Abstract
Crystallographic stability is an important factor that affects the stability of perovskites. The stability dictates the commercial applications of lead-based organometal halide perovskites. The tolerance factor (t) and octahedral factor (μ) form the state-of-the-art criteria used to evaluate the perovskite crystallographic stability. We studied the crystallographic stabilities of halide and chalcogenide perovskites by exploring an effective alternative descriptor, the global instability index (GII) that was used as an indicator of the stability of perovskite oxides. We particularly focused on determining crystallographic reliability by calculating GII. We analyzed the bond valence models of the 243 halide and chalcogenide perovskites that occupied the lowest-energy cubic-phase structures determined by conducting the first-principles-based total energy minimization calculations. The decomposition energy (ΔHD) reflects the thermodynamic stability of the system and is considered as the benchmark that helps assess the effectiveness of GII in evaluating the crystallographic stability of the systems under study. The results indicated that the accuracy of predicting thermodynamic stability was significantly higher when GII (73.6%) was analyzed compared to the cases when t (55%) and μ (39.1%) were analyzed to determine the stability. The results obtained from the machine learning-based data mining method further indicate that GII is an important descriptor of the stability of the perovskite family.
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