Preparation of ultra-porous graphene oxide using a glucose-mediated hydrothermal method for efficient removal of fluoride ions from water: kinetics, isotherms and co-existing ions studies
Source abstract
Abstract
Porous graphene oxide (P-GO) was successfully synthesized by using a simple glucose mediated hydrothermal method form prepared graphene oxide (GO). Then the P-GO was characterized by X-ray Powder Diffraction (XRD), Fourier-Transform Infrared (FITR), Raman, Brunauer–Emmett–Teller (BET), Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM) analysis to determine the crystallinity, surface functionality, surface defect, surface area and porous nature of the material. For the comparative properties studies with P-GO, the synthesised GO was also characterised using the aforementioned analytical techniques. The formation of macroporous 2D sheet-like structure of P-GO with pore size diameters of 0.2–0.5 µm was confirmed by FESEM and TEM images. The surface area of P-GO was found to be 1272 m2/g which is much higher compare to GO (i.e., 172 m2/g) because of porous structure. P-GO was used for the adsorptive removal of F− ions from water using batch adsorption method. The highest adsorption occurs in the pH range of 5–7 with maximum adsorption capacity of 1272 mg/g. The experimental data revealed that the adsorption process obeys Langmuir monolayer isotherm model. The kinetic analysis revealed that the adsorption procedure is extremely rapid and mainly fit to the Pseudo-second-order (PSO) model. The effect of co-existing ions on fluoride adsorption capacity by P-GO decreases in the following order: PO43− > CO32− > SO42− > HCO3− > NO3− > Cl−. The mechanism of adsorption of fluoride onto the P-GO surface includes electrostatic interactions and hydrogen bonding.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Fluoride Effects and Removal · Adsorption and biosorption for pollutant removal · Graphene and Nanomaterials Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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