Surface-Enhanced Raman Spectroscopy Method for Sensitive Detection of Antibiotic Residues by Layer-Optimized...

Surface-enhanced Raman scattering (SERS) has been widely applied to food safety screening owing to its high sensitivity and fingerprint recognition. However, SERS faces challenges in practical applications related to the precise control of the number of hot spots and the determination of how many of them actually contribute to the collected signal. In this study, silver nanoparticles (AgNPs) were used to construct a series of layer-tunable AgNP film structures by assembling one to five layers of AgNP thin films using a liquid-liquid interface self-assembly method to obtain a large number of vertically coupled nanogap structures. The relationship between the stacking number and the effective enhancement was evaluated using crystal violet as a probe molecule. The results showed that the SERS intensity increased from one to three layers and then declined, mainly originating from the competition between the vertical plasmon coupling and the finite optical penetration depth; the point-to-point relative standard deviation of the crystal violet signal at 1617 cm^-1, determined from 30 randomly selected positions, was lowest for the three-layer film (5.52%) and rose to 10.15% for the five-layer film. Finite element simulations and monolayer WS₂ buried-probe measurements supported this result. Using the optimized three-layer AgNP film, four fluoroquinolone antibiotics were detected. The method was also applied to antibiotic residue screening in spiked chicken extracts. The layer-optimization approach may be adapted to other nanoparticle sizes and excitation wavelengths for broader SERS applications in environmental and food safety monitoring.