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Nanomaterial Enabled Biosensors for Pathogen Monitoring - A Review
Abstract
One promising, but currently underexplored, area for the future of drinking water pathogen monitoring stems from the development of nanomaterial-enabled detection strategies. The nanoscience literature contains numerous reports of nanoenabled biosensors; however, to date only a small percentage have focused on the detection of whole cells, in general, and waterborne pathogens, in particular. There are significant opportunities for the use of nanoenabled biosensors for environmental monitoring, and this review is intended to both illustrate the state of this field and to spur additional research in this area.
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Citations
Cited by
Applications of nanotechnology in water and wastewater treatment
Qu, X., Alvarez, P. J. J., & Li, Q. (2013) · Water Research · doi:10.1016/j.watres.2012.09.058 · Cited by 2,444
Qu, X., Brame, J., Li, Q., & Alvarez, P. J. J. (2013) · Accounts of Chemical Research · doi:10.1021/ar300029v · Cited by 799
The Environmental Impact of Micro/Nanomachines: A Review
Gao, W., & Wang, J. (2014) · ACS Nano · doi:10.1021/nn500077a · Cited by 594
Nanotechnology Based Solutions for Wastewater Treatment
Baruah, A., Chaudhary, V., Malik, R., & Tomer, V. K. (2019) · Nanotechnology in Water and Wastewater Treatment · doi:10.1016/b978-0-12-813902-8.00017-4 · Cited by 121
Metadata
- Authors
- Vikesland, P. J., & Wigginton, K. R.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-05-15
- Volume
- 44
- Issue
- 10
- Pages
- 3656-3669
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2003778082
- Cited by
- 269
- References
- 0
- FWCI
- 10.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Vikesland, P. J., & Wigginton, K. R. (2010). Nanomaterial Enabled Biosensors for Pathogen Monitoring - A Review. Environmental Science & Technology. https://doi.org/10.1021/es903704z
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
