Automated crystal characterization with a fast neighborhood graph analysis method†,Soft Matter

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Automated crystal characterization with a fast neighborhood graph analysis method†
Soft Matter ( IF 2.9 ) Pub Date : 2018-07-04 00:00:00 , DOI: 10.1039/c8sm00960k
Wesley F. Reinhart _{1,

2,

3,

4} , Athanassios Z. Panagiotopoulos _{1,

2,

3,

4}

Affiliation

We present a significantly improved, very fast implementation of the Neighborhood Graph Analysis technique for template-free characterization of crystal structures [W. F. Reinhart et al., Soft Matter, 2017, 13, 4733]. By comparing local neighborhoods in terms of their relative graphlet frequencies, we reduce the computational cost by four orders of magnitude compared to the original stochastic method. Furthermore, we present protocols for the detection of topologically important structures and assignment of visually informative colors, providing a fully automated procedure for characterization of crystal structures from particle tracking data. We demonstrate the flexibility of our method on a wide range of crystal structures which have proven difficult to classify by previously available techniques.

中文翻译：

使用快速邻域图分析方法自动进行晶体表征†

我们提出了邻域图分析技术的显着改进，非常快速的实现，用于无模板表征晶体结构[WF Reinhart等。，软物质，2017年，13，4733]。通过比较局部邻域的相对小图频率，与原始随机方法相比，我们将计算成本降低了四个数量级。此外，我们提出了用于检测重要拓扑结构和视觉信息色的分配的协议，从而为从粒子跟踪数据中表征晶体结构提供了一种全自动程序。我们证明了我们的方法在多种晶体结构上的灵活性，这些晶体结构已被证明很难通过现有技术进行分类。

更新日期：2018-07-04

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