Polarization controlling idea in graphene-based patch antenna

Kiani, Narges; Hamedani, Farzad Tavakkol; Rezaei, Pejman

doi:10.1016/j.ijleo.2021.166795

Cited by 24 publications

(9 citation statements)

References 20 publications

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“…Compared to this study, the present work exhibits higher radiation efficiency (76% compared to 16.2%). Furthermore, unlike the proposed antenna, none of the antennas reported in [25][26][27][28][29][30][31][32][33][34][35] demonstrate completely similar LHCP and RHCP radiation patterns.…”

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confidence: 88%

“…Compared to this study, the present work demonstrates a significantly enhanced radiation efficiency of 76%, as opposed to the 30% achieved in the former. Furthermore, unlike the proposed antenna, none of the antennas reported in [25][26][27][28][29][30][31][32][33][34][35] demonstrate similar LHCP and RHCP radiation patterns. Additionally, it is worth noting that this study reports the novel application of a static magnetic field for polarization reconfiguration, marking a notable advancement in the field.…”

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confidence: 88%

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Graphene-based terahertz antenna with polarization reconfiguration

Fakhte,

Taskhiri

2023

Phys. Scr.

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This article presents the design of a terahertz antenna with the ability to reconfigure its polarization using graphene's anisotropic properties. By applying a DC magnetic flux, the graphene conductivity tensor can be transformed into a non-diagonal tensor. Conversely, the magnetic bias can be switched off to revert the tensor to a diagonal state. This approach allows the antenna to switch between linear and circular polarizations, making it highly versatile for terahertz applications. Additionally, by altering the direction of the applied DC magnetic bias, one can select the rotation direction of circular polarization between left and right hand. The feeding line and ground plane of the antenna are made of silver metal, and its behavior in the terahertz band is described using the Modified Relaxation-Effect model, which is more accurate than the skin effect model for this band. The finite element numerical method is utilized to analyze the antenna, which yields results consistent with the design predictions. The antenna’s impedance bandwidth spans 2.8 to 3.22 terahertz for linear polarization and 2.9 to 3.18 THz for circular polarization. The antenna’s maximum gain is 6 dB for linear polarization and 5 dB for circular polarization. The axial ratio for circular polarization is 1.36 in the middle of the band, which is below the 3dB threshold for circular polarization. The antenna produces directive patterns for both linear and circular polarizations. The key innovation of this antenna design lies in its unique utilization of a magnetostatic field to achieve reconfiguration in the terahertz graphene dielectric resonator antenna, a method that has not been previously documented in literature.

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confidence: 88%

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confidence: 88%

Graphene-based terahertz antenna with polarization reconfiguration

Fakhte,

Taskhiri

2023

Phys. Scr.

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“…Since we can change the chemical potential of graphene by external bias voltage or chemical doping, graphene is an adjustable metamaterial [14]. We used this graphene capability to design the antennas with performance in far-field and terahertz range central frequency due to control its polarization just by changing the Fermi energy level of the graphene [15][16][17][18].…”

Section: Fig 1 Exfoliation Of Graphite To Create Graphenementioning

confidence: 99%

Multiband Polarization Insensitive and Tunable Terahertz Metamaterial Perfect Absorber Based on The Heterogeneous Structure of Graphene

Razani

Rezaei

2021

Preprint

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In this paper, we present and investigate a multi-band metamaterial perfect absorber (MPA) based on the heterogeneous structure of graphene with Cu and SiO 2 substrates. The top layer of structure consist of one graphene disk at the center and four graphene solid triangle with semicircular cuts on them that surround the central disk. This heterogeneous structure causes us to achieve 97.06%, 94.71%, 99.7% and 99.5% perfect absorptions peaks at 28239.7 nm, 31048.9 nm, 50898.6 nm and 70689.1 nm, respectively. The absorption mechanism based on electric fields has been investigated. We can shift the wavelength of absorption peaks to our required wavelength by changing the Fermi level (µc) of graphene. Two absorption peaks of this absorber remain unchanged in different incident angle. In addition, very important point about this structure is that it is not sensitive to polarization and this feature makes the proposed absorber very suitable for applications such as imaging, filtering, sensing and detecting applications.

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“…[1] Microstrip antennas have a lot of appealing characteristics, such as small size, light weight, low cost, and so on. [2] This type of antenna is used in a wide range of wireless communication applications, particularly in mobile communication devices. Microstrip patch antennas, on the other hand, have a low gain and an extremely narrow In this study, a model is used to design an RFID tag antenna utilizing graphene materialbased deep learning to avoid unnecessary delays.…”

Section: Introductionmentioning

confidence: 99%

“…Deep Learning RFID Tag Antenna is suggested high-frequency antenna, a one atom thick two-dimensional carbon crystal based on graphene material, might improve radio communications. [2] These advances might be possible because to graphene's unique structure. Finally, the choice of graphene as the basis for this micro antenna was influenced by electron behavior.…”

Section: Introductionmentioning

confidence: 99%

Development of RFID Tag Antenna With Graphene Material Using Deep Learning

Rajalakshmi¹,

Jagan²,

Padmapriya³

et al. 2022

J. Phys.: Conf. Ser.

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To avoid unnecessary delays, develop an RFID tag antenna using graphene material-based deep learning in this project. The Deep Learning RFID Tag Antenna, a one-atom thick two-dimensional carbon crystal based on graphene material, is suggested as a high-frequency antenna that could improve radio communications. The experimental results reveal that the deep learning method performs well and accurately in predicting the EM response of graphene-based materials, with an accuracy of over 99 percent and a time savings of at least 99 percent.

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Polarization controlling idea in graphene-based patch antenna

Cited by 24 publications

References 20 publications

Graphene-based terahertz antenna with polarization reconfiguration

Graphene-based terahertz antenna with polarization reconfiguration

Multiband Polarization Insensitive and Tunable Terahertz Metamaterial Perfect Absorber Based on The Heterogeneous Structure of Graphene

Development of RFID Tag Antenna With Graphene Material Using Deep Learning

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