Abstract NiTi-Cu shape memory alloys (SMAs) represent a critical class of functional materials renowned for their superior superelasticity, shape memory effect (SME), and tunable thermomechanical responses, which are essential for advanced applications in aerospace, biomedical systems, and smart actuators. The strategic incorporation of copper (Cu) into NiTi alloys serves as a powerful approach to modulate phase transformation temperatures, minimize thermal hysteresis, and enhance mechanical and elastocaloric stability. However, producing NiTi-Cu SMAs via fusion-based additive manufacturing (AM) methods remains challenging due to high thermal gradients, residual stress accumulation, and non-uniform phase distribution. Binder Jet Additive Manufacturing (BJAM), a powder sintering-based technique, has emerged as a promising non-fusion alternative capable of fabricating intricate geometries while mitigating thermal-induced defects. This review presents a comprehensive and critical evaluation of recent progress in the fabrication of NiTi-Cu SMAs, with a distinct focus on the potential and optimization of the BJAM process. Key topics include the influence of Cu on phase transformation pathways, microstructural evolution, and the elastocaloric performance of NiTi-Cu alloys. In addition, this review has examined the influence of particle morphology, binder chemistry, sintering dynamics, and post-processing strategies on densification, mechanical behavior, and shape memory functionality. Special attention is given to the integration of computational tools such as CALPHAD and machine learning (ML) for predictive alloy design and process optimization, offering a data-driven roadmap for scalable production. This review identifies critical knowledge gaps, including the lack of experimental studies on BJAM-specific NiTi-Cu fabrication and the challenges associated with Cu segregation, intermetallic formation, and contamination during sintering. By consolidating foundational insights and proposing a structured research framework, this study aims to advance the scientific understanding and industrial applicability of BJAM in the manufacturing of high-performance NiTi-Cu SMAs, ultimately bridging the gap between fundamental research and practical deployment in smart material systems.

Contactless, laser-based resonant ultrasound spectroscopy was utilized to monitor changes in elastic properties in single-crystalline NiTi shape memory alloy. It was observed that the elastic behavior of the temperature-induced B19′ martensite, which is formed by a fine mixture of variants, adopts the symmetry elements of the parent austenite phase and thus, the changes over the transformation temperature can be represented by the temperature evolution of three cubic elastic coefficients. The experiments confirm that the transition during the cooling run is preceded by pronounced softening of the c44 elastic coefficient, which leads to nearly complete vanishing of elastic anisotropy prior to the transition. Below the transition, this coefficient remains soft, and the character of anisotropy switches from c44/c′ > 1 to c44/c′ < 1. We rationalize this behavior from the mechanical instability of the B19′ lattice with respect to shears along the (001)B19′ plane, which is known from first-principles calculations.

This paper deals with the design of (TiHfZr)(NiCoCu) high-entropy and high-temperature shape memory alloys (HE-HT-SMAs). It explains the chronology and the progress of this design starting from the experimental work of Georgi Firstov initiated in the 2015s until the advent of data-driven alloy approaches. A state-of-the-art (TiHfZr)(NiCoCu) HE-HT-SMA family is presented and enriched by a database used as input for a data-driven approach. The paper then focuses on the comparison of martensitic transformation temperatures provided by: (i) the experimental work of Firstov et al. started in 2015, (ii) other recent experimental studies and, (iii) those predicted by two numerical approaches. The first approach consists of a linear regression model proposed by Peltier et al., while the second one is proposed and enriched by Thiercelin et al. using a data-driven technique (random forest regression). The results from the data-driven approach yield accurate predictions that align with the experimental data from both the literature and previous studies. Thus demonstrating the importance of physics-informed, inspired techniques to optimize the design of future alloys, in particular HE-HT-SMAs.

Potassium sodium niobate is considered a prominent material system as a substitute for lead-containing ferroelectric materials. It exhibits first-order phase transformations and ferroelectricity with potential applications ranging from energy conversion to innovative cooling technologies, thereby addressing important societal challenges. However, a major obstacle in the application of potassium sodium niobate is its multi-scale heterogeneity and the lack of understanding of its phase transition pathway and microstructure. This can be seen from the findings of Pop-Ghe et al. (Ceram Int 47(14):20579–20585, 2021, https://doi.org/10.1016/j.ceramint.2021.04.067) which also reveal the occurrence of a phenomenon they term intermediate twinning during the phase transition. Here, we show that intermediate twinning is a consequence of energy minimization. We develop a geometrically nonlinear electroelastic energy function for potassium sodium niobate, including the cubic-tetragonal-orthorhombic transformations and ferroelectricity. The construction of the minimizers is based on compatibility conditions which ensure continuous deformations and pole-free interfaces. These minimizers agree with the experimental observations, including laminates between tetragonal variants under the cubic to tetragonal transformation, crossing twins under the tetragonal to orthorhombic transformation, intermediate twinning and spontaneous polarization. This shows how the full nonlinear electroelastic model provides a powerful tool in understanding, exploring, and tailoring the electromechanical properties of complex ferroelectric ceramics.