Multiplex Nanopore Detection of Structurally Diverse Per- and Polyfluoroalkyl Substances in Surface Water

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) make up a large class of emerging chemical pollutants that have caused extensive contamination of global water sources. As the toxicity of PFAS becomes increasingly recognized, there is a growing demand for low-cost and rapid sensors capable of screening water samples for multiple PFAS species. However, most electrochemical and optical sensors can detect only one or two PFASs, despite the high structural diversity of these compounds in aquatic environments. Here, we report a single-molecule nanopore sensor that enables simultaneous detection of nine PFASs in a single measurement. By incorporating a β-cyclodextrin (β-CD) adapter into a mutant α-hemolysin (α-HL) nanopore, translocating PFAS molecules produce distinct current blockades that allow clear discrimination based on carbon chain lengths, hydrogen substitutions, and terminal functional groups. With assistance from a machine learning classifier, an overall identification accuracy of 95.83% is achieved. This strategy allows direct, label-free, and rapid discrimination of multiple PFASs in surface water samples at environmentally relevant concentrations as low as the microgram per liter level, without chemical labeling, separation, or enrichment. The successful demonstration of nanopore sensing in complex real-world matrices highlights its strong potential for practical, field-deployable environmental analysis.

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Publication Details

Journal
ACS Nano
Published
2025-10-17
DOI
https://doi.org/10.1021/acsnano.5c12164
Citations
2
Primary Topic
Per- and polyfluoroalkyl substances research
Type
article
Field-Weighted Citation Impact
1.72
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article

Multiplex Nanopore Detection of Structurally Diverse Per- and Polyfluoroalkyl Substances in Surface Water

Shuanghong Yan, Xiaolei Qu, Yudong Zhou, Qianqian Cao et al.
2 citations
ACS Nano
Per- and polyfluoroalkyl substances research
1.72
article

Multiplex Nanopore Detection of Structurally Diverse Per- and Polyfluoroalkyl Substances in Surface Water

Shuanghong Yan, Xiaolei Qu, Yudong Zhou, Qianqian Cao, Xiaofeng Lu, Xiaoyu Du, Juan Li, Yuqin Wang, Renjie Li, Junjie Cao, Qi An, Dong Zhong, Liping Kang, Na Fan
article en
2 citations

Abstract

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) make up a large class of emerging chemical pollutants that have caused extensive contamination of global water sources. As the toxicity of PFAS becomes increasingly recognized, there is a growing demand for low-cost and rapid sensors capable of screening water samples for multiple PFAS species. However, most electrochemical and optical sensors can detect only one or two PFASs, despite the high structural diversity of these compounds in aquatic environments. Here, we report a single-molecule nanopore sensor that enables simultaneous detection of nine PFASs in a single measurement. By incorporating a β-cyclodextrin (β-CD) adapter into a mutant α-hemolysin (α-HL) nanopore, translocating PFAS molecules produce distinct current blockades that allow clear discrimination based on carbon chain lengths, hydrogen substitutions, and terminal functional groups. With assistance from a machine learning classifier, an overall identification accuracy of 95.83% is achieved. This strategy allows direct, label-free, and rapid discrimination of multiple PFASs in surface water samples at environmentally relevant concentrations as low as the microgram per liter level, without chemical labeling, separation, or enrichment. The successful demonstration of nanopore sensing in complex real-world matrices highlights its strong potential for practical, field-deployable environmental analysis.

ACS NanoVol. 19(42)
Hangzhou Normal University (CN), Beijing Normal University (CN), State Key Laboratory of Pollution Control and Resource Reuse (CN), Early Warning (United States) (US), Nanjing University (CN)
Openalex Percentile: Top 14%
Per- and polyfluoroalkyl substances research
1.72
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