based systems. Alloy composition and heat treatment significantly influence martensitic transformation temperatures (MTTs), thermal hysteresis, superelasticity (SE), shape memory effect (SME), and elastocaloric effect (eCE) through precipitation reactions, compositional partitioning, and lattice strain effects. These parameters are summarized in the tables. Furthermore, recent advances in machine learning have provided powerful tools for predicting MTTs and thermal hysteresis. Important features governing phase transformation behavior, as well as suitable regression models for predicting MTT and thermal hysteresis, are introduced. These developments demonstrate a transition from empirical alloy development toward data-driven and physics-informed design of next-generation HE-SMAs.
Yoko Yamabe‐Mitarai (Thu,) studied this question.
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