fig10

Machine learning-enabled optoelectronic material discovery: a comprehensive review

Figure 10. (A) Scheme of the proposed target-driven method. Selection of A-, B- and X-site elements, data generation based on the combination of selected elements, use of tolerance factor. Schematic diagram of feature engineering and ML technology. Calculations of crystal structures, electronic structures and thermodynamic stabilities of final candidates by DFT. Copyright 2021, Elsevier, Reproduced with permission[146]; (B) The impact of formation energy on the prediction results of energy above the hull is depicted; (C) The prediction results of the bandgap and the heatmap of features based on the SHAP values. Copyright 2024, Wiley, Reproduced with permission[147]. ML: Machine learning; DFT: density functional theory; SHAP: Shapley Additive exPlanations.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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