Issue 29, 2018

Automated crystal characterization with a fast neighborhood graph analysis method

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

Supplementary files

Article information

Article type
Paper
Submitted
09 May 2018
Accepted
30 Jun 2018
First published
04 Jul 2018

Soft Matter, 2018,14, 6083-6089

Author version available

Automated crystal characterization with a fast neighborhood graph analysis method

W. F. Reinhart and A. Z. Panagiotopoulos, Soft Matter, 2018, 14, 6083 DOI: 10.1039/C8SM00960K

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