MCUT Research

Chemical Engineering Journal/ 2025, Vol. 521, 166636

Artificial intelligence integrated three-dimensional hybrid SERS sensor towards trace level molecular detection

Main authors: Petchi Raman Mariappan, Nazar Riswana Barveen, Chih-Yu Kuo, Yu-Wei Cheng/ MCUT/NTUT

A flexible 3D PPy@Au/PVDF SERS substrate was developed via oxidative polymerization and in-situ AuNP growth. The platform provides dense plasmonic hotspots with an EF of ~10⁹ and LOD of 10^-11 M for thiram. Integration with ANN enables 100% accurate spectral classification, demonstrating high sensitivity, selectivity, and reliability for real-sample detection. (論文連結)

This platform is suitable for rapid, non-destructive detection of pesticide residues on food surfaces. It also shows strong potential in environmental monitoring of organic pollutants and biomedical sensing of trace biomarkers, particularly for portable and real-time diagnostic systems.

The proposed AI-integrated SERS system advances food safety assurance and environmental surveillance, addressing critical public health concerns. It supports the development of smart sensing technologies, strengthening national capabilities in precision agriculture, sustainable monitoring and next-generation analytical diagnostics.