IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1305-d732234.html
   My bibliography  Save this article

AAO Template-Assisted Fabrication of Ordered Ag Nanoparticles-Decorated Au Nanotubes Array for Surface-Enhanced Raman Scattering Detection

Author

Listed:
  • Kexi Sun

    (Key Laboratory of Electromagnetic Transformation and Detection of Henan Province, College of Physics and Electronic Information, Luoyang Normal University, Luoyang 471934, China
    Key Laboratory of Materials Physics and Anhui Key Laboratory of Nanomaterials and Technology, Institute of Solid State Physics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China)

  • Quan Deng

    (Institute of Plasma Physics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China)

  • Haibin Tang

    (Key Laboratory of Materials Physics and Anhui Key Laboratory of Nanomaterials and Technology, Institute of Solid State Physics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
    University of Science and Technology of China, Hefei 230026, China)

Abstract

Highly sensitive and reproducible surface-enhanced Raman scattering (SERS) substrates are the main challenge for practical applications. In this work, an ordered and hierarchical Ag nanoparticles (Ag-NPs)-decorated Au nanotubes (Au-NTs) array was achieved based on a funnel-shaped pore anodic aluminum oxide (AAO) template-assisted strategy. First, funnel-pore-AAO templates were fabricated by further oxidation of conical-pore-AAO templates achieved by multistep anodization and etching. Then physical sputtering was used to assemble the Au-NTs and Ag-NPs using the as-prepared funnel-pore-AAO as sacrificial templates. SEM revealed abundant sub-10 nm neighboring gaps and sub-10 nm nanocavities at the bottom of the nanotubes because of the special shape of the AAO template, which resulted in abundant strong “hot spots” contributing to the sensitive SERS detection. The resultant hierarchical substrates manifested a SERS enhancement factor of 1.8 × 10 7 and reproducible response to 10 −11 M rhodamine 6G and 10 −8 M methyl parathion, showing potential in SERS-based rapid detection of trace pollutants in the environment.

Suggested Citation

  • Kexi Sun & Quan Deng & Haibin Tang, 2022. "AAO Template-Assisted Fabrication of Ordered Ag Nanoparticles-Decorated Au Nanotubes Array for Surface-Enhanced Raman Scattering Detection," Sustainability, MDPI, vol. 14(3), pages 1-9, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1305-:d:732234
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1305/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/3/1305/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1305-:d:732234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.