Abstract
Bismuth oxychloride is a lamellar semiconductor with fascinating features in photocatalysis due to its excellent charge storage capacity, sufficient reduction/oxidation potentials, stable chemical properties, wide distribution of elements, and low toxicity. The wider application of this semiconductor for many technological and industrial applications is hindered by the resistive factors of wide band gap and the ease of recombination of photo-generated electrons and holes. Oxygen vacancy creation in bismuth oxychloride semiconductor controls and adjusts the band gap to the desired spectrum region and subsequently acts like electron trapping centers for the prevention of carrier's re-union. The formation of oxygen vacancy peaks for the lattice and adsorbed oxygen species in the de-convoluted O 1s spectra of x-ray photoelectron spectroscopy (XPS) at a particular value of binding energy experimentally confirms oxygen vacancy creation for photocatalytic activity enhancement. This work focuses on modeling the energy gap (Eg) of bismuth oxychloride semiconductor with oxygen vacancies using the binding energy (BE) of the de-convoluted O 1s lattice oxygen and oxygen vacancy as descriptors through hybrid particle swarm-based support vector regression (PSVR) model as well as stepwise regression (STR) model. The developed PSVR-Eg model shows performance improvement of 23.38%, 55.96%, and 66.54% over the STR-Eg model on the basis of the coefficient of correlation, root means square error, and mean absolute error. The developed PSVR-Eg further predicts the influence of lattice oxygen and oxygen vacancy on the energy gap of the semiconductor. The characteristic precision, accuracy, and quickness of the developed models are highly meritorious in determining the level of oxygen vacancy that adjusts the semiconductor energy gap to the desired value for photocatalytic activity enhancement at a reduced cost and without experimental stress.
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•Hybrid PSVR-Eg model was developed for determining band gap of bismuth oxychloride.•PSVR-Eg outperforms STR-Eg using lattice oxygen and oxygen vacancy descriptors.•Significance of lattice oxygen and oxygen vacancy on band gap was investiaged•Estimates of PSVR-Eg show persitence closeness with the measured band gap.