Photocatalytic degradation of 2,4,6-trinitrotoluene (TNT) in the presence of ZnS, NiS and ZnS/NiS supported Clinoptilolite under UV irradiation: experimental and neural network modelling

Abstract

ABSTRACT The Photocatalytic degradation of 2,4,6-trinitrotoluene (TNT), catalysed by nanosized ZnS, NiS and ZnS/NiS photocatalysts, was studied under UV irradiation. ZnS, NiS and ZnS/NiS nanoparticles were incorporated onto Iranian natural Clinoptilolite (CP) zeolite by calcination of Zn+2and Ni+2 ion-exchanged Clinoptilolite. The photocatalysts were characterised by the TEM, FT-IR, XRD, DRS, UV-VIS, HPLC and COD methods. The average particle size of different photocatalysts incorporated onto CP was calculated through XRD analyzes between 70–40 µm. The degradation extent of TNT was investigated by UV–Vis spectrophotometry, COD and HPLC. The influence of pH, concentration of TNT in aqueous solution, contact time, amount of photocatalysts and concentration of ion exchange solution on the degradation efficiency has also been studied. After 160 minutes of photocatalytic degradation experiments, the highest degradation (88.5%) was recorded at a concentration of 55 mg.L−1 of TNT and the lowest degradation (37.9%) at pH = 7. It has been revealed that0.075 g ZnS7.1%/NiS2.7%nanoCP (NCP)photocatalyst at pH = 11, with 55 mg.L−1 TNT solution was the optimum parameters of the experiment. A feed-forward Artificial neural network (ANN) was employed to predict the photocatalytic degradation of 2,4,6-trinitrotoluene (TNT)based on a set of experimental tests. The results indicated that the ANN model prediction and experimental data have excellent accordance and the model can be used for prediction of photocatalytic degradation efficiency. The sensitivity analysis revealed that the concentration of TNT has a considerable effect on degradation efficiency (about 26.19%).