journal article·2021-09

Surface structure, morphology and crystal phase-dependent photoactivity of MnO2 nanocatalysts under sunlight

Samriti Thakur, Devanshi Tinna, Bonamali Pal

Bulletin of Materials Science· Volume 44· Issue 3
Publisher page

Abstract

MnO2 exhibits numerous catalytic applications owing to its wide structural diversity with different chemical and physical properties. Different morphologies of MnO2 nanomaterial have been prepared to investigate oxidation of methylene blue dye and reduction of nitrobenzene under natural sunlight. MnO2 nanostructures displayed versatile photoactivity due to different surface and crystal structural morphologies. The prepared materials were characterized by XRD, SEM, EDS, DRS, DLS and fluorescence spectroscopy. The change in absorption maxima from 441 (sea urchin) to 444 nm (nanospheres) is due to change in shape, size and exposure of surface ligand density. Particle size distribution of α-MnO2 nanorods, sea urchin is 51 and 90–190 nm, respectively, with body-centred tetragonal crystalline structure. The structure of synthesized polymorphs consists of octahedral (MnO6) with different arrangements of edge and phase sharing. From SEM, variation in shapes from sea urchin to nanorods to nanospheres can be seen. MnO2-sea urchin (98%) and α-MnO2 nanorods (91%) give better activity in photo-oxidation of dye relative to MnO2 nanospheres. The overall photo-oxidation reaction follows pseudo first-order kinetics. Nitrobenzene (25 μmol) is selectively reduced to 80% aniline (20.5 μmol) by α-nanotubes of MnO2 catalyst and 82.2% with MnO2-sea urchin photocatalyst. This paper explored the correlations between shape-dependent chemical and structural factors of surface of a catalyst. The excellent performance of hierarchical MnO2 represents a potential heterogeneous catalyst for wastewater treatment.
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Research context

OpenAlex topics: Advanced Photocatalysis Techniques · Nanomaterials for catalytic reactions · Advanced Nanomaterials in Catalysis

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

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