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A Filter-based Surface Enhanced Raman Spectroscopic Assay for Rapid Detection of Chemical Contaminants
Published on: February 19, 2016
Stellaris Somnia-inspired interlaced gold nanoarray as a novel hotspot-optimized SERS platform for food hazards
Pengxiang Wang1, Hong Lin1, Limin Cao1
1State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong 266003, China.
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Surface-enhanced Raman spectroscopy (SERS) holds great promise for sensitive molecular detection across diverse fields, including environmental monitoring and food safety. However, its practical efficacy is often constrained by relatively low sensitivity and poor reproducibility over large areas. In this study, a hotspot-optimized SERS platform is developed via the interfacial co-assembly of gold nanoparticles (AuNPs) of two distinct sizes. Inspired by the clustered luminosity of stars, this Stellaris Somnia-inspired interlaced nanoarray (SSIN) features a monolayer of larger AuNPs (>90 nm) complemented by smaller AuNPs (21 nm) intercalated within interstitial gaps, significantly increasing hotspot density and SERS enhancement. This strategy enables the fabrication of highly sensitive and signal-stable nanoarrays without relying on complex anisotropic nanomaterials or laborious top-down processes. The SSIN substrate achieved exceptional detection limits of 0.392 ng/L for malachite green (MG). In real fish samples such as large yellow croaker and channel catfish, the platform successfully detected malachite green at concentrations as low as 0.5 μg/kg. The results were consistent with those obtained by HPLC-MS/MS, confirming high analytical accuracy. The substrate enabled label-free detection of trace pesticides, including difenoconazole, thiabendazole, and thiram, demonstrating broad-spectrum applicability. Moreover, the SSIN substrate maintains over 75 % of its SERS activity after 180 days of storage at room temperature, highlighting its long-term stability. This work introduces a rational, scalable, and materials-efficient co-assembly strategy to engineer robust, hotspot-dense SERS platforms. The SSIN substrate holds great promise for practical applications in environmental contaminants and food hazards monitoring and the broader field of trace analyte detection.

