Investigation of optical properties of molybdenum trioxide (MoO3) thin films using neural networks

Abstract

Nowadays, transition metal oxide, the semiconductor molybdenum trioxide (MoO3), is a favorable choice because it has several industrial applications and alluring qualities. It has a significant role as an industrial catalyst due to its electrochromic properties. The optical behavior of the MoO3 thin film onto various substrates of the powder of MoO3 was investigated. x-ray diffraction analysis revealed an orthorhombic structure. Measurements of the average crystallite size and dislocation density were obtained, which were 132.8 nm and 5.7× 10–4 nm−2, respectively. Spectrophotometric measurements of transmittance (T) and reflectance (R) at normal incidence in the 300–1400 nm wavelength range of the film onto various substrates were examined. The dispersion and indirect optical transitions and nonlinear optical parameters were identified for glass and quartz substrates. An estimation of the optical behavior of the MoO3 thin film using the artificial neural network (ANN) model was carried out. Experimental data were used as inputs. The optical characterization of ANN modeling outputs provides excellent results. Error values support the success of the modeling process, with a mean squared error value of < 10−1. Moreover, the theoretical equation describing the experimental results was obtained depending on the ANN model, representing the relation between the inputs and outputs. According to the findings of this research, the ANN model can be utilized as an efficient tool to simulate and predict the optical parameters of the MoO3 thin film. Additionally, it can establish strong connections between theoretical and experimental fields.