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Review of computational approaches to predict the thermodynamic stability of inorganic solids

  • Computational Materials Design
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Abstract

Improvements in the efficiency and availability of quantum chemistry codes, supercomputing centers, and open materials databases have transformed the accessibility of computational materials design approaches. Thermodynamic stability predictions play a central role in the efficacy of these approaches and should be considered carefully. This review covers the fundamentals of calculating thermodynamic stability using first-principles methods. Stability is delineated into two main topics—stability with respect to decomposition into competing phases and stability with respect to phase transition into alternative structures at fixed composition. For each topic, a summary of the state-of-the-art is provided along with a tutorial overview of practical considerations. The application of machine learning to both kinds of stability predictions is also covered. Finally, the limitations of thermodynamic stability predictions are discussed within the context of predicting the synthesizability of materials.

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Acknowledgements

This work was supported as part of GENESIS: A Next Generation Synthesis Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award Number DESC0019212. The author gratefully acknowledges the input of Matthew McDermott and Nathan Szymanski, who provided essential feedback on an early draft of this work. The author would also like to acknowledge Prof. Gerbrand Ceder, Dr. Aaron Holder, Dr. Stephan Lany, Prof. Charles Musgrave, Prof. Vladan Stevanović, and Prof. Wenhao Sun for extensive discussions on the thermodynamic properties of materials over the last several years.

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    Christopher J. Bartel

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Bartel, C.J. Review of computational approaches to predict the thermodynamic stability of inorganic solids. J Mater Sci 57, 10475–10498 (2022). https://doi.org/10.1007/s10853-022-06915-4

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