Quantification of Crystal Packing Similarity from Spherical Harmonic Transform
Quantification of Crystal Packing Similarity from Spherical Harmonic Transform
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DOI：
10.1021/acs.cgd.2c00933
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发表时间：
2022-10-27
影响因子：
3.8
通讯作者：
Hattori，Shinnosuke
中科院分区：
文献类型：
--
作者：
Zhu，Qiang;Tang，Weilun;Hattori，Shinnosuke
在这项工作中，我们提出了一种新的计算方法来表征和分类固态分子堆积。关键思想是根据相互作用能将每个相邻分子（或短接触）从中心分子投射到单位球体中。因此，可以根据基于最大互相关的球谐波展开来评估两个球面图像之间的相似性。我们应用这种方法成功地在少量数据上重现了先前的打包分配，并改进了分类。此外，我们对 2000 个碳氢化合物晶体数据集进行了堆积相似性分析，发现了一组丰富的堆积图案。与之前基于真实空间的主观视觉比较的方法不同，我们的方法提供了一种更稳健的方法来测量堆积相似性，从而为大规模晶体数据的快速分类铺平了道路。
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.