Fig. 2: Fabrication details, classification method and molecular variables. | npj Computational Materials

Fig. 2: Fabrication details, classification method and molecular variables.

From: Data-driven optimization and machine learning analysis of compatible molecules for halide perovskite material

Fig. 2

a Fabrication steps to obtain 96 molecule-modified perovskite films in photoelectrochemical experiments, including introduction of precursor additives, solvents and post-treatment dye sensitizers. b Data visualization of photocurrents from the photoelectrochemical experiments. The photocurrent data are classified into two groups (’stable’ and ’unstable’) to represent the aqueous optoelectronic stability of the thin film materials. The label ’1’ represents the ’stable’ hybrid materials if 0.9 < residue index < 1.1, while the others (residue index ≥1.1 or ≤0.9) correspond to ’unstable’ systems and are labeled as ’0’. A total of 384 (96 materials × 4 measurements) photocurrent data points are collected. c Experimental variables (solvent ratio, additive and post-treatment molecule) to fabricate the surface molecule-modified CH3NH3PbI3 nanocomposite system.

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