We are pleased to present the first collection dedicated to highlighting the research of our Editorial Board, entitled Editors’ Showcase: Metamaterials. This exclusive collection is open to Editorial Board members only and will feature high quality contributions from our Associate and Review Editors. Specialty Chief Editor Professor Huanyang Chen leads this initiative which will focus on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Metamaterials. The work presented here celebrates the broad diversity of research performed across the section’s scope and aims to put a spotlight on all areas of interest to our Editors. This collection aims to further support Frontiers’ strong community by recognizing and promoting the work of highly deserving Editors. Additionally, work submitted in this collection will be taken into consideration when nominating the candidates for the inaugural Frontiers in Materials Awards.

Xiamen University

. This research topic focuses on metasurfaces and their applications in computational imaging, programmable far-field pattern shaping, two-dimensional topological photonic research, and subwavelength metallic gratings. <ul> <li>A frequency-diversity MIMO metasurface antenna is proposed that consists of 2x2 sub-apertures with randomly distributed surface impedance.</li> <li>A four-layer artificial neural network is proposed to predict the far-field radar cross section (RCS) of programmable metasurfaces in an environment with obstacles.</li> <li>A new type of nodal loop in a photonic band structure is observed, which is protected by mirror symmetry and enabled by a bilayer metasurface design.</li> <li>A generalized diffraction law reveals that the phase gradient plays a significant role in the famous effect of Wood’s anomalies and Rayleigh’s conjecture.</li> </ul>

Frontiers in Materials

Metamaterials

Editors’ Showcase: Metamaterials

The metamaterials/metasurfaces have become an important platform for exploring light-matter interactions and light field manipulations. In particular, the metasurfaces as a two-dimensional version of metamaterials have attracted great research interest recently since their optical response is engineered locally, addressing large degrees of freedom. The planar structures are compatible with mature microfabrication techniques. This Research Topic aimed to explore recent developments in this area with a focus on diffraction optics and topological photonics. The deep learning-driven reconfigurable metasurface is also highlighted.A study by <a href="https://www.frontiersin.org/articles/10.3389/fmats.2022.901794/full">Quan et al.</a> reexamines the famous Wood anomalies in metallic gratings from phase gradient metasurfaces (PGM). They show that due to the gauge invariance in PGM, that is, the diffraction law of PGM is independent of the choice of the initial value of abrupt phase shift, the well-studied subwavelength metallic grating can be regarded as a special case of PGM. Thereafter, their optical diffracting properties can be explained more deeply by the generalized grating diffraction equation. For example, they find that when the abrupt phase shift along the interface covers full 2π and satisfies the condition of PGM, the intensity of Wood anomalies becomes strongest. This work provides more insight into the design of diffraction components such as the retroreflector and wavefront control applications.Another study by <a href="https://www.frontiersin.org/articles/10.3389/fmats.2022.909381/full">Li et al.</a> experimentally demonstrates a new type-III nodal loop (NL) in an artificially designed bilayer metasurface. This type-III NL is created by the crossing between a resonant flat band and a positively dispersive band, which is different from the conventional NL in terms of the band slopes and the spatial dispersion of the crossing point. Here, the NL is protected by a mirror symmetry of the bilayer metasurface along the out-of-plane direction. By breaking the structural symmetries, the sequential topological transitions of band degeneracy from the NL via the Dirac point to the gapped phase are also observed. The bilayer design of high-structural tuning degrees of freedom allows for the exploration of rich physics in two-dimensional topological photonics.Another study by <a href="https://www.frontiersin.org/articles/10.3389/fmats.2022.1112339/full">Wang et al.</a> demonstrates a frequency-diverse multiple-input-multiple-output (MIMO) metasurface antenna for computational imaging (CI). The frequency response of the metasurface antenna can be engineered by the metallic gap width. Basically, the imaging quality of CI depends on the orthogonal measurement modes. By adopting the aperture rotation technique (ART) in a passive frequency-diverse 2 × 2 MIMO, more radiation modes can be obtained and the imaging resolution performance can be significantly improved, although at the cost of imaging speed.The past years have witnessed the fast development of deep learning in various research areas. Different from the traditional optimization algorithms requiring repeated iterative training for each computation, the data Research Topic and network training for deep learning are only a one-time cost. Hence, such data-driven models have shown great power for the on-demand design of photonic structures by using hierarchically structured layers. The study by <a href="https://www.frontiersin.org/articles/10.3389/fmats.2022.996956/full">Jiang et al.</a> reports using a four-layer fully connected network to realize the far-field radar cross-section (RCS) prediction of programmable metasurfaces. This work has potential applications in future 6G communications.J-hC and HC were guest editors of the Research Topic and wrote the paper text.J-hC is supported by the National Natural Science Foundation of China (Grants No. 62005231, 12274357). HC is supported by the National Natural Science Foundation of China (Grants No. 92050102).We thank the authors of the papers published in this Research Topic for their valuable contributions and the referees for their rigorous review.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Editorial: Editors’ showcase: Metamaterials

