Automatic Collection and Visualization of the Models Given by Thorough Search Analysis and Its Application to the MoO3 EXAFS Analysis

Kido, Daiki; Wada, Takahiro; Asakura, Kiyotaka

E-journal of surface science and nanotechnology, 2023

Permalink : https://hdl.handle.net/2115/89750

このアイテムのアクセス数:331件（2026-10-09 05:36 集計）

ファイル	フォーマット	サイズ	閲覧回数	説明
https://doi.org/10.1380/ejssnt.2023-026			24

アクセス権	open access
URI	https://hdl.handle.net/2115/89750
タイトル	Automatic Collection and Visualization of the Models Given by Thorough Search Analysis and Its Application to the MoO3 EXAFS Analysis
著者	Kido, Daiki ; Wada, Takahiro ; Asakura, Kiyotaka
著者名 Kido, Daiki
著者名 Wada, Takahiro
e-Rad_Researcher 60175164 著者名 Asakura, Kiyotaka
言語	英語
キーワード	EXAFS
	Thorough search method
	Machine learning
	K-means
	PCA
発行日	2023-06-12
出版者	日本表面科学会, The Surface Science Society of Japan, SSSJ
収録物名	E-journal of surface science and nanotechnology
抄録	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.
資源タイプ	学術雑誌論文
出版タイプ	Version of Record
PISSN	1348-0391
関連情報 (isIdenticalTo)	出版社版DOI https://doi.org/10.1380/ejssnt.2023-026