AI-Augmented terahertz metamaterial biosensor for rapid and accurate isoquercitrin detection in herbal medicines
Year: 2025
Type: article
Abstract: We 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 (300 GHz·RIU-1) and detects refractive index changes as small as 0.05 RIU. Its precision is validated by a near-perfect linear correlation (R2 = 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.
Source: Nanocomposites
Institutions: University of Science and Technology of China, Kyambogo University, University of Houston, University of Ha'il, Princess Nourah bint Abdulrahman University, National University of Science and Technology, National University of Science and Technology, National University of Science and Technology, National University of Sciences and Technology, Beni-Suef University, Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,590
Award: G1807826938
OpenAlex ID: W4416852805