A High-Efficiency and Reconfigurable Rectenna Array for Dynamic Output DC Power Control

Wang, Yuchao; Song, Yangkun; Zhang, Bohan; Chen, Shaonan; Chen, Qiang; Zhang, Cheng

doi:10.3389/fphy.2022.866656

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…The EM characteristics of metamaterials rely on the pattern and order of the meta-atom (Cui, 2017). In the past few decades, metamaterial-inspired devices, such as the frequency selective filter (Khan and Eibert, 2018;Zhang et al, 2021a), perfect absorber (Peng et al, 2019;Zhang et al, 2021b), holographic imaging (Tsai et al, 2013;Wan et al, 2017), and meta-lens (Pendry, 2000), have found variety of applications in academia and industries (Zhang et al, 2021c;Dong et al, 2022;Wang et al, 2022). Among these applications, metamaterial absorbers (MMA) have been realized in the spectrum ranging from microwave to optics.…”

Section: Introductionmentioning

confidence: 99%

Fussy Inverse Design of Metamaterial Absorbers Assisted by a Generative Adversarial Network

et al. 2022

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The increasing demands for metasurfaces have led researchers to seek effective inverse design methods, which are counting on the developments in the optimization theory and deep learning techniques. Early approaches of the inverse design based on deep learning established a unique mapping between the device’s geometry parameters and its designated EM characteristics. However, the generated solution based on the traditional inverse design method may not be applicable due to practical fabrication conditions. The designers sometimes want to choose the most practical one from multiple schemes which can all meet the requirements of the given EM indicators. A fuzzy inverse design method is quite in demand. In this study, we proposed a fuzzy inverse design method for metamaterial absorbers based on the generative adversarial network (GAN). As a data-driven method, self-built data sets are constructed and trained by the GAN, which contain the absorber’s design parameters and their corresponding spectral response. After the training process is finished, it can generate multiple possible schemes which can satisfy the customized absorptivity and frequency bands for absorbers. The parameters generated by this model include structure sizes and impedance values, which indicates that it has the ability to learn a variety of features. The effectiveness and robustness of the proposed method have been verified by several examples for the design of both narrowband and broadband metamaterial absorbers. Our work proves the feasibility of using deep learning methods to break the limits of one-to-one mapping for the traditional inverse design method. This method may have profound usage for more complex EM device design problems in the future.

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Section: Introductionmentioning

confidence: 99%

Fussy Inverse Design of Metamaterial Absorbers Assisted by a Generative Adversarial Network

et al. 2022

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2D Material‐Enabled Optical Rectennas with Ultrastrong Light‐Electron Coupling

Nguyen

Yen

et al. 2022

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Optical rectennas extend the electromagnetic wave rectification process into the visible regime and provide a route toward high‐performance photodetection and energy harvesting. Here, the promise of 2D materials toward on‐chip optical rectennas is demonstrated. A self‐aligned patterning process yields lateral MIM structures where a nanometer‐sized air gap separates a 2D material contact from a metal electrode. This device can be scalably produced in large arrays using established microfabrication techniques. Different from previous approaches, the performance of the 2D rectenna can be adjusted through electrostatic gating. Optimization of the band alignment leads to strong rectification at wavelengths around 500 nm and clear polarization control. Comparison of wavelength‐dependent rectenna performance with a photon‐assisted tunneling model reveals a tenfold increase in photon‐electron coupling over nanotube‐based rectennas. The results highlight the potential of 2D material‐based rectennas for future quantum computing applications.

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High-Efficiency Rectenna Design for Batteryless Implantable Medical Devices Powered by RF Energy Harvesting in the ISM Band

Bouchoucha,

Omri,

Aguili

2023

2023 IEEE International Conference on E-Health Networking, Application &Amp;amp; Services (Healthcom)

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A High-Efficiency and Reconfigurable Rectenna Array for Dynamic Output DC Power Control

Cited by 4 publications

References 17 publications

Fussy Inverse Design of Metamaterial Absorbers Assisted by a Generative Adversarial Network

Fussy Inverse Design of Metamaterial Absorbers Assisted by a Generative Adversarial Network

2D Material‐Enabled Optical Rectennas with Ultrastrong Light‐Electron Coupling

High-Efficiency Rectenna Design for Batteryless Implantable Medical Devices Powered by RF Energy Harvesting in the ISM Band

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