New tolerance factor to predict the stability of perovskite oxides and halides
Abstract
Predicting the stability of the perovskite structure remains a long-standing challenge for the discovery of new functional materials for many applications including photovoltaics and electrocatalysts. We developed an accurate, physically interpretable, and one-dimensional tolerance factor, τ, that correctly predicts 92% of compounds as perovskite or nonperovskite for an experimental dataset of 576 ABX3 materials (X = O2–, F–, Cl–, Br–, I–) using a novel data analytics approach based on SISSO (sure independence screening and sparsifying operator). τ is shown to generalize outside the training set for 1034 experimentally realized single and double perovskites (91% accuracy) and is applied to identify 23,314 new double perovskites (A2BB'X6) ranked by their probability of being stable as perovskite. Furthermore, this work guides experimentalists and theorists toward which perovskites are most likely to be successfully synthesized and demonstrates an approach to descriptor identification that can be extended to arbitrary applications beyond perovskite stability predictions.
- Authors:
-
[1];
[3];
[4];
[2];
- Univ. of Colorado, Boulder, CO (United States)
- Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin (Germany)
- Univ. of Michigan, Ann Arbor, MI (United States)
- Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Hydrogen Fuel Cell Technologies Office
- OSTI Identifier:
- 1496850
- Report Number(s):
- NREL/JA-5K00-73346
Journal ID: ISSN 2375-2548
- Grant/Contract Number:
- AC36-08GO28308
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Science Advances
- Additional Journal Information:
- Journal Volume: 5; Journal Issue: 2; Journal ID: ISSN 2375-2548
- Publisher:
- AAAS
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; perovskites; functional materials; photovoltaics; electrocatalysts
Citation Formats
Bartel, Christopher J., Sutton, Christopher, Goldsmith, Bryan R., Ouyang, Runhai, Musgrave, Charles B., Ghiringhelli, Luca M., and Scheffler, Matthias. New tolerance factor to predict the stability of perovskite oxides and halides. United States: N. p., 2019.
Web. doi:10.1126/sciadv.aav0693.
Bartel, Christopher J., Sutton, Christopher, Goldsmith, Bryan R., Ouyang, Runhai, Musgrave, Charles B., Ghiringhelli, Luca M., & Scheffler, Matthias. New tolerance factor to predict the stability of perovskite oxides and halides. United States. https://doi.org/10.1126/sciadv.aav0693
Bartel, Christopher J., Sutton, Christopher, Goldsmith, Bryan R., Ouyang, Runhai, Musgrave, Charles B., Ghiringhelli, Luca M., and Scheffler, Matthias. Fri .
"New tolerance factor to predict the stability of perovskite oxides and halides". United States. https://doi.org/10.1126/sciadv.aav0693. https://www.osti.gov/servlets/purl/1496850.
@article{osti_1496850,
title = {New tolerance factor to predict the stability of perovskite oxides and halides},
author = {Bartel, Christopher J. and Sutton, Christopher and Goldsmith, Bryan R. and Ouyang, Runhai and Musgrave, Charles B. and Ghiringhelli, Luca M. and Scheffler, Matthias},
abstractNote = {Predicting the stability of the perovskite structure remains a long-standing challenge for the discovery of new functional materials for many applications including photovoltaics and electrocatalysts. We developed an accurate, physically interpretable, and one-dimensional tolerance factor, τ, that correctly predicts 92% of compounds as perovskite or nonperovskite for an experimental dataset of 576 ABX3 materials (X = O2–, F–, Cl–, Br–, I–) using a novel data analytics approach based on SISSO (sure independence screening and sparsifying operator). τ is shown to generalize outside the training set for 1034 experimentally realized single and double perovskites (91% accuracy) and is applied to identify 23,314 new double perovskites (A2BB'X6) ranked by their probability of being stable as perovskite. Furthermore, this work guides experimentalists and theorists toward which perovskites are most likely to be successfully synthesized and demonstrates an approach to descriptor identification that can be extended to arbitrary applications beyond perovskite stability predictions.},
doi = {10.1126/sciadv.aav0693},
journal = {Science Advances},
number = 2,
volume = 5,
place = {United States},
year = {2019},
month = {2}
}
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Figures / Tables:
Fig. 1: Perovskite structure and composition. (A) ABX3, in the cubic single perovskite structure (Pm$\overline{3}$m), where the A cation is surrounded by a network of cornersharing BX6 octahedra. (B) A2BB′X6, in the rock salt double perovskite structure (Fm $\overline{3}$m), where the A cations are surrounded by an alternating network ofmore »
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