Issue 10, 2022

Facile and robust fabrication of hierarchical Au nanorods/Ag nanowire SERS substrates for the sensitive detection of dyes and pesticides

Abstract

Surface enhanced Raman spectroscopy (SERS) has emerged as a promising tool for the rapid and ultrasensitive recognition of trace amounts of environmental pollutants. Hierarchical SERS substrates usually show superior performance to single-component substrates but require complicated preparation protocols. Herein, a facile, robust and low-cost route for the fabrication of hierarchical SERS substrates has been reported, in which no complicated laborious protocols or sophisticated equipment is needed. In the hierarchical SERS substrate, Au nanorods were distributed onto the network of Ag nanowires through evaporation induced self-assembly. The density of the Au nanorods and Ag nanowires could be easily tailored by tuning the number of droplets of gold nanorod solution and the concentration of silver nanowire solution. The nanogaps formed between Au nanorods and Ag nanowires were able to induce a rich enhanced electromagnetic field area via localized surface plasmon resonances and surface plasmon polaritons to achieve amplification of the Raman signal. The as-prepared substrate showed high uniformity and was capable of identifying 10−12 M rhodamine 6G, 10−10 M thiram and 10−10 M crystal violet, with correlation coefficients (R2) all higher than 0.98. This approach can be employed for the detection of trace dyes, pesticides or other environmental pollutants with high sensitivity and uniformity.

Graphical abstract: Facile and robust fabrication of hierarchical Au nanorods/Ag nanowire SERS substrates for the sensitive detection of dyes and pesticides

Supplementary files

Article information

Article type
Paper
Submitted
08 Dec 2021
Accepted
09 Feb 2022
First published
14 Feb 2022

Anal. Methods, 2022,14, 1041-1050

Facile and robust fabrication of hierarchical Au nanorods/Ag nanowire SERS substrates for the sensitive detection of dyes and pesticides

S. Wang, B. Sun, H. Jiang, Y. Jin, J. Feng, F. An, H. Wang and W. Xu, Anal. Methods, 2022, 14, 1041 DOI: 10.1039/D1AY02080C

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