Abstract-In this paper, modeling and experimentation of a Rectangular Patch Resonator (RPR) covered with a dielectric superstrate are investigated.The RPR criteria are established theoretically and experimentally, to be used in future prospects as an electromagnetic (EM) sensor for the characterization of superstrates. The theoretical model is based on the moment method (MoM) via Galerkin's approach, in which three types of basis and testing functions are used. These functions as well as the spectral dyadic Green function are efficiently implanted with compact structured Fortran 90 codes. The EM commercial HFSS and CST Microwave Studio softwares are used to simulate the proposed RPR prototypes. The accuracy of the obtained results is assessed using four prototypes of RPRs operating around 6 GHz, taking into account only the resonant frequency of the fundamental dominant mode. The theoretical model is compared to simulation and measurement results, and very good agreements are observed.

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ABSTRA CT:Closed-form expressions for two kinds of Hankel transform integrals, which are encountered in the spectral moment method solution of a circular patch, are obtained. Application of the newly obtained formulas alleviates dramatically the algebraic work for determining the Hankel transforms of the current basis functions involving Chebyshev polynomials and edge condition. Computed moment method results using these expressions are presented. The effects of both uniaxial anisotropy in the substrate on the resonant frequency and bandwidth are investigated.

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"Toxic gases are responsible for the loss of many human lives around the world, which is increasing every year. Toxicity can have various biological aspects on the human body. The exposure to its gases leads to harmful consequences for the organism, which leads to metabolic reactions and even death. For this purpose, the initial step is to detect these gases with miniature flexible structures and solid progressed estimation methods using a simulation software tool. The studied sensor is based on the frequency characterization of an RF Planar Resonant Structure, in which the active element is a patch of radiating graphene printed on a polyimide film (Kapton). The objective of this work is to use our Graphene-Kapton sensor for non-invasive testing applications. In our case, the device is tested to detect and recognize several dangerous and toxic gases such as Fluorine azide (F2N), Hydrogen Iodide (HI), Nitrogen (N2), Methane (CH4), and Carbon monoxide (CO). The simulation results indicate that the Graphene-Kapton flexible sensor exhibits an important sensing performance. The sensor is able to detect all the tested gases with a good sensitivity depending on each gas. As well as, the sensor shows a high sensitivity (0.1± 0.01)* 106 [ppm]-1 (0.1 [ppt]-1) of methane (CH4) gas with detection limit of (9±0.1) *10-6 ppm (9 ppt). "

In-body implanted antennas are surrounded by materials (muscle, fat tissue, skin, etc.), which have special electromagnetic parameters. The effects of these near-field mediums on the implanted antenna are unknown. Performance patch resonator, as the resonant frequency and the quality factor depends on the dielectric parameters of the various materials involved in their structures. In applications of microwave system for the dielectric substrate and superstrate are made of materials with low losses for the best operation. When used as sensors, some of the dielectric layers may be made with an unknown material; changes of parameters of the resonator, mainly the change of the increase in the frequency and quality factor are closer to the complex permittivity of the unknown material. In the particular application, a patch sensor can be used to evaluate the specific permittivity layers by comparing the measured parameters of the patch with a reference structure and those obtained with the unknown material. This work aims to study a planar biosensor for characterizing biological materials in order to derive the dielectric parameters. The medical applications are to detect abnormalities body using the structures raised as nondestructive applicators. To focus on this issue, it is necessary to make simulations with HFSS on a rectangular planar resonator by a coaxial fed, to use this device as an applicator to characterize various homogeneous and heterogeneous materials such as muscle, skin and fat.

The authors' research work has for objective the study of a sensor with planar resonator for applications in the non-destructive control. In this context, two approaches were defined. In a first part, a conception, a modeling, a simulation with commercial software (HFSS, CST), a realization and measurements were treated on Rectangular Patch Resonators (RPR). The proposed theoretical analysis is based on the Moment Method (MoM) via the Galerkin's approach, in which three types of entire domain basis functions are used to expand the patch currents. While, the first two types of basic functions involve a set of sinusoidal cavity modes without edge conditions (sbf-wo-ec) and with edge conditions (sbf-w-ec), and in order to incorporate the edge conditions (cp-ec), the third one consists of Chebyshev polynomials combinations with weighting factors. These last ones as well as the Green Dyadic spectral functions are efficiently implanted with compact Fortran 90 codes. Two EM commercial software HFSS and CST was used to validate the proposed RPR prototypes. The exactness of the obtained results is estimated using four prototypes operating near 6 GHz, taking into account only the fundamental mode resonant frequency. The theoretical model is compared with the simulations and the measurement results. The second approach of the authors' work which is developed in this paper is focused on the characterization of biological materials in vitro using the RPR prototypes proposed as applicator in the non-destructive control and the medical domain to find the abnormalities of these tissues such as: eczema, psoriasis, cancer, etc. The authors' center of interest will be managed towards the dielectric properties of the biological material to extract the relative permittivity and the loss factor on several samples (liver, fat, chicken, butter, foie gras, etc.).