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This paper provides an overview of balanced (or differential-mode) structures operating at microwaves, including common-mode suppression filters, balanced filters and circuits with intrinsic common-mode suppression, and differential-mode sensors. The increasing interest for balanced structures within the framework of communication circuits and sensors, related to their major robustness against electromagnetic interference (EMI), noise, and environmental factors, is duly justified. Then the paper reports various approaches for the implementation of common-mode suppression filters, balanced filters and circuits (including narrowband and wideband filters, multi-band filters, power dividers, couplers and phase shifters), and differential-mode sensors (mainly devoted to the measurement of permittivity and related variables). Rather than providing a detailed analysis of the different considered implementations/approaches, the main goal of this review paper is to discuss, and compare in some cases, the main proposed strategies (pointed out in the up-to-date state-of-the-art) for optimizing the performance of the various differential-mode devices under study.

Simple methods using a microstrip coupled-line directional coupler (CLDC) are presented for dielectric constant measurements. The material under test (MUT) is placed on the coupled-line section of the coupler, and either the coupler’s coupling ( |S31| ) or its isolation level ( |S41| ) is considered as the sensor’s response. Putting different MUTs on the microstrip line leads to a change in the effective dielectric constant of the structure and consequently causing a change in the coupling coefficient. In addition, since the isolation level of a microstrip coupled-line coupler depends on the phase velocity difference between the substrate and the medium above the signal strips, putting different MUTs on the line significantly changes the isolation level. This change is significantly greater than the change in |S21| level of a microstrip line when loaded with different MUTs. Validation of the method is presented through measurements for both solid and liquid MUTs.

Altres ajuts: ICREA award Altres ajuts: Universidad Politécnica de Madrid y Administración de la Comunidad de Madrid por el apoyo dentro del V Programa de Excelencia PRICIT para Profesorado Universitario (Número de Beca: M190020074B) It is shown in this paper that a microstrip line loaded with a dumbbell-shaped defect ground structure (DB-DGS) is useful for complex permittivity measurements. The working principle of the sensor is the variation in the notch (resonance) frequency and depth caused by the material under test (MUT), when it is put in contact with the sensitive region of the device, i.e., the capacitive slot. It is demonstrated that the relative sensitivity of the sensor, defined as the variation of the resonance frequency of the DB-DGS with the dielectric constant of the MUT relative to the resonance frequency of the bare structure, does not depend on the geometry of the DB-DGS, provided the substrate is thick enough. The relative sensitivity, the key figure of merit, is dictated by the equivalent dielectric constant of the substrate, and it increases as the substrate permittivity decreases. Using the circuit model of the sensing structure, simple analytical expressions providing the dielectric constant and the loss tangent of the MUT are derived. Such analytical formulas depend on the notch frequency and depth of the sensor with and without MUT in contact with it, i.e., easily measurable quantities. The analysis carried out is corroborated through full-wave electromagnetic simulation and experiments.

This paper examines the effect of finger fat pad thickness on the accuracy performance of complementary split-ring resonator (CSRR)-based microwave sensors for non-invasive blood glucose level detection. For this purpose, a simplified four-layer Cole–Cole model along with a CSRR-based microwave sensor have been comprehensively analyzed and validated through experimentation. Computed scattering parameter (S-parameter) responses to different fat layer thicknesses are employed to verify the concordance of the studied model with the measurement results. In this respect, a figure of merit (FM) based on the normalized squared difference is introduced to assess the accuracy of the considered Cole–Cole model. We have demonstrated that the analyzed model agrees closely with the experimental validation. In fact, the maximum error difference for all five fingertips does not exceed 1.73 dB over the entire frequency range of interest, from 1 GHz to 4 GHz.

Altres ajuts: ICREA award A microfluidic sensor based on a microstrip line loaded with a composite resonator is reported in this paper. The composite resonator combines a shunt connected step impedance resonator (SIR) and a complementary split ring resonator CSRR) etched in the ground plane. By etching the CSRR beneath the patch of the SIR, the composite CSRR-loaded SIR resonator exhibits two transmission zeros and a pole in between. The operating principle of the sensor is the variation of the transmission coefficient at the pole frequency of the bare resonator, when a material or liquid under test (LUT) is in contact with the CSRR (the sensitive element). By designing the CSRR-loaded SIR resonator with closely spaced pole and transmission zeros, highly sensitive sensors are obtained. Despite the fact that the proposed sensor can also operate as a frequency variation sensor, using it as a single-frequency sensor based on the variation of the transmission coefficient (caused by the LUT) at a specific frequency reduces sensor costs. The reason is that a harmonic signal injected to the input port of the microstrip-based sensor plus a simple amplitude modulation (AM) detector (connected to the output port) suffices for measuring purposes. The proposed microfluidic sensor is applied to the characterization of volume fraction of solutions of isopropanol in deionized (DI) water. The sensor is able to resolve volume fractions as small as 5%, and the maximum measured sensitivity is as good as 4 mV/%.

