固体:原子几何混乱的描述符

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Hagen Eckert, Sebastian A. Kube, Simon Divilov, Asa Guest, Adam C. Zettel, David Hicks, Sean D. Griesemer, Nico Hotz, Xiomara Campilongo, Siya Zhu, Axel van de Walle, Jan Schroers, Stefano Curtarolo
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引用次数: 0

摘要

裁剪材料的性能往往需要了解凝固过程。在这里,我们引入了几何描述符固体,它在数值上捕获了材料的平移无序与有序状态之间的欧几里得传输成本。作为实验平台,我们将液态法应用于玻璃成形金属合金的分类。通过扩展和结合金属薄膜(玻璃/非玻璃)的实验库和aflow.org计算数据库(混合物的几何和能量信息),我们发现溶度和生成焓的组合产生了一个有效的玻璃形成分类器。然后使用这样的分类器来处理金属玻璃的公共数据集,表明Soliquity的玻璃不可知假设对于理解动力学控制的相变是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Soliquidy: a descriptor for atomic geometrical confusion

Soliquidy: a descriptor for atomic geometrical confusion

Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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