Highly efficient graphene-supported transition metal carbides as multifunctional material for the adsorption and oxygen evolution reaction applications
Source abstract
Abstract
Developing highly efficient and stable electrocatalysts for electrochemical water splitting remains a significant challenge. In this work, a high-performance catalyst based on ceramic materials (titanium and tungsten carbides (G)) supported by graphene (C) (G/C) was prepared, characterized, and applied for removing an organic model compound (methylene blue (MB) dye) and the generation of oxygen gas. Scanning electron microscopy coupled with energy-dispersive spectroscopy revealed details of the material. The structural properties demonstrated that the synthesized nanocomposite consists of graphene, titanium carbide, and tungsten carbide phases. The application of the material for removing MB dye from textile effluent exhibited a maximum adsorption capacity of 175.44 mg/g at ≈ pH 5.5, with an adsorbent mass of 0.015 g and an operation time of 20 min. Meanwhile, when the material was used as an electrocatalyst for promoting the oxygen evolution reaction (OER), its catalytic activity was found to be remarkably efficient with good durability in strong alkaline media. However, the G/C nanocomposite exhibited an OER overvoltage of about 266 mV at a current density ( j ) of 10 mA cm -2 , remaining stable during 30 h. These significant results could be attributed to the strong link between the graphene support and the transitional metal-based carbides, as well as to the mesoporous structure, which provides more active adsorption sites, facilitates oxygen bubble release, and enhances mass transfer during OER kinetics. The synthesis of the G/C nanocomposite in this work paves the way for future large-scale treatment applications and energy-saving production.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Electrocatalysts for Energy Conversion · Advanced oxidation water treatment · Membrane-based Ion Separation Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (77)
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