Dual-Mode Detection of Perfluorooctanoic Acid Using Up-Conversion Fluorescent Silicon Quantum Dots-Molecularly Imprinted Polymers and Smartphone Sensing.

Hongli Ye, Xinran Wang, Xiangqian Xu, Hongyang Xu, Rui Yuan, Ping Cheng

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Excitonic and Optical Transduction Mechanisms in Quantum Dot Sensors for Environmental Pollutant Detection.Sensors (Basel, Switzerland) · 2026
Review

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hongli YeLaboratory of Aquatic Product Quality, Safety and Processing, Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China.ORCID 0000-0001-9253-2300

Xinran WangLaboratory of Aquatic Product Quality, Safety and Processing, Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China.

Xiangqian XuLaboratory of Aquatic Product Quality, Safety and Processing, Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China.

Hongyang XuSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.

Rui YuanLaboratory of Aquatic Product Quality, Safety and Processing, Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China.

Ping ChengSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.

Funding

National Natural Science Foundation of China 22204175the Central PublicInterest Scientific Institution Basal Research Fund (East China Sea Fisheries Research Institute) 2025YC02

6 · The paper itself

Abstract

Perfluorooctanoic acid (PFOA) is a persistent and bioaccumulative hazardous pollutant, presenting substantial threats to the environment and human health. The dual-mode, portable, sensitive, low-background, and cost-effective detection methods for PFOA were developed by integrating up-conversion fluorescent silicon quantum dot-molecularly imprinted polymer (MIPs) with a smartphone-based sensing system. The interaction between PFOA and MIPs resulted in a fluorescence quenching with a range of 2-20 µmol/L and a limit of detection (LOD) of 37.5 nmol/L for the low-background up-conversion fluorescence detection of PFOA, whereas the portable smartphone sensing platform enabled the detection of PFOA with a linear range of 0-5 µmol/L and a LOD of 73.9 nmol/L. Furthermore, the established methods were successfully applied to the detection of PFOA in environmental waters and food samples. This study provides the dual-mode, portable, novel, practical and low-background approaches for the detection of PFOA in the environment and food products.

Indexed as

molecular imprinting technologyperfluorooctanoic acidrapid detectionsilicon quantum dotssmartphone sensingup-conversion

Identifiers

PMID41596929

DOI10.3390/foods15020331

PMCPMC12841523

What OpenQuestion holds

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LicenceCC BY

Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.