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arXiv · 2207.12548

Quantification of Crystal Packing Similarity from Spherical Harmonic Transform

Qiang Zhu·Weilun Tang·Shinnosuke Hattori
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Abstract

In this work, we present a new computational approach to characterize and classify molecular packing in the solid states. The key idea is to project each neighboring molecule (or short contact) from the centered molecule into a unit sphere according to the interaction energy. Consequently, the similarity between two spherical images can be evaluated from the spherical harmonics expansion based on the maximum cross-correlation. We apply this approach to successfully reproduce the previous packing assignment on a small amount of data with an improved categorization. Furthermore, we conduct a packing similarity analysis over 2000 hydrocarbon crystal data sets and uncover a set of abundant packing motifs. Unlike the previous approaches based on the subjective visual comparison at the real space, our approach provides a more robust way to measure the packing similarity, thus paving the way for a rapid classification of large scale crystal data.

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Qiang Zhu, Weilun Tang, Shinnosuke Hattori. 2022-07-25. Quantification of Crystal Packing Similarity from Spherical Harmonic Transform. https://doi.org/10.1021/acs.cgd.2c00933

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