Abstract
A complex crystal-chemical analysis of 1567 oxygen positions in 216 crystal structures of lead- containing minerals belonging to the classes of silicates, phosphates, oxides, oxohalides, and a number of others has been carried out. It was shown that the combined application of the bond valence method and the analysis of the geometric characteristics of Voronoi-Dirichlet polyhedra make it possible to confidently distinguish between oxygen positions related to cation structure blocks and oxygen positions for which a description based on an anion-centered approach is more justified. Numerical indicators for such a separation of oxygen positions are substantiated, which can be used to analyze large arrays of structural data using the machine learning approaches.
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