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- W4307644848 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." @default.
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- W4307644848 date "2022-10-27" @default.
- W4307644848 modified "2023-10-18" @default.
- W4307644848 title "Quantification of Crystal Packing Similarity from Spherical Harmonic Transform" @default.
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- W4307644848 doi "https://doi.org/10.1021/acs.cgd.2c00933" @default.
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