Sensors for Detecting per- and Polyfluoroalkyl Substances (PFAS): A Critical Review of Development Challenges, Current Sensors, and Commercialization Obstacles
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2021/08/01
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Description:Per- and polyfluoroalkyl substances (PFAS) are a class of compounds that have become environmental contaminants of emerging concern. They are highly persistent, toxic, bioaccumulative, and ubiquitous which makes them important to detect to ensure environmental and human health. Multiple instrument-based methods exist for sensitive and selective detection of PFAS in a variety of matrices, but these methods suffer from expensive costs and the need for a laboratory and highly trained personnel. There is a big need for fast, inexpensive, robust, and portable methods to detect PFAS in the field. This would allow environmental laboratories and other agencies to perform more frequent testing to comply with regulations. In addition, the general public would benefit from a fast method to evaluate the drinking water in their homes for PFAS contamination. A PFAS sensor would provide almost real-time data on PFAS concentrations that can also provide actionable information for water quality managers and consumers around the planet. In this review, we discuss the sensors that have been developed up to this point for PFAS detection by their molecular detection mechanism as well as the goals that should be considered during sensor development. Future research needs and commercialization challenges are also highlighted. [Description provided by NIOSH]
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ISSN:1385-8947
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Volume:417
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NIOSHTIC Number:nn:20068135
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Citation:Chem Eng J 2021 Aug; 417:129133
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Contact Point Address:Charles S. Henry, Department of Chemistry, Colorado State University, 1872 Campus Delivery, Fort Collins, CO 80523, USA
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Email:Chuck.Henry@colostate.edu
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Federal Fiscal Year:2021
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Performing Organization:Colorado State University - Ft. Collins
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Peer Reviewed:True
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Start Date:20030915
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Source Full Name:Chemical Engineering Journal
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End Date:20270914
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Main Document Checksum:urn:sha-512:3542616bd771bfc928eba99fcdb41b9bd418091d183cbff13677da8eaac35640cfae891f3d603179ad9f569387399b82ef6f5b2e1a2adc869171d62ffa9ad6ea
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