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Research Article

Efficient removal of Triton X-100 from water samples by graphene oxide-humic acid nanocomposite

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Pages 2879-2898 | Received 03 Dec 2020, Accepted 26 Feb 2021, Published online: 29 Mar 2021
 

ABSTRACT

Triton X-100 (TX-100) is one of the non-ionic surfactants which is used widely in different industries and has high toxicity for aquatics and humans. Therefore, the application of an efficient method for its removal is highly recommended. In this paper, graphene oxide (GO) modified humic acid (HA) was used as an efficient adsorbent for the removal of TX-100 from water samples. GO was synthesised from graphite by the Hummer method and modified by HA to synthesise graphene oxide-humic acid (GO-HA) nanocomposite. The synthesised GO-HA adsorbent was characterised by the Fourier Transform-Infrared spectrophotometry (FT-IR), scanning electron microscopy (SEM), atomic force microscopy (AFM), X-Ray Diffraction (XRD) and Brunauer-Emmett-Teller (BET).The main parameters affecting the removal efficiency, such as pH, stirring rate, adsorbent dosage and contact time, were studied and optimised. It was found that maximum removal percentage was obtained at pH 3, 5 mg adsorbent and 60 min contact time. Also, the adsorption isotherms including Langmuir and Freundlich equations were studied and the results showed that the removal of TX-100 obeys from the Langmuir isotherm with the maximum adsorption capacity of 435 mg g−1.The study of different kinetic models including the linear and non-linear pseudo-first- and second-order kinetic models as well as the Elovich and Intraparticle diffusion models showed that the adsorption of TX-100 on GO-HA nanocomposite follows by the non-linear pseudo-first-order kinetic model. Finally, the proposed GO-HA nanocomposite was successfully applied for the removal of TX-100 from real water samples.

Acknowledgments

The authors wish to thank the Ferdowsi University of Mashhad for the financial support of this project (Grant Number 50256).

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This work was supported by the Ferdowsi University of Mashhad [50256].

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