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.