Abstract
Quaternary perovskite solar cells are being extensively studied, with the goal of increasing solar cell efficiency and securing stability by changing the ratios of methylammonium, formamidinium, I3, and Br3. However, when the stoichiometric ratio is changed, the photoelectric properties reflect those of different materials, making it difficult to study the physical properties of the quaternary perovskite. In this study, the optical properties of perovskite materials with various stoichiometric ratios were measured using ellipsometry, and the results were analyzed using an optical simulation model. Because it is difficult to analyze the spectral pattern according to composition using the existing method of statistical regression analysis, an artificial neural network (ANN) structure was constructed to enable the hyperregression analysis of n-dimensional variables. Finally, by inputting the stoichiometric ratios used in the fabrication and the wavelength range to the trained artificial intelligence model, it was confirmed that the optical properties were similar to those measured with an ellipsometer. The refractive index and extinction coefficient extracted through the ellipsometry analysis show a tendency consistent with the color change of the specimen, and have a similar shape to that reported in the literature. When the optical properties of the unmodified perovskite are predicted using the verified artificial intelligence model, a very complex change in pattern is observed, which is impossible to analyze with a general regression method. It can be seen that this change in optical properties is well maintained, even during rapid variations in the pattern according to the change in composition. In conclusion, hyperregression analysis with n-dimensional variables can be performed for the spectral patterns of thin-film materials using a simple big data construction method.
Highlights
The ratios of methyl ammonium (MA), FA, I3, Br3, and wavelengths within the range of 300–900 nm were continuously input into the constructed AI model, and the predicted refractive index and extinction coefficient for each wavelength were compared with the measurement results
It is judged that this error increases as the number of irregular patterns of the optical characteristic spectrum increases, and in the case of refractive index, since the irregularity of this spectrum is larger than the extinction coefficient, it is thought that it can be improved by collecting more specimen information
The optical properties of perovskite materials according to the stoichiometric ratio were measured using ellipsometry, and the measured results were analyzed using an optical simulation model
Summary
Lead–halogen perovskite materials are being increasingly used in solar cells as light absorbers. Such materials were first reported in 1978, and their utility in opto-electronic fields has been studied by applying them to devices such as photodetectors and lasers [1–6]. Owing to the advantageous optical and electrical properties of these materials, they have been the focus of considerable interest, especially in the photovoltaic industry. The first solar cell manufactured using the organic–inorganic lead halide perovskite compounds
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