• Photonics Insights
  • Vol. 1, Issue 1, R01 (2022)
Qian Ma1、2、†, Che Liu1、2, Qiang Xiao1、2, Ze Gu1、2, Xinxin Gao1、2, Lianlin Li3, and Tie Jun Cui1、2、*
Author Affiliations
  • 1State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, China
  • 2Institute of Electromagnetic Space, Southeast University, Nanjing, China
  • 3State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, China
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    DOI: 10.3788/PI.2022.R01 Cite this Article
    Qian Ma, Che Liu, Qiang Xiao, Ze Gu, Xinxin Gao, Lianlin Li, Tie Jun Cui. Information metasurfaces and intelligent metasurfaces[J]. Photonics Insights, 2022, 1(1): R01 Copy Citation Text show less


    Metamaterials and metasurfaces have inspired worldwide interest in the recent two decades due to their extraordinary performance in controlling material parameters and electromagnetic properties. However, most studies on metamaterials and metasurfaces are focused on manipulations of electromagnetic fields and waves, because of their analog natures. The concepts of digital coding and programmable metasurfaces proposed in 2014 have opened a new perspective to characterize and design metasurfaces in a digital way, and made it possible to control electromagnetic fields/waves and process digital information simultaneously, yielding the birth of a new direction of information metasurfaces. On the other hand, artificial intelligence (AI) has become more important in automatic designs of metasurfaces. In this review paper, we first show the intrinsic natures and advantages of information metasurfaces, including information operations, programmable and real-time control capabilities, and space–time-coding strategies. Then we introduce the recent advances in designing metasurfaces using AI technologies, and particularly discuss the close combinations of information metasurfaces and AI to generate intelligent metasurfaces. We present self-adaptively smart metasurfaces, AI-based intelligent imagers, microwave cameras, and programmable AI machines based on optical neural networks. Finally, we indicate the challenges, applications, and future directions of information and intelligent metasurfaces.

    1 Introduction

    In the past two decades, metamaterials have attracted widespread attention all over the world and have been fully studied in various fields due to their unparalleled capabilities in manipulating material parameters[13]. In the early stage, metamaterial research was focused mainly on the control of effective medium parameters based on bulk structures in three-dimensional (3D) versions, driven by the enthusiasm on negative refractions[47], invisibility cloaks[815], and perfect/super lenses[1620]. However, 3D metamaterials usually have high loss and fabrication complexity, which apparently limit their further developments and applications. Therefore, the idea of a planarized metamaterial design was proposed and gradually formed the concept of metasurfaces[2124], which can be regarded as two-dimensional (2D) versions of metamaterials. Metasurfaces not only possess the powerful control abilities of 3D metamaterials but also have the advantages of an ultra-low profile, easy fabrication, and low loss. In 2011 and 2012, the generalized Snell’s law was proposed based on a metasurface[22,25], showing a new method to delicately tailor the reflection and transmission of electromagnetic (EM) waves. This work successfully inspired researchers to design metasurfaces using their phase and amplitude distributions and also stimulated abundant applications such as ultrathin cloaks[22,24,26],holograms[27,28], planar optical lenses[29], polarization converters[22,30,31], absorbers[3234], and vortex-beam generators[27,35]. Because of the above-mentioned advantages, metasurfaces significantly expand their application ranges, including wireless communications[3640], EM imaging[4143], satellite antennas[4446], cloaking[26,4749], and so on. Based on passive metasurfaces, tunable[5055] and reconfigurable[5664] metasurfaces dynamically promote the aforementioned application scenarios.

    Qian Ma, Che Liu, Qiang Xiao, Ze Gu, Xinxin Gao, Lianlin Li, Tie Jun Cui. Information metasurfaces and intelligent metasurfaces[J]. Photonics Insights, 2022, 1(1): R01
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