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Polycyclic aromatic hydrocarbons (PAHs), due to their high hydrophobicity, have low affinity for metallic SERS-active surfaces, which leads to their low SERS detection sensitivity. Various functional groups have been used to improve the affinity of metallic substrates towards the target PAHs. However, a large portion of the signals generated from the “first-layer effect” of the functionalized substrates may complicate the spectrum, leading to a distortion in the assignment of the intrinsic SERS fingerprints of PAHs. In this study, a SERS sensor composed of Au nanoparticles (AuNPs) and reoxidized graphene oxide (rGO) was developed for the simultaneous determination of 16 EPA priority PAHs. The synthesis of the rGO/AuNP substrate can be realized without a complicated modification process. All the 16 PAHs could be identified based on their characteristic peaks in the presence of the composited substrate, with estimated LOD as low as 0.2–2 ng·mL −1 . The binary linear regression was optimized as the fitting model for all PAHs except for benzo(k)fluoranthene, with the linear correlation coefficient ranging from 0.9889 to 0.9997. Based on the developed SERS substrates and sample pretreatment, the characteristic SERS peaks of four PAHs in Chinese traditional fried food (youtiao) were identified without any background interference. The whole detection process only takes approximately 15 minutes. The results demonstrate the potential of the multicomponent on-field detection of PAHs.

A Versatile SERS Sensor for Multiple Determinations of Polycyclic Aromatic Hydrocarbons and Its Application Potential in Analysis of Fried Foods