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Carbon‐Dots‐Based Lab‐On‐a‐Nanoparticle Approach for the Detection and Differentiation of Antibiotics
Author(s) -
Qiao Li'na,
Qian Sihua,
Wang Yuhui,
Yan Shifeng,
Lin Hengwei
Publication year - 2018
Publication title -
chemistry – a european journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.687
H-Index - 242
eISSN - 1521-3765
pISSN - 0947-6539
DOI - 10.1002/chem.201706056
Subject(s) - antibiotics , carbon nanoparticles , nanotechnology , nanoparticle , carbon fibers , computer science , microbiology and biotechnology , biology , materials science , composite number , algorithm
Fluorescent carbon dots (CDs) have received considerable attention in recent years due to their superior optical properties. To take further advantages of these unique features, herein, a CDs‐based “lab‐on‐a‐nanoparticle” approach for the detection and discrimination of antibiotics is developed. The sensing platform was designed based on the different channel's fluorescence recoveries or further quenching of the full‐color emissive CDs (F‐CDs) and metal ion ensembles upon the addition of antibiotics. The F‐CDs exhibited unusually comparable emission intensity nearly across the entire visible spectrum even as the excitation wavelength is shifted, making it very suitable for the construction of multi‐channel sensing systems. The sensing platform was fabricated on the basis of the competing interaction of metal ions with the F‐CDs and antibiotics. Three metal ions (i.e., Cu 2+ , Ce 3+ and Eu 3+ ) can efficiently quench the fluorescence of the F‐CDs. Upon the addition of antibiotics, the fluorescent intensities either recovered at different emission wavelengths or were further quenched to various degrees. The fluorescence response patterns at different emission wavelength were characteristic for each antibiotic and can be quantitatively differentiated by standard statistical methods (e.g., hierarchical clustering analysis and principal component analysis). Moreover, as an example, the proposed method was applied for quantitative detection of oxytetracycline with a limit of detection to be 0.06 μ m . Finally, the sensing system was successfully employed for residual antibiotics detection and identification in real food samples.