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Automated crystal characterization with a fast neighborhood graph analysis method

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Abstract

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.

Graphical abstract: Automated crystal characterization with a fast neighborhood graph analysis method

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Publication details

The article was received on 09 May 2018, accepted on 30 Jun 2018 and first published on 04 Jul 2018


Article type: Paper
DOI: 10.1039/C8SM00960K
Citation: Soft Matter, 2018, Advance Article
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    Automated crystal characterization with a fast neighborhood graph analysis method

    W. F. Reinhart and A. Z. Panagiotopoulos, Soft Matter, 2018, Advance Article , DOI: 10.1039/C8SM00960K

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