Microwave resonators are widely adopted as high sensitivity sensors in both applied and fundamental metrology, to measure a number of different physical quantities, such as temperature, humidity, pressure, length and material properties. High sensitivity, and thus potential high measurement precision and accuracy, can be achieved by resorting to high-quality-factor ( $Q$ ) resonators. Nonetheless, in order to accurately measure a high- $Q$ resonance and obtain low measurement uncertainty, as required by metrology applications, the entire measurement set-up must be carefully designed. This papers presents an overview of resonance frequency measurements for metrology applications, illustrating the various aspects and issues to be dealt with when pursuing highly accurate measurements, as well as of the most relevant achievements in this field.

A capacitive microwave sensor with homogeneous field distribution is presented. It relies on a high-impedance parallel-plate arrangement and a properly positioned guard electrode to mitigate fringing field effects. The distance between the capacitor plates can be as large as their diameter. Such an arrangement allows permittivity measurements of irregularly shaped objects like individual biological cells. This is demonstrated with a microchip sensor in a microfluidic setup. The calibration requires only a single reference fluid.

Accurate and stable in-orbit radiometric calibration of a satellite instrument is fundamental to Earth geophysical parameter estimation. This article addresses the intercalibration of the microwave temperature sounder (MWTS) on the Chinese second-generation polar-orbiting meteorological satellite, Fengyun 3D (FY-3D), against the advanced technology microwave sounder (ATMS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. First, ocean and land microwave radiative transfer models (RTM) are constructed by combining the sea and land surface emissivity models and atmospheric absorption model, as well as the intercalibration equations. Then, the MWTS and ATMS observations are resampled into a 1° × 1° regular grid space, and the matching brightness temperatures (TBs) under clear-sky/near clear-sky conditions are collected. Next, the TBs at top-of-atmosphere are simulated using the RTM and the fifth generation of European Centre for Medium-Range Weather Forecast atmospheric reanalysis (ERA5) data. After that, the double differences between FY-3D MWTS and S-NPP ATMS and the theoretical observations in FY-3D MWTS channels are calculated. Finally, the radiometric calibration coefficients of FY-3D MWTS are successfully derived from the observations of S-NPP ATMS by linear fits on the matching TBs. In contrast to the ATMS measurements, FY-3D MWTS observations are generally overestimated, and the in-orbit radiometric calibration errors (mean ± standard deviation at the mean) are 1.83 ± 1.45, 0.45 ± 0.94, 1.87 ± 0.60, −0.20 ± 0.36, −0.02 ± 0.37, 0.19 ± 0.24, 1.69 ± 0.28, 2.25 ± 0.29, 1.97 ± 0.33, 1.74 ± 0.42, 2.84 ± 0.42, 0.07 ± 0.65, and 0.32 ± 1.18 K in FY-3D MWTS channels 1–13, respectively. The results with Hewison's semi-empirical land surface emissivity (LSE) model and the results with LSEs derived from the coincident ATMS observations at 50.3 GHz are consistent. Moreover, the intercalibration results obtained by the RTM in this work also agree well with the results obtained by the community radiative transfer model.

