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.

基于机器学习算法，开发了一种从 X 射线吸收光谱确定混合物组分结构参数的方法。对于每个组件，为其结构的所有可能变形构建光谱数据库。PyFitIt 软件包中实现的机器学习方法允许快速计算所考虑的族结构变形的频谱，并通过将理论频谱拟合到实验频谱来优化混合物的结构参数。