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arXiv 1901.04124cond-mat.mtrl-sci
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Zr $_{50}$ Cu $_{45}$ Al $_{5}$金属玻璃短程有序结构的原子模型研究

Short-Range Order Structure Motifs Learned from an Atomistic Model of a Zr$_{50}$Cu$_{45}$Al$_{5}$ Metallic Glass

Jason J. Maldonis, Arash Dehghan Banadaki, Srikanth Patala, Paul M. Voyles

摘要:

使用称为基序提取的新结构分析方法从原子模型中学习Zr $_{50}$ Cu $_{45}$ Al $_{5}$金属玻璃的结构基序,该方法采用点模式匹配和机器学习聚类技术。这些图案是玻璃的最邻近的构建块,并且揭示了作为配位数的函数的明确的结构层次。一些基序是二十面体或准二十面体的结构,而另一些基序则是每个配位数的最紧密堆积的几何结构。这些结果为在金属玻璃中开发更清晰的结构-性能联系奠定了基础。模体提取可以应用于任何无序材料,以识别其结构模体,而无需人工输入。

英文摘要:

The structural motifs of a Zr$_{50}$Cu$_{45}$Al$_{5}$ metallic glass were learned from atomistic models using a new structure analysis method called motif extraction that employs point-pattern matching and machine learning clustering techniques. The motifs are the nearest-neighbor building blocks of the glass and reveal a well-defined hierarchy of structures as a function of coordination number. Some of the motifs are icosahedral or quasi-icosahedral in structure, while others take on the structure of the most close-packed geometries for each coordination number. These results set the stage for developing clearer structure-property connections in metallic glasses. Motif extraction can be applied to any disordered material to identify its structural motifs without the need for human input.

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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