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Utilization of Graphene Oxide-Chitosan Nanocomposite for the Removal of Heavy Metals: Kinetics, Isotherm, and Error Analysis

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Abstract

In this study, the synthesis of nanocomposite using graphene oxide and chitosan and its application for the removal of Cr (VI) and Ni (II) ions from wastewater was explored. The characterization of the synthesized graphene oxide-chitosan nanocomposite (GO-CNC) has been investigated with XRD, FT-IR, and SEM. The effect of pH, adsorbent dosage, effluent concentration, and contact time on Cr(VI) and Ni(II) removal was studied. It was found that for Cr (VI) maximum of 90.74% removal was observed at pH 5, 105 min, initial metal ion concentration 10 mg L−1, and adsorbent dosage of 20 g L−1. Ni(II) removal of 58.56% occurred at pH of 8, 90 min, initial metal ion concentration of 10 mg L−1, and adsorbent dosage of 20 g L−1. Adsorption isotherms Langmuir, Freundlich, and Temkin were used. Best fit for Cr(VI) was Freundlich isotherm ions and Langmuir isotherm for Ni(II) with correlation coefficient values greater than 0.9. The Freundlich isotherm value 1/n less than 1 implies the favorability of the adsorption onto the GO-CNC. Our experimental data was described by the pseudo-second order kinetic model for both the metal ions. To forecast the best model, error functions, the sum of squared errors (SSE), the average relative error (ARE), the sum of absolute errors (EABS), and Marquardt’s percent standard deviation (MPSD) were used to predict the single parameters by using non-linear regression analysis to reduce the bias of linear correlation coefficient. The regeneration of GO-CNC nanocomposite showed significant removal efficiencies up to four cycles.

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NSE, & SMJ: Conducted experimental works, Methodology, Manuscript draft & graph plotting; CK: Supervision, Review and Editing, Approval of final manuscript.

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Correspondence to Chithra Kumaran.

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Elumalai, N.S., Jaisankar, S.M. & Kumaran, C. Utilization of Graphene Oxide-Chitosan Nanocomposite for the Removal of Heavy Metals: Kinetics, Isotherm, and Error Analysis. Water Conserv Sci Eng 9, 9 (2024). https://doi.org/10.1007/s41101-024-00241-3

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