Abstract
Graphene-based materials such as graphene oxide (GO) and reduced graphene oxide (rGO), have been extensively used for wastewater purification and treatment. Their unique properties, including large surface area, tunable pore structures, high adsorption capacity, electrical conductivity, rich surface chemistry and catalytic activity, make them highly efficient as adsorbents and photocatalysts for the removal of a wide range of pollutants. Consequently, innovative and cost-effective methods for the preparation of these materials are required to broaden their application. This review comprehensively elucidates recent advances in the synthesis of graphene-based adsorbents and photocatalysts derived from various agricultural wastes, including oil palm trunks, coconut shells, tea wastes and rice straws. The manuscript focuses on methodologies used to convert agricultural residues into graphene, highlighting key processes such as pyrolysis and chemical reduction. Innovative approaches for reducing of GO to rGO using plant extracts as reducing agents are discussed in detail, with an examination of their synthetic mechanisms and potential drawbacks. Special emphasis is placed on the characterization techniques employed for the prepared materials including X-ray diffraction (XRD), Raman Spectroscopy, Atomic Force Microscopy (AFM), X-ray Photoelectron Spectroscopy (XPS), Fourier transform infrared (FTIR), Scanning Electron Microscopy (SEM), and Nuclear Magnetic Resonance (NMR). Additionally, the review provides a timely overview of the adsorption performance of these graphene materials in removing various organic and inorganic pollutants, such as dyes, heavy metals, and pharmaceuticals. The photocatalytic efficiency of these materials in degrading pollutants under different light sources is also critically evaluated. Overall, this review highlights the potential of graphene derived from agricultural wastes as a promising solution for sustainable environmental remediation and lays the groundwork for future innovations in this field.
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