In this paper, a broadband metamaterial microwave absorber is designed, simulated and measured. Differently from the traditional method which is only based on unit cell boundary conditions, we carried out full-wave finite integration simulations using full-sized configurations. Starting from an elementary unit cell structure, four kinds of coding metamaterial blocks, 2 × 2, 3 × 3, 4 × 4 and 6 × 6 blocks were optimized and then used as building blocks (meta-block) for the construction of numerous 12 × 12 topologies with a realistic size scale. We found the broadband absorption response in the frequency range 16 GHz to 33 GHz, in good agreement with the equivalent medium theory prediction and experimental observation. Considering various applications of metamaterials or metamaterial absorbers in the electromagnetic wave processing, including the radars or satellite communications, requires the frequency in the range up to 40 GHz. Our study could be useful to guide experimental work. Furthermore, compared to the straightforward approach that represents the metamaterials configurations as 12 × 12 matrices of random binary bits (0 and 1), our new approach achieves significant gains in the broadband absorption. Our method also may be applied to the full-sized structures with arbitrary dimensions, and thus provide a useful tool in the design of metamaterials with specific desired frequency ranges.

We theoretically investigate the plasmonic properties of mid-infrared graphene-based metamaterials and apply deep learning of a neural network for the inverse design. These artificial structures have square periodic arrays of graphene plasmonic resonators deposited on dielectric thin films. Optical spectra vary significantly with changes in structural parameters. To validate our theoretical approach, we carry out finite difference time domain simulations and compare computational results with theoretical calculations. Quantitatively good agreements among theoretical predictions, simulations, and previous experiments allow us to employ this proposed theoretical model to generate reliable data for training and testing deep neural networks. By merging the pre-trained neural network with the inverse network, we implement calculations for inverse design of the graphene-based metameterials. We also discuss the limitation of the data-driven approach.

Nano/micro polystyrene (PS) beads have found many applications in different fields spanning from drug delivery, bio-diagnostics, and hybrid plasmonics to advanced photonics. The sizes of the PS beads are an important parameter, especially in plasmonic and photonic experiments. In this work, we demonstrate a quick and straightforward method to estimate the diameters of sub-microspheres (0.2 μm to 0.8 μm) using the transmission spectra of a close-packed monolayer of polystyrene beads on glass or quartz substrates. Experimental transmission spectra of the PS monolayers were verified against finite-difference time-domain (FDTD) simulation and showed good agreement. The effects of the substrates on the transmission spectra and, hence, the accuracy of the method were also studied by simulation, which showed that common transparent substrates only cause minor deviation of the PS bead sizes calculated by the proposed method.

Rotary-dependent metasurfaces incorporating with kirigami configuration feature unique properties that offer alternative and active solutions in reconfigurable structures and devices providing diverse platforms to control electromagnetic (EM) waves on the deep subwavelength scale. Herein, a transformable metasurface using a switchable rotating kirigami configuration that absorbs EM waves at different frequency regions and overcomes several fundamental limitations of conventional metasurfaces, including non-reconfigurability, narrow bandwidth operation, and sensitive polarization, is introduced. By rotating kirigami-pixels in predestinated orientations, the absorption bandwidths can be mechanically switched to cover the S, C, X and Ku bands. The concept and physical phenomena were confirmed by numerical simulations, theoretical analysis, and experiments. Such a switchable metasurface promotes an impressive approach to realize reconfigurable meta-devices that are lightweight, cost-effective and flexible.