Abstract
The Pauling rules have been used for decades to rationalise the crystal structures of ionic compounds. Despite their importance, there has been no statistical assessment of the performances of these five empirical rules so far. Here, we rigorously and automatically test all five Pauling rules for a large data set of around 5000 known oxides. We discuss each Pauling rule separately, stressing their limits and range of application in terms of chemistries and structures. We conclude that only 13 % of the oxides simultaneously satisfy the last four rules, indicating a much lower predictive power than expected.
Highlights
Understanding and predicting the crystal structure of inorganic materials is an important goal of chemistry
Building on recent advances in crystal structure analysis tools including the automatic identification of local environments and their connectivity,9, 10, 11 we report here on the first statistical evaluation of the Pauling rules on several thousands of compounds
Our analysis relies on the use of a tool for automatic local environment detection on a set of oxides coming from the Inorganic Crystal Structure Database (ICSD) and present in the Materials Project database
Summary
Understanding and predicting the crystal structure of inorganic materials is an important goal of chemistry. The Pauling rules apply to ionic compounds and describe what are the preferred local environments of a cation and how these environments connect to each other These rules have become a cornerstone of solid-state chemistry and remain the main empirical theory rationalizing crystal structure stability. Pauling developed these five rules by combining his knowledge of inorganic crystal structures and simple electrostatic arguments. They have not been yet assessed statistically on a large scale The absence of such a rigorous assessment of the validity of the Pauling rules inhibits their use for true prediction and prevents the development of improved and alternative rules. Our work shines light on their strengths and limits, enables their more cautious use and offers a first necessary step towards their future improvement
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