Prediction of Phase Formation in Layered Perovskite Arsenic Fluorides

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Abstract We identify a phase formation indicator that is generally unknown in multinary compounds and use it to predict phase formation in new materials. In particular, we focus on layered perovskite compounds as a typical example of multinary systems to identify indicators as mathematical formulas (phase formation determinants) that can be used to predict phase formation in this system. Using hundreds of experimental data on the phase formation, we developed machine learning models to predict the phase formation in new layered perovskite arsenic fluorides.

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