A SERS sensor based on 3D nanocone forests capable of intelligent classification of aquatic product dyes

Abstract

In this work, a novel surface-enhanced Raman scattering (SERS) sensor with high performance and capable of intelligent classification is developed for detection of prohibited dyes in aquatic products. The sensor is composed of nanocone forests (NCFs) grafted with gold (Au) nanoparticles (AuNPs), which are further attached with silver (Ag) NPs. The prepared 3D Ag-AuNPs@NCFs exhibit plasmonic hybridization modes, and thus are able to form enhanced electromagnetic fields, endowing the sensor with high sensitivity. The detection limit of this sensor for R6G is as low as 10⁻⁹ M, and the relative standard deviation is smaller than 6.84%. Based on this sensor, aquatic product dyes with concentrations lower than the limits of visual recognition are conveniently detected. Besides, with the assistance of a convolutional neural network model, the different dyes with coincident Raman peaks and similar colors are100% classified. These results indicate that such a 3D Ag-AuNPs@NCF-based SERS sensor has great potential in practical applications.