Since the first demonstration, remarkable progress has been made in the theoretical analysis, structural design, numerical simulation, and potential applications of metamaterial absorbers (MAs). With the continuous advancement of novel materials and creative designs, the absorption of MAs is significantly improved over a wide frequency spectrum from microwaves to the optical regime. Further, the integration of active elements into the MA design allows the dynamical manipulation of electromagnetic waves, opening a new platform to push breakthroughs in metadevices. In the last several years, numerous efforts have been devoted to exploring innovative approaches for incorporating tunability to MAs, which is highly desirable because of the progressively increasing demand on designing versatile metadevices. Here, a comprehensive and systematical overview of active MAs with adaptive and on-demand manner is presented, highlighting innovative materials and unique strategies to precisely control the electromagnetic response. In addition to the mainstream method by manipulating periodic patterns, two additional approaches, including tailoring dielectric spacer and transforming overall structure are called back. Following this, key parameters, such as operating frequency, relative tuning range, and switching speed are summarized and compared to guide for optimum design. Finally, potential opportunities in the development of active MAs are discussed.
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http://dx.doi.org/10.1002/adma.202202509 | DOI Listing |
Microsyst Nanoeng
January 2025
Sichuan University, 610207, Chengdu, China.
In conventional nondispersive infrared (NDIR) gas sensors, a wide-spectrum IR source or detector must be combined with a narrowband filter to eliminate the interference of nontarget gases. Therefore, the multiplexed NDIR gas sensor requires multiple pairs of narrowband filters, which is not conducive to miniaturization and integration. Although plasmonic metamaterials or multilayer thin-film structures are widely applied in spectral absorption filters, realizing high-performance, large-area, multiband, and compact filters is rather challenging.
View Article and Find Full Text PDFMicromachines (Basel)
November 2024
College of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Metamaterial absorbers have gained widespread applications in fields such as sensing, imaging, and electromagnetic cloaking due to their unique absorption characteristics. This paper presents the design and fabrication of a novel K-band polarization-sensitive metamaterial absorber, which operates in the frequency range of 20.76 to 24.
View Article and Find Full Text PDFLangmuir
January 2025
Catalysts and Organic Synthesis Research Laboratory, Department of Chemistry, Iran University of Science and Technology, 16846-13114 Tehran, Iran.
Carbon microspheres (CMSs) are recognized as highly effective microwave absorbers due to their exceptional wave absorption properties. In this study, 5,10,15,20-tetrakis(4-aminophenyl)porphyrin, a metamaterial, was chemically bonded to CMSs─considered a conjugated carbon structure─using a 1,3-dibromopropane linker to explore the synergistic properties and microwave absorption capabilities of the synthesized composite. The synthesized structures were characterized by using X-ray diffraction, FE-SEM, Fourier transform infrared, diffuse reflectance spectroscopy, and VNA analyses.
View Article and Find Full Text PDFSci Rep
January 2025
Electrical Engineering Department, Kuwait University, 13060, Kuwait City, Kuwait.
Sci Rep
December 2024
Division of Advanced Electrical and Electronics Engineering, Tokyo University of Agriculture and Technology, 2- 24-16 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan.
A hyperbolic metamaterial absorber has great potential for improving the performance of photo-thermoelectric devices targeting heat sources owing to its broadband absorption. However, optimizing its geometry requires considering numerous parameters to achieve absorption that aligns with the radiation spectrum. Here, we compare three algorithms using deep reinforcement learning for the optimization of a hyperbolic metamaterial absorber.
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