De-embedding method for a sensing area characterization of planar microstrip sensors without evaluating error networks.

A de-embedding method for determining all scattering (S-) parameters (e.g., characterization) of a sensing area of planar microstrip sensors (two-port network or line) is proposed using measurements of S-parameters with no calibration. The method requires only (partially known) non-reflecting line and reflecting line standards to accomplish such a characterization. It utilizes uncalibrated S-parameter measurements of a reflecting line, direct and reversed configurations of a non-reflecting line, and direct and reversed configurations of the sensing area. As different from previous similar studies, it performs such a characterization without any sign ambiguity. The method is first validated by extracting the S-parameters of a bianisotropic metamaterial slab, as for a two-port network (line), constructed by split-ring-resonators (SRRs) from waveguide measurements. Then, it is applied for determining the S-parameters of a sensing area of a microstrip sensor involving double SRRs next to a microstrip line. The root-mean-square-error (RMSE) analysis was utilized to analyze the accuracy of our method in comparison with other techniques in the literature. It has been observed from such an analysis that our proposed de-embedding technique has the lowest RMSE values for the extracted S-parameters of the sensing area of the designed sensor in comparison with those of the compared other de-embedding techniques in the literature, and have similar RMSE values in reference to those of the thru-reflect-line calibration technique. For example, while RMSE values of real and imaginary parts of the forward reflection S-parameter of this sensing area are, respectively, around 0.0271 and 0.0279 for our de-embedding method, those of one of the compared de-embedding techniques approach as high as 0.0318 and 0.0324.

Simple and inexpensive microwave setup for industrial based applications: Quantification of flower honey adulteration as a case study.

A simple and inexpensive microwave measurement setup based on measurements of magnitudes of transmission properties ( | S 21 | dB ) is proposed for industrial-based microwave aquametry (moisture or water content) applications. An easy-to-apply calibration procedure based on normalization is implemented to eliminate systematic errors in the measurement system. As a case study, we applied this setup for the quantification of water-adulteration in flower honey. After validating this system by distilled water and pure flower honey measurements, | S 21 | dB measurements of the pure flower honey with various adulteration percentages ( δ ) up to 9% are conducted to examine the performance of the measurement setup for quantification of water adulteration. A multi-dimensional fitting procedure is implemented to predict δ using the proposed inexpensive microwave measurement setup. It is shown that it is possible to quantify an adulteration level with an accuracy better than ∓ 1 % by the proposed measurement setup and the applied multi-dimensional fitting procedure.

A Microwave Differential Dielectric Sensor Based on Mode Splitting of Coupled Resonators.

This study explores the viability of using the avoided mode crossing phenomenon in the microwave regime to design microwave differential sensors. While the design concept can be applied to any type of planar electrically small resonators, here, it is implemented on split-ring resonators (SRRs). We use two coupled synchronous SRRs loaded onto a two-port microstrip line system to demonstrate the avoided mode crossing by varying the distance between the split of the resonators to control the coupling strength. As the coupling becomes stronger, the split in the resonance frequencies of the system increases. Alternatively, by controlling the strength of the coupling by materials under test (MUTs), we utilize the system as a microwave differential sensor. First, the avoided mode crossing is theoretically investigated using the classical microwave coupled resonator techniques. Then, the system is designed and simulated using a 3D full-wave numerical simulation. To validate the concept, a two-port microstrip line, which is magnetically coupled to two synchronous SRRs, is utilized as a sensor, where the inter-resonator coupling is chosen to be electric coupling controlled by the dielectric constant of MUTs. For the experimental validation, the sensor was fabricated using printed circuit board technology. Two solid slabs with dielectric constants of 2.33 and 9.2 were employed to demonstrate the potential of the system as a novel differential microwave sensor.

Simulation and optimization of rectenna systems.

