Coding metamaterials, digital metamaterials and programmable metamaterials

By T. Cui, M. Qi, Xiang Wan, Jie Zhao, Qiang Cheng. Light: Science & Applications, 2014

3,260 citations recorded by the source corpus.

Metamaterials are artificial structures that are usually described by effective medium parameters on the macroscopic scale, and these metamaterials are referred to as ‘analog metamaterials’. Here, we propose ‘digital metamaterials’ through two steps. First, we present ‘coding metamaterials’ that are composed of only two types of unit cells, with 0 and π phase responses, which we name ‘0’ and ‘1’ elements, respectively. By coding ‘0’ and ‘1’ elements with controlled sequences (i.e., 1-bit coding), we can manipulate electromagnetic (EM) waves and realize different functionalities. The concept of coding metamaterials can be extended from 1-bit coding to 2-bit coding or higher. In 2-bit coding, four types of unit cells, with phase responses of 0, π/2, π, and 3π/2, are required to mimic the ‘00’, ‘01’, ‘10’ and ‘11’ elements, respectively. The 2-bit coding has greater freedom than 1-bit coding for controlling EM waves. Second, we propose a unique metamaterial particle that has either a ‘0’ or ‘1’ response controlled by a biased diode. Based on this particle, we present ‘digital metamaterials’ with unit cells that possess either a ‘0’ or ‘1’ state. Using a field-programmable gate array, we realize digital control over the digital metamaterial. By programming different coding sequences, a single digital metamaterial has the ability to manipulate EM waves in different manners, thereby realizing ‘programmable metamaterials’. The above concepts and physical phenomena are confirmed through numerical simulations and experiments using metasurfaces. Smart materials offering great freedom in manipulating electromagnetic radiation have been developed. This exciting new concept was realized by Tie Jun Cui and co-workers at the Southeast University, China, who developed digital metamaterials consisting of two kinds of unit cells whose different phase responses allow them to act as ‘0’ and ‘1’ bits. These cells can be judiciously arranged in sequences to enable controlled manipulation of electromagnetic waves. This is one-bit coding; higher-bit coding is possible by employing more kinds of unit cells. The researchers developed a metamaterial cell whose binary response can be controlled by a biased diode. By using a field-programmable gate array, they demonstrated that this digital metamaterial can be programmed. Such metamaterials are attractive for controlling radiation beams in antennas and for realizing other ‘smart’ metamaterials.

Subfields: Aerospace Engineering, Electronic, Optical and Magnetic Materials

View Paper: https://www.semanticscholar.org/paper/222d8412c7c157a0b772850c4d44981f5249079d

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Citations in the corpus

Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security (2019, methodology): “Recently, intelligent reflecting surface (IRS) has been proposed as a promising technique due to its capability to achieve high spectrum-/energy-efficiency through controlling the wireless propagation environment [6].”
Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network (2019, methodology): “By controlling its biasing voltage via a direct-current (DC) feeding line, the PIN diode can be switched between “On” and “Off” states as shown in the equivalent circuits, thereby generating a phase-shift difference of π in rad [13].”
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning (2020, neutral): “, reflect-arrays and metasurfaces, and on realizing point-to-point experimental tests [9], [10].”
Intelligent Reflecting Surface Enhanced Wireless Network: Joint Active and Passive Beamforming Design (2018, background): “, metasurface) have made the reconfigurability of reflecting surfaces possible, even via controlling the phase shifters in real time [3].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “which can be viewed as the foundation of RISs, can be found in [68].”
Snapshot Compressive Imaging: Theory, Algorithms, and Applications (2021, methodology): “One research direction is to use new materials, such as metamaterials [103] and metasurfaces, to implement the modulation, but the image space coding described in the “Imaging Systems of SCI” section may be a concern since pixel-to-pixel correspondence is challenging.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, neutral): “in [68].”