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arXiv · 2308.11816

Assessing Thermodynamic Selectivity of Solid-State Reactions for the Predictive Synthesis of Inorganic Materials

Abstract

Synthesis is a major challenge in the discovery of new inorganic materials. Currently, there is limited theoretical guidance for identifying optimal solid-state synthesis procedures. We introduce two selectivity metrics, primary and secondary competition, to assess the favorability of target/impurity phase formation in solid-state reactions. We used these metrics to analyze 3,520 solid-state reactions in the literature, ranking existing approaches to popular target materials. Additionally, we implemented these metrics in a data-driven synthesis planning workflow and demonstrated its application in the synthesis of barium titanate (BaTiO$_3$). Using an 18-element chemical reaction network with first-principles thermodynamic data from the Materials Project, we identified 82,985 possible BaTiO$_3$ synthesis reactions and selected nine for experimental testing. Characterization of reaction pathways via synchrotron powder X-ray diffraction reveals that our selectivity metrics correlate with observed target/impurity formation. We discovered two efficient reactions using unconventional precursors (BaS/BaCl$_2$ and Na$_2$TiO$_3$) that produce BaTiO$_3$ faster and with fewer impurities than conventional methods, highlighting the importance of considering complex chemistries with additional elements during precursor selection. Our framework provides a foundation for predictive inorganic synthesis, facilitating the optimization of existing recipes and the discovery of new materials, including those not easily attainable with conventional precursors.

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BibTeXRIS

Matthew J. McDermott, Brennan C. McBride, Corlyn Regier, Gia Thinh Tran, Yu Chen, Adam A. Corrao, Max C. Gallant, Gabrielle E. Kamm, Christopher J. Bartel, Karena W. Chapman, Peter G. Khalifah, Gerbrand Ceder, James R. Neilson, Kristin A. Persson. 2023-09-27. Assessing Thermodynamic Selectivity of Solid-State Reactions for the Predictive Synthesis of Inorganic Materials. https://doi.org/10.1021/acscentsci.3c01051

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