In this paper, we present an entirely simulation-based method to predict the performance of a complete rectenna system that includes all its components: the receiving antenna, the matching circuits between the antenna and the rectification circuit, and the load circuit. Whereas previous efforts to predict the performance of a rectenna system subdivided the system into the antenna part (radiation to AC power conversion) and the circuit part (AC power to DC power conversion), and made assumptions about the performance of the non-linear part of the rectenna based on a specified power level and frequency, in this method, the radiation part of the system is incorporated into the simulation by using Thevenin theorem. The method proposed in this work enables the rectenna designer to predict the performance of the complete rectenna system, at the design stage, for variation in the incident field's power density, angle of incidence, and operating frequency. Such performance prediction was not available before. Furthermore, the proposed method enables the rectenna designers to optimize the entire system over a portion of or the entire range of the operating frequency. Experimental results are provided to demonstrate the accuracy of the method.

Microwave bone fracture diagnosis using deep neural network.

This paper studies the feasibility of a deep neural network (DNN) approach for bone fracture diagnosis based on the non-invasive propagation of radio frequency waves. In contrast to previous "semi-automated" techniques, where X-ray images were used as the network input, in this work, we use S-parameters profiles for DNN training to avoid labeling and data collection problems. Our designed network can simultaneously classify different complex fracture types (normal, transverse, oblique, and comminuted) and estimate the length of the cracks. The proposed system can be used as a portable device in ambulances, retirement houses, and low-income settings for fast preliminary diagnosis in emergency locations when expert radiologists are not available. Using accurate modeling of the human body as well as changing tissue diameters to emulate various anatomical regions, we have created our datasets. Our numerical results show that our design DNN is successfully trained without overfitting. Finally, for the validation of the numerical results, different sets of experiments have been done on the sheep femur bones covered by the liquid phantom. Experimental results demonstrate that fracture types can be correctly classified without using potentially harmful and ionizing X-rays.

Mammography using low-frequency electromagnetic fields with deep learning.

In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining images of the breast, low-frequency electromagnetic fields are leveraged. To capture breast impressions, a metasurface, which can be thought of as analogous to X-rays film, has been employed. To achieve deep and sufficient penetration within the breast tissues, the source of excitation is a simple narrow-band dipole antenna operating at 200 MHz. The metasurface is designed to operate at the same frequency. The detection mechanism is based on comparing the impressions obtained from the breast under examination to the reference case (healthy breasts) using machine learning techniques. Using this system, not only would it be possible to detect tumors (benign or malignant), but one can also determine the location and size of the tumors. Remarkably, deep learning models were found to achieve very high classification accuracy.

A Highly Sensitive 3D Resonator Sensor for Fluid Measurement.

Planar sub-wavelength resonators have been used for sensing applications, but different types of resonators have different advantages and disadvantages. The split ring resonator (SRR) has a smaller sensing region and is suitable for microfluidic applications, but the sensitivity can be limited. Meanwhile, the complementary electric-LC resonator (CELCR) has a larger sensing region and higher sensitivity, but the topology cannot be easily designed to reduce the sensing region. In this work, we propose a new design that combines the advantages of both SRR and CELCR by incorporating metallic bars in a trapezoid-shaped resonator (TSR). The trapezoid shape allows for the sensing region to be reduced, while the metallic bars enhance the electric field in the sensing region, resulting in higher sensitivity. Numerical simulations were used to design and evaluate the sensor. For validation, the sensor was fabricated using PCB technology with aluminum bars and tested on dielectric fluids. The results showed that the proposed sensor provides appreciably enhanced sensitivity in comparison to earlier sensors.

Cancer cell detector based on a slab waveguide of anisotropic, lossy, and dispersive left-handed material.

