Quantitative Analysis of Perfluorooctanoic Acid and Perfluorooctane Sulfonate Mixtures Using 3D Surface-Enhanced Raman Spectroscopy with Single-Photon Detection

Per- and polyfluoroalkyl substances (PFASs) are persistent environmental contaminants that commonly occur as mixtures, yet their weak Raman scattering and overlapping vibrational features make direct optical quantification challenging. Here, we develop a plasmonic nanosensing platform that integrates three-dimensional Ag nanoparticle surface-enhanced Raman spectroscopy (SERS) substrates with single-photon Raman readout for quantitative analysis of binary perfluorooctanoic acid (PFOA)/perfluorooctane sulfonate (PFOS) mixtures. The multilayer silver nanoparticle (AgNP) architecture provides dense electromagnetic hot spots to amplify weak PFAS signatures, while photon-counting detection improves the measurement of low-intensity Raman features. Mixed spectra obtained from a 4 × 4 concentration matrix spanning 10−6 to 10−15 M exhibited substantial peak overlap, band broadening, and concentration-dependent spectral contour changes, highlighting the limitations of single-band calibration. Full-spectrum multivariate regression was therefore used to extract composition-dependent information from the coupled SERS response. Under nested cross-validation with replicates grouped by mixture composition, both partial least squares regression and linear support vector regression captured the main concentration-dependent spectral variation, achieving R2 values of approximately 0.81–0.87 across the two analytes and identifying experimental concentration levels within one adjacent level after nearest-level assignment. These results demonstrate that coupling engineered plasmonic AgNP substrates with single-photon Raman detection enables mixture-resolved PFAS quantification from weak and overlapping SERS signatures, providing a nanomaterial-enabled framework for environmental molecular sensing.