arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.04603cond-mat.dis-nncond-mat.mtrl-sci
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拓扑约束理论与玻璃的刚性

Topological Constraint Theory and Rigidity of Glasses

Mathieu Bauchy

摘要:

拓扑约束理论已经成为一种越来越流行的工具,用于预测玻璃性质的组成依赖性或精确定位具有定制功能的有前途的组合物。这种方法将复杂的无序网络简化为更简单的机械桁架。因此,拓扑约束理论捕捉到重要的原子拓扑结构,控制宏观性能,同时过滤掉不太相关的二阶结构的细节。因此,拓扑约束理论可用于解码玻璃的基因组,即识别和破译玻璃的基本结构构建块如何控制其工程特性-就像人类基因组提供信息作为个人生长和发展的蓝图一样。由于其优雅和简单,拓扑约束理论已经使各种基于物理的模型,可以分析预测玻璃的各种属性的发展。在这一章中,我将介绍一些玻璃科学的一般背景,原子刚性的概念,拓扑约束理论。拓扑约束枚举方案提出了各种原型玻璃,并用于了解他们的玻璃形成能力的起源。最后,各种拓扑模型,使玻璃性能的预测进行了审查,重点是硬度,断裂韧性,粘度,脆性,玻璃化转变温度和溶解动力学。

英文摘要:

Topological constraint theory has become an increasingly popular tool to predict the compositional dependence of glass properties or pinpoint promising compositions with tailored functionalities. This approach reduces complex disordered networks into simpler mechanical trusses. Thereby, topological constraint theory captures the important atomic topology that controls macroscopic properties while filtering out less relevant second-order structural details. As such, topological constraint theory can be used to decode the genome of glass, that is, to identify and decipher how the basic structural building blocks of glasses control their engineering properties---in the same way as the human genome offers information that serves as a blueprint for an individual's growth and development. Thanks to its elegance and simplicity, topological constraint theory has enabled the development of various physics-based models that can analytically predict various properties of glass. In this Chapter, I introduce some general background in glass science, concepts of atomic rigidity, and topological constraint theory. The topological constraints enumeration scheme is presented for various archetypical glasses and is used to understand the origin of their glass-forming ability. Finally, various topological models enabling the prediction of glass properties are reviewed, with a focus on hardness, fracture toughness, viscosity, fragility, glass transition temperature, and dissolution kinetics.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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