Sensing of perfluorinated compounds using a functionalized tricolor upconversion nanoparticle based fluorescence sensor array. Issue 10 (2nd September 2020)

• Record Type: Journal Article
• Authors: Yin, Mingyuan; Che, Lihua; Jiang, Shizheng; Deng, Qiliang; Wang, Shuo
• Is Part Of: Environmental science. Volume 7:Issue 10(2020)
• Page Start: 3036
• Page End: 3046
• Publication Date: 2020-09-02
• Subjects: Environmental sciences -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/d0en00554a
• Languages: English
• ISSNs: 2051-8153

Abstract

Abstract : Detection and identification of perfluorinated compounds (PFCPs) plays a crucial role in environmental monitoring, food safety and public health. Abstract : Detection and identification of perfluorinated compounds (PFCPs) plays a crucial role in environmental monitoring, food safety and public health. Fluorescence sensor arrays with multiple cross-reactive receptors can offer a highly effective approach for the purpose. Herein, we constructed an upconversion fluorescence sensor array based on perfluorooctyltriethoxysilane functionalized lanthanide-doped tricolor nanoparticles. The significant signal difference of probes toward targets endows such a sensor array an excellent discrimination property. The clustering map and dendrogram for identifying seven species of PFCPs (including perfluorooctanesulfonate potassium, perfluorodecanoic acid, perfluorononanoic acid, perfluorooctanoic acid, perfluoroheptanoic acid, perfluorohexanesulfonic acid potassium, and perfluorohexanoic acid) were obtained by linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA), respectively. The resulting fluorescence sensor array displayed sensitive response to targets even at a low level (40 nM). Blends of PFCPs could be identified accurately. Furthermore, PFCPs in real samples (tap water, surface seawater, river water and food packaging) have been effectively discriminated with 92.9% accuracy. The developed upconversion fluorescence sensor array provides a powerful tool for high-throughput identification of PFCPs in food and environmental samples, which overcomes the time-consuming complex analysis and heavy dependence of specific recognition elements.