摘要
非晶态固体没有长程的平移对称性, 因而缺少像晶体中那样具有明确定义的缺陷及其运动来解释塑性的产生. 长期以来, 人们推测非晶态固体的塑性可能起源于物理意义上的局部软区. 与此相比, 在Cubuk等人最近发表在《科学》杂志上的论文中, 作者基于机器学习技术定义了一个微观结构量“软度”, 并提出可以通过“软度”来衡量多种不同非晶态固体(分子玻璃、 胶体玻璃、 金属玻璃等)的塑性的结构起源. 尽管基于机器学习而得到的“软度”的物理意义仍值得进一步研究, 但是由此得到的“软度”区域确实显示出与局部重排区域非常好的相关性. 这个发现为探究多种非晶态固体塑性的结构起源提供了一个定量的理解.
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Acknowledgements
Yang Y acknowledges the research funding from Research Grant Council (RGC) of Hong Kong with the grant number CityU 11207215 and CityU11209317.
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Xiaodi Liu obtained his bachelor and master degree from Shandong University, Jinan, China, in 2012 and 2015 respectively. He is currently a PhD student under the supervision of Prof. Yong Yang at the Department of Mechanical Engineering, City University of Hong Kong, Hong Kong, China. His research focuses on the creep and relaxation behavior of metallic glasses.
Fucheng Li is currently a PhD candidate at the Department of Mechanical Engineering, City University of Hong Kong, Hong Kong, China. He received his bachelor degree and master degree from Central South University, Changsha, China in 2013 and 2016, respectively. His PhD research focuses on the mechanical behavior of both bulk nano-grained metallic glass and metallic-glass based nanostructures.
Yong Yang obtained his bachelor degree in 2001 from Peking University, Beijing, China, and PhD in 2007 from Princeton University, NJ, USA. He is currently a Professor at Department of Mechanical Engineering, City University of Hong Kong, Hong Kong, China. His research focuses on mechanical behavior of structural materials and the high throughput design of alloys, such as metallic glasses and high entropy alloys.
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Liu, X., Li, F. & Yang, Y. “Softness” as the structural origin of plasticity in disordered solids: a quantitative insight from machine learning. Sci. China Mater. 62, 154–160 (2019). https://doi.org/10.1007/s40843-018-9316-2
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DOI: https://doi.org/10.1007/s40843-018-9316-2