Coding Metasurfaces and Applications

Metasurfaces are the planar counterparts of metamaterials, and they consist of a single-layer or a few-layers stack of planar structures, which can be fabricated using lithography and nanoprinting methods. Such artificial structures are usually described by effective medium parameters at the macroscopic scale. In this chapter, we deal with “coding metasurfaces,” composed of only two types of unit cells, with 0 and π phase responses, from which electromagnetic (EM) waves can be manipulated and different functionalities can be realized. We review the recent progress in the physics of metasurfaces operating at wavelengths ranging from microwave to visible. We provide an overview of key metasurface concepts, such as diffusion, anomalous reflection and refraction, and introduce metasurfaces based on some optimization methods to design metasurfaces, as well as their use in wave-front shaping and beam-forming applications, followed by a discussion of polarization conversion in few-layer metasurfaces and their related properties. An overview of diffusion coding metasurface reveals their ability to realize unique functionalities to reduce the radar cross-section (RCS). We also describe diffusion coding metasurfaces that can improve the field uniformity in reverberation chambers. Finally, we conclude by providing our opinions on opportunities and challenges in this rapidly developing research field

Supervised-learning-enabled EM-driven development of low scattering metasurfaces

The recent advances in the development of coding metasurfaces created new opportunities to elevate the stealthiness of combat aircrafts. Metasurfaces, composed of optimized geometries of meta-atoms arranged as periodic lattices, are devised to obtain desired electromagnetic (EM) scattering characteristics, and have been extensively exploited in stealth applications to reduce radar cross section (RCS). They rely on the manipulation of backward scattering of electromagnetic (EM) waves into various oblique angles. Despite potential benefits, a practical obstacle hindering widespread metasurface utilization is the lack of systematic design procedures. Conventional approaches are largely intuition-inspired and demand heavy designer’s interaction while exploring the parameter space and pursuing optimum unit cell geometries. Another practical obstacle that hampers efficient design of metasurfaces is implicit handling of RCS performance. To achieve essential RCS reduction, the design task is normally formulated in terms of phase reflection characteristics of the unit cells, whereas their reflection amplitudes—although contributing to the overall performance of the structure—is largely ignored. A further practical issue is insufficiency of the existing performance metrics, specifically, monostatic and bistatic evaluation of the reflectivity, especially at the design stage of metasurfaces. Both provide a limited insight into the RCS reduction properties, with the latter being dependent on the selection of the planes over which the evaluation takes place. As a consequence of raised concerns, the existing design methodologies are still insufficient, especially in the context of controlling the EM wavefront through parameter tuning of unit cells. Furthermore, they are unable to determine truly optimum solutions. Therefore, we have introduced a novel machine-learning-based framework for automated and computationally efficient design of metasurfaces realizing broadband RCS reduction. We have employed a three-stage design procedure involving global surrogate-assisted optimization of the unit cells, followed by their local refinement. In its final stage, a direct EM-driven maximization of the RCS reduction bandwidth has been performed, facilitated by appropriate formulation of the objective function involving regularization terms. Moreover, to handle the combinatorial explosion in the design closure of multi-bit coding metasurfaces, a sequential-search strategy has been developed that enabled global search capability at the concurrent unit cell optimization stage. Latterly, the metasurface design task with explicit handling of RCS reduction at the level of unit cells has been introduced that has accounted for both the phase and reflection amplitudes of the unit cells. The design objective has been defined so as to directly optimize the RCS reduction bandwidth at the specified level (e.g., 10 dB) w.r.t. the metallic surface. The appealing feature of the said framework has consisted in its ability to optimize the RCS reduction bandwidth directly at the level of the entire metasurface as opposed to merely optimizing unit cell geometries. Besides, the obtained design has required minimum amount of tuning at the level of the entire metasurface. Lastly, a new performance metric for evaluating scattering characteristics of a metasurface, referred to as Normalized Partial Scattering Cross Section (NPSCS), has been proposed. The metric involved integration of the scattered energy over a specific solid angle, which allows for a comprehensive assessment of the structure performance in a format largely independent of the particular arrangement of the scattering lobes. Our design methodologies have been utilized to design several instances of novel scattering metasurface structures with the focus on RCS reduction bandwidth enhancement and the level of RCS reduction. Experimental validations confirming the numerical findings have been also provided. To the best of the author’s knowledge, the presented study is the first systematic investigation of this kind in the literature and can be considered a step towards the development of efficient, low-cost, and more high performing scattering structures

Recent developments of metamaterials/metasurfaces for RCS reduction

In this paper, recent developments of metamaterials and metasurfaces for RCS reduction are reviewed, including basic theory, working principle, design formula, and experimental verification. Super-thin cloaks mediated by metasurfaces can cloak objects with minor impacts on the original electromagnetic field distribution. RCS reduction can be achieved by reconfiguring scattering patterns using coding metasurfaces. Novel radar absorbing materials can be devised based on field enhancements of metamaterials. When combined with conventional radar absorbing materials, metamaterials can expand the bandwidth, enlarge the angular range, or reduce the weight. Future tendency and major challenges are also summarized

Recent Advances in Metasurface Design and Quantum Optics Applications with Machine Learning, Physics-Informed Neural Networks, and Topology Optimization Methods

As a two-dimensional planar material with low depth profile, a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface. Thus, it offers more flexibility to control the wave front. A traditional metasurface design process mainly adopts the forward prediction algorithm, such as Finite Difference Time Domain, combined with manual parameter optimization. However, such methods are time-consuming, and it is difficult to keep the practical meta-atom spectrum being consistent with the ideal one. In addition, since the periodic boundary condition is used in the meta-atom design process, while the aperiodic condition is used in the array simulation, the coupling between neighboring meta-atoms leads to inevitable inaccuracy. In this review, representative intelligent methods for metasurface design are introduced and discussed, including machine learning, physics-information neural network, and topology optimization method. We elaborate on the principle of each approach, analyze their advantages and limitations, and discuss their potential applications. We also summarise recent advances in enabled metasurfaces for quantum optics applications. In short, this paper highlights a promising direction for intelligent metasurface designs and applications for future quantum optics research and serves as an up-to-date reference for researchers in the metasurface and metamaterial fields

Antenna Designs for 5G/IoT and Space Applications

This book is intended to shed some light on recent advances in antenna design for these new emerging applications and identify further research areas in this exciting field of communications technologies. Considering the specificity of the operational environment, e.g., huge distance, moving support (satellite), huge temperature drift, small dimension with respect to the distance, etc, antennas, are the fundamental device allowing to maintain a constant interoperability between ground station and satellite, or different satellites. High gain, stable (in temperature, and time) performances, long lifecycle are some of the requirements that necessitates special attention with respect to standard designs. The chapters of this book discuss various aspects of the above-mentioned list presenting the view of the authors. Some of the contributors are working strictly in the field (space), so they have a very targeted view on the subjects, while others with a more academic background, proposes futuristic solutions. We hope that interested reader, will find a fertile source of information, that combined with their interest/background will allow efficiently exploiting the combination of these two perspectives