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Detection and Identification of Nitrile Compounds via Recognition-Enabled Chromatographic 19F NMR.
Bao, Wenjing; Gu, Guangxing; Wu, Jian; Gu, Yu-Cheng; Zhao, Yanchuan.
  • Bao W; Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Ling-Ling Road, Shanghai 200032, China.
  • Gu G; Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Ling-Ling Road, Shanghai 200032, China.
  • Wu J; Instrumental Analysis Center, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China.
  • Gu YC; Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K.
  • Zhao Y; Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Ling-Ling Road, Shanghai 200032, China.
Anal Chem ; 96(11): 4463-4468, 2024 Mar 19.
Article en En | MEDLINE | ID: mdl-38462969
ABSTRACT
The surge in applications of nitrile compounds across diverse fields, such as pharmaceuticals, agrochemicals, dyes, and functional materials, necessitates the development of rapid and efficient detection and identification methods. In this study, we introduce a chemosensing strategy employing a novel 19F-labeled probe, facilitating swift and accurate analysis of a broad spectrum of nitrile-containing analytes. This approach leverages the reversible interaction between the 19F-labeled probe and the analytes to produce chromatogram-like outputs, ensuring the precise identification of various pharmaceuticals and pesticides within complex matrices. Additionally, this dynamic system offers a versatile platform to investigate through-space 19F-19F interactions, showcasing its potential for future applications in mechanistic studies.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article