Sensitive detection of bisphenol A by coupling solid phase microextraction based on monolayer graphene-coated Ag nanoparticles on Si fibers to surface enhanced Raman spectroscopy

In this work, a facile method coupling solid phase microextraction (SPME) with surface enhanced Raman spectroscopy (SERS) was developed for the detection of trace bisphenol A (BPA). Monolayer graphene-coated Ag nanoparticles (Ag NPs) were fabricated on the Si fiber, which made the Si fiber retain functions of both as a SERS-active substrate and SPME fiber to realize in situ rapid determination of BPA. The SERS-active SPME fiber was immersed in water to extract BPA prior to its detection by SERS. The relative standard deviation (RSD) values of the uniformity and the reproducibility of the SERS-active SPME fiber are 14% and 13%, respectively. The characteristic SERS intensity versus BPA concentration showed a linear relationship (R2 = 0.958). Due to the combination of the SERS method with SPME, this method exhibits extremely high sensitivity and excellent stability for the detection of BPA, with a limit of detection as low as 1 μg L−1. The method was successfully used for the determination of BPA in water samples with spiked recoveries ranging from 97% to 110%. Compared to the conventional SERS methods used for the detection of BPA, the present method not only retains the advantages of SERS but also provides several unique advantages including preconcentration of analytes, separation of analyte from sample matrices and improvement of sensitivity, thus making its promising application in environmental analysis of BPA. [Display omitted] •BPA was rapidly determined in situ by a SPME-SERS method.•Monolayer graphene-coated Ag NPs were fabricated on the Si fiber as a SERS-active SPME fiber.•Preconcentration of BPA by the SPME also enhanced the sensitivity of the proposed method.•This method exhibits extremely high sensitivity and excellent stability for the detection of BPA.•This method was successfully used for the determination of BPA in water samples.