表題番号：2019C-646
日付：2020/03/18
研究課題機械学習による構造相転移する有機結晶の開拓
| 研究者所属（当時） | 資格 | 氏名 | |
|---|---|---|---|
| （代表者） | データ科学総合研究教育センター | 講師 | 谷口 卓也 |
- 研究成果概要
- The structural phase transition of molecular crystals is a mechanism to exhibit and/or regulate materials’ properties such as electromagnetic effects and actuation response. While the development of crystals with phase transition is of substantial importance, it has been still difficult to predict the occurrence which molecular crystals afford the rare phenomenon. To solve this problem, I tried to find efficient descriptors to account for a structural phase transition. In the first step, I compared available crystallographic software as to usability and interpretability. I tested COMPACK implemented in Mercury, XPac, CrystalCMP, CrystalExplore. Based on the comparison of some crystal data, XPac was useful to compare a small number of isostructural crystals, and CrystalCMP was useful for dendrogram visualization when the amount of data is much more. CrystalExplore can visualize intermolecular interaction as Hirshfeld surface and plot. It has an advantage in the interpretability of structural factors for a phase transition. Currently, some polymorphic crystals data are analyzed by the visualization and the obtained descriptors with these software.