4.6 Article

Carbon-Dots-Based Lab-On-a-Nanoparticle Approach for the Detection and Differentiation of Antibiotics

期刊

CHEMISTRY-A EUROPEAN JOURNAL
卷 24, 期 18, 页码 4703-4709

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/chem.201706056

关键词

antibiotics; carbon dots; lab-on-a-nanoparticle; multidimensional sensing; statistical analysis

资金

  1. Ningbo Science and Technology Bureau [2016A610268, 2016C50009]
  2. Natural Science Foundation of China [21607160]
  3. W. C. Wong Education Foundation [rczx0800]
  4. Science Technology Department of Zhejiang Province [2016C37038]

向作者/读者索取更多资源

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., Cu2+, Ce3+ and Eu3+) 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 0.06m. Finally, the sensing system was successfully employed for residual antibiotics detection and identification in real food samples.

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