Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Optical detection of waterborne pathogens using nanomaterials

Authors
Bhardwaj, NehaBhardwaj, Sanjeev K.Bhatt, DeepanshuLim, Dong KwonKim, Ki-HyunDeep, Akash
Issue Date
4월-2019
Publisher
ELSEVIER SCI LTD
Keywords
Nanomaterials; Optical; Pathogen; Sensors; Contamination
Citation
TRAC-TRENDS IN ANALYTICAL CHEMISTRY, v.113, pp.280 - 300
Indexed
SCIE
SCOPUS
Journal Title
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
Volume
113
Start Page
280
End Page
300
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/66429
DOI
10.1016/j.trac.2019.02.019
ISSN
0165-9936
Abstract
The consumption of microbiologically contaminated water poses serious threats to human health in the form of outbreaks of severe waterborne diseases. The accurate detection and identification of microbial pathogens (e.g., bacteria, fungi, viruses, and parasites) in water is thus imperative to prevent such undesirable situations. This review is organized to describe methodological approaches developed for optical sensing systems based on various nanomaterials (NMs: e.g., gold nanoparticles, quantum dots, fluorescent polymers, and optical fibers) for the waterborne pathogens. These sensors are considered a promising alternative to conventional methods that are often not feasible for use with non-culturable microbes. An overview of these sensing methods is thus provided in terms of performance (e.g., accuracy, specificity, fast response, and robustness) to expand our basic knowledge of sensing waterborne pathogens with respect to the design of advanced sensing systems and their working principle. (C) 2019 Elsevier B.V. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > KU-KIST Graduate School of Converging Science and Technology > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE