A green carbon dots-based fluorescent sensor for selective and visual detection of nitrite triggered by the nitrite–thiol reaction. (13th May 2020)

• Record Type: Journal Article
• Authors: Yue, Xiaoyue; Zhou, Zijun; Wu, Yongmei; Jie, Mingsha; Li, Yan; Guo, Haobin; Bai, Yanhong
• Is Part Of: New journal of chemistry. Volume 44:Number 20(2020)
• Page Start: 8503
• Page End: 8511
• Publication Date: 2020-05-13
• Subjects: Chemistry -- Periodicals; Chimie -- Périodiques; 540
• DOI: 10.1039/d0nj01025a
• Languages: English
• ISSNs: 1144-0546

Abstract

Abstract : Selective and visual detection of nitrite is realized through the inner-filter effect triggered by the nitrite–thiol reaction based on green carbon dots. Abstract : Nitrite misuse seriously threatens food safety, therefore, it is of significance to develop a facile, sensitive and selective methodology for trace detection of nitrite in food samples for ensuring people's health and safety. Herein, a novel fluorescent sensor was successfully designed for selective, sensitive and visual detection of nitrite. This sensing mechanism involves the inner-filter effect between synthetic green carbon dots and the S -nitrosothiol compound. Green carbon dots were synthesized using a one-step hydrothermal method and used as fluorescent probes, and S -nitrosothiol was generated through the π-conjugation triggered nitrite–thiol reaction. Selective and sensitive nitrite detection was realized using a fluorescence spectrophotometer in the detection range of 0.4–20 μg mL −1 . The detection limit of the developed method was calculated to be 0.23 μg mL −1 with satisfactory recoveries ranging from 86.61% to 103.22%. Upon illumination with the help of a portable ultraviolet lamp, the brightness and color of the green fluorescent probe changed with the addition of nitrite at different concentrations. Visual changes were directly observed with the naked eye and used for the qualitative and semiquantitative analysis of nitrite contents. The developed fluorescent sensor offers an effective, simple, rapid and low cost analytical method for sensitive and visual nitrite detection in meat samples to monitor and reduce the risk of nitrite overuse in food processing.