Ultrasensitive, Rapid, and Incubation-Free Surface-Enhanced Raman Scattering Detection of Sulfasalazine with a GF@PDDA-Ag/rGO Functionalized Membrane and Machine Learning

Developing rapid detection methods with high sensitivity and real-time capabilities is a critical challenge for monitoring antibiotic pollution. This study presents a flexible surface-enhanced Raman scattering (SERS) sensing substrate (GF@PDDA-Ag/rGO) based on the poly dimethyl diallyl ammonium chloride (PDDA)-bridged assembly for real-time, ultrasensitive sulfasalazine detection. PDDA provided a positively charged polyelectrolyte layer, which directs AgNPs to assemble uniformly into hotspots, while reduced graphene oxide (rGO) enhances charge transfer and concentrates target molecules near these hotspots. The synergistic interaction among PDDA, Ag, and rGO endows this composite substrate with excellent performance. This is the first application of SERS for sulfasalazine detection, achieving a lowest detection concentration as low as 10–11 M, significantly outperforming other detection methods. No preprocessing or incubation is required, and the measurement time is within 1 s, enabling a highly sensitive response. In addition, this substrate demonstrated excellent uniformity (relative standard deviation, RSD = 2.67%) and long-term stability (>60 days). Furthermore, the addition of the Random Forest Regression (RFR) model for concentration prediction enhances both accuracy and convenience, with an R2 value of 0.9852. This efficient detection strategy has significant potential for on-site monitoring of antibiotic pollutants in food and environmental samples.