A Real-Time Self-Adaptive Thermal Metasurface

Higher-Order Topological In-Bulk Corner State in Pure Diffusion Systems

Compared with conventional topological insulator that carries topological state at its boundaries, the higher-order topological insulator exhibits lower-dimensional gapless boundary states at its corners and hinges. Leveraging the form similarity between Schrödinger equation and diffusion equation, research on higher-order topological insulators has been extended from condensed matter physics to thermal diffusion. Unfortunately, all the corner states of thermal higher-order topological insulator reside within the band gap. Another kind of corner state, which is embedded in the bulk states, has not been realized in pure diffusion systems so far. Here, we construct higher-dimensional Su-Schrieffer-Heeger models based on sphere-rod structure to elucidate these corner states, which we term "in-bulk corner states." Because of the anti-Hermitian properties of diffusive Hamiltonian, we investigate the thermal behavior of these corner states through theoretical calculation, simulation, and experiment. Furthermore, we study the different thermal behaviors of in-bulk corner state and in-gap corner state. Our results would open a different gate for diffusive topological states and provide a distinct application for efficient heat dissipation.

Intelligent wireless power transfer via a 2-bit compact reconfigurable transmissive-metasurface-based router

With the rapid development of the Internet of Things, numerous devices have been deployed in complex environments for environmental monitoring and information transmission, which brings new power supply challenges. Wireless power transfer is a promising solution since it enables power delivery without cables, providing well-behaved flexibility for power supplies. Here we propose a compact wireless power transfer framework. The core components of the proposed framework include a plane-wave feeder and a transmissive 2-bit reconfigurable metasurface-based beam generator, which constitute a reconfigurable power router. The combined profile of the feeder and the beam generator is 0.8 wavelengths. In collaboration with a deep-learning-driven environment sensor, the router enables object detection and localization, and intelligent wireless power transfer to power-consuming targets, especially in dynamic multitarget environments. Experiments also show that the router is capable of simultaneous wireless power and information transfer. Due to the merits of low cost and compact size, the proposed framework may boost the commercialization of metasurface-based wireless power transfer routers.

Deep Learning-Assisted Active Metamaterials with Heat-Enhanced Thermal Transport

Heat management is crucial for state-of-the-art applications such as passive radiative cooling, thermally adjustable wearables, and camouflage systems. Their adaptive versions, to cater to varied requirements, lean on the potential of adaptive metamaterials. Existing efforts, however, feature with highly anisotropic parameters, narrow working-temperature ranges, and the need for manual intervention, which remain long-term and tricky obstacles for the most advanced self-adaptive metamaterials. To surmount these barriers, heat-enhanced thermal diffusion metamaterials powered by deep learning is introduced. Such active metamaterials can automatically sense ambient temperatures and swiftly, as well as continuously, adjust their thermal functions with a high degree of tunability. They maintain robust thermal performance even when external thermal fields change direction, and both simulations and experiments demonstrate exceptional results. Furthermore, two metadevices with on-demand adaptability, performing distinctive features with isotropic materials, wide working temperatures, and spontaneous response are designed. This work offers a framework for the design of intelligent thermal diffusion metamaterials and can be expanded to other diffusion fields, adapting to increasingly complex and dynamic environments.

Flexible Metasurfaces for Multifunctional Interfaces

Optical metasurfaces, capable of manipulating the properties of light with a thickness at the subwavelength scale, have been the subject of extensive investigation in recent decades. This research has been mainly driven by their potential to overcome the limitations of traditional, bulky optical devices. However, most existing optical metasurfaces are confined to planar and rigid designs, functions, and technologies, which greatly impede their evolution toward practical applications that often involve complex surfaces. The disconnect between two-dimensional (2D) planar structures and three-dimensional (3D) curved surfaces is becoming increasingly pronounced. In the past two decades, the emergence of flexible electronics has ushered in an emerging era for metasurfaces. This review delves into this cutting-edge field, with a focus on both flexible and conformal design and fabrication techniques. Initially, we reflect on the milestones and trajectories in modern research of optical metasurfaces, complemented by a brief overview of their theoretical underpinnings and primary classifications. We then showcase four advanced applications of optical metasurfaces, emphasizing their promising prospects and relevance in areas such as imaging, biosensing, cloaking, and multifunctionality. Subsequently, we explore three key trends in optical metasurfaces, including mechanically reconfigurable metasurfaces, digitally controlled metasurfaces, and conformal metasurfaces. Finally, we summarize our insights on the ongoing challenges and opportunities in this field.

Graphene-Enabled Tunable Phase Gradient Metasurface for Broadband Dispersion Manipulation of Terahertz Wave

With the increasing demand for the miniaturization and flexibility of optical devices, graphene-based metasurfaces have emerged as a promising ideal design platform for realizing planar and tunable electromagnetic or optical devices. In this paper, we propose a tunable metasurface with low-dispersion phase gradient characteristics that is composed of an array of double-layer graphene ribbons sandwiched with a thin insulating layer and a polymer substrate layer with a gold ground plane. As two typical proof-of-concept examples, metasurfaces act as a planar prism and a planar lens, respectively, and the corresponding performances of tunable broadband dispersion are demonstrated through full-wave simulation experiments. By changing the Fermi level of each graphene ribbon individually to introduce abrupt phase shifts along the metasurface, the broadband continuous dispersion effect of abnormal reflection and beam focusing is achieved within a terahertz (THz) frequency region from 3.0 THz to 4.0 THz, and the dispersion results can be freely regulated by reconfiguring the sequence of Fermi levels via the bias voltage. The presented graphene metasurface provides an avenue for the dispersion manipulation of a broadband terahertz wave and may have great prospects in the fields of optics, imaging, and wireless communication.

In situ Simulation of Thermal Reality

Simulated reality encompasses virtual, augmented, and mixed realities-each characterized by different degrees of truthfulness in the visual perception: "all false," "coexistence of true and false," and "difficult distinction between true and false," respectively. In all these technologies, however, the temperature rendering of virtual objects is still an unsolved problem. Undoubtedly, the lack of thermal tactile functions substantially reduces the quality of the user's real-experience perception. To address this challenge, we propose theoretically and realize experimentally a technological platform for the in situ simulation of thermal reality. To this purpose, we design a thermal metadevice consisting of a reconfigurable array of radiating units, capable of generating the thermal image of any virtual object, and thus rendering it in situ together with its thermal signature. This is a substantial technological advance, which opens up new possibilities for simulated reality and its applications to human activities.

Recent Progress in Reconfigurable and Intelligent Metasurfaces: A Comprehensive Review of Tuning Mechanisms, Hardware Designs, and Applications

Intelligent metasurfaces have gained significant importance in recent years due to their ability to dynamically manipulate electromagnetic (EM) waves. Their multifunctional characteristics, realized by incorporating active elements into the metasurface designs, have huge potential in numerous novel devices and exciting applications. In this article, recent progress in the field of intelligent metasurfaces are reviewed, focusing particularly on tuning mechanisms, hardware designs, and applications. Reconfigurable and programmable metasurfaces, classified as space gradient, time modulated, and space-time modulated metasurfaces, are discussed. Then, reconfigurable intelligent surfaces (RISs) that can alter their wireless environments, and are considered as a promising technology for sixth-generation communication networks, are explored. Next, the recent progress made in simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) that can achieve full-space EM wave control are summarized. Finally, the perspective on the challenges and future directions of intelligent metasurfaces are presented.