volume | PIER Journals

Abstract

This paper presents a reconfigurable multilayer graphene antenna for terahertz sensing, machine learning-based frequency and bandwidth estimation. The antenna utilizes the tunable electromagnetic properties of graphene, enabling dynamic reconfiguration of the resonant frequency and bandwidth. By adjusting key physical parameters including chemical potential, relaxation time, and temperatur, the antenna achieves frequency tuning from 1.542 THz to 1.562 THz, with an improved return loss reaching -30.8 dB and a bandwidth range from 91 GHz to 96 GHz. Furthermore, the resonance frequency and bandwidth are predicted using machine learning algorithms, including Random Forest and XGBoost, with results that closely match simulation data. These results highlight the potential of the proposed structure not only for adaptive communication systems but also for terahertz sensing platforms requiring frequency agility and environmental responsiveness.

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Dr. Hamza Ben Krid

Prof. Aymen Hlali

Professor Hassen Zairi