Iranian Journal of

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Background and Objective: Nickel (II) and cadmium (II) are important in environmental pollutant. Biosorption of heavy metals can be an effective process for the removal and recovery of heavy metal ions from aqueous solutions because of the decrease in sludge problems, economical issues, high efficiency and compatibility with the environment.
Materials and Methods: power of wasted activated sludge have been contact with nickel (II) and cadmium (II) solutions in 0.25 and 0.75 milli molar invarious pHs and mixing pace, at 24-26 0C temperature on batch reactor system .After two hours (continuously 5-420 min in kinetic study) samples were analyzed with atomic absorption spectrophotometer.
Results:The kinetic study results show that equilibrium adsorption time for nickel (II) and cadmium
(II) reached within 2 hr, but the profile curve of cadmium (II) biosorption was smoother than nickel (II) biosorption. Both metals adsorption followed the Langmuir model and the maximum adsorption capacity (qmax) for nickel (II) and cadmium (II) was 0.195 and 0.37 milli mole per gram respectively. The increase in pH resulted in adsorption increase for both metals. For cadmium (II) at 0.25 and 0.75 mMinitial concentration there was no adsorption at pH 2 where as nickel (0.25 mM) adsorption was observed at the same pH. The optimum mixing rate for both metals was 200 rpm and this effect was more obviously in greater concentration.
Conclusion: Like othe biosorbents ,wasted activated sludge showed greater capacity for cadmium(II) biosorption than nickel (II). Cadmium (II) in modeling and biosorption characteristics study had more conformity than nickel (II).

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Background and Objectives: Biosorption is a new and inexpensive technique in heavy metals removal and recovery from aqueous solutions. In order to evaluate the potential of this method for the removal of nickel ions, biosorption of nickel ions from aqueous solution was studied using Cystoseira indica biomass in a packed bed column. Materials and Methods: The uptake capacity of nickel ions was investigated using protonated biomass at different influent concentrations and flow rates. In addition, the experimental breakthrough curve obtained under definite experimental conditions was modeled using Thomas, Yoon & Nelson, Dose-Response, and Belter models. Results: It was found that increasing influent concentration from 58 to 100 mg/l led to the increase of driving force for mass transfer and uptake capacity raised from 55.84 to 95.69 mg/g. The investigation of flow rate effect showed when the process is intraparticle mass transfer controlled, a slower flow rate favors the sorption. In the case of external mass transfer control, a higher flow rate decreases the film resistance and leads to an increase in mass transfer. Modeling the experimental data revealed that the abovementioned models were suitable to predict the breakthrough curves, especially Dose-Response. Measurement of pH of the effluent solution indicated that ion exchange is one of the main mechanisms of nickel biosorption using this biosorbent. Conclusion: The results of this study are complementary of the batch equilibrium sorption experiments. Therefore, from process viewpoint, this biomass can be proposed in the sorption columns as a sorbent for nickel ions.

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Background and Objectives: In this work, biosorption of hexavalent chromium from aqueous solution with excess municipal sludge was studied. Moreover, the performance of neural networks to predict the biosorption rate was investigated.

Materials and Methods: The effect of operational parameters including initial metal concentration, initial pH, agitation speed, adsorbent dosage, and agitation time on the biosorption of chromium was assessed in a batch system. A part of the experimental results was modeled using Feed-Forward Back propagation Neural Network (FFBP-ANN). Another part of the test results was simulated to assess the model accuracy. Transfer function in the hidden layers and output layers and the number of neurons in the hidden layers were optimized.

Results: The maximum removal of chromium obtained from batch studies was more than 96% in 90 mg/L initial concentration, pH 2, agitation speed 200 rpm and adsorbent dosage 4 g/L. Maximum biosorption capacity was 41.69 mg/g. Biosorption data of Cr(VI) are described well by Freundlich isotherm model and adsorption kinetic followed pseudo-second order model.  Tangent sigmoid function determined was the most appropriate transfer function in the hidden and output layer. The optimal number of neurons in hidden layers was 13. Predictions of model showed excellent correlation (R=0.984) with the target vector. Simulations performed by the developed neural network model showed good agreement with experimental results.

Conclusion: Overall, it can be concluded that excess municipal sludge performs well for the removal of Cr ions from aqueous solution as a biological and low cost biosorbent. FFBP-ANN is an appropriate technique for modeling, estimating, and prediction of biosorption process If the Levenberg-Marquardt training function, tangent sigmoid transfer function in the hidden and output layers and the number of neurons is between 1.6 to 1.8 times the input data, proper predication results could be achieved.