Abstract-The concept of a novel reactive impedance surface (RIS) as a substrate for planar antennas, that can miniaturize the size and significantly enhance both the bandwidth and the radiation characteristics of an antenna is introduced. Using the exact image formulation for the fields of elementary sources above impedance surfaces, it is shown that a purely reactive impedance plane with a specific surface reactance can minimize the interaction between the elementary source and its image in the RIS substrate. An RIS can be tuned anywhere between perfectly electric and magnetic conductor (PEC and PMC) surfaces offering a property to achieve the optimal bandwidth and miniaturization factor. It is demonstrated that RIS can provide performance superior to PMC when used as substrate for antennas. The RIS substrate is designed utilizing two-dimensional periodic printed metallic patches on a metal-backed high dielectric material. A simplified circuit model describing the physical phenomenon of the periodic surface is developed for simple analysis and design of the RIS substrate. Also a finite-difference time-domain (FDTD) full-wave analysis in conjunction with periodic boundary conditions and perfectly matched layer walls is applied to provide comprehensive study and analysis of complex antennas on such substrates. Examples of different planar antennas including dipole and patch antennas on RIS are considered, and their characteristics are compared with those obtained from the same antennas over PEC and PMC. The simulations compare very well with measured results obtained from a prototype 10 miniaturized patch antenna fabricated on an RIS substrate. This antenna shows measured relative bandwidth, gain, and radiation efficiency of = 6 7%, = 4 5 dBi, and = 90%, respectively, which constitutes the highest bandwidth, gain, and efficiency for such a small size thin planar antenna.

Abstract-In this paper, the unique features of periodic magneto-dielectric meta-materials in electromagnetics are addressed. These materials, which are arranged in periodic configurations, are applied for the design of novel EM structures with applications in the VHF-UHF bands. The utility of theses materials are demonstrated by considering two challenging problems, namely, design of miniaturized electromagnetic band-gap (EBG) structures and antennas in the VHF-UHF bands. A woodpile EBG made up of magneto-dielectric material is proposed. It is shown that the magneto-dielectric woodpile not only exhibits band-gap rejection values much higher than the ordinary dielectric woodpile, but also for the same physical dimensions it shows a rejection band at a much lower frequency. The higher rejection is a result of higher effective impedance contrasts between consecutive layers of the magneto-dielectric woodpile structure. Composite magneto-dielectrics are also shown to provide certain advantages when used as substrates for planar antennas. These substrates are used to miniaturize antennas while maintaining a relatively high bandwidth and efficiency. An artificial anisotropic meta-substrate having , made up of layered magneto-dielectric and dielectric materials is designed to maximize the bandwidth of a miniaturized patch antenna. Analytical and numerical approaches, based on the anisotropic effective medium theory (AEMT) and the finite-difference time-domain (FDTD) technique, are applied to carry out the analyzes and fully characterize the performance of finite and infinite periodic magneto-dielectric meta-materials integrated into the EBG and antenna designs.Index Terms-Anisotropic effective medium theory (AEMT), antenna miniaturization, electromagnetic band-gap (EBG) materials, finite-difference time-domain (FDTD) technique, magneto-dielectrics, meta-materials, periodic structures.

Abstract-Magnetic properties were imparted to a naturally nonmagnetic material by metallic inclusions. A patch antenna tested the performance of the magnetic metamaterial as a substrate and validated that a single substrate can achieve a range of miniaturization values. The effective medium metamaterial substrate employed electromagnetically small embedded circuits (ECs) to achieve permeability and permittivity greater than that of the host dielectric. Geometric control of the ECs allowed and to be tailored to the application. The magnetic metamaterial exhibited enhanced and with acceptable loss-factor levels. Models for predicting and are presented, the benefits of employing metamaterial substrates are discussed, and the results in this antenna experiment are presented. The metamaterial exhibits performance characteristics not achievable from natural materials. Of particular significance is that with the permeability varying strongly and predictably with frequency, the miniaturization factor may be selected by tuning the operating frequency.

