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Automatic Collection and Visualization of the Models Given by Thorough Search Analysis and Its Application to the MoO3 EXAFS Analysis
| Title: | Automatic Collection and Visualization of the Models Given by Thorough Search Analysis and Its Application to the MoO3 EXAFS Analysis |
| Authors: | Kido, Daiki Browse this author | | Wada, Takahiro Browse this author | | Asakura, Kiyotaka Browse this author →KAKEN DB |
| Keywords: | EXAFS | | Thorough search method | | Machine learning | | K-means | | PCA |
| Issue Date: | 12-Jun-2023 |
| Publisher: | 日本表面科学会, The Surface Science Society of Japan, SSSJ |
| Journal Title: | E-journal of surface science and nanotechnology |
| Publisher DOI: | 10.1380/ejssnt.2023-026 |
| Abstract: | The thorough search (TS) method was introduced to solve the problems in a conventional extended X-ray absorption fine structure analysis method. The TS method gives all possible and rational structures (structure candidates) which can reproduce the experimental data well in the parameter space. However, it still has difficulties how to decide the number of structure candidates without discretion and visualize the parameter sets with dimensions of more than 3. In this paper, we have applied the K-means method and principal component analysis and discussed its merits and drawbacks. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/89750 |
| Appears in Collections: | 触媒科学研究所 (Institute for Catalysis) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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