This paper presents a planar and compact microwave resonator sensor to characterize materials. The geometry of the resonator is based on the Sierpinski fractal curve and has four poles in the frequency range from 0.5 GHz to 5.5 GHz. Any of the four poles can be used to measure samples with low permittivity values, where the first pole is suitable for samples with high permittivity values. The sensitivity of the poles and return losses of the sensor are presented and obtained using a full-wave 3D simulator software. The device is manufactured and validated through a comparison between simulated and measured results. © 2020 P. H. B. Cavalcanti Filho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The detection of chemical samples having close dielectric response is a big challenge as the detection principle is driven by the variations in the dielectric parameters of the investigated samples. In the current work, a new metamaterial-based sensor is designed and fabricated in order to be used for the detection of liquid chemicals in the frequency range from 8 to 12 GHz. Several designs were tested using genetic algorithm, which is embedded in the CST microwave studio, in order to optimize the desired dimensions of the resonator. The simulation and experimental results showed that the proposed sensor is working well to detect various liquids, including (i) clean and waste transformer oils, (ii) corn, cotton and olive oils, (iii) branded and unbranded diesels and (iv) aniline doped ethyl-alcohol and benzene doped carbon tetrachloride. This was made possible through the occurrence of a shift in the resonant frequency of about 250 MHz, 200 MHz, 250 MHz, 150 MHz and 50 MHz for the aforementioned samples, respectively. The sensing mechanism was interpreted through the surface current and electric field distributions. We believe that the proposed sensor is viable to be used in various applications including liquid chemicals detection and industrial applications. © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This paper presents an overview of the use of additive manufacturing (AM) technologies for the implementation of microwave components. Two major technological solutions, based on the AM of plastic materials, are discussed: in the former case, the AM plastic is used as a dielectric material that constitutes the component. Conversely, in the latter case, the plastic material is a mere support of the metallization, thus avoiding the contact of the AM plastic with the electromagnetic field and reducing losses. Several examples are illustrated and discussed, to highlight benefits and limitations of AM techniques in the current scenario of microwave applications.

A microwave planar resonator sensor design supporting spoof surface plasmon waves is used for wafer dielectric characterization. The proposed circuit guides the microwave as a surface wave across the metal signal line, from port to port of the device. The surface wave effectively interacts with the sample being measured, placed on top of the planar sensor. The proposed planar sensor is fabricated on an RF-35 substrate, resulting in a low-cost implementation. The sensor is used to discriminate between wafers with different dielectric permittivity and thickness. Quartz, borosilicate, BK7 glass, and Silicon wafers have been characterized using the proposed sensor. The sensor resonant frequency and losses change according to the permittivity and the thickness of the samples, with an achieved sensor sensitivity of 60.22 MHz/?r. Simulation and measurements demonstrate that the proposed spoof surface plasmon resonator sensor can be used to create a high sensitivity sensor for dielectric material characterization. The dielectric constant and loss tangent of the samples are inferred from a polynomial fit obtained from sample simulations and confirmed through measurements. © 2017 IEEE.

With rising healthcare costs and the rapid increase in remote physiologic monitoring and care delivery, there is an increasing need for economical, accurate, and non-invasive continuous measures of blood analytes. Based on radio frequency identification (RFID), a novel electromagnetic technology (the Bio-RFID sensor) was developed to non-invasively penetrate inanimate surfaces, capture data from individual radio frequencies, and convert those data into physiologically meaningful information and insights. Here, we describe groundbreaking proof-of-principle studies using Bio-RFID to accurately measure various concentrations of analytes in deionized water. In particular, we tested the hypothesis that the Bio-RFID sensor is able to precisely and non-invasively measure and identify a variety of analytes in vitro. For this assessment, varying solutions of (1) water in isopropyl alcohol; (2) salt in water, and (3) commercial bleach in water were tested, using a randomized double-blind trial design, as proxies for biochemical solutions in general. The Bio-RFID technology was able to detect concentrations of 2000 parts per million (ppm), with evidence suggesting the ability to detect considerably smaller concentration differences.

Microwave imaging is a high-resolution, noninvasive, and noncontact method for detecting hidden defects, cracks, and objects with applications for testing nonmetallic components such as printed circuit boards, biomedical diagnosis, aerospace components inspection, etc. In this paper, an array of microwave sensors designed based on complementary split ring resonators (CSRR) are used to evaluate the hidden features in dielectric media with applications in nondestructive testing and biomedical diagnosis. In this array, each element resonates at a different frequency in the range of 1 GHz to 10 GHz. Even though the operating frequencies are not that high, the acquisition of evanescent waves in extreme proximity to the imaged object and processing them using near-field holographic imaging allows for obtaining high-resolution images. The performance of the proposed method is demonstrated through simulation and experimental results.

