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The shape memory thin films are most suitable candidates as actuators in MEMS applications than other smart materials due to its ability to produce larger recovery strains at low operation voltages. Recently, Ti based shape memory alloys are gaining attention due to its ability to produce stable shape memory properties at high temperatures. In current study, Ti-Zr-Mo high-temperature shape memory thin films were fabricated using multi-target DC/RF magnetron sputtering system on Si (100) substrate. Deposition time and target power were varied to obtain the desired composition. Post-annealing was carried out at 500 °C, 600 °C and 700 °C for 15 min each to crystallize the thin films that were amorphous in the homogenized condition. The annealing temperature was varied to observe the structural and morphological changes. The total thickness of the film was found to be around 300 nm measured from the cross-sectional micrographs. The results suggest that flatness of surface topography is attributed to higher ad-atom mobility with increasing the annealing temperature. The martensite phase (α’) was observed after annealing at 500 °C and the formation of silicides was observed with annealing at higher temperatures. The transformation temperature of 220 °C was obtained from electrical resistivity measurement. The enhanced mechanical properties with maintaining structural stability was observed in Ti-Zr-Mo thin film annealed at 500 °C for 15 min.

Tuning the martensite transformation temperature through composition design has become an important way to broaden the applicable temperature range of shape memory alloys (SMAs). The empirical formula based on traditional statistics is a key reference for composition design. Due to the lack of experimental data, a large deviation may exist among the prediction results from the empirical formulas obtained by different data sources. In present work, we proposed an augmentation strategy of empirical formula based on a machine learning method to build the relationship between martensite transformation start temperature (Ms) and compositions in Cu-Al-based SMA system. A series of ML models were established by physical and chemical features and a Gaussian radial basis kernel function support vector machine (SVR.rbf) model was screened out based on mathematical and domain knowledge criteria. An augmented empirical formula of Ms as the function of compositions was fitted based on the abundant augmented dataset combined experimental data with predicted data by the SVR.rbf model. Compared with previous empirical formula fitted by small experimental dataset, the accuracy and robustness of the augmented empirical formula was significantly improved without additional experimental cost. This strategy offers a recipe to build empirical formula based on a small experimental dataset.

Summary Copper based shape memory alloy exhibits high transformation temperature and ability to differ the achieved properties through alloying additions. A quaternary Cu–Al–Be–Mn shape memory alloys of 0.2–0.4 wt% of manganese, 0.4–0.5 wt% of Beryllium and 10–14 wt% of aluminium with remaining copper, showing β-phase at higher temperature and show shape memory effect when quenching to lower temperatures, SMA's were prepared by induction melting. The objective is to study the effect of thermal ageing at different temperatures A f (above austenitic phase finish temperature) and at different time on shape memory effect and transformation temperatures. The aged specimens or SMA's were studied by DSC, OM and hardness measurements. The results from this study help to find the applications in different thermal conditions.

In this paper, quaternary Ti48.5-xNi49.5Nb2Zrx (x=0∼5at%) shape memory alloys were prepared by non-consumable vacuum arc melting. The microstructure and phase compositions of the shape memory alloys were investigated by scanning electron microscope and X-Ray Diffraction. The effects of Zr element and thermal mechanical heat treatments on the transformation temperature were studied by using differential scanning calorimetry. In addition, the mechanical properties of the alloys were tested. The results showed that the microstructure of ternary TiNiNb alloy was comprised of TiNi matrix and a Nb-enriched secondary phase. As for Zr element addition, when its content is lower than 3at.%, the Zr element was mainly dissolved in the TiNi matrix. When the content of Zr reaches 3at.%, a new secondary phase(Ti, Zr) 2Ni appeared and resulted in a degradation of workability. The martensite start temperature of the alloys decreased from 28.5 °C to 16.1 °C with the content of Zr element increasing from 0at.% to 5at.%. For Zr element increasing from 0at.% to 2at.%, the room temperature yielding strength of the alloys increased from 692 MPa to 873 MPa and the fracture strength increased from 472 MPa to 578 MPa.

In the work, a dependence of the γ→α a martensite transformation starting temperature on the grain size D is derived. A formula for the critical grain size D c is proposed reflecting the effect of physical parameters on D c ; among the parameters are the group velocity v s and the attenuation Γ s for s-electrons, the ratio of spatial scales characteristic of martensite crystal nucleation in the elastic field of an individual dislocation, and the energy range critical for the selection of pairs of active electronic states. With D c , the martensite transformation is suppressed, M s (D c ) = 0. In the framework of dynamic theory, M s is identified with the optimum temperature at which nonequilibrium d-electrons generate waves responsible for the growth of martensite crystals. It is shown that the Γ s dependence of D c is singular and allows explanation of the existence of concentration boundaries of alloying elements. Comparison is made between the obtained results and available experimental data.