Improving the functional stability of shape memory alloys (SMAs), which undergo a reversible martensitic transformation, is critical for their applications and remains a central research theme driving advances in shape memory technology. By using a thin‐film composition‐spread technique and high‐throughput characterization methods, the lattice parameters of quaternary Ti–Ni–Cu–Pd SMAs and the thermal hysteresis are tailored. Novel alloys with near‐zero thermal hysteresis, as predicted by the geometric non‐linear theory of martensite, are identified. The thin‐film results are successfully transferred to bulk materials and near‐zero thermal hysteresis is observed for the phase transformation in bulk alloys using the temperature‐dependent alternating current potential drop method. A universal behavior of hysteresis versus the middle eigenvalue of the transformation stretch matrix is observed for different alloy systems. Furthermore, significantly improved functional stability, investigated by thermal cycling using differential scanning calorimetry, is found for the quaternary bulk alloy Ti50.2Ni34.4Cu12.3Pd3.1.

This paper describes the use of thin film high-throughput experimentation methods for the efficient development of multifunctional materials, using Ni – Ti – X and ferromagnetic shape memory alloys as examples. The thin films were fabricated in the form of binary, ternary, and quaternary materials libraries by special magnetron sputter deposition processes. These materials libraries were subsequently processed and characterized by high-throughput experimentation methods in order to relate compositional information with structural and functional properties. For this, appropriate visualization of the data is necessary. Results show that the martensitically transforming regions in ternary thin films are generally larger than was known from literature. Within these regions, the variation of the functional properties can be mapped with respect to the composition and microstructure, and thus the most suitable materials for applications can be effectively selected.

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