The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Conventional and green methods of synthesis of silver nanoparticles and their antimicrobial properties
Open accessAbstract
Silver nanoparticles possess a wide variety of properties that makes them valuable for different purposes. However, one of their most beneficial properties is their antimicrobial activity. In a world threatened by the rise of antimicrobial resistance, the use of silver nanoparticles in drug delivery systems may help solve this emerging problem. Therefore, their large-scale synthesis has the potential of being extremely useful, especially in healthcare. There are three primary methods of synthesizing silver nanoparticles viz physical methods, chemical methods and biological methods. While choosing the technique of synthesis, it is essential to opt for the method that can give a good yield of pure silver nanoparticles while minimally impacting human health and the environment. In view of climate change and global warming, all industries, including the scientific community, are endeavouring to adopt environment-friendly methods of functioning. Biological methods have an edge over physical and chemical methods in context of green chemistry. Being a cleaner method of synthesis, biological methods can prove to be more suitable for large-scale synthesis, thereby providing a sustainable method to exploit their antimicrobial activity. This review article explores the three key methods of synthesis of silver nanoparticles, their advantages, and disadvantages in the context of green chemistry.
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Cites
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Cited by
Parsaee, S., Jahani, N., Salehiniya, H., & Raeison, M. (2024) · Journal of Breast Diseases · doi:10.61186/ijbd.17.1.84
Metadata
- Authors
- Vishwanath, R., & Negi, B.
- Venue
- Current Research in Green and Sustainable Chemistry
- Publisher
- Elsevier BV
- Published
- 2021
- Volume
- 4
- Pages
- 100205
- ISSN
- 2666-0865 (ISSN-L)
- OpenAlex
- W3210668565
- Cited by
- 280
- References
- 60
- FWCI
- 11.93
- Type
- journal article
- Language
- en
- Open access
- gold
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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.