Precise monitoring of fluid flow rates constitutes an integral problem in various lab-on-a-chip applications. While off-chip flow sensors are commonly used, new sensing mechanisms are being investigated to address the needs of increasingly complex lab-on-a-chip platforms which require local and non-intrusive flow rate sensing. In this regard, the deformability of microfluidic components has recently attracted attention as an on-chip sensing mechanism. To develop an on-chip flow rate sensor, here we utilized the mechanical deformations of a 220 nm thick Silicon Nitride membrane integrated with the microfluidic channel. Fluid flow induces deformations on the membrane, which is electronically probed by the changes in the capacitance and resonance frequency of an overlapping microwave resonator. By tracking the resonance frequency, both liquid and gas flows were probed with the same device architecture. For liquid flow experiments, a secondary sensing mechanism emerged when it was observed that steady liquid flow induces periodic deformations on the membrane. Here, the period of membrane deformation depends on the flow rate and can again be measured electronically by the microwave sensor. Flow rate measurements based on the deformation and instability of thin membranes demonstrate the transduction potential of microwave resonators for fluid-structure interactions at micro and nanoscales.

Ocean Water Quality (OWQ) monitoring provides insights into the quality of water in marine and near-shore environments. OWQ measurements can contain the physical, chemical, and biological characteristics of oceanic waters, where low OWQ values indicate an unhealthy ecosystem. Many parameters of water can be estimated from Remote Sensing (RS) data. Thus, RS offers significant opportunities for monitoring water quality in estuaries, coastal waterways, and the ocean. This paper reviews various RS systems and techniques for OWQ monitoring. It first introduces the common OWQ parameters, followed by the definition of the parameters and techniques of OWQ monitoring with RS techniques. In this study, the following OWQ parameters were reviewed: chlorophyll-a, colored dissolved organic matter, turbidity or total suspended matter/solid, dissolved organic carbon, Secchi disk depth, suspended sediment concentration, and sea surface temperature. This study presents a systematic analysis of the capabilities and types of spaceborne systems (e.g., optical and thermal sensors, passive microwave radiometers, active microwave scatterometers, and altimeters) which are commonly applied to OWQ assessment. The paper also provides a summary of the opportunities and limitations of RS data for spatial and temporal estimation of OWQ. Overall, it was observed that chlorophyll-a and colored dissolved organic matter are the dominant parameters applied to OWQ monitoring. It was also concluded that the data from optical and passive microwave sensors could effectively be applied to estimate OWQ parameters. From a methodological perspective, semi-empirical algorithms generally outperform the other empirical, analytical, and semi-analytical methods for OWQ monitoring. © 2022 Elsevier Ltd

Ocean Water Quality (OWQ) monitoring provides insights into the quality of water in marine and near-shore environments. OWQ measurements can contain the physical, chemical, and biological characteristics of oceanic waters, where low OWQ values indicate an unhealthy ecosystem. Many parameters of water can be estimated from Remote Sensing (RS) data. Thus, RS offers significant opportunities for monitoring water quality in estuaries, coastal waterways, and the ocean. This paper reviews various RS systems and techniques for OWQ monitoring. It first introduces the common OWQ parameters, followed by the definition of the parameters and techniques of OWQ monitoring with RS techniques. In this study, the following OWQ parameters were reviewed: chlorophyll-a, colored dissolved organic matter, turbidity or total suspended matter/solid, dissolved organic carbon, Secchi disk depth, suspended sediment concentration, and sea surface temperature. This study presents a systematic analysis of the capabilities and types of spaceborne systems (e.g., optical and thermal sensors, passive microwave radiometers, active microwave scatterometers, and altimeters) which are commonly applied to OWQ assessment. The paper also provides a summary of the opportunities and limitations of RS data for spatial and temporal estimation of OWQ. Overall, it was observed that chlorophyll-a and colored dissolved organic matter are the dominant parameters applied to OWQ monitoring. It was also concluded that the data from optical and passive microwave sensors could effectively be applied to estimate OWQ parameters. From a methodological perspective, semi-empirical algorithms generally outperform the other empirical, analytical, and semi-analytical methods for OWQ monitoring. © 2022 Elsevier Ltd

