Abstract
An empirical map of martensitic transformation temperatures versus average valence electrons per atom (e v/a) and valence electron concentration (c v) was developed in order to design ZrCu-based shape memory alloys (SMAs). The martensitic transformation temperatures of about 40 different alloys (Ni, Co, Hf, Ag, Ti, Al, Cr, etc.), covering nearly all possible replacements of Zr or Cu, are exhibited. The relationship between transformation temperature and cv or electron density (n) was determined. The results indicate that the transformation temperatures of ZrCu-based alloys gradually decrease until reaching an inflection point at c v = 0.218, above which the transformation temperatures go down. A linear dependence of the transformation temperatures of ZrCu-based alloys on the electron density is revealed by data-fitting. Under the guidance of these contour maps describing transformation temperatures and thermal hysteresis, a series of ZrCu-based alloys that can function under different conditions can be designed.
摘要
本文建立了一个关于马氏体相变温度和价电子数及电子浓度的经验图谱并设计了一系列ZrCu基形状记忆合金. 这些相变温度包括了所有报道过的经Ni、Co、Hf、Ag、Ti、Al、Cr等掺杂替换Zr或者Cu原子的约40种合金. 反映了转变温度和电子浓度或者电子密度之间的关系. 结果显示ZrCu基合金的转变温度逐渐下降, 当c v > 0.218时, 相变温度急剧下降. ZrCu基合金的马氏体相变温度与电子密度呈线性关系. 基于相变温度和滞后图谱的结果可以设计出在不同条件下工作的ZrCu基合金.
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Weihong Gao is currently a PhD candidate in the Department of Material Physics and Chemistry at Harbin Institute of Technology, China. She received his BSc degree and MSc degree majored in material physics and chemistry at Harbin Engineering University. Her current research is mainly on martensite phase transformation; microstructure and interface of high temperature shape memory alloys.
Xianglong Meng is currently a professor at Harbin Institute of Technology. He obtained his PhD degree from Harbin Institute of Technology in 2004. His research interests focus mainly on high temperature shape memory alloys, martensitic transformation and microstructure.
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Gao, W., Meng, X., Song, G. et al. Empirical mapping of ZrCu-based alloys with valence electrons versus transformation temperatures. Sci. China Mater. 59, 151–157 (2016). https://doi.org/10.1007/s40843-016-0124-z
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DOI: https://doi.org/10.1007/s40843-016-0124-z