Semiconductor SERS Platform Enables Rapid Discrimination of Structurally Similar Flavonoids in Multicomponent Systems

Rapid and reliable discrimination of structurally similar small molecules in complex systems remains a significant challenge for chemical sensing, particularly when subtle structural variations lead to highly overlapping spectral features. Herein, we develop a semiconductor surface-enhanced Raman scattering (SERS) platform based on ZnO superstructures for the reliable discrimination of structurally similar flavonoids in both single-component and multicomponent systems. The ZnO-based SERS platform enables the generation of molecule-specific spectral fingerprints, with characteristic variations in both skeletal vibration and functional group regions, allowing effective differentiation of closely related flavonoids. By integrating multivariate statistical analysis, robust classification, and discrimination of flavonoids with highly similar structures were achieved, including in mixed-component systems. The practical applicability of the platform is further validated using real plant-derived samples, where distinct spectral signatures enable effective discrimination of samples with different compositional profiles, thereby demonstrating its capability for botanical origin authentication. Notably, the proposed approach allows rapid analysis with minimal sample pretreatment and without the need for chromatographic separation. These results demonstrate that ZnO-based semiconductor SERS sensing provides a robust and scalable strategy for the detection and discrimination of structurally similar flavonoids in complex systems, highlighting its practical applicability for quality control and authenticity assessment in food and plant-derived materials.