©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper presents an embroidered textile frequency-splitting microwave sensor based on a pair of identical stepped-impedance resonators (SIRs) loading a microstrip transmission line. The sensor is implemented by means of conductive threads. The sensing region of the proposed structure is the capacitive square patch of one of the SIRs. If such region is kept unaltered, the structure is symmetric, and the frequency response (transmission coefficient) exhibits a single transmission zero. However, if symmetry is broken (e.g., through liquid absorption in the sensing region), the frequency response of the proposed sensor exhibits two transmission zeros (frequency splitting). The difference (in frequency and magnitude) between such zeros (or notches) is intimately related to the dielectric properties of the absorbed liquids to be sensed / detected. The proposed sensing structure is applied to the detection of deionized (DI) water absorption, and to the quantification of the number of DI water drops. The maximum measured sensitivity is found to be 2.70 MHz /µl and 0.03 dB /µl for the incremental frequency and incremental magnitude of the notches. This work was supported by MICIIN-Spain (projects PID2019-103904RB-I00, TEC2016-79465-R, and PDC2021-121085-I00),Generalitat de Catalunya (project 2017SGR-1159), Institució Catalana de Recerca i Estudis Avançats (who awarded Ferran Martín), and by FEDER funds.

The measurement of water cut in crude oil is an essential procedure in petroleum production and it is desirable to obtain these data through an automatic and real-time method. Microwave sensors can be used for the task, and they are safe, robust and can cover the whole water cut range. However, they are relatively susceptible to the water conductivity and temperature, and the algorithms for addressing these problems are still rare in the literature. In this paper, a microwave transmission sensor that can measure the water cut under varying salinity conditions is proposed, and the algorithm for solving the water cut and salinity simultaneously with the measured amplitude and phase is described in detail. Experiments under different water cut and salinity conditions are conducted, and the results are used to verify the model and algorithm. Finally, a simplified and fast method for uncertainty analysis is proposed and applied to the iteration algorithm under test conditions. It can be concluded that accuracy higher than 95% in the water cut measurements can be expected under the 0~100% water cut range, and an error of about 10% in the water conductivity is achievable under water-continuous flow conditions. The uncertainty analysis shows that the calculated water cut and salinity results are negatively correlated, and the water salinity uncertainty tends to be larger than the water cut uncertainty. When the water salinity is high, the water cut uncertainty tends to be high whereas the water salinity uncertainty tends to be low.

Sensing motion and distinguishing its source as human or nonhuman, with high precision, has tremendous applications in a variety of areas from health monitoring to energy efficiency. One strategy to achieve this goal is to detect the small motion of breathing, which is a consistent indicator of human presence. Among the many smart sensing schemes proposed, microwave and RF sensors have shown great promise due to their simplicity, privacy, and effective range. In this paper, we propose the use of a dynamic metasurface antenna (DMAs) as an alternative hardware platform for sensing motion inside a residential setting using microwave signals. The proposed device is a single-port planar cavity that excites an array of electronically-tunable metamaterial elements. The DMA can generate spatially diverse patterns at a single frequency, avoiding complexities related to wideband operation or high hardware costs of antenna arrays. We demonstrate that it is capable of detecting minute movements, such as breathing emulated by a mannequin, to distinguish human presence. This motion can be detected whether the target is in the the sensor's direct line of sight or out of the direct line of sight. Furthermore, we show that the DMA sensing platform requires a single noise-floor calibration and can operate in different room geometries or configurations (e.g. when furniture is displaced). The proposed DMA-sensor with its single frequency operation and simple hardware is an appealing alternative hardware for intruder detection, human presence detection/activity recognition in smart homes, or seamless health monitoring.

A novel, low-cost, sensitive microwave microfluidic glucose detecting biosensor incorporating molecularly imprinted polymer (MIP) is presented. The sensing device is based on a stub resonator to characterize water glucose solutions. The tip of one of the stubs is coated with MIP to increase the selectivity of the sensor and hence the sensitivity compared to the uncoated or to the coated with non-imprinted polymer (NIP) sensor. The sensor was fabricated on a FR4 substrate for low-cost purposes. In the presence of the MIP, the sensor loaded with a glucose solution ranging from 50 mg/dL to 400 mg/dL is observed to experience an absorption frequency shift of 73 MHz when the solutions flow in a microfluidic channel passing sensing area, while the lower limit of detection (LLD) of the sensor is discovered to be 2.4 ng/dL. The experimental results show a high sensitivity of 1.3 MHz/(mg/dL) in terms of absorption frequency.

