Wekalao, JacobJonas MuhekiHussein A. ElsayedHaifa A. AlqhtaniMayi Bin-JumahAmuthakkannan RajakannuAhmed MehaneyStefano Belluci2025-12-052025-12-052025-12-01Wekalao, J., Muheki, J., Elsayed, H. A., Alqhtani, H. A., Bin-Jumah, M., Rajakannu, A., ... & Belluci, S. (2025). AI-Augmented terahertz metamaterial biosensor for rapid and accurate isoquercitrin detection in herbal medicines. Nanocomposites, 11(1), 297-319.https://www.tandfonline.com/doi/full/10.1080/20550324.2025.2592170https://hdl.handle.net/20.500.12504/2679We present a novel metamaterial-based terahertz biosensor integrated with AI for rapid isoquercitrin detection in herbal medicines. The sensor, optimized through COMSOL simulations, delivers exceptional sensitivity (300GHzRIU-1) and detects refractive index changes as small as 0.05 RIU. Its precision is validated by a near-perfect linear correlation (R2 ¼ 99.73%) and stable performance metrics, including a 0.015 THz FWHM and Quality Factor of 47. Uniquely, a one-dimensional convolutional neural network augments predictive capability, achieving R2 values up to 1.00 across diverse conditions. This synergistic approach—combining terahertz spectroscopy, metamaterial-enhanced signal amplification, and AI-driven modeling—offers a transformative solution for standardizing and quality-controlling botanical therapeutics. By enabling fast, accurate, and scalable quantification of bioactive compounds, the system sets a new benchmark for analytical methodologies in natural product research.enMetamaterial sensorherbal medicinegraphenemultiresonatorquality controlabsorption predictionArticle