Metasurface antennas have been proposed for computational imaging (CI) systems, which can reconstruct images without using mechanical scanning or large antenna arrays. In a CI system based on metasurface antennas, a variety of different radiation fields, which can be applied to sample the objects, are generated by exciting different frequency points in broadband. According to the compressed sensing theory, the imaging performance of the system is mainly limited by frequency-diversity radiation modes. In general, it is difficult to achieve rich radiation modes; therefore, a special design of metasurface aperture is required. In this paper, we propose a frequency-diversity MIMO metasurface antenna that consists of 2 × 2 sub-apertures with randomly distributed surface impedance. By employing the aperture rotation technique (ART) which rotates the MIMO metasurface antenna around the panel axis, the pseudo-randomness of the radiation fields is utilized. The diversity of the radiation field is improved on the premise of ensuring the relatively low complexity of the system. The ART significantly improves the measurement richness at the cost of increasing the measurement time. The performance of the proposed method is evaluated through simulations and experiments, suggesting that the proposed 2 × 2 MIMO metasurface antenna and the ART are effective to reconstruct high-quality images.

Metasurface antennas have been proposed for computational imaging (CI) systems, which can reconstruct images without using mechanical scanning or large antenna arrays. In a CI system based on metasurface antennas, a variety of different radiation fields, which can be applied to sample the objects, are generated by exciting different frequency points in broadband. According to the compressed sensing theory, the imaging performance of the system is mainly limited by frequency-diversity radiation modes. In general, it is difficult to achieve rich radiation modes; therefore, a special design of metasurface aperture is required. In this paper, we propose a frequency-diversity MIMO metasurface antenna that consists of 2 &#xd7; 2 sub-apertures with randomly distributed surface impedance. By employing the aperture rotation technique (ART) which rotates the MIMO metasurface antenna around the panel axis, the pseudo-randomness of the radiation fields is utilized. The diversity of the radiation field is improved on the premise of ensuring the relatively low complexity of the system. The ART significantly improves the measurement richness at the cost of increasing the measurement time. The performance of the proposed method is evaluated through simulations and experiments, suggesting that the proposed 2 &#xd7; 2 MIMO metasurface antenna and the ART are effective to reconstruct high-quality images.

Frequency-diverse MIMO metasurface antenna for computational imaging with aperture rotation technique

Programmable metasurfaces have attracted significant attention in various applications such as radar and 6G communications, owing to their ability freely shape the far-field pattern. However, complex calculations and simulations are always required when designing specific far-field patterns, especially when irregular obstacles are outside the metasurface. In this article, we propose a method using a four-layer artificial neural network to realize the far-field radar cross section (RCS) prediction of programmable metasurfaces in an environment with obstacles, and the prediction value agreed with the simulation data reasonably well. Results show that the proposed prediction model is characterized by better learning and generalization capacity. Our work has broad application prospects and value in complex environment signal transmission, metasurface inverse design, etc.