Sea-surface petroleum pollution is observed as “oil slicks” (i.e., “oil spills” or “oil seeps”) and can be confused with “look-alike slicks” (i.e., environmental phenomena, such as low-wind speed, upwelling conditions, chlorophyll, etc.) in synthetic aperture radar (SAR) measurements, the most proficient satellite sensor to detect mineral oil on the sea surface. Even though machine learning (ML) has become widely used to classify remotely-sensed petroleum signatures, few papers have been published comparing various ML methods to distinguish spills from look-alikes. Our research fills this gap by comparing and evaluating six traditional techniques: simple (naive Bayes (NB), K-nearest neighbor (KNN), decision trees (DT)) and advanced (random forest (RF), support vector machine (SVM), artificial neural network (ANN)) applied to different combinations of satellite-retrieved attributes. 36 ML algorithms were used to discriminate “ocean-slick signatures” (spills versus look-alikes) with ten-times repeated random subsampling cross validation (70-30 train-test partition). Our results found that the best algorithm (ANN: 90%) was >20% more effective than the least accurate one (DT: ~68%). Our empirical ML observations contribute to both scientific ocean remote-sensing research and to oil and gas industry activities, in that: (i) most techniques were superior when morphological information and Meteorological and Oceanographic (MetOc) parameters were included together, and less accurate when these variables were used separately; (ii) the algorithms with the better performance used more variables (without feature selection), while lower accuracy algorithms were those that used fewer variables (with feature selection); (iii) we created algorithms more effective than those of benchmark-past studies that used linear discriminant analysis (LDA: ~85%) on the same dataset; and (iv) accurate algorithms can assist in finding new offshore fossil fuel discoveries (i.e., misclassification reduction).

Planar microwave angular displacement and angular velocity sensors implemented in microstrip technology are proposed. The transducer element is a circularly shaped divider/combiner, whereas the sensing element is an electric-LC resonator, attached to the rotating object and magnetically coupled to the circular (active) region of the transducer. The angular variables are measured by inspection of the transmission characteristics, which are modulated by the magnetic coupling between the resonator and the divider/combiner. The degree of coupling is hence sensitive to the angular position of the resonator. As compared with coplanar waveguide angular displacement and velocity sensors, the proposed microstrip sensors do not require air bridges, and the ground plane provides backside isolation.

This article is focused on the analysis and modeling of coplanar waveguide (CPW) transmission lines loaded with multisection stepped impedance resonators (MS-SIRs), transversely etched on the back substrate side. The considered structure consists of a CPW loaded with a 5-section SIR (5S-SIR) with wide (capacitive) central and external sections cascaded with narrow (inductive) sections. The general case of a 5S-SIR with arbitrary lengths and widths of the different sections is considered. The structure is described by a pair of inductively coupled grounded series resonators coupled to the line through the capacitance of the central 5S-SIR section. If the structure is symmetric, the transmission coefficient exhibits a single transmission zero. Hence, these structures can be used as notch filters exhibiting wide bandwidths, provided the inductance of the 5S-SIR can be made small, and the capacitance can be enhanced by virtue of the broadside coupling. However, if symmetry is broken, two notches separated a distance that depends on the level of asymmetry and inductive coupling appear. Therefore, these structures are also useful for the implementation of differential sensors and comparators. The proposed model is validated through parameter extraction and experiment, and a proof-of-concept of a comparator is reported.

International audience; A differential microwave sensor, based on a pair of uncoupled microstrip lines each one loaded with a split ring resonator (SRR), is applied to the measurement of electrolyte concentration in deionized (DI) water. For that purpose, fluidic channels are added on top of the SRR gaps, the most sensitive parts of the structure. The operating principle is based on the measurement of the cross-mode insertion loss, highly sensitive to small asymmetries caused by differences between the reference liquid and the liquid under test (LUT). In this work, the reference liquid is pure DI water (the solvent), whereas the solution, DI water with electrolyte content, is injected to the LUT channel. The proposed sensor is able to detect electrolyte concentrations as small as 0.25 g/L, with maximum sensitivity of 0.033 (g/L)-1. The sensor is validated by measuring the concentration of three types of electrolytes, i.e., NaCl, KCl and CaCl2. Finally, the sensor is applied to monitor variations of total electrolyte concentration in urine samples.

Fine-grained water quality data can facilitate the optimized management of water resources, which have become increasingly scarce due to population growth, increased demand for safe sources of water, and environmental pollutions. There is a pressing need for cost-effective, reliable, re-usable, and autonomous water sensing technologies that can provide accurate real-time water quality measurements. In this paper, we present a microwave sensor array with sensing elements operating at different frequencies in the wide frequency band of 1 GHz to 10 GHz. The use of array allows for collecting more information compared with a single sensor system. The sensor array can be fabricated in a cost-effective way through standard printed circuit board (PCB) technology. Here, it is tested with water solutions of various contaminants and parameter values. The dielectric properties of the water sample with different contaminants and parameter values are measured and provided as well.

