A knowledge-inherited learning for intelligent metasurface design and assembly

Chimera metasurface for multiterrain invisibility

Invisibility, a fascinating ability of hiding objects within environments, has attracted broad interest for a long time. However, current invisibility technologies are still restricted to stationary environments and narrow band. Here, we experimentally demonstrate a Chimera metasurface for multiterrain invisibility by synthesizing the natural camouflage traits of various poikilotherms. The metasurface achieves chameleon-like broadband in situ tunable microwave reflection mimicry of realistic water surface, shoal, beach/desert, grassland, and frozen ground from 8 to 12 GHz freely via the circuit-topology-transited mode evolution, while remaining optically transparent as an invisible glass frog. Additionally, the mechanic-driven Chimera metasurface without active electrothermal effect, owning a bearded dragon-like thermal acclimation, can decrease the maximum thermal imaging difference to 3.1 °C in tested realistic terrains, which cannot be recognized by human eyes. Our work transitions camouflage technologies from the constrained scenario to ever-changing terrains and constitutes a big advance toward the new-generation reconfigurable electromagnetics with circuit-topology dynamics.

All-dielectric six-foci metalens for infrared polarization detection based on Stokes space

The detection technology of infrared polarization has gained significant attention due to its ability to provide better identification and obtain more information about the target. In this paper, based on the expression of the full polarization state in Stokes space, we designed micro-nano metasurface functional arrays to calculate the polarization state of the incident light by reading the Stokes parameters (a set of parameters that describe the polarization state). Metalens with linear and circular polarization-dependent functions are designed based on the propagation and geometric phases of the dielectric Si meta-atoms in the infrared band, respectively. The device exhibits a high polarization extinction ratio. The influence of incident angle on polarization-dependent metalens is discussed, and the analysis of incident angle is of great significance for the practical application. An infrared six-foci metalens is proposed, each corresponding to the Poincaré sphere's coordinate component (a graphical polarization state method). By matching the six polarization components of the incident light and the Stokes parameters, the polarization detection function can be realized by calculating the polarization state of the incident light. There is a slight error between the theoretical value and the calculated value of the unit coordinate component of the Stokes parameters. At the same time, the intensity distribution of different incident light polarization azimuth angles and ellipticity angles on the focal plane agrees with the theory. The advantage of the device is that the polarization state of the incident light can be directly calculated without passing through other components. The six-foci metalens have potential applications in polarization detection and imaging, space remote sensing, etc.

Regulation of Near-Field Radiative Heat Transfer between Multilayer BP/hBN Heterostructures

As an allotrope of phosphorus and a promising 2D semiconductor, black phosphorus (BP) exhibits in-plane anisotropy along its armchair and zigzag crystal directions, allowing for efficient regulation of near-field radiative heat transfer (NFRHT). In this work, we investigate the NFRHT between two multilayer BP/hBN heterostructures and theoretically demonstrate that thermal regulation can be realized by tuning the electron density and rotation angle of BP. Results show that a larger electron density leads to the coupling of anisotropic surface plasmon polaritons (SPPs) of BP with hyperbolic modes of hBN, and rotation of BP changes the anisotropic characteristic of coupled SPPs on both sides, whereby a regulation ratio of 5.8 can be obtained. We also analyze the effects of period number, hBN layer thickness, and topmost-layer material on the NFRHT. This work may be beneficial for efficient nanoscale thermal management and physical understanding of radiative heat transfer based on anisotropic SPPs.

Correlating metasurface spectra with a generation-elimination framework

Inferring optical response from other correlated optical response is highly demanded for vast applications such as biological imaging, material analysis, and optical characterization. This is distinguished from widely-studied forward and inverse designs, as it is boiled down to another different category, namely, spectra-to-spectra design. Whereas forward and inverse designs have been substantially explored across various physical scenarios, the spectra-to-spectra design remains elusive and challenging as it involves intractable many-to-many correspondences. Here, we first dabble in this uncharted area and propose a generation-elimination framework that can self-orient to the best output candidate. Such a framework has a strong built-in stochastically sampling capability that automatically generate diverse nominations and eliminate inferior nominations. As an example, we study terahertz metasurfaces to correlate the reflection spectra from low to high frequencies, where the inaccessible spectra are precisely forecasted without consulting structural information, reaching an accuracy of 98.77%. Moreover, an innovative dimensionality reduction approach is executed to visualize the distribution of the abstract correlated spectra data encoded in latent spaces. These results provide explicable perspectives for deep learning to parse complex physical processes, rather than "brute-force" black box, and facilitate versatile applications involving cross-wavelength information correlation.