Ultra-sensitive detection of PFASs using surface enhanced Raman scattering and machine learning: a promising approach for environmental analysis-Reference-Cited by-同舟云学术

Ultra-sensitive detection of PFASs using surface enhanced Raman scattering and machine learning: a promising approach for environmental analysis

Published:2024 Issue:8 Volume:3 Page:1272-1284
ISSN:2635-0998
Container-title:Sensors & Diagnostics
language:en
Short-container-title:Sens. Diagn.

Author:

Rothstein Joshua C.¹,Cui Jiaheng²^ORCID,Yang Yanjun¹^ORCID,Chen Xianyan³,Zhao Yiping¹^ORCID

Affiliation:

1. Department of Physics and Astronomy, Franklin College of Arts and Sciences, The University of Georgia, Athens, GA, 30602, USA

2. School of Electrical and Computer Engineering, College of Engineering, The University of Georgia, Athens, GA, 30602, USA

3. Department of Epidemiology & Biostatistics, College of Public Health, The University of Georgia, Athens, GA, 30602, USA

Abstract

SERS combined with machine learning was employed using AgNR substrates. The method demonstrates high sensitivity and specificity in detecting and differentiating PFASs in water or methanol samples.

Funder

National Institute of Food and Agriculture

Division of Electrical, Communications and Cyber Systems

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/SD/D4SD00052H

Reference54 articles.

1. A Never-Ending Story of Per- and Polyfluoroalkyl Substances (PFASs)?

2. Recent advances in the analysis of per- and polyfluoroalkyl substances (PFAS)—A review

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4. Selectivity of Per- and Polyfluoroalkyl Substance Sensors and Sorbents in Water

5. A molecularly imprinted chitosan doped with carbon quantum dots for fluorometric determination of perfluorooctane sulfonate