학술논문

Magneto-Dielectric Composites Characterization Using Resonant Sensor and Neural Network Modeling
Document Type
Periodical
Source
IEEE Microwave and Wireless Technology Letters IEEE Microw. Wireless Tech. Lett. Microwave and Wireless Technology Letters, IEEE. 34(4):447-450 Apr, 2024
Subject
Fields, Waves and Electromagnetics
Magnetic resonance
Magnetic separation
Integrated circuit modeling
Q-factor
Nanoparticles
Sensors
Iron
Artificial neural networks (ANNs)
microwave characterization
PDMS-Fe₃O₄ composite
Language
ISSN
2771-957X
2771-9588
Abstract
This article presents a novel way to estimate magnetodielectric composites’ complex permittivity ( $\varepsilon $ ) and permeability ( $\mu $ ). A methodology based on artificial neural network (ANN) modeling is proposed to determine $\varepsilon $ and $\mu $ from $S$ -parameter measurements around 2.45 GHz, obtained using a new microstrip split ring resonator (SRR)-based resonant sensor.