Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the remediation of arsenite from water using the response surface methodology (RSM) model: Modeling and optimization

Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the... This study aimed to investigate the feasibility of carboxymethyl cellulose-stabilized iron nanoparticles (C-nZVI) for the removal of arsenite ions from aqueous solutions. Iron nanoparticles and carboxymethyl cellulose-stabilized iron nanoparticles were freshly synthesized. The synthesized nanomaterials had a size of 10nm approximately. The transmission electron microscope (TEM) images depicted bulkier dendrite flocs of non-stabilized iron nanoparticles. It described nanoscale particles as not discrete resulting from the aggregation of particles. The scanning electron microscopy (SEM) image showed that C-nZVI is approximately discrete, well-dispersed and an almost spherical shape. The energy dispersive x-ray spectroscopy (EDAX) and X-ray diffraction (XRD) spectrum confirmed the presence of Fe0 in the C-nZVI composite. The central composite design under the Response Surface Methodology (RSM) was employed in order to investigate the effect of independent variables on arsenite removal and to determine the optimum condition. The reduced full second-order model indicated a well-fitted model since the experimental values were in good agreement with it. Therefore, this model is used for the prediction and optimization of arsenite removal from water. The maximum removal efficiency was estimated to be 100% when all parameters are considered simultaneously. The predicted optimal conditions for the maximum removal efficiency were achieved with initial arsenite concentration, 0.68mgL−1; C-nZVI, 0.3 (gL−1); time, 31.25 (min) and pH, 5.2. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Contaminant Hydrology Elsevier

Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the remediation of arsenite from water using the response surface methodology (RSM) model: Modeling and optimization

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0169-7722
eISSN
1873-6009
D.O.I.
10.1016/j.jconhyd.2017.06.005
Publisher site
See Article on Publisher Site

Abstract

This study aimed to investigate the feasibility of carboxymethyl cellulose-stabilized iron nanoparticles (C-nZVI) for the removal of arsenite ions from aqueous solutions. Iron nanoparticles and carboxymethyl cellulose-stabilized iron nanoparticles were freshly synthesized. The synthesized nanomaterials had a size of 10nm approximately. The transmission electron microscope (TEM) images depicted bulkier dendrite flocs of non-stabilized iron nanoparticles. It described nanoscale particles as not discrete resulting from the aggregation of particles. The scanning electron microscopy (SEM) image showed that C-nZVI is approximately discrete, well-dispersed and an almost spherical shape. The energy dispersive x-ray spectroscopy (EDAX) and X-ray diffraction (XRD) spectrum confirmed the presence of Fe0 in the C-nZVI composite. The central composite design under the Response Surface Methodology (RSM) was employed in order to investigate the effect of independent variables on arsenite removal and to determine the optimum condition. The reduced full second-order model indicated a well-fitted model since the experimental values were in good agreement with it. Therefore, this model is used for the prediction and optimization of arsenite removal from water. The maximum removal efficiency was estimated to be 100% when all parameters are considered simultaneously. The predicted optimal conditions for the maximum removal efficiency were achieved with initial arsenite concentration, 0.68mgL−1; C-nZVI, 0.3 (gL−1); time, 31.25 (min) and pH, 5.2.

Journal

Journal of Contaminant HydrologyElsevier

Published: Aug 1, 2017

References

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