Multicomponent Analysis in Surface-Enhanced Raman Spectroscopy: From Plasmonic Interfaces to Computational Analysis

Reliable multicomponent analysis has become an increasingly important objective in surface-enhanced Raman spectroscopy (SERS) as analytical applications extend beyond the detection of predefined molecular targets. However, identifying and quantifying multiple constituents within chemically complex samples remains challenging because SERS spectra do not directly represent the underlying chemical composition. Instead, they are shaped by selective molecular representation at plasmonic interfaces and the superposition of signals from multiple constituents, creating an inherently ambiguous relationship between spectral observations and the chemical system being analyzed. This review examines the physicochemical origins of these challenges and the analytical strategies developed to overcome them. Existing approaches are organized according to their primary analytical function, encompassing selective interfacial control, physical separation, computational analysis, and integrated analytical workflows. Each strategy is evaluated in the context of the specific analytical limitations it addresses, providing a structured perspective on the capabilities and remaining challenges of multicomponent SERS analysis.