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Controllable MXene Nano-sheet/Au Nanostructure Architectures for the Ultra-sensitive Molecule Raman Detection

Abstract

Surface enhanced Raman scattering (SERS) spectroscopy aims to enhance the relatively weak molecule vibration based on the electromagnetic enhancement (EE) and chemical enhancement (CE) mechanisms, and offers a potential way for the material identification even up to single molecule level at the atmosphere condition. We subtly combine advantages of the EE and CE, and propose new MXene (Ti3C2TX) nano-sheet/Au nanostructure architectures to break through the limitation of the Raman detection with a long time stability. The MXene nano-sheets with an excellent biocompatibility can effectively prevent structural distortion from the interaction with the Au NSs, can also guarantee a high enchantment effect owing to the spatially extended electromagnetic field distribution and electron injection into molecules. The self-assembled Au nanostructures are aggregated based on the Volmer-Weber growth model, and the electromagnetic field distribution radically evolves depending on the morphologies of the resultant Au nanostructures, resulting in a drastic compensation for the limited EE of the MXene nano-sheets. As a consequence, the intensified Raman vibrational signals of R6G molecules leads to a high enhancement factor of 2.9 × 107 even at an ultra-low concentration of 10-10 M. Likewise, the Raman signals of the methylene blue (MB) and crystal violet (CV) molecules can be also detected at low concentrations below 10-8 M, manifesting universal applications of the MXene/Au architectures for the ultra-sensitive molecule detection at the atmosphere condition.

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Supplementary files

Publication details

The article was received on 27 Sep 2019, accepted on 28 Oct 2019 and first published on 29 Oct 2019


Article type: Communication
DOI: 10.1039/C9NR08340E
Nanoscale, 2019, Accepted Manuscript

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    Controllable MXene Nano-sheet/Au Nanostructure Architectures for the Ultra-sensitive Molecule Raman Detection

    M. Yu, S. Liu, D. Su, S. Jiang, G. Zhang, Y. Qin and M. Li, Nanoscale, 2019, Accepted Manuscript , DOI: 10.1039/C9NR08340E

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