Efficient and easily recyclable photocatalytic reduction of Se(IV) from wastewater using stable TiO2/BiOBr/cloth: Mechanism insight and machine learning modeling

[Display omitted] •Novel TiO2/BiOBr/cloth was synthesized and applied for Se(IV) removal.•The TiO2/BiOBr/cloth has excellent stability and reusability, as well as its easy recyclability.•The mechanism of catalyst photocatalytic reduction of Se(IV) was elucidated.•The ANN and LSTM models were developed and tested for predicting Se(IV) removal rate. Photocatalytic technology is extensively employed for the reductive removal of water contaminants; however, it contends with low catalytic efficiency and challenges in catalyst recovery. In this study, we propose integrating experimental procedures with artificial intelligence modeling to enhance the purification of Se(IV)-contaminated wastewater. We present an efficient, easily recyclable, and cost-effective strategy for photocatalyst fabrication. Specifically, we develop a novel method for Se(IV) removal by immobilizing TiO2/BiOBr onto glass fiber cloth surfaces using chitosan for Se(IV) reduction in aqueous solutions. The TiO2/BiOBr/cloth (TB-4/cloth) catalyst achieves a remarkable 99.2 % Se(IV) removal within 2 h under visible light and maintains excellent Se(IV) reduction photocatalytic activity (86.4 %) even after eight cycles, remaining easily reusable. Additionally, we develop two machine learning models, namely artificial neural network (ANN) and long short-term memory (LSTM), to validate the anticipated experimental outcomes. Both models exhibit high accuracy and predictive capability (R2 > 0.99, RMSE