Cancer is a disease that takes place when human cells grow uncontrollably. When detected and cured early, it can be non-life-threatening. It becomes life-threatening in case of late discovery where it affects the ability of an organ to function. In this work, a symmetric slab waveguide sensor is analyzed for the detection of cancer cells. The covering layers are assumed anisotropic lossy dispersive left-handed materials. Different from other sensors in which the analyte is located in the cladding region where the evanescent field exists, the cancerous cell is placed in the guiding film region that supports the oscillating field. Hence, the proposed sensor avoids the acute weakness of conventional optical waveguide sensors. Due to the high localization of the electromagnetic wave in the analyte region, the proposed sensor shows unusual sensitivity enhancement. The results revealed that the sensitivities obtained are 110%, 325%, and 450% for the first, second, and third modes, respectively. The enhancement of the sensitivity of the third mode relative to the conventional waveguide sensors is nearly a factor of 18.

Ternary optimization for designing metasurfaces.

A fully automated approach for designing metasurfaces whose unit cell may include metallic vias is proposed. Towards this aim, a ternary version of the particle swarm optimization (PSO) algorithm is employed in order to find the optimal metallic pattern and via-hole positions simultaneously. In the proposed design method, the upper surface of the unit cell is first pixelated. One of the possible three states of a metallic covered pixel, an uncovered etched pixel and a pixel containing a centered metalized via-hole is assigned to each pixel. The optimal state of each pixel is then determined by utilizing a ternary PSO algorithm to achieve favorable design goals. This method can be used for designing various metasurfaces as well as other via-assisted electromagnetic structures. As a proof of concept, the proposed method was applied to design two surfaces: a frequency selective surface with a minimum resonance frequency, and a linear-to-circular polarization converter with a maximum polarization conversion bandwidth. Comparison of the results with previous works confirms the efficiency and capability of the proposed method to design diverse metasurfaces in an automated fashion without the need for any theoretical or physical model.

Real-time multi-functional near-infrared wave manipulation with a 3-bit liquid crystal based coding metasurface.

We propose a new generation of reprogrammable multi-functional bias encoded metasurfaces for dynamic wave manipulation using liquid crystals (LC). This metadevice is an array of unit-cells based on LCs to provide the desired phase steps based on its large birefringence property. The presented 3-bit coding metasurface (CM) use 8 states of "000"-"111" to control and manipulate the scattered wave at λ=1.4µm for several applications. The metasurface is introduced in detail and followed by several examples to show its versatility. Steered pencil, regular, and focused vortex beams with different topological charges are realized. The theoretical predictions are confirmed by numerical simulations. The proposed CM enables the realization of multifunctional optical wavefront manipulation and future intelligent optical devices.

Intelligent Sensing Using Multiple Sensors for Material Characterization.

This paper presents a concept of an intelligent sensing technique based on modulating the frequency responses of microwave near-field sensors to characterize material parameters. The concept is based on the assumption that the physical parameters being extracted such as fluid concentration are constant over the range of frequency of the sensor. The modulation of the frequency response is based on the interactions between the material under test and multiple sensors. The concept is based on observing the responses of the sensors over a frequency wideband as vectors of many dimensions. The dimensions are then considered as the features for a neural network. With small datasets, the neural networks can produce highly accurate and generalized models. The concept is demonstrated by designing a microwave sensing system based on a two-port microstrip line exciting three-identical planar resonators. For experimental validation, the sensor is used to detect the concentration of a fluid material composed of two pure fluids. Very high accuracy is achieved.

A Pixelated Microwave Near-Field Sensor for Precise Characterization of Dielectric Materials.

A highly sensitive microwave near-field sensor based on electrically-small planar resonators is proposed for highly accurate characterization of dielectric materials. The proposed sensor was developed in a robust complete-cycle topology optimization procedure wherein first the sensing area was pixelated. By maximizing the sensitivity as our goal, a binary particle swarm optimization algorithm was applied to determine whether each pixel is metalized or not. The outcome of the optimization is a pixelated pattern of the resonator yielding the maximum possible sensitivity. A curve fitting method was applied to the full-wave simulation results to derive a closed form expression for extracting the dielectric constant of a chemical material from the shift in the resonance frequency of the sensor. As a proof of concept, the sensor was fabricated and used to measure the permittivity of two known liquids (cyclohexane and chloroform) and their mixtures with different volume ratios. The experimentally extracted dielectric constants were in an excellent agreement with the reference data (for pure cyclohexane and chloroform) or those obtained by mixture formulas.

