The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Nanostructured metal oxides and its hybrids for photocatalytic and biomedical applications
Abstract
Metal oxide nanoparticles and its hybrids are deemed to be one of the most attractive materials in an extensive range of applications due to their impressive optical, electronic, photocatalytic, and biological properties. Metal oxide based nanomaterials with extraordinary characteristics have been proposed, prepared, and used as main materials in the recent area of photocatalysis and biomedicine, due to their non-toxic nature, large specific surface area, useful optical bandgap, and high biological activity. Herein, this review reveals the recent advance development in the area like photocatalytic, anticancer and antibacterial performance of metal oxide nanomaterials for multidimensional applications. Consequently, we also focused on the encountered difficulties and prospects for the future application of metal oxide-based composites as promising candidates for the development of highly efficient photocatalytic and biomedical systems. This review article also delivers advanced knowledge to the scientific community who intends to design efficient photocatalytic and biomedical systems.
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Cites
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Metadata
- Authors
- Kannan, K., Radhika, D., Sadasivuni, K. K., Reddy, K. R., & Raghu, A. V.
- Venue
- Advances in Colloid and Interface Science
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 281
- Pages
- 102178
- ISSN
- 0001-8686 (ISSN-L)
- OpenAlex
- W3024064809
- Cited by
- 341
- References
- 49
- FWCI
- 9.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kannan, K., Radhika, D., Sadasivuni, K. K., Reddy, K. R., & Raghu, A. V. (2020). Nanostructured metal oxides and its hybrids for photocatalytic and biomedical applications. Advances in Colloid and Interface Science. https://doi.org/10.1016/j.cis.2020.102178
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
