Synthesis of various nanocomposites and investigation their photocatalytic activities in textile wastewater

Due to the significant water pollution caused by effluent dyes, there is an urgent need to identify effective dye degradation technologies to safeguard human health and the environment. In this study, TPA@h-BN nanocomposites were synthesized by immobilizing TPA, in varying amounts from 10% to 40%, on porous hexagonal boron nitride (h-BN) nanosheets. The 30%TPA@h-BN composite demonstrated superior photocatalytic performance in the degradation of methylene blue (MB) dye. The photocatalytic process was investigated using batch experiments designed by central composite design (CCD). Subsequently, response surface methodology (RSM), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were employed to model the effects of reaction time, catalyst dosage, dye concentration, and stirring speed. Obtained results indicate that the RSM and ANN models possesses higher predictive capability and accuracy compared to ANFIS model. Optimal photocatalytic dye degradation of 95.40% was achieved under the conditions of 240 min of reaction time, 60 mg of photocatalyst dosage, 15 ppm of dye concentration, and a stirring rate of 550 rpm. The findings highlight that dye concentration and catalyst dosage are critical factors influencing the efficiency of photocatalytic activity. The kinetics of photocatalytic degradation for the 30%TPA@h-BN composite were determined to follow a pseudo-first order reaction, in accordance with the Langmuir–Hinshelwood model, with a rate constant (k) of 0.01303 min-1.