Microwave Structures Research Articles

Using the dispersion model of a chiral metamaterial to calculate the characteristics of homogeneous and heterogeneous reflective and waveguide structures

Currently, metamaterials are actively used in the creation of microwave and optic devices for various purposes. This is due to their non-traditional properties, compared to dielectric, conductive and other materials. One type of metamaterial is chiral media, which contain conductive microelements of mirror asymmetric shape. Such metamaterials have dispersion and, as a consequence, it is necessary to take it into account when developing various microwave structures. The work demonstrates taking into account the dispersion of the dielectric constant and the chirality parameter for calculating waveguide and reflecting structures with homogeneous and inhomogeneous chiral layers. The work carried out an electrodynamic analysis of the reflective properties of an inhomogeneous chiral layer and a rectangular waveguide, with a homogeneous layer of chiral metamaterial located in the transverse plane. The work has developed a method for calculating the reflection and transmission coefficients of an optical wave from the inhomogeneous chiral structure under consideration, which is based on the use of the differential sweep method. When constructing a mathematical model, we took into account the cross-polarization of the optical wave field, which consists in the appearance of orthogonal components during the interaction of the field with a chiral metamaterial. The solution to the problem was reduced to a matrix differential equation for the unknown reflection coefficients of the main and cross-polarized components of the optical field. The work examined chiral metamaterials with linear and parabolic inhomogeneity profiles. The results of the work can be applied in the design of new microwave and optics devices with layers of metamaterial, which can expand their functionality.

Stealthy and hyperuniform isotropic photonic band gap structure in 3D.

In photonic crystals, the propagation of light is governed by their photonic band structure, an ensemble of propagating states grouped into bands, separated by photonic band gaps. Due to discrete symmetries in spatially strictly periodic dielectric structures their photonic band structure is intrinsically anisotropic. However, for many applications, such as manufacturing artificial structural color materials or developing photonic computing devices, but also for the fundamental understanding of light-matter interactions, it is of major interest to seek materials with long range nonperiodic dielectric structures which allow the formation of isotropic photonic band gaps. Here, we report the first ever 3D isotropic photonic band gap for an optimized disordered stealthy hyperuniform structure for microwaves. The transmission spectra are directly compared to a diamond pattern and an amorphous structure with similar node density. The band structure is measured experimentally for all three microwave structures, manufactured by 3D laser printing for metamaterials with refractive index up to . Results agree well with finite-difference-time-domain numerical investigations and a priori calculations of the band gap for the hyperuniform structure: the diamond structure shows gaps but being anisotropic as expected, the stealthy hyperuniform pattern shows an isotropic gap of very similar magnitude, while the amorphous structure does not show a gap at all. Since they are more easily manufactured, prototyping centimeter scaled microwave structures may help optimizing structures in the technologically very interesting region of infrared.

Microwave Investigation of DMSO‐Doped PEDOT:PSS Patch Resonators Under Varying Relative Humidity

AbstractPoly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a conductive polymer widely used in various microwave sensing components. Enhancing the efficiency of PEDOT:PSS‐based microwave structures relies on improving the polymer's conductivity, achievable by adding secondary solvents such as dimethyl sulfoxide (DMSO), which significantly boosts the electrical conductivity. However, the performance of DMSO‐doped PEDOT:PSS films in microwave regime requires investigations. Herein, patch resonators are fabricated using solution processing of aqueous dispersion of PEDOT:PSS doped with varying concentrations of DMSO from 0 to 8 wt.% to investigate their microwave behavior within the frequency range of 4.5–6.5 GHz. The PEDOT:PSS patch structures are implemented on a glass substrate and their resonant characteristics, including resonant frequency and amplitude, are studied in response to varying relative humidity (RH) levels ranging from 0% to 70%. The significant variations in the microwave responses are observed at the resonant amplitude, confirming the main impact of humidity on the conductivity of the films. According to the measured results, the 2 wt.% doped patch shows greater sensitivity to the changes to the RH in contrast to the 8 wt.% doped patches, where the response shows less sensitivity to the humidity variation. The results indicate that a lower percentage of DMSO enhances sensitivity to the humidity at the cost of increased electromagnetic loss in the resonant patch structures for humidity sensing applications.

