In the present study, an attempt was made to remove toxic heavy metal ion chromium (VI) using polymer-enhanced ultrafiltration (PEUF) process and polyethyleneimine (PEI) was selected as the chelating agent. The objective purpose of this work was to predict the performance index (PFI) of the membrane evaluated as the solute rejection times the permeate flux and then to optimize the process conditions, namely, cross-flow rate, transmembrane pressure, pH and polymer to metal ratio in order to maximize performance index for the removal of toxic chromium (VI) from aqueous solution. The maximum PFI values suggested by the Central Composite Design of response surface methodology (RSM) were quite high; the predicted PFI, especially for polymer to metal ratio 41 was 92.53 L m2 h1 , which hinted at the success of PEUF technique. Further, Artificial Neural Network (ANN) model was generated to validate the RSM predictions. The differences observed while comparing the optimization results along with the response surface (RS) plots derived by RSM with those provided by ANN models, reflected the advantages and disadvantages of both the methodologies, and essentially the non-linear character of the PEUF process. The accuracy of the predictive models was, nevertheless, affirmed by the comparison drawn between the predicted and experimental data.

Experimental analysis, modeling and optimization of chromium (VI) removal from aqueous solutions by polymer-enhanced ultrafiltration

Chakraborty S;CURCIO, Stefano
2014

Abstract

In the present study, an attempt was made to remove toxic heavy metal ion chromium (VI) using polymer-enhanced ultrafiltration (PEUF) process and polyethyleneimine (PEI) was selected as the chelating agent. The objective purpose of this work was to predict the performance index (PFI) of the membrane evaluated as the solute rejection times the permeate flux and then to optimize the process conditions, namely, cross-flow rate, transmembrane pressure, pH and polymer to metal ratio in order to maximize performance index for the removal of toxic chromium (VI) from aqueous solution. The maximum PFI values suggested by the Central Composite Design of response surface methodology (RSM) were quite high; the predicted PFI, especially for polymer to metal ratio 41 was 92.53 L m2 h1 , which hinted at the success of PEUF technique. Further, Artificial Neural Network (ANN) model was generated to validate the RSM predictions. The differences observed while comparing the optimization results along with the response surface (RS) plots derived by RSM with those provided by ANN models, reflected the advantages and disadvantages of both the methodologies, and essentially the non-linear character of the PEUF process. The accuracy of the predictive models was, nevertheless, affirmed by the comparison drawn between the predicted and experimental data.
Removal of chromium (VI); Polymer-enhanced ultrafiltration; Artificial Neural Network
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/151022
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