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Ultrabright gap-enhanced Raman tags for high-speed bioimaging

Author

Listed:
  • Yuqing Zhang

    (Shanghai Jiao Tong University
    Hangzhou Dianzi University)

  • Yuqing Gu

    (Shanghai Jiao Tong University)

  • Jing He

    (Shanghai Jiao Tong University)

  • Benjamin D. Thackray

    (Shanghai Jiao Tong University)

  • Jian Ye

    (Shanghai Jiao Tong University
    Shanghai Jiao Tong University
    Shanghai Jiao Tong University)

Abstract

Surface-enhanced Raman spectroscopy (SERS) is advantageous over fluorescence for bioimaging due to ultra-narrow linewidth of the fingerprint spectrum and weak photo-bleaching effect. However, the existing SERS imaging speed lags far behind practical needs, mainly limited by Raman signals of SERS nanoprobes. In this work, we report ultrabright gap-enhanced Raman tags (GERTs) with strong electromagnetic hot spots from interior sub-nanometer gaps and external petal-like shell structures, larger immobilization surface area, and Raman cross section of reporter molecules. These GERTs reach a Raman enhancement factor beyond 5 × 109 and a detection sensitivity down to a single-nanoparticle level. We use a 370 μW laser to realize high-resolution cell imaging within 6 s and high-contrast (a signal-to-background ratio of 80) wide-area (3.2 × 2.8 cm2) sentinel lymph node imaging within 52 s. These nanoprobes offer a potential solution to overcome the current bottleneck in the field of SERS-based bioimaging.

Suggested Citation

  • Yuqing Zhang & Yuqing Gu & Jing He & Benjamin D. Thackray & Jian Ye, 2019. "Ultrabright gap-enhanced Raman tags for high-speed bioimaging," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11829-y
    DOI: 10.1038/s41467-019-11829-y
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    Cited by:

    1. Jacopo Cardellini & Caterina Dallari & Ilaria Santis & Lorenzo Riccio & Costanza Ceni & Amelia Morrone & Martino Calamai & Francesco Saverio Pavone & Caterina Credi & Costanza Montis & Debora Berti, 2024. "Hybrid lipid-AuNP clusters as highly efficient SERS substrates for biomedical applications," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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