Issue 21, 2023

Excellent Cr(vi) adsorbent made from pyrolyzed green coconut trash with parametric modelling and optimization using RSM and experimental data

Abstract

Biochar generated from pyrolyzed leftover green coconut was used to explore the impact of various experimental settings. The optimization of this biochar using response surface methodology (RSM), the Box-Behnken design, and statistical modelling led to the optimal parameters, such as pH 2.3 ± 0.1, solution temperature of 303 K, and the adsorbent weight of 6 g L−1, which resulted in approximately 99.99% expulsion of Cr(VI) from the aqueous solution. By using FESEM, EDAX, elemental mapping, FTIR spectroscopy, XRD, XPS, and pHZPC, the surface characteristics of coconut biochar (CB) were evaluated. The functional groups C–O, C–H, C[double bond, length as m-dash]O, and O–H were found to be present and were primarily in charge of controlling the adsorption mechanism. The change in Cr(VI) oxidation state was confirmed by XPS analysis, and the presence of Cr(VI) on CB after adsorption was confirmed by EDAX. With high R2 values, the pseudo-second-order rate was the best adsorption mechanism for Cr(VI). The ideal adsorption capacity of 9.75 mg g−1was obtained from the Langmuir isotherm. The thermodynamic study confirmed that the experiment was exothermic with spontaneous nature. According to the adsorption mechanism, electrostatic attraction, reduction, and complexation were the main causes of Cr(VI) adsorption on CB. The efficiency of CB as an adsorbent for extracting Cr(VI) from an aqueous solution was thus supported by all available studies.

Graphical abstract: Excellent Cr(vi) adsorbent made from pyrolyzed green coconut trash with parametric modelling and optimization using RSM and experimental data

Supplementary files

Article information

Article type
Paper
Submitted
14 Jan 2023
Accepted
26 Apr 2023
First published
10 May 2023

New J. Chem., 2023,47, 10078-10089

Excellent Cr(VI) adsorbent made from pyrolyzed green coconut trash with parametric modelling and optimization using RSM and experimental data

A. Kumar, S. N. Upadhyay, P. K. Mishra and M. K. Mondal, New J. Chem., 2023, 47, 10078 DOI: 10.1039/D3NJ00224A

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