Artificial intelligence-aided preparation of perovskite SrFexZr1-xO3-δ catalysts for ozonation degradation of organic pollutant concentrated water after membrane treatment. (March 2023) - Wang, Xu; Zhang, Yanan; Zhang, Cheng; Wei, Huangzhao; Jin, Haibo; Mu, Zhao; Chen, Xiaofei; Chen, Xinru; Wang, Ping; Guo, Xiaoyan; Ding, Fuchen; Liu, Xiaowei; et al.
Abstract: Membrane technology has been widely used to treat wastewater from a variety of industries, but it also results in a large amount of concentrated wastewater containing organic pollutants after membrane treatment, which is challenging to decompose. Here in this work, a series of perovskite SrFex Zr1-x O3-δ catalysts were prepared via a modified co-precipitation method and evaluated for catalytic ozone oxidative degradation of m-cresol. An artificial neural intelligence networks (ANN) model was employed to train the experimental data to optimize the preparation parameters of catalysts, with SrFe0.13 Zr0.87 O3-δ being the optimal catalysts. The resultant catalysts before and after reduction were then thoroughly characterized and tested for m-cresol degradation. It was found that the co-doping of Fe and Zr at the B-site and the improvement of oxygen vacancies and oxygen active species by reduction dramatically increased TOC removal rates up to 5 times compared with ozone alone, with the conversion rate of m-cresol reaching 100%. We also proposed a possible mechanism for m-cresol degradation via investigating the intermediates using GC-MS, and confirmed the good versatility of the reduced SrFe0.13 Zr0.87 O3-δ catalyst to remove other common organic pollutants in concentrated wastewater. This work demonstrates new prospects for the use of perovskite materials in wastewater treatment. Graphical abstract: Image 1 Highlights: Preparation of perovskite SrFe x Zr 1-x O 3-δ catalysts using a modified co-precipitation method. Cross-validation using neural network models (AI) and experimental data to optimize catalysts-. Reduction treatment improves SrFe 0.13 Zr 0.87 O 3-δ oxygen vacancies and catalytic activity. SrFe 0.13 Zr 0.87 O 3-δ generates reactive radicals to improve the reaction rate of CWOO.