Revisiting the Extended X-ray Absorption Fine Structure Fitting Procedure through a Machine Learning-Based Approach.

Autor: Martini A; The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, 344090 Rostov-on-Don, Russia.; Department of Chemistry, University of Torino, Via P. Giuria 7, 10125 Torino, Italy., Bugaev AL; The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, 344090 Rostov-on-Don, Russia.; Southern Scientific Centre, Russian Academy of Sciences, Chekhova 41, 344006 Rostov-on-Don, Russia., Guda SA; The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, 344090 Rostov-on-Don, Russia.; Institute of mathematics, mechanics and computer science, Southern Federal University, Milchakova 8a, 344090 Rostov-on-Don, Russia., Guda AA; The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, 344090 Rostov-on-Don, Russia., Priola E; Department of Chemistry, University of Torino, Via P. Giuria 7, 10125 Torino, Italy.; CrisDi, Interdepartemental Center for Crystallography, University of Turin, Torino, Via P. Giuria 7, I-10125 Italy., Borfecchia E; Department of Chemistry, University of Torino, Via P. Giuria 7, 10125 Torino, Italy., Smolders S; Department of Microbial and Molecular Systems (M2S); Centre for Membrane separations, Adsorption, Catalysis and Spectroscopy for Sustainable Solutions (cMACS), KU Leuven, Celestijnenlaan 200F, Post box 2454, 3001 Leuven, Belgium., Janssens K; Department of Microbial and Molecular Systems (M2S); Centre for Membrane separations, Adsorption, Catalysis and Spectroscopy for Sustainable Solutions (cMACS), KU Leuven, Celestijnenlaan 200F, Post box 2454, 3001 Leuven, Belgium., De Vos D; Department of Microbial and Molecular Systems (M2S); Centre for Membrane separations, Adsorption, Catalysis and Spectroscopy for Sustainable Solutions (cMACS), KU Leuven, Celestijnenlaan 200F, Post box 2454, 3001 Leuven, Belgium., Soldatov AV; The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, 344090 Rostov-on-Don, Russia.
Jazyk: angličtina
Zdroj: The journal of physical chemistry. A [J Phys Chem A] 2021 Aug 19; Vol. 125 (32), pp. 7080-7091. Date of Electronic Publication: 2021 Aug 05.
DOI: 10.1021/acs.jpca.1c03746
Abstrakt: A novel approach for the analysis of extended X-ray absorption fine structure (EXAFS) spectra is developed exploiting an inverse machine learning-based algorithm. Through this approach, it is possible to explore and account for, in a precise way, the nonlinear geometry dependence of the photoelectron backscattering phases and amplitudes of single and multiple scattering paths. In addition, the determined parameters are directly related to the 3D atomic structure, without the need to use complex parametrization as in the classical fitting approach. The applicability of the approach, its potential and the advantages over the classical fit were demonstrated by fitting the EXAFS data of two molecular systems, namely, the KAu (CN) 2 and the [RuCl 2 (CO) 3 ] 2 complexes.
Databáze: MEDLINE