Complete-basis-reprogrammable coding metasurface for generating dynamicallycontrolled holograms under arbitrary polarization states

Reprogrammable metasurfaces,which establish a fascinating bridge between physical and information domains,can dynamically control electromagnetic(EM)waves in real time and thus have attracted great attentions from researchers around the world.To control EM waves with an arbitrary polarization state,it is desirable that a complete set of basis states be controlled independently since incident EM waves with an arbitrary polarization state can be decomposed as a linear sum of these basis states.In this work,we present the concept of complete-basis-reprogrammable coding metasurface(CBR-CM)in reflective manners,which can achieve independently dynamic controls over the reflection phases while maintaining the same amplitude for left-handed circularly polarized(LCP)waves and right-handed circularly polarized(RCP)waves.Since LCP and RCP waves together constitute a complete basis set of planar EM waves,dynamicallycontrolled holograms can be generated under arbitrarily polarized wave incidence.The dynamically reconfigurable metaparticle is implemented to demonstrate the CBR-CM’s robust capability of controlling the longitudinal and transverse positions of holograms under LCP and RCP waves independently.It’s expected that the proposed CBR-CM opens up ways of realizing more sophisticated and advanced devices with multiple independent information channels,which may provide technical assistance for digital EM environment reproduction.

Direct field-to-pattern monolithic design of holographic metasurface via residual encoderdecoder convolutional neural network

Complex-amplitude holographic metasurfaces(CAHMs)with the flexibility in modulating phase and amplitude profiles have been used to manipulate the propagation of wavefront with an unprecedented level,leading to higher image-reconstruction quality compared with their natural counterparts.However,prevailing design methods of CAHMs are based on Huygens-Fresnel theory,meta-atom optimization,numerical simulation and experimental verification,which results in a consumption of computing resources.Here,we applied residual encoder-decoder convolutional neural network to directly map the electric field distributions and input images for monolithic metasurface design.A pretrained network is firstly trained by the electric field distributions calculated by diffraction theory,which is subsequently migrated as transfer learning framework to map the simulated electric field distributions and input images.The training results show that the normalized mean pixel error is about 3%on dataset.As verification,the metasurface prototypes are fabricated,simulated and measured.The reconstructed electric field of reverse-engineered metasurface exhibits high similarity to the target electric field,which demonstrates the effectiveness of our design.Encouragingly,this work provides a monolithic field-to-pattern design method for CAHMs,which paves a new route for the direct reconstruction of metasurfaces.

Simplistic framework of single-pixelprogrammable metasurfaces integrated with a capsuled LED array

Coding metasurfaces can manipulate electromagnetic wave in real time with high degree of freedom,the fascinating properties of which enrich the metasurface design with a wide range of application prospects.However,most of the coding metasurfaces are designed based on external excitation framework with the wired electrical or wireless light control devices,thus inevitably causing the interference with electromagnetic wave transmission and increasing the complexity of the metasurface design.In this work,a simplistic framework of single-pixel-programmable metasurfaces integrated with a capsuled LED array is proposed to dynamically control electromagnetic wave.The framework fully embeds the photoresistor in the meta-atom,controlling the LED array to directly illuminate the photoresistor to modulate the phase response.With this manner,the complex biasing network is transformed to the universal LED array,which means the physical control framework can be transformed to a software framework,and thus the functions of the metasurface can be freely manipulated by encoding the capsuled LED array avoiding mutual coupling of adjacent meta-atoms in real time.All the results verify that the far-field scattering pattern can be customized with this singlepixel-programmable metasurface.Encouragingly,this work provides a universal framework for coding metasurface design,which lays the foundation for metasurface intelligent perception and adaptive modulation.

