Automated elucidation of crystal and electronic structures in boron nitride from X-ray absorption spectra using uniform manifold approximation and projection

Abstract

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.