journal article·2023-05-27

Crystal structure, optical and electrochemical studies of mixed metal oxide nanoparticles and their application in photodegradation of methylene blue

S Arul Vathana, T Daniel, K Amudhavalli

Bulletin of Materials Science· Volume 46· Issue 2
Publisher page

Abstract

Silver-doped manganese copper oxide nanoparticles (Ag-doped MnCuO NPs) were synthesized by a simultaneous green chemistry reduction approach using Bambusa seed extract. Aqueous extract from the seed was used as a reducing and capping agent. The X-ray diffraction analysis revealed that the NPs appear crystalline, and the detailed crystal structure was investigated. The average crystallite size of NPs was found to be 26.85 nm. Fourier transform infrared analysis confirmed the presence of functional groups present in NPs. The energy gap, Eg of NPs, was 1.75 eV from the UV-DRS. SEM micrographs showed an orthorhombic structure and some agglomeration-shaped NPs. Simple EDX mapping reveals the presence of Ag, Mn, Cu, C and O. Further, the prepared composites were tested for their electrochemical properties. The modified electrode was investigated by cyclic voltammetry. The specific capacitance of the synthesized Ag-doped MnCuO-nanostructured electrodes has been calculated from the cyclic voltammetry curve and the value is found for different scan rates (10–500 mV s–1). The photocatalytic activity of methylene blue (MB), a hazardous dye, was increased by 98.62% after 60 min of exposure to solar light radiation using an Ag-doped MnCuO catalyst (0.05 g) at pH = 9. The correlation coefficient value of MB’s pseudo-first-order kinetic model of photocatalytic degradation is high (R2 > 0.95). It was found that Ag-doped MnCuO NPs have higher photocatalytic efficiency and can be used as potential photocatalysts for industrial dye degradation.
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Research context

OpenAlex topics: Copper-based nanomaterials and applications · Transition Metal Oxide Nanomaterials · ZnO doping and properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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