An infrared reflectarray metasurface with engineered birefringent behavior is demonstrated. The array reradiates incoming light into two orthogonal, linearly polarized reflections. The reflectarray is composed of rectangular metallic patch nanoantennas placed on top of a grounded dielectric stand-off layer. The patches are designed to locally manipulate the phase front of the incoming wave. They tailor the reflection phase to transform the phase front on the surface to the one desired for both orthogonal polarizations at the same time. The proposed nanoantenna metasurface can find applications in many optical devices, such as birefringent modulators, waveplates, polarizers, and splitters.

The concept of an ultra-thin metasurface made of single layer of only-dielectric disks for successful phase control over a full range is demonstrated. Conduction loss is avoided compared to its plasmonic counterpart. The interaction of the Mie resonances of the first two modes of the dielectric particles, magnetic and electric dipoles, is tailored by the dimensions of the disks, providing required phase shift for the transmitted beam from 0° to 360°, together with high transmission efficiency. The successful performance of a beam-tilting array and a large-scale lens functioning at 195 THz demonstrates the ability of the dielectric metasurface that is thin and has also high efficiency of more than 80%. Such configurations can serve as outstanding alternatives for plasmonic metasurfaces especially that it can be a scalable design.

As optical metasurfaces become progressively ubiquitous, the expectations from them are becoming increasingly complex. The limited number of structural parameters in the conventional metasurface building blocks, and existing phase engineering rules do not completely support the growth rate of metasurface applications. In this paper, we present digitized-binary elements, as alternative high-dimensional building blocks, to accommodate the needs of complex-tailorable-multifunctional applications. To design these complicated platforms, we demonstrate adaptive genetic algorithm (AGA), as a powerful evolutionary optimizer, capable of handling such demanding design expectations. We solve four complex problems of high current interest to the optics community, namely, a binary-pattern plasmonic reflectarray with high tolerance to fabrication imperfections and high reflection efficiency for beam-steering purposes, a dual-beam aperiodic leaky-wave antenna, which diffracts TE and TM excitation waveguides modes to arbitrarily chosen directions, a compact birefringent all-dielectric metasurface with finer pixel resolution compared to canonical nano-antennas, and a visible-transparent infrared emitting/absorbing metasurface that shows high promise for solar-cell cooling applications, to showcase the advantages of the combination of binary-pattern metasurfaces and the AGA technique. Each of these novel applications encounters computational and fabrication challenges under conventional design methods, and is chosen carefully to highlight one of the unique advantages of the AGA technique. Finally, we show that large surplus datasets produced as by-products of the evolutionary optimizers can be employed as ingredients of the new-age computational algorithms, such as, machine learning and deep leaning. In doing so, we open a new gateway of predicting the solution to a problem in the fastest possible way based on statistical analysis of the datasets rather than researching the whole solution space.

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Metagratings are flat and thin surfaces that rely on unique, periodically repeating (non-gradient), arbitrary shaped light scattering units for wave manipulation. However, the absence of an empirical relationship between the structural and diffraction properties of the units enforces utilization of brute force numerical optimization techniques to determine the unit shape for a desired application. Here, we present an artificial neural network based methodology to develop a fast-paced numerical relationship between the two. We demonstrate the training and the performance of a numerical function, utilizing simulated diffraction efficiencies of a large set of units, that can instantaneously mimic the optical response of any other arbitrary shaped unit of the same class. We validate the performance of the trained neural network on a previously unseen set of test samples and discuss the statistical significance. We then utilize the virtually instantaneous network operations to inverse design the metagrating unit shapes for a desired diffraction efficiency distribution. The proposed inter-disciplinary combination of advanced information processing techniques with Maxwell's equation solvers opens a pathway for the fast-paced prediction of metagrating designs rather than full wave computation.