2025-11-10 東京理科大学,東京大学,東京科学大学,筑波大学,科学技術振興機構
図1： 今回開発した手法の概要
窒化ホウ素(BN)を対象として、シミュレーションにより獲得したXASスペクトルをUMAPというアルゴリズムを用いて自動解析した。
＜関連情報＞
- https://www.tus.ac.jp/today/archive/20251104_1297.html
- https://www.nature.com/articles/s41598-025-18580-z
均一多様体近似と投影を用いたX線吸収スペクトルからの窒化ホウ素の結晶構造と電子構造の自動解明 Automated elucidation of crystal and electronic structures in boron nitride from X-ray absorption spectra using uniform manifold approximation and projection
Reika Hasegawa,Arpita Varadwaj,Alexandre Lira Foggiatto,Masahito Niibe,Takahiro Yamazaki,Masafumi Horio,Yasunobu Ando,Takahiro Kondo,Iwao Matsuda &Masato Kotsugi
Scientific Reports Published:10 November 2025
DOI:https://doi.org/10.1038/s41598-025-18580-z
Abstract
X-ray absorption spectroscopy (XAS) provides valuable information on the structure and electronic states of materials. Its spectral profiles are complex, influenced by crystal structure and defects, and require extensive expertise for conventional analysis. This study presents an automated XAS analysis approach using various dimension reduction methods to characterize crystal and electronic structure. We show that, Uniform Manifold Approximation and Projection (UMAP), outperforms traditional methods such as Principal Component Analysis (PCA) and Multidimensional Scaling (MDS) in capturing the key features of complex spectra. Applying UMAP to simulated XAS spectra of boron nitride (BN), high-dimensional data can be precisely classified by crystal system, defect type, and structural dimensionality. By correlating UMAP-derived embeddings with electronic states, we identify nontrivial electronic properties. The successful application of this model to experimental data demonstrates its potential for autonomous structural identification, offering new possibilities for data-driven materials design and advancing novel material development.