Unconditionally stable FDTD algorithm for 3-D electromagnetic simulation of nonlinear media.

For the first time, an unconditionally stable finite-difference time-domain (FDTD) method for 3-D simulation of dispersive nonlinear media is presented. By applying a new adopted alternating-direction implicit (ADI) time-splitting scheme and the auxiliary differential equation (ADE) technique, the time-step in the FDTD simulations can be increased much beyond the Courant-Friedrichs-Lewy (CFL) stability limit. Thus, in comparison to the classical nonlinear FDTD method, the computational time for the proposed approach is decreased significantly while maintaining a reasonable level of accuracy. Numerical examples are presented to demonstrate the validity, stability, accuracy and computational efficiency of the proposed method.

Pixelated Metasurface for Dual-Band and Multi-Polarization Electromagnetic Energy Harvesting.

A dual-band and polarization-independent electromagnetic energy harvester composed of an array of pixelated unit cells is proposed. The pixelated unit cell is basically a dual-band resonator loaded with two resistors which model the input impedance of a power combining circuit in a complete harvesting system. To design the unit cell, a topology optimization approach based on pixelization of the surface of the unit cell and application of a binary optimization algorithm is used. The optimization goal is set to maximize harvesting efficiency at 2.45 GHz and 6 GHz. In our design, full symmetry of the unit cell is considered to achieve insensitivity to the polarization of the incident wave. Once, the unit cell is designed, as a proof of the concept, a metasurface harvester composed of 9 × 9 pixelated cells is designed. The full-wave electromagnetic simulation results demonstrate that the proposed metasurface absorbs the incident electromagnetic wave energy with nearly unity efficiency at both frequencies of interest and irrespective the polarization of the incident field while simultaneously delivering the absorbed power to the loads. To validate the simulations, the metasurface harvester is fabricated and tested in an anechoic chamber. A strong agreement between the simulation results and measurements is observed.

Near Field Breast Tumor Detection Using Ultra-Narrow Band Probe with Machine Learning Techniques.

In this work, we propose a near-field microwave sensing modality that uses a single probe combined with a classification algorithm to help in detecting the presence of tumors in the human female breast. The concept employs a near-field resonant probe with an ultra-narrow frequency response. The resonant probe is highly sensitive to the changes in the electromagnetic properties of the breast tissues such that the presence of the tumor is gauged by determining the changes in the magnitude and phase response of the sensor's reflection coefficient. A key feature of our proposed detection concept is the simultaneous sensing of tissue property changes to the two female breasts since the right and left healthy breasts are morphologically and materially identical. Once the probe response is recorded for both breasts, the Principle Component Analysis (PCA) method is employed to emphasize the difference in the probe responses. For validation of the concept, tumors embedded in a realistic breast phantoms were simulated. To provide additional confidence in the detection modality introduced here, experimental results of three different sizes of metallic spheres, mimicking tumors, inserted inside chicken and beef meat were detected using an electrically-small probe operating at 200 MHz. The results obtained from the numerical tests and experiments strongly suggest that the detection modality presented here might lead to an inexpensive and portable early and regular screening for breast tumor.

Harvesting the Energy of Multi-Polarized Electromagnetic Waves.

We present the idea and design of a dual polarized metasurface for electromagnetic energy harvesting. A 4 × 4 super cell with alternating vias between adjacent cells was designed to allow for capturing the energy from various incident angles at an operating frequency of 2.4 GHz. The collected energy is then channeled to a feeding network that collects the AC power and feeds it to a rectification circuitry. The simulation results yielded a radiation to AC and an AC to DC conversion efficiencies of around 90% and 80%, respectively. As a proof of concept, an array consisting of 9 super cells was fabricated and measured. The experimental results show that the proposed energy harvester is capable of capturing up to 70% of the energy from a planewave having various polarizations and converting it to usable DC power.

