• prediction of copper ion biosorption with sargassum and padina .sps brown algae by multiple-regression analysis

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1389/07/20
    • تاریخ انتشار در تی پی بین: 1389/07/20
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     in comparison to the conventional physicochemical treatment methods for mining contaminated effluents, biosorption gained importance due to its inherent advantages such as low operating costs, high efficiency, and possible biomass regeneration. brown algae due to their high number of binding sites are most promising absorbent in biosorption applications. dried biomass of the marine macro algae sargassum .sp and padina .sp (brown) are studied in terms of their cu (ii) biosorption performance. the purpose of this research is application of multiple-regression analysis to predict the removal capacity of the biosorbents and determine the most influencing parameters in batch biosorption such as ph, initial solution concentration, retention time, shaking rate and sorbent dosage. comparing the simulated and real data showed a good correlation for the predictably of proposed models. the developed multiple-regression model can provide accurate information for treatment process of copper loaded mine effluents by the considered biosorption technique.

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