UV‐Curable 3D‐Printable Microwave‐Absorbing Material with a Sword‐Sheath Structure Based on Multiwalled Carbon Nanotube/Polypyrrole Nanotube/Fe3O4 Composites

Multiwalled carbon nanotube (MWCNT)/polypyrrole nanotube (PPyNT)/triiron tetraoxide (Fe3O4) composites with a sword‐sheath structure are added to a UV‐curable resin to form a unique highly microwave‐absorbing material with a low absorbent content. Specifically tailored for high‐precision stereolithography three‐dimensional (3D) printers, the low absorbent content ensures an efficient curing and molding of the photosensitive resin. The conducting polymer polypyrrole is coated on the MWCNTs via free‐radical polymerization, forming a sheath structure. The initiator of the free‐radical polymerization, FeCl3, is converted into Fe3O4 and loaded onto the sheath structure. This ternary composite material is uniformly dispersed in the photosensitive resin with interconnected sword‐sheath structures, ensuring a favorable dielectric loss performance even at a low absorbent content. Importantly, the material exhibits both dielectric loss and magnetic loss properties. Using a UV‐cured microwave‐absorbing material with an absorbent content of 0.5 wt%, an electromagnetic loss of −22.5 dB can be achieved with a thickness of 1 mm. This UV‐cured microwave‐absorbing material facilitates the high‐precision 3D printing of microwave structures with various intricate shapes, broadening the application scope of microwave‐absorbing materials.

Model of phase fiber optic sensors

Fiber-optic sensors today represent a dynamically developing industry of optoelectronics. The main advantages of measuring systems based on fiber-optic sensors include a wide range of measured values, high measurement accuracy, immunity of fiber sensors to electromagnetic radiation, fire safety, the possibility of remote and distributed measurements. Currently, in the process of designing optoelectronic devices, software modeling complexes are widely used, which make it possible to evaluate the characteristics of the devices being created. There are a number of software packages, for example optiwave optisystem, microwave office, which allow you to evaluate the directional properties of microwave structures and fiber optics, but these software environments are not designed for direct modeling of fiber devices as sensors, which causes a number of difficulties when using them. Thus, during the creation of the. In the conclusion, the main results of this work are highlighted, as well as an approach for solving such a problem, close to real conditions, is proposed.

3D-printed microfluidic-microwave device for droplet network formation and characterisation.

Microfluidic-microwave devices (MMDs) have emerged as precision tools for the rapid, accurate, sensitive, and non-invasive characterisation of liquids in low-volumes. However, the fabrication of MMDs remains a significant challenge. This is due to the complexities associated with integrating fluidic ducts and electronic components. Herein, we present a versatile and economical 3D-printing approach using ducts filled with liquid metal as an electrical conductor. Cyclic olefin copolymer, polylactic acid, and polypropylene were identified as printable dielectric materials for MMD fabrication. Substrates of 3D-printed cyclic olefin copolymer exhibited the lowest loss tangent (0.002 at 2.7 GHz), making them suitable materials for high-frequency microwave devices. Liquid metal, specifically gallium-indium eutectic, was injected into the printed ducts to form electrically conductive microwave structures. Exemplary MMDs operating at 2 GHz integrated split-ring microwave resonators that serve as sensitive detection geometries able to measure changes in dielectric properties, with droplet-forming fluidic junctions and flow channels. The performance of 3D-printed MMDs for microwave droplet sensing was comprehensively evaluated. These devices were used in the formation and characterisation of water-in-oil emulsions, constructing definable lipid-segregated droplet interface bilayer (DIB) networks. This work indicates the feasibility of using 3D-printed manifolds for the rapid prototyping of customised MMDs, and also demonstrates the potential of MMDs as new analytical research tools in droplet-based materials and biochemistry studies.

A High-Quality Data Acquisition Method for Machine-Learning-Based Design and Analysis of Electromagnetic Structures

Electromagnetic (EM) structures play a significant role in wireless communication, radar detection, medical imaging, and so on. Machine learning (ML) has been increasingly applied to facilitate the design and analysis of EM structures. Data acquisition is a major bottleneck. Conventional methods blindly sweep geometric parameters on a uniform grid and acquire corresponding responses via simulation. Acquired data have unstable quality due to inconsistent informativeness of responses, leading to a low ratio of model performance to data amount. This article proposes a high-quality data acquisition method to increase the ratio of model performance to data amount. It anticipates and generates high-quality data by analyzing the distribution of existing data iteratively. Comparative analysis of four implementations proves that the proposed method reduces the required data amount by around 40% for the same model performance and hence saves around 40% simulation and computing resources. The proposed method benefits ML applications of metasurfaces, antennas, and many other microwave structures.

Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement

A variety of surrogate modeling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up reliable design-ready surrogates of modern microwave components. The difficulty of the modeling task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across extended ranges of material, geometry, and operational parameters, is far from easy. As a matter of fact, conventional modeling techniques are merely capable of building models for microwave structures featuring a relatively small number of designable parameters within reduced ranges thereof. One possible way of mitigating these obstacles may be the employment of the recently proposed two-stage performance-driven modeling approach. Therein, the surrogate model domain is narrowed down to the section of the space where the vectors of adequate quality are located, thereby permitting significantly reducing the cost of acquiring the training data. Seeking even further cost reduction, this work introduces a novel modeling framework, which exploits problem-specific knowledge extracted from the circuit responses to achieve substantial cost-savings of training data acquisition. In our methodology, the modeling procedure targets response features instead of the complete responses. The response features are the characteristic locations of the circuit response, such as relevant minima or maxima over selected frequency bands. The dependency of the coordinates of the said features on circuit dimensions is considerably less nonlinear than is observed for the complete characteristics, which enables sizable reduction of the data acquisition cost. Numerical validation of our procedure involving three microwave structures corroborates its remarkable efficiency, which allows for setting design-ready surrogates using only a handful of samples.

The Design of Cavity Resonators and Microwave Filters Applying Shape Deformation Techniques

This article introduces shape deformation as a new approach to the computer-aided design (CAD) of high-frequency components. We show that geometry deformation opens up new design possibilities and offers additional degrees of freedom in the 3-D modeling of microwave structures. Such design flexibility is highly desirable if the full potential of additive manufacturing (AM) is to be exploited in the fabrication of RF and microwave devices. The use of deformation techniques in the design of high-frequency components allows the attainment of improved electrical parameters, such as high-quality factors for cavity resonators and wide higher-order mode separation. In this work, shape deformation with radial basis functions (RBFs) is integrated with an electromagnetic field simulator based on the 3-D finite-element method (FEM), allowing the semiautomated optimization of microwave components, such as cavity resonators and filters. The proposed strategy is used for the design of high <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -factor cavity resonators, cavity bandpass filters with improved spurious mode separation, and a compact twisted waveguide filter. Three designs of waveguide cavity filters with complex geometry are experimentally verified using 3-D-printed prototypes fabricated with selective laser melting (SLM) technology.

Transfer Learning for the Behavior Prediction of Microwave Structures

Microwave structure behavior prediction is an important research topic in radio frequency (RF) design. In recent years, deep-learning-based techniques have been widely implemented to study microwaves, and they are envisaged to revolutionize this arduous and time-consuming work. However, empirical data collection and neural network training are two significant challenges of applying deep learning techniques to practical RF modeling and design problems. To this end, this letter investigates a transfer-learning-based approach to improve the accuracy and efficiency of predicting microwave structure behaviors. Through experimental comparisons, we validate that the proposed approach can reduce the amount of data required for training while shortening the neural network training time for the behavior prediction of microwave structures.

Space–Time Adaptive Modeling and Shape Optimization of Microwave Structures With Applications to Metasurface Design

This article presents a time-domain modeling and shape optimization framework for microwave structures, including metasurfaces, based on a nodal discontinuous Galerkin time-domain (DGTD) method. In particular, we employ an unstructured mesh and the inherent mesh refinement ability of DGTD to model multiscale geometries via adaptive mesh refinement. More importantly, we integrate a multitier local time-stepping technique into the time integration of DGTD, which significantly alleviates the cost introduced by mesh refinement. We further present a flexible parameterization approach by defining the contours of metasurface unit cells by B-spline curves, which allows us to explore a wide range of smooth shapes by only a few design variables. Besides, we adopt a polynomial chaos-Kriging (PCK) surrogate method to approximate the full-wave DGTD model, reducing the computational cost for optimization problems that require time-consuming simulations by three orders of magnitude. The B-spline parameterization and the PCK surrogate model are combined with a pattern search-based Pareto front algorithm to optimize metasurfaces for multiple design objectives. The proposed optimization framework is also applicable to other microwave structures. We demonstrate the effectiveness of our approach through the optimization of an omega-bianisotropic Huygens’ metasurface unit cell and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> -plane microwave T-junction.

