Neural network, isotherm and kinetic study for wastewater treatment using Populus alba’s pruned material

Abstract

Dyes are utilized in several plants and factories. Contaminated wastewaters containing dyes cause many illnesses and have many adverse effects on humans, animals, and plants. This research aims the usage of Populus alba tree’s sawdust as a costless pruned agricultural waste material for the removal of crystal violet from simulated wastewater in batch adsorption experiments. The dye removal process by the adsorbent was performed by varying various parameters such as the weight of adsorbent, pH of the solution, adsorption time, and the initial dye concentration. Generally, increasing the weight of adsorbent and decreasing the initial dye concentration led to increasing removal efficiency. The optimum solution pH was found to be 6.5. Also, the optimum weight of adsorbent and the optimum initial dye concentration were found to be 0.15 g and 10 mg L-1, respectively. Moreover, the adequate adsorption time for the accomplishment of the treatment procedure was 10 min. Adsorption data were fitted well by the Langmuir adsorption isotherm model and the maximum amount of the adsorbate on the adsorbent (qmax) was calculated to be 12.25 mg g-1. The kinetic study data illustrated the adaption of the adsorption rate with the pseudo second order kinetic model. The results of the ANN model proved the fitness of theoretical and experimental data according to the obtained correlation coefficient values. Eventually, the dye removal efficiency reached 97% in the optimum conditions of the experiments. So the sawdust of Populus alba tree’s pruned hardwood is introduced as a costless and highly capable adsorbent for the adsorption of crystal violet from contaminated wastewaters in order to perform a successful wastewater treatment beside the accomplishment of a waste management procedure.