A label-free, sensitive, miniaturized sensing device was developed for detecting living cells in their flow stream. The outstanding performance of this biosensor in distinguishing living cells in cell suspension was achieved by integrating microstrip stub resonator above a microfluidic structure using the metallic nanowire-filled membrane technology. The cell suspension flows in a microfluidic channel placed between the tip of the stub resonator and its ground plane as the substrate to take advantage of the uniform and concentrated field distribution. We studied the changes in relative permittivity due to the presence of a single living cell in the phase of the transmitted signal (S21). An average variation of as much as 22.85 ± 1.65° at ~11.1 GHz is observed for the living cell sensing using this optimized device. This biosensor could detect rapid flowing cells in their biological medium in real-time and hence, can be used as an early diagnosis and monitoring tool for diseases.

In this work, a novel, to the best of our knowledge, metamaterial-based microwave sensor is designed, numerically simulated, and experimentally tested for milk and dairy products in the frequency range of 8 to 9 GHz. The proposed structure is composed of copper split-ring resonators printed on Arlon Diclad 527 dielectric substrate. Reflection coefficient S 11 was determined by using numerical simulation, and the structure was experimentally tested to validate the sensor at the X band frequency. The material under the test was placed in the sensor layer just behind the proposed structure, and the design was optimized to sense the change in the dielectric constant via resonance frequency shifts. The proposed study was not only used for fat contents and freshness checking of milk, it was also applied to other dairy products such as cheese, ayran, and yogurt. The maximum resonance frequency shift was observed in yogurt to be 140 MHz, and the minimum frequency shift was observed in fresh and spoiled ayran to be around 40 MHz. This work provides a new approach to the current metamaterial sensor studies existing in literature by having novel material applications with new microwave metamaterial sensors.

A radar sensor suitable to record carotid wall movements has been developed and tested. The sensor is based on a double-sideband continuous-wave coherent transceiver, operating at 2.45 GHz, and on a bow-tie planar antenna optimized to operate in contact with the neck. Measured transceiver responses on a sliding short load are in good agreement with an analytical model and simulation results. An artificial model of the neck with an embedded pulsatile carotid-artery mockup has been built to test the radar. When the radar antenna is placed in contact with the neck model, an output voltage signal following the carotid diameter variations is measured. The signal amplitude follows the pressure wave imposed on the carotid artery mockup.

Microwave sensor technology is widely accepted as a non-destructive and hygienic means for food evaluation and analysis. However, its applications concentrate on in-lab investigations, which are not widely applied for on-line measurement in food industry. Motivated by the rapid progress of microwave technologies and the lack of on-line measurement systems in industry, this paper aims to provide a comprehensive overview of microwave sensors for food measurement, define the technological gap, and suggest the potential solutions. With a brief introduction to the fundamentals, classification and analysis of the traditional methods and technologies are presented, followed by a discussion of calibration and decision-making methods. Based on the analysis of the cutting-edge microwave sensing technologies, the limitations and challenges facing the present studies are identified. Then, focusing on some new emerging technologies including Monolithic Microwave Integrated Circuits (MMIC), antenna array, and System on Chip (SoC) Ultra-Wide Band (UWB) pulse-based time domain systems, the feasibility and prospective of potential solutions in this particular area are suggested. In addition, integration of emerging Information and Communication Technologies (ICT) and new design concepts of the sensor system concerning the practical use for smart manufacturing are also illustrated. The potentiality of the suggested new emerging technologies and integration of ICT to satisfy future digitised industry will be inspirational and of interest to researchers of both microwave engineering and food sectors.

WOS: 000404530900034, A metamaterial-based sensor has been realized to distinguish authentic and inauthentic fuel samples in the microwave frequency regime. Unlike the many studies in literature on metamaterial-based sensor applications, this study focuses on a compact metamaterial-based sensor operating in the X-band frequency range. Firstly, electromagnetic properties of authentic and inauthentic fuel samples were obtained experimentally in a laboratory environment. Secondly, these experimental results were used to design and create a highly efficient metamaterial-based sensor with easy fabrication characteristics and simple design structure. The experimental results for the sensor were in good agreement with the numerical ones. The proposed sensor offers a more efficient design and can be used to detect fuel and multiple other liquids in various application fields from medical to military areas in several frequency regimes., TUBITAK [115E788]; Turkish Academy of Sciences, F.D. acknowledges support from TUBITAK under Project No. 115E788 and partial support from the Turkish Academy of Sciences.

