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Antibacterial and Antiviral Functional Materials: Chemistry and Biological Activity toward Tackling COVID-19-like Pandemics
Open accessAbstract
The ongoing worldwide pandemic due to COVID-19 has created awareness toward ensuring best practices to avoid the spread of microorganisms. In this regard, the research on creating a surface which destroys or inhibits the adherence of microbial/viral entities has gained renewed interest. Although many research reports are available on the antibacterial materials or coatings, there is a relatively small amount of data available on the use of antiviral materials. However, with more research geared toward this area, new information is being added to the literature every day. The combination of antibacterial and antiviral chemical entities represents a potentially path-breaking intervention to mitigate the spread of disease-causing agents. In this review, we have surveyed antibacterial and antiviral materials of various classes such as small-molecule organics, synthetic and biodegradable polymers, silver, TiO 2, and copper-derived chemicals. The surface protection mechanisms of the materials against the pathogen colonies are discussed in detail, which highlights the key differences that could determine the parameters that would govern the future development of advanced antibacterial and antiviral materials and surfaces.
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Cited by
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Metadata
- Authors
- Balasubramaniam, B., Prateek, Ranjan, S., Saraf, M., Kar, P., Singh, S. P., Thakur, V. K., Singh, A., & Gupta, R. K.
- Venue
- ACS Pharmacology & Translational Science
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-12-29
- Volume
- 4
- Issue
- 1
- Pages
- 8-54
- ISSN
- 2575-9108 (ISSN-L)
- OpenAlex
- W3114969372
- Cited by
- 285
- References
- 347
- FWCI
- 15.95
- Type
- journal article
- Language
- en
- Open access
- green
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
