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晶体材料中结构无序的分类与统计分析

Classification and statistical analysis of structural disorder in crystalline materials.

作者信息

Antypov Dmytro, Collins Chris M, Dyer Matthew S, Claridge John B, Rosseinsky Matthew J

机构信息

Leverhulme Research Centre for Functional Materials Design Materials Innovation Factory University of Liverpool Liverpool UK.

Department of Chemistry University of Liverpool Liverpool UK.

出版信息

J Appl Crystallogr. 2025 May 29;58(Pt 3):659-677. doi: 10.1107/S1600576725003000. eCollection 2025 Jun 1.

DOI:10.1107/S1600576725003000
PMID:40475947
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12135987/
Abstract

Approximately 50% of entries in the Inorganic Crystal Structure Database (ICSD; https://www.fiz-karlsruhe.de/en) exhibit some form of structural disorder. This work aims to provide a thorough analysis of structurally disordered materials within the ICSD, using data extracted from crystallographic information files. To achieve this, we derive a classification of structurally disordered crystalline materials described by their spatially averaged structures and introduce a range of quantitative measures of structural disorder. The overarching aim of this classification and analysis is to facilitate high-throughput and machine learning studies of disordered materials. To demonstrate the application of our approach, we perform statistical analysis of the disordered compounds reported in the ICSD to identify general trends in the distribution of disorder across different chemical elements, structures and classes of materials.

摘要

无机晶体结构数据库（ICSD；https://www.fiz-karlsruhe.de/en）中约50%的条目呈现出某种形式的结构无序。这项工作旨在利用从晶体学信息文件中提取的数据，对ICSD内的结构无序材料进行全面分析。为实现这一目标，我们根据空间平均结构对结构无序晶体材料进行分类，并引入了一系列结构无序的定量测量方法。这种分类和分析的总体目标是促进对无序材料的高通量和机器学习研究。为了证明我们方法的应用，我们对ICSD中报告的无序化合物进行统计分析，以确定不同化学元素、结构和材料类别中无序分布的一般趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/6c569299eb04/j-58-00659-fig15.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/6c569299eb04/j-58-00659-fig15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/92539d2ce15c/j-58-00659-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/80f698d448d8/j-58-00659-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/a8d43a35117d/j-58-00659-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/ca688fcce3f8/j-58-00659-fig4.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/1e4f02c9fba2/j-58-00659-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/d4db73bf3d07/j-58-00659-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/86e6c31dd904/j-58-00659-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/9cf90ba71100/j-58-00659-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/3c0c85033792/j-58-00659-fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/5f3b0a1ace34/j-58-00659-fig11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/4ac83f5fae3b/j-58-00659-fig12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/d8c6bf6a9c93/j-58-00659-fig13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/0d2363d1a928/j-58-00659-fig14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/12135987/6c569299eb04/j-58-00659-fig15.jpg

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