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The effect of alloying element X (X = Al, Sn, Zr, Ta) on the transformation strains and phase stabilities of Ti-12.5 at%Nb and Ti-25 at%Nb alloys was investigated. The principle strain, © 2 , was calculated as a function of the X concentration. The value of © 2 of Ti-12.5 at%Nb-6.25 at%Zr was larger than that of Ti-12.5 at%Nb-6.25 at%Ta. This is consistent with the experimental results. The difference of solution energy, ÁH ¡ 00 À¢ sol , was also calculated. The value of ÁH ¡ 00 À¢ sol increased with the addition of Al, Sn, Zr, and Ta to Ti-12.5 at% Nb-6.25 at%X alloys. We found a good linear correlation between the experimental values for the decrease of the martensitic transformation start temperature (Ms), dMs/ dc, and the calculated values of ÁH ¡ 00 À¢sol . The effect of the alloying element on the shape-memory properties of Ti-Nb-based alloys were evaluated from the first-principles calculations.

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A key property for the design of new shape memory alloys is their working temperature range that depends on their transformation temperature T0. In previous works, T0 was predicted using a simple linear regression with respect to the energy difference between the parent and the martensitic phases, [Formula: see text]E[Formula: see text]. In this paper, we developed an accurate method to predict T0 based on machine learning assisted by the first-principles calculations. First-principles calculations were performed on 15 shape memory alloys; then, we proposed an artificial neural network method that used not only computed [Formula: see text]E[Formula: see text] but also bulk moduli as input variables to predict T0. The prediction error of T0 was improved to 49 K for the proposed artificial neural network compared with 188 K for simple linear regression.

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