A Study of Cadmium Removal from Aqueous Solutions by Sunflower Powders and its Modeling Using Artificial Neural Network

Background and Cadmium is hazardous and non-biodegradable material entering the food chain. In this paper, the removal of cadmium from aqueous solutions by sunflower powder (the natural biosorbent) was investigated. The experiments were performed in a batch system. The effect of parameters such as contact time, pH, cadmium concentration and adsorbent dose were evaluated. The results showed that increasing of pH, contact time and adsorbent dose caused increasing efficiency of removal cadmium from aqueous solutions. The results were modeled using biosorption kinetics and a neural network with four hidden neurons, including bias which was able to predict the concentration dependency of data very accurately. On the basis of the results, could be used from sunflower residues as a cost and efficient biosorbent for treatment of wastewater with Cadmium. The prediction of the artificial neural network model fit the experimental data very precisely.