2021/04/05 by Fabio Iesari, Iesari, Fabio, Hiroyuki Setoyama +15
Materials Science · Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Statistics and Probability (physics.data-an) #X-ray Diffraction in Crystallography #X-ray Spectroscopy and Fluorescence Analysis
paper · pdf · doi:10.48550/arxiv.2104.01805
openalex publication_date 2021/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Analysis of extended X-ray absorption fine structure (EXAFS) data by the use of sparse modeling is presented. We consider the two-body term in the n-body expansion of the EXAFS signal to implement the method, together with calculations of amplitudes and phase shifts to distinguish between different back-scattering elements. Within this approach no a priori assumption about the structure is used, other than the elements present inside the material. We apply the method to the experimental EXAFS signal of metals and oxides, for which we were able to extract the radial distribution function peak positions, and the Debye-Waller factor for first neighbors.