Pixelated Checkerboard Metasurface for Ultra-Wideband Radar Cross Section Reduction.

In this paper we designed and fabricated a metasurface working as a radar cross section (RCS) reducer over an ultra wide band of frequency from 3.8 to 10.7 GHz. The designed metasurface is a chessboard-like surface made of alternating tiles, with each tile composed of identical unit cells. We develop a novel, simple, highly robust and fully automated approach for designing the unit cells. First, a topology optimization algorithm is used to engineer the shape of the two unit cells. The area of each unit cell is pixelated. A particle swarm optimization algorithm is applied wherein each pixel corresponds to a bit having a binary value of 1 or 0 indicating metallization or no metallization. With the objective of reducing the RCS over a specified frequency range, the optimization algorithm is then linked to a full wave three-dimensional electromagnetic simulator. To validate the design procedure, a surface was designed, fabricated and experimentally tested showing significantly enhanced performance than previous works. Additionally, angular analysis is also presented showing good stability and wide-angle behavior of the designed RCS reducer. The automated design procedure has a wide range of applications and can be easily extended to design surfaces for antennas, energy harvesters, noise mitigation in electronic circuit boards amongst others.

Spherical aberration in electrically thin flat lenses.

We analyze the spherical aberration of a new generation of lenses made of flat electrically thin inhomogeneous media. For such lenses, spherical aberration is analyzed quantitatively and qualitatively, and comparison is made to the classical gradient index rod. Both flat thin and thick lenses are made of gradient index materials, but the physical mechanisms and design equations are different. Using full-wave three-dimensional numerical simulation, we evaluate the spherical aberrations using the Maréchal criterion and show that the thin lens gives significantly better performance than the thick lens (rod). Additionally, based on ray tracing formulation, third-order analysis for longitudinal aberration and optical path difference are presented, showing strong overall performance of thin lenses in comparison to classical rod lenses.

A Non-Invasive Phase Sensor for Permittivity and Moisture Estimation Based on Anomalous Dispersion.

The traditional microwave resonance sensors are based on the measurement of the frequency shift and bandwidth of a resonator's amplitude spectrum. Here we propose a novel sensing scheme in which the material properties are estimated by determining the changes in the phase spectrum of an anomalous-phase resonator. In the proposed phase sensing, we exploit the unique double phase reversal which takes place on the edges of the anomalous dispersion region as a signature to detect the resonance. We show that with the phase sensing, a significant reduction in detection errors compared to the traditional sensing can be obtained because of the noise immunity offered by the phase detection and also due to the strong dispersive phase response that reduces the sensor's dependence on the external environment. We also show that the bandwidth determination procedure of the resonance which is needed to characterize the sample losses is significantly simplified. The concept of phase sensing is shown by devising an experimental microstrip open stub resonator whose frequency response lies in the anomalous dispersion region. The dielectric characteristics of the samples placed on the stub are extracted from the resonant frequency and the slope of the phase response. We also demonstrate that the changes in moisture levels can also be detected by utilizing the phase sensing method.

Refraction in electrically thin inhomogeneous media.

This work presents a new formulation for refraction from flat electrically thin lenses and reflectors comprised of inhomogeneous material. Inhomogeneous electrically thin flat lenses and reflectors cannot make use of the Snell law since this classical formulation works solely at interfaces of planar homogeneous media. The refraction of a perpendicularly incident plane wave at a planar interface is physically explained through the phase advance of the rays within the medium. The Huygens principle is then used to construct the refracted wavefront. The formulation is validated using numerical full wave simulation for several examples where the refractive angle is predicted with good accuracy. Furthermore, the formulation gives a physical insight of the phenomenon of refraction from electrically thin inhomogeneous media.