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

Amouei, Abdol Iman and Amooey, Ali Akbar and Asgharzadeh, Fatemeh (2013) A Study of Cadmium Removal from Aqueous Solutions by Sunflower Powders and its Modeling Using Artificial Neural Network. Iranian Journal of Health Sciences, 1 (3). pp. 28-34.

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Official URL: http://jhs.mazums.ac.ir/article-1-119-en.html

Abstract

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.

Item Type: Article
Uncontrolled Keywords: Sunflower powder,Aqueous Two Phase, Biosorption,Cadmium, Biokinetics, Neural Network
Depositing User: Unnamed user with email eprints@mazums.ac.ir
Date Deposited: 04 Jan 2018 11:19
Last Modified: 04 Jan 2018 11:19
URI: http://eprints.mazums.ac.ir/id/eprint/229

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