Automated crystal characterization with a fast neighborhood graph analysis method

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,...

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Bibliographic Details
Published inSoft matter Vol. 14; no. 29; pp. 6083 - 6089
Main Authors Reinhart, Wesley F, Panagiotopoulos, Athanassios Z
Format Journal Article
LanguageEnglish
Published England Royal Society of Chemistry 2018
Subjects
Automation
Computer applications
Crystal structure
Particle tracking
Stochasticity
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Summary: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.
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ISSN:1744-683X
1744-6848
DOI:10.1039/c8sm00960k