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Quantitative Analysis of X-Ray Spectral Data for a Mixture of Compounds Using Machine-Learning Algorithms

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Abstract

Based on machine-learning algorithms, a method is developed for determining the structural parameters of the components of a mixture from X-ray absorption spectra. For each component, a database of spectra is constructed for all possible deformations of its structure. The machine-learning method implemented in the PyFitIt software package allows quick calculation of the spectrum for deformations of structures from the considered family and optimization of the structural parameters of the mixture by fitting the theoretical spectrum to the experimental one. The capabilities of the method are examined by analyzing changes in the structural characteristics and concentrations of the components of the mixture for the bis-dioxolene complex of cobalt with functionalized iminopyridine ligands during its valence-tautomeric interconversion depending on temperature.

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Funding

This work was supported by the Council for Grants of the President of the Russian Federation for Young Scientists (Grant no. MK-2730.2019.2).

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Authors and Affiliations

  1. International Research Institute of Intellectual Materials, Southern Federal University, 344090, Rostov-on-Don, Russia

    A. S. Algasov, S. A. Guda, A. A. Guda, Yu. V. Rusalev & A. V. Soldatov

  2. Institute of Mathematics, Mechanics and Computer Science, Southern Federal University, 344090, Rostov-on-Don, Russia

    A. S. Algasov & A. A. Guda

Authors
  1. A. S. Algasov
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  2. S. A. Guda
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  3. A. A. Guda
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  4. Yu. V. Rusalev
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  5. A. V. Soldatov
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Corresponding authors

Correspondence to A. S. Algasov or A. A. Guda.

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Algasov, A.S., Guda, S.A., Guda, A.A. et al. Quantitative Analysis of X-Ray Spectral Data for a Mixture of Compounds Using Machine-Learning Algorithms. J. Surf. Investig. 15, 495–501 (2021). https://doi.org/10.1134/S1027451021030034

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  • DOI: https://doi.org/10.1134/S1027451021030034

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