Flexible Silver Nanoflower SERS Substrates with Optical Spot-Size Matching: Preparation and High-Performance Detection of Veterinary Drug Residues

The reproducibility and reliability of surface-enhanced Raman spectroscopy (SERS) detection are constrained by the heterogeneous distribution of “hot spots”. While conventional physical deposition or template assembly methods can produce rigid and homogeneous substrates, they struggle to precisely regulate the self-assembly behavior of nanoparticles in flexible hydrogels. The core challenge lies in minimizing the variation in “hot spots” density across detection zones within hydrogels to enhance detection consistency and reliability of flexible SERS substrates. To address these issues, this study successfully constructed a flexible SERS substrate that integrates a high density of uniformly distributed SERS “hot spots” and environmental interference resistance. This was achieved by elucidating the synergistic matching mechanism between silver nanoflower morphology and laser spot size, combined with the flexible carrier properties of hydrogel chips. Using veterinary drug enrofloxacin in complex matrices as a model to validate the analytical performance of the SERS substrate, the results demonstrated significant advantages: its sensitivity reached 47.96 ppb, the entire detection process was completed within 20 min, and it effectively resisted background interference. In real milk sample validations, the substrate demonstrated spike recovery rates of 88.3%-114%, with relative standard deviations (RSD) controlled within 1.78%-7.83% across all concentration gradients. This work establishes a novel, sensitive, and reliable analytical platform for rapid screening of veterinary drug residues in food systems, holding significant application potential in food safety monitoring.