Metasurface holography offers significant advantages, including a broad field of view, minimal noise, and high imaging quality, making it valuable across various optical domains such as 3D displays, VR, and color displays. However, most passive pure-structured metasurface holographic devices face a limitation: once fabricated, as their functionality remains fixed. In recent developments, the introduction of multiplexed and reconfigurable metasurfaces breaks this limitation. Here, the comprehensive progress in holography from single metasurfaces to multiplexed and reconfigurable metasurfaces is reviewed. First, single metasurface holography is briefly introduced. Second, the latest progress in angular momentum multiplexed metasurface holography, including basic characteristics, design strategies, and diverse applications, is discussed. Next, a detailed overview of wavelength-sensitive, angle-sensitive, and polarization-controlled holograms is considered. The recent progress in reconfigurable metasurface holography based on lumped elements is highlighted. Its instant on-site programmability combined with machine learning provides the possibility of realizing movie-like dynamic holographic displays. Finally, we briefly summarize this rapidly growing area of research, proposing future directions and potential applications.

Underwater acoustic metasurfaces have broad application prospects for the stealth of underwater objects. However, problems such as a narrow operating frequency band, poor operating performance, and considerable thickness at low frequencies remain. In this study a reverse design method for ultra-thin underwater acoustic metasurfaces for low-frequency broadband is proposed using a tandem fully connected deep neural network. The tandem neural network consists of a pre-trained forward neural network and a reverse neural network, based on which a set of elements with flat phase variation and an almost equal phase shift interval in the range of 700–1150 Hz is designed. A diffuse underwater acoustic metasurface with 60 elements was designed, showing that the energy loss of the metasurface in the echo direction was greater than 10 dB. Our work opens a novel pathway for realising low-frequency wideband underwater acoustic devices, which will enable various applications in the future.

Reconfigurable metasurfaces have been regarded as an emerging subfield of metasurfaces that can manipulate electromagnetic wave information in a smart manner. They stimulate a gradual transition in metasurface holography from passive to active elements. To date, intelligent dynamic holographic imaging schemes typically rely on iterative or data-driven methods to obtain holograms at a fixed imaging distance, which significantly hinders the development of intelligent dynamic holographic imaging in practical scenarios involving high demands for dynamic imaging distances. Herein, a computer-generated hologram algorithm with a dynamic imaging distance and a reconfigurable metasurface are proposed, which is referred to as a generator and physical diffractive network. Simulation results of time–distance division for three-dimensional imaging are provided to demonstrate the reliability and high efficiency of the proposed algorithm.

Electromagnetic (EM) waves that bypass obstacles to achieve focus at arbitrary positions are of immense significance to communication and radar technologies. Small-sized and low-cost metasurfaces enable the accomplishment of this function. However, the magnitude-phase characteristics are challenging to analyze when there are obstacles between the metasurface and the EM wave. In this study, we creatively combined the deep reinforcement learning algorithm soft actor–critic (SAC) with a reconfigurable metasurface to construct an SAC-driven metasurface architecture that realizes focusing at any position under obstacles using real-time simulation data. The agent learns the optimal policy to achieve focus while interacting with a complex environment, and the framework proves to be effective even in complex scenes with multiple objects. Driven by real-time reinforcement learning, the knowledge learned from one environment can be flexibly transferred to another environment to maximize information utilization and save considerable iteration time. In the context of future 6G communications development, the proposed method may significantly reduce the path loss of users in an occluded state, thereby solving the open challenge of poor signal penetration. Our study may also inspire the implementation of other intelligent devices.

Holograms show great potential in optical or acoustical waves applications due to their capability to reconstruct images. In this paper, we propose a novel scheme to realize acoustic holograms based on an ultrathin metasurface with arbitrary phase control ability. Compared with the conventional imaging method, e.g., concave mirror, which has a bulky size and limited imaging effects, the acoustic metasurface comprises a single layer of Helmholtz-like elements that can largely reduce the complexity of production. With this ultrathin reflective metasurface, acoustic holograms are constructed through a subtle structure design for single and multiple focal imaging, while the potential thermoviscous effects are minimized. We further demonstrate that the metasurface has the capability of arbitrary phase control in a certain frequency range, where the reflected phase dispersion is linear. Our proposed ultrathin metasurface holograms would be very useful in numerous applications, such as acoustic sensing, medical imaging, and so on.

Most electromagnetic invisibility devices are designed while relying on rigid structures, which have limitations in adapting to complex curved surfaces and dynamic deployment. In contrast, flexible invisibility structures have great application value due to their bendable and easy-to-fit characteristics. In this paper, we propose a flexible metasurface suitable for broadband SAR (Synthetic Aperture Radar) imaging invisibility, which realizes multi-domain joint regulation of electromagnetic waves by designing two subwavelength unit structures with differentiated reflection characteristics and combining array inverse optimization methods. The metasurface employs a sponge-like dielectric substrate and integrates resistive ink to construct a resonant structure, which can suppress electromagnetic scattering through joint phase and amplitude modulation, achieving low detectability of targets in UAV (Unmanned Aerial Vehicle) detection scenarios. Indoor microwave anechoic chamber tests and outdoor UAV-borne SAR experiments verify its stable invisibility performance in a wide frequency band, providing theoretical and experimental support for the application of flexible metasurfaces in dynamic electromagnetic detection countermeasures.