An informatics approach to transformation temperatures of NiTi-based shape memory alloys

• Published in: Acta materialia Vol. 125; no. C; pp. 532 - 541
• Main Authors: Xue, Dezhen, Xue, Deqing, Yuan, Ruihao, Zhou, Yumei, Balachandran, Prasanna V., Ding, Xiangdong, Sun, Jun, Lookman, Turab
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 15.02.2017; Elsevier
• Subjects: Machine learning; Material informatics; Regression; Shape memory alloys; Transformation temperature; Regression; Shape memory alloys; Material informatics; Machine learning; Transformation temperature

The martensitic transformation serves as the basis for applications of shape memory alloys (SMAs). The ability to make rapid and accurate predictions of the transformation temperature of SMAs is therefore of much practical importance. In this study, we demonstrate that a statistical learning approac...