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

Background and purpose: 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. Materials and Methods: The experiments were performed in a batch system. The effect of parameters such as contact time, pH, cadmium concentration and adsorbent dose were evaluated. Results: 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. Conclusion: 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.

Keywords:

Sunflower powder , Aqueous Two Phase , Biosorption , Cadmium , Biokinetics , Neural Network