Low-Cost Design Optimization of Microwave Passives Using Multifidelity EM Simulations and Selective Broyden Updates

Geometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect the operation and performance of these devices, such as cross-coupling effects. As a consequence, the designs yielded with the use of equivalent network models may only serve as starting points that need further refinement. Unfortunately, simulation-driven numerical optimization is computationally demanding even in the case of local search procedures. Thus, significant research efforts have been aimed toward identifying effective ways of expediting EM-driven optimization procedures, critical from the point of view of cost of design cycles. Among these, one may list the recently proposed multifidelity optimization frameworks. Another option for accelerating simulation-driven design procedures is sparse sensitivity updating schemes, where costly gradient estimation through finite differentiation (FD) is suppressed for selected variables. This work proposes a novel algorithm that capitalizes on both aforementioned mechanisms to reduce the optimization cost of local gradient-based parameter tuning of compact microwave components. In our approach, multifidelity optimization is further expedited by replacing expensive FD sensitivity updates with the Broyden formula for selected design variables. Verification using two microwave structures, a branch-line coupler and a power divider, demonstrates average savings of around 80% over the basic trust-region (TR) routine, with only minor degradation of the design quality.

Experimental Verification of Backscattering Protection in PTD-Symmetric Bifilar Edge Waveguides

This article presents the design and experimental characterization of microwave structures based on parity time-reversal duality symmetric bifilar edge waveguides (PTD-BEWs) realized through a parallel plate waveguide (PPW) loaded by a metasurface. The analyzed structures include transmission lines with bends and multiple line arrangements. Due to their unique symmetry properties, these structures are robust against backscattering, thus resembling the behavior of topological WGs, despite the fact they are reciprocal. This makes it possible to guide the electromagnetic (EM) waves along the edge with low insertion losses and unique matching properties. Measurements, performed in the frequency range between 24 and 32 GHz, have confirmed the feasibility of the theoretical concept.

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Inverse Faraday Effect in an Optomagnonic Waveguide

Single-mode high-index-contrast waveguides have been ubiquitously exploited in optical, microwave, and phononic structures for achieving enhanced wave-matter interactions. Although microscale optomechanical and electro-optical devices have been widely studied, optomagnonic devices remain a grand challenge at the microscale. Here, we introduce a planar optomagnonic waveguide platform based on a ferrimagnetic insulator that simultaneously supports single transverse mode of spin waves (magnons) and highly confined optical modes. The colocalization of spin and light waves gives rise to an enhanced inverse Faraday effect, and as a result, magnons are excited by an effective magnetic field generated by interacting optical photons. Moreover, the strongly enhanced optomagnonic interaction allows us to observe such an effect using low-power (milliwatt level) light signals in the continuous-wave form, as opposed to high-intensity (megawatt peak power) light pulses that are typically required in magnetic bulk materials or thin films. The optically driven magnons are detected electrically with preserved phase coherence, showing the feasibility for launching spin waves with low-power continuous optical fields.

A Novel Surrogate-Based Approach to Yield Estimation and Optimization of Microwave Structures Using Combined Quadratic Mappings and Matrix Transfer Functions

Yield estimation and yield-driven design optimization play important roles in microwave design. Existing surrogate-based yield estimation/optimization methods need to develop separate surrogate models or a large surrogate model with high complexity to deal with multiport problems, which is computationally inefficient. This article proposes a novel surrogate-based method to expedite yield estimation/optimization of multiport microwave structures using combined quadratic mappings and matrix-valued transfer functions. For multiport structures, the responses of different transfer functions corresponding to different pairs of input–output ports are computed with separate residues, while the responses of transfer functions for all pairs of input–output ports are computed with a common set of poles. Taking advantage of this, we propose to formulate a set of quadratic functions to map the relationship between the separate residues and statistical/geometrical parameters while employing merely one quadratic function to map the relationship between the common poles and statistical/geometrical parameters. The resultant mappings together with the matrix-format transfer function form an efficient surrogate to expedite the yield estimation and optimization processes for microwave structures. Compared with existing surrogate-based methods, the proposed method can achieve similar yield estimation accuracy in a shorter time due to fewer electromagnetic (EM) simulations. Three microwave structures are used to demonstrate the advantages of the proposed method. Based on accurate yield estimations, we further perform yield-driven design optimization incorporating the proposed surrogate for all the three examples.

