fig5

Figure 5. (A) Parity plots are shown for predictive models trained using 90% of the CdTe + CdSe + CdS dataset as the training set, with performances shown for the training, test and out-of-sample points using the elemental and unit cell defect descriptors. Copyright 2020, Springer Nature, Reproduced with permission^[126]; (B) Performance of the developed model for band gap estimation. Copyright 2024, American Chemical Society, Reproduced with permission^[127]; (C) Schematic workflow of the present study and parity plot between CGCNN-predicted and DFT (PBESol)-calculated. Copyright 2024, Springer Nature, Reproduced with permission^[128]. CGCNN: Crystal graph convolutional neural network; DFT: density functional theory.