fig6

Figure 6. (A) ML workflow for predicting band alignment types in 2D hybrid perovskites. Feature contributions of the finally selected nine features towards output Y. Confusion matrix for the type I and II classification of considered 2D perovskite. Copyright 2023, Royal Society of Chemistry, Reproduced with permission^[129]; (B) Electronic structures of VOHPs fluctuate over a 5 ps (5,000 snapshots) period at 300 K, with histograms showing band gaps, VBM, and CBM energies along AIMD trajectories, and mutual information between band gap and critical structural features; (C) Displays excited-state charge carrier dynamics under ambient conditions, tracking nonradiative electron-hole recombination over time, absolute NAC values between VBM and CBM over 5 ps, and mutual information of NAC with structural features. Copyright 2024, American Chemical Society, Reproduced with permission^[130]. ML: Machine learning; 2D: two-dimensional; VOHPs: vacancy-ordered halide perovskites; VBM: valence band maximum; CBM: conduction band minimum; AIMD: ab initio molecular dynamics; NAC: nonadiabatic coupling.