2021
DOI: 10.48550/arxiv.2101.02298
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Implementation of conformal digital metasurfaces for THz polarimetric sensing

Abstract: Monitoring and controlling the state of polarization of electromagnetic waves is of significant interest for various basic and practical applications such as linear position sensing and medical imaging. Here, we propose the first conformal digital metamaterial absorber to detect the polarization state of THz incident waves. The proposed polarimeter is capable of characterizing four independent polarization states of (TE, TM, ±45 • linear, and RCP/LCP) by observing the reflectivity of the structure with respect… Show more

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Cited by 2 publications
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“…ML is a branch of artificial intelligence extensively used in different engineering applications in making decisions or predictions. This study addresses the challenge of using optimized ML models to forecast the metamaterial antenna's gain and bandwidth [1,2].…”
Section: Introductionmentioning
confidence: 99%
“…ML is a branch of artificial intelligence extensively used in different engineering applications in making decisions or predictions. This study addresses the challenge of using optimized ML models to forecast the metamaterial antenna's gain and bandwidth [1,2].…”
Section: Introductionmentioning
confidence: 99%
“…Metamaterials,as artificial media composed of engineered subwavelength periodic or nonperiodic geometric arrays, have witnessed enormous attentions due to their exotic properties to modify the permittivity and permeability of materials. [1][2][3] Today, just two decades after the first implementation of metamaterials by David Smith and colleagues 4 who unearthed Veselago's original paper, 5 metamaterials and their 2D counterpart, metasurfaces, have been widely used in practical applications such as, but not limited to, polarization conversion, 6,7 reconfigurable wave manipulation, 8,9 vortex generation, 10,11 and perfect absorption. 12,13 However, all of the above-mentioned works are based on a traditional design approaches, consisting of model designs, trial-and-error method, parameter sweep, and optimization algorithms.…”
Section: Introductionmentioning
confidence: 99%