Programmable metasurfaces have attracted significant attention in various applications such as radar and 6G communications, owing to their ability freely shape the far-field pattern. However, complex calculations and simulations are always required when designing specific far-field patterns, especially when irregular obstacles are outside the metasurface. In this article, we propose a method using a four-layer artificial neural network to realize the far-field radar cross section (RCS) prediction of programmable metasurfaces in an environment with obstacles, and the prediction value agreed with the simulation data reasonably well. Results show that the proposed prediction model is characterized by better learning and generalization capacity. Our work has broad application prospects and value in complex environment signal transmission, metasurface inverse design, etc.

Programmable metasurface RCS prediction under obstacles based on DNN

In momentum space, the nodal loop is regarded as a ring-shaped band degeneracy and is classified into type-I and type-II configurations depending on the positive/negative dispersions of the degenerating bands. Here, we experimentally observe a new class of nodal loop in the photonic band structure, employing an artificially designed bilayer metasurface. Such degeneracy, termed type-III nodal loop, is formed by the crossing between a resonant flat band and a positively dispersive band and is protected by mirror symmetry <mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi>z</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, which manifests in the metasurface’s bilayer architecture. Furthermore, the sequential topological transitions of band degeneracy from the nodal loop via Dirac point to gapped phase are demonstrated at the metasurfaces. Such transitions are enabled by the bilayer design and end with a pair of edge states on the domain wall of gapped systems. Our work reveals that properly engineered bilayer metasurfaces offer rich physics and vast flexibility in two-dimensional topological photonic research through assembling and tunning more symmetries and degrees of freedom along the stacking direction.

In momentum space, the nodal loop is regarded as a ring-shaped band degeneracy and is classified into type-I and type-II configurations depending on the positive/negative dispersions of the degenerating bands. Here, we experimentally observe a new class of nodal loop in the photonic band structure, employing an artificially designed bilayer metasurface. Such degeneracy, termed type-III nodal loop, is formed by the crossing between a resonant flat band and a positively dispersive band and is protected by mirror symmetry <math id="m1"><mrow><msub><mi>M</mi><mi>z</mi></msub></mrow></math>, which manifests in the metasurface’s bilayer architecture. Furthermore, the sequential topological transitions of band degeneracy from the nodal loop via Dirac point to gapped phase are demonstrated at the metasurfaces. Such transitions are enabled by the bilayer design and end with a pair of edge states on the domain wall of gapped systems. Our work reveals that properly engineered bilayer metasurfaces offer rich physics and vast flexibility in two-dimensional topological photonic research through assembling and tunning more symmetries and degrees of freedom along the stacking direction.

Photonic Type-III Nodal Loop and Topological Phase Transitions at Bilayer Metasurfaces

Phase-gradient metasurfaces (PGMs) have provided unprecedented opportunities for manipulating light. Here, we reexamine ordinary and well-studied subwavelength metallic gratings (OMGs) from the concept of PGMs to provide more insight into their diffraction properties. We will show that due to the existence of gauge invariance in PGMs, i.e., the diffraction law of PGMs is independent of the choice of initial value of abrupt phase shift that induces the phase gradient, the well-studied OMGs can be regarded as a PGM strictly, with its diffraction properties can be fully predicted by generalized diffraction law with phase gradient. In particular, the generalized diffraction law reveals that the phase gradient plays a significant role in the famous effect of Wood’s anomalies and Rayleigh’s conjecture.

Phase-gradient metasurfaces (PGMs) have provided unprecedented opportunities for manipulating light. Here, we reexamine ordinary and well-studied subwavelength metallic gratings (OMGs) from the concept of PGMs to provide more insight into their diffraction properties. We will show that due to the existence of gauge invariance in PGMs, i.e., the diffraction law of PGMs is independent of the choice of initial value of abrupt phase shift that induces the phase gradient, the well-studied OMGs can be regarded as a PGM strictly, with its diffraction properties can be fully predicted by generalized diffraction law with phase gradient. In particular, the generalized diffraction law reveals that the phase gradient plays a significant role in the famous effect of Wood&#x2019;s anomalies and Rayleigh&#x2019;s conjecture.