The power of controlling objects with mind has captivated a popular fascination to human beings. One possible path is to employ brain signal collecting technologies together with emerging programmable metasurfaces (PM), whose functions or operating modes can be switched or customized via on-site programming or pre-defined software. Nevertheless, most of existing PMs are wire-connected to users, manually-controlled and not real-time. Here, we propose the concept of remotely mind-controlled metasurface (RMCM) via brainwaves. Rather than DC voltage from power supply or AC voltages from signal generators, the metasurface is controlled by brainwaves collected in real time and transmitted wirelessly from the user. As an example, we demonstrated a RMCM whose scattering pattern can be altered dynamically according to the user’s brain waves via Bluetooth. The attention intensity information is extracted as the control signal and a mapping between attention intensity and scattering pattern of the metasurface is established. With such a framework, we experimentally demonstrated and verified a prototype of such metasurface system which can be remotely controlled by the user to modify its scattering pattern. This work paves a new way to intelligent metasurfaces and may find applications in health monitoring, 5G/6G communications, smart sensors, etc.
For camouflage applications, the performance requirements for metamaterials in different electromagnetic spectra are usually contradictory, which makes it difficult to develop satisfactory design schemes with multispectral compatibility. Fortunately, empowered by machine learning, metamaterial design is no longer limited to directly solving Maxwell’s equations. The design schemes and experiences of metamaterials can be analyzed, summarized, and learned by computers, which will significantly improve the design efficiency for the sake of practical engineering applications. Here, we resort to the machine learning to solve the multispectral compatibility problem of metamaterials and demonstrate the design of a new metafilm with multiple mechanisms that can realize small microwave scattering, low infrared emissivity, and visible transparency simultaneously using a multilayer backpropagation neural network. The rapid evolution of structural design is realized by establishing a mapping between spectral curves and structural parameters. By training the network with different materials, the designed network is more adaptable. Through simulations and experimental verifications, the designed architecture has good accuracy and robustness. This paper provides a facile method for fast designs of multispectral metafilms that can find wide applications in satellite solar panels, aircraft windows, and others.
Metasurfaces with simultaneously and independently controllable amplitude and phase have provided a higher degree of freedom in manipulating electromagnetic (EM) waves. Compared with phase- or amplitude-only modulation, the capability of simultaneously controlling the phase and amplitude of EM waves can enable holography with a higher resolution. However, this drastically increases the design complexity of holographic metasurfaces, and the design process is usually quite time-consuming. In this paper, we propose an inverse design of meta-atoms that can simultaneously and independently tailor the phase and amplitude of transmitted waves using customized deep ResNet while eliminating the coupling of parameters. To demonstrate the design method, two holographic metasurfaces were designed using the trained network without the need for parameter sweeping, which will significantly enhance design efficiency. Prototypes were fabricated and measured. Both the simulated and measured results show that high-resolution holography is obtained, which sufficiently verifies the reliability of the design method. Our work paves the way for the intelligent design of metasurfaces and can also be applied to the design of other artificial materials or surfaces.
The a half-wave wall is usually adopted as the transparent window for electromagnetic (EM) waves ranging from microwave to optical regimes. Due to the interference nature, the bandwidth of the half-wave wall is usually quite narrow, especially under extreme angles for TE-polarized waves. It is usually contradictory to expand the bandwidth and to keep high transmission. To overcome this contradiction, we propose to extend the transmission bandwidth of half-wave walls under extreme angles by introducing Lorentz-type resonances using metasurfaces. The impedance of the half-wave wall is firstly analyzed. To improve the impedance matching, the impedance below and above the half-wave frequency should be increased. To this end, metallic wires and I-shaped structures are incorporated into the half-wave wall as the mid-layer. Due to the Lorentz-type resonance of the metallic wire, effective permittivity below the half-wave frequency can be reduced while that above the half-wave frequency can be increased due to Lorentz-type resonance of the I-shaped structures, both under large incident angles. In this way, the impedance matching, and thus the transmission, can be improved within an extended band. A proof-of-principle prototype was designed, fabricated, and measured to verify this strategy. Both simulated and measured results show that the prototype can operate in 14.0-19.0GHZ under incident angle [70°, 85°] with significant transmission enhancement for TE-polarized waves. This work provides an effective method of enhancing the transmission of EM waves and may find applications in radomes, IR windows, and others.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.