Magnetoelectric gradient structures: Properties and applications

This paper is devoted to a comprehensive study on a new type of microwave structures named magnetoelectric (ME) gradient structures. These structures are studied in this paper to understand the possibilities and application principles in feasible devices. The structure under study was calculated at different values of the applied electric field and different values of the relative permittivity of the artificial dielectric layer. The layered multiferroic structure in inhomogeneous electric and magnetic fields was calculated on the basis of the previously proposed mathematical model. The eigenwaves spectrum for several considered cases was the result of the performed calculation. The concept of using ME gradient structures in the design of electronically controlled microwave devices is formed on the basis of the results of a numerical experiment. Structures of this type will preferably be used in electronically controlled devices for the directional transmission of microwave signals, as it was shown in the theoretical part of the paper.

An MOR Algorithm Based on the Immittance Zero and Pole Eigenvectors for Fast FEM Simulations of Two-Port Microwave Structures

The aim of this article is to present a novel model-order reduction (MOR) algorithm for fast finite-element frequency-domain simulations of microwave two-port structures. The projection basis used to construct the reduced-order model (ROM) comprises two sets: singular vectors and regular vectors. The first set is composed of the eigenvectors associated with the poles of the finite-element method (FEM) state-space system, while the second one is made up from the eigenvectors corresponding to the zeros of the diagonal elements of the matrix-valued immittance transfer function. Importantly, just one LU factorization of the FEM system is required to construct the projection basis during the reduction process, due to the application of a new formulation based on the Schur complement. The sets of eigenvectors that are used in the basis are independent of one another, which makes the new technique better suited for parallel computing compared with previously developed methods, which are sequential in nature. The reliability and accuracy of the proposed scheme are compared with that of the standard MOR technique, namely, the reduced-basis method (RBM), and verified through the analysis of three microwave structures: an eighth-order dual-mode waveguide filter, a dielectric resonator filter, and a folded waveguide filter.

Novel Prediction Methods of Multicarrier Multipactor for Space Industry Standards

Multipactor prediction methods are of high relevance for the space industry in order to prevent its appearance during the design phase of RF high-power components. Up to the present time, prediction for multicarrier signals has been covered by an empirical rule, the 20-gap-crossing rule (20GCR), proposed in the 2003 version of the multipactor standard published by the European Cooperation for Space Standardization (ECSS). The 20GCR has been widely used by the space industry, although some studies have demonstrated that it might be inaccurate in some situations. The latest version of the ECSS multipactor standard, published in 2020, presents two novel methods for multipactor prediction with multicarrier signals: the pulsed method and the envelope sweep (ES) method, both simple, accurate enough, and suitable for industry standards. While the pulsed model is a simple and fast method based on a 1-D analytical theory, the ES method is more accurate and able to deal with real 3-D microwave structures. This article details both multipactor prediction methods, as well as their practical validation with a large dataset from previous analytical studies and experimental activities.

Design and analysis of a wideband microwave absorber based on graphene-assisted metamaterial

Microwave absorption materials or structures show great application prospects in the design of 5 G systems. A graphene-assisted wideband metamaterial microwave absorber with polarization insensitivity and wide incidence angle is proposed based on the round-with-square-hole (RSH) shaped monolayer graphene structure in this paper. The calculation results of the device over an ultra-wideband (16–100 GHz) yields good absorption above 90% when the chemical potential of graphene is 0.1 eV. The fractional bandwidth is 145% for both transverse electric and transverse magnetic polarizations with normal incidence. The influences of the geometry structure parameters and graphene chemical potential on absorption characteristics have been investigated. The structure exhibits polarization independent and wide incidence angle properties since the geometrical symmetry structure. In addition, the structure provides excellent performance when the whole thickness of the device is less than 1 mm. Mechanism of the wideband operation is deciphered based on the normalized relative impedance, surface current and electric field distributions. The novel microwave absorber demonstrates great potential in various fields of electromagnetic stealth, electromagnetic interference shielding, 5 G systems, and so on.