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Graphene oxide nanomaterials for the removal of non-ionic surfactant from water
[Display omitted] •GO and rGO were successfully synthesized and characterized.•The kinetics of TX-100 adsorption onto GO and rGO were very fast.•Strong hydrophobic and π–π interactions play an important role for TX-100 graphene nanomaterials adsorption.•High removal capacities of 1683 and 1203 mg/g...
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Published in: | Journal of environmental chemical engineering 2018-02, Vol.6 (1), p.1536-1545 |
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Main Authors: | , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | [Display omitted]
•GO and rGO were successfully synthesized and characterized.•The kinetics of TX-100 adsorption onto GO and rGO were very fast.•Strong hydrophobic and π–π interactions play an important role for TX-100 graphene nanomaterials adsorption.•High removal capacities of 1683 and 1203 mg/g for rGO and GO, respectively.•rGO was successfully used in three consecutive cycles, thereby keeping the adsorption capacities high.
The presence of surfactants in aquatic environment is a major public health concern. Recently, several methods have been developed to remove these compounds, among these are the adsorption processes. The great challenge of this technology is to achieve high removal capacities, fast adsorption and efficient adsorbent recoveries. The aim of our study was to synthesize GO and rGO and use them for non-ionic surfactant (TX-100) adsorption in consecutive cycles. Both nanomaterials were synthesized and characterized by several analyses including BET method for superficial area, XRD, Raman Spectroscopy, CP/MAS 13C NMR, TGA, FT-IR, XPS, SEM and TEM microscopies. The optimization of the adsorption process was performed by varying many parameters, including the experiment time, nanomaterials/surfactant ratio, temperature, pH and ultrasound irradiation. GO and rGO showed fast TX-100 adsorption, about 30 min to reach equilibrium. The experiments showed that the pH variation affects the removal efficiency for both nanomaterials with pH 6 being the optimized condition. The pseudo-second order kinetic model showed the best fit to the experimental data for both nanomaterials. The equilibrium data for GO and rGO were fitted to the Fowler-Guggenheim and the Langmuir models, respectively. The rGO was verified as the best adsorbent for TX-100 removal, suggesting that hydrophobic and π-stacking interactions are dominant in the process. Besides the superior adsorption efficiency, rGO formed larger aggregates after TX-100 removal than GO, facilitating its separation from solution. Under optimized conditions, GO and rGO revealed superior removal capacities when compared to others adsorbents (1203 and 1683 mg/g, respectively). |
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ISSN: | 2213-3437 2213-3437 |
DOI: | 10.1016/j.jece.2018.01.072 |