Six-channel programmable coding metasurface simultaneously for orthogonal circular and linear polarizations

Metasurfaces have intrigued long-standing research interests and developed multitudinous compelling applications owing to their unprecedented capability for manipulating electromagnetic waves,and the emerging programmable coding metasurfaces(PCMs)provide a real-time reconfigurable platform to dynamically implement customized functions.Nevertheless,most existing PCMs can only act on the single polarization state or perform in the limited polarization channel,which immensely restricts their practical application in multitask intelligent metadevices.Herein,an appealing strategy of the PCM is proposed to realize tunable functions in co-polarized reflection channels of orthogonal circularly polarized waves and in co-polarized and cross-polarized reflection channels of orthogonal linearly polarized waves from 9.0 to 10.5 GHz.In the above six channels,the spindecoupled programmable meta-atom can achieve high-efficiency reflection and 1-bit digital phase modulation by selecting the specific ON/OFF states of two diodes,and the phase coding sequence of the PCM is dynamically regulated by the field-programmable gate array to generate the desired function.A proof-of-concept prototype is constructed to verify the feasibility of our methodology,and numerous simulation and experimental results are in excellent agreement with the theoretical predictions.This inspiring design opens a new avenue for constructing intelligent metasurfaces with higher serviceability and flexibility,and has tremendous application potential in communication,sensing,and other multifunctional smart metadevices.

Virtual metasurfaces:reshaping electromagnetic waves in distance

Metasurface has provided unprecedented freedoms in manipulating electromagnetic(EM) waves, exhibiting fascinating functions. Conventionally, these functions are implemented right on metasurfaces, where spatial modulations on EM wave amplitudes or phases are achieved by meta-atoms. This study proposes the concept of virtual metasurface(VM), which is formed by arrays of foci away from the entity metasurface. Unlike conventional metasurfaces, spatial modulations on the amplitudes or phases of EM waves occur in the air, with a focal length distance from the entity metasurface. As a proof of concept, we demonstrated a transmissive VM. The entity metasurface consists of transmissive focusing metasurface tiles(TFMTs) with the same focal length. Two TFMTs were designed with phase difference π to enable the most typical checkerboard configuration. The TFMTs were assembled to form the entity metasurface, whereas their foci formed the VM. Due to the π phase difference among adjacent foci, EM propagation along the normal direction was cancelled, leading to four tilted far-field beams. The concept of VM can be readily extended to higher frequencies from terahertz to optical regimes and may find wide applications in communication, camouflage, and other fields.

Machine-learning-empowered multispectral metafilm with reduced radar cross section,low infrared emissivity,and visible transparency

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 engineer-ing 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 back-propagation 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.

Remotely mind-controlled metasurface via brainwaves

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.

Quasi-omnibearing retro-reflective metagrating protected by reciprocity

Reciprocity is ubiquitous in antennas for receiving and radiating electromagnetic(EM) waves, i.e., if an antenna has good receiving performance at a given direction, it also has good radiation performance in that direction.Inspired by this, we propose a method of designing a quasi-ominibearing retro-reflective metagrating(RRMG)protected by the reciprocity of antennas. Based on the second-order mode around 15.0 GHz of a short-circuited structured patch antenna(SPA), incident transverse magnetic waves can be received, channeled into the coaxial lines, reflected by the shortened end, and finally re-radiated into free space with a reversed wave vector. RRMGs are contrived consisting of this identical SPA, with a grating constant allowing ±2nd-, ±1st-, and zeroth-order diffractions. Oblique incidence, plus the tilted nulls of the re-radiation pattern, can eliminate -1st, zeroth,+1st, and +2nd orders, and only the -2nd order is left to achieve retro-reflections. Prototypes were fabricated and measured. Simulated and measured results show that the RRMGs maintain only -2nd-order diffraction for incident angles 32.2° ≤ θ_(i)< 90.0° in four quadrants, and that RRMGs can achieve quasi-omnibearing retro-reflections for θ_(i)= 50.0°. The use of higher-order diffraction brings more degrees of freedom in manipulating EM waves, and this strategy can be readily extended to millimeter waves, THz wave, or even optical regimes.