(10e) New Tolerance Factor to Predict the Stability of Perovskite Oxides and Halides

Bartel, C. J., University of Colorado at Boulder
Sutton, C., Fritz Haber Institute of the Max Planck Society
Goldsmith, B., University of Michigan
Musgrave, C. B., University of Colorado Boulder
Ghiringhelli, L. M., Fritz Haber Institute
Scheffler, M., Fritz-Haber-Institut der Max-Planck-Gesellschaft
Predicting the stability of the perovskite structure remains a longstanding challenge for the discovery of new functional materials for photovoltaics, fuel cells, and many other applications. Using a novel data analytics approach based on SISSO (sure independence screening and sparsifying operator), an accurate, physically interpretable, and one-dimensional tolerance factor, τ, is developed that correctly classifies 92% of compounds as perovskite or nonperovskite for an experimental dataset containing 576 ABX3 materials (X = O2-, F-, Cl-, Br-, I-). In comparison, the widely used Goldschmidt tolerance factor, t, achieves a maximum accuracy of only 74% for the same set of materials. The probability of forming stable perovskites is mapped continuously as a function of the sizes of the A, B, and X ions revealing physical insights into how these relative sizes yield stable and unstable perovskite structures. Additionally, the new tolerance factor is shown to compare well with DFT-calculated decomposition enthalpies of single and double perovskite oxides and chalcogenides. τ is applied to identify more than a thousand inorganic (Cs2BB’Cl6) and hybrid organic-inorganic (MA2BB’Br6) double perovskites that are predicted to be stable.