This paper proposes a differential sensor based on a pair of open split ring resonators (OSRR) operating in reflection. The output signal is thus the differential reflection coefficient of both resonators, intimately related to their dielectric loading. Thus, for identical loads in both sensing resonators, the individual reflection coefficients are equal, thereby providing an ideally null output signal. By contrast, when unequal dielectric loads truncate the symmetry, the reflection coefficients are different, resulting in a differential output signal related to the level of asymmetry. In order to ease the measurement of the output signal, a rat-race hybrid coupler is used. The OSRR sensing loads are connected to the coupled ports of the hybrid coupler, whereas the input signal is injected to the Δ-port, and the output signal is collected at the isolated port (Σ-port). By this means, the output signal, i.e. the differential reflection coefficient between both sensing loads, is obtained from the transmission coefficient of a simple two-port structure. For experimental validation purposes, the sensor is applied to the measurement of isopropanol content in aqueous solutions, and for that purpose, the sensitive regions are equipped with microfluidic channels.

In this paper, reflective-mode phase-variation sensors based on open-ended stepped-impedance transmission lines with optimized sensitivity for their use as defect detectors and dielectric constant sensors are reported. The sensitive part of the sensors consists of either a 90° high-impedance or a 180° low-impedance open-ended sensing line. To optimize the sensitivity, such a sensing line is cascaded to a 90° transmission line section with either low or high characteristic impedance, resulting in a stepped-impedance transmission line configuration. For validation purposes, two different sensors are designed and fabricated. One of the sensors is implemented by means of a 90° high impedance (85 Ω) open-ended sensing line cascaded to a 90° low impedance (15 Ω) transmission line section. The other sensor consists of a 180° 15-Ω open-ended sensing line cascaded to a 90° 85-Ω line. Sensitivity optimization for the measurement of dielectric constants in the vicinity of that corresponding to the Rogers RO4003C substrate (i.e., with dielectric constant 3.55) is carried out. The functionality as a defect detector is demonstrated by measuring the phase-variation in samples consisting of the uncoated Rogers RO4003C substrate (the reference sample) with arrays of holes of different densities.

This paper highlights interest in the implementation of microwave sensors based on resonant elements, the subject of a special issue in the journal. A classification of these sensors on the basis of the operating principle is presented, and the advantages and limitations of the different sensor types are pointed out. Finally, the paper summarizes the different contributions to the special issue.

Reliable streamflow and flood-affected area forecasting is vital for flood control and risk assessment in the Brahmaputra River basin. Based on the satellite remote sensing from four observation sites and ground observation at the Bahadurabad station, the Burg entropy spectral analysis (BESA), the configurational entropy spectral analysis (CESA), maximum likelihood (MLE), ordinary least squares (OLS), and the Yule&ndash, Walker (YW) method were developed for the spectral analysis and flood-season streamflow forecasting in the basin. The results indicated that the BESA model had a great advantage in the streamflow forecasting compared with the CESA and other traditional methods. Taking 20% as the allowable error, the forecast passing rate of the BESA model trained by the remote sensing data can reach 93% in flood seasons during 2003&ndash, 2017, which was significantly higher than that trained by observed streamflow series at the Bahadurabad station. Furthermore, the segmented flood-affected area function with the input of the streamflow forecasted by the BESA model was able to forecast the annual trend of the flood-affected area of rice and tea but needed further improvement in extreme rainfall years. This paper provides a better flood-season streamflow forecasting method for the Brahmaputra River basin, which has the potential to be coupled with hydrological process models to enhance the forecasting accuracy.

This work presents a non-invasive, reusable and submersible permittivity sensor that uses a microwave technique for the dielectric characterization of liquid materials. The proposed device consists of a compact split ring resonator excited by two integrated monopole antennas. The sensing principle is based on the notch introduced by the resonators in the transmission coefficient, which is affected due to the introduction of the sensor in a new liquid material. Then, a frequency shift of the notch and the Q-factor of the proposed sensor are related with the changes in the surrounding medium. By means of a particular experimental procedure, commercial liquids are employed to obtain the calibration curve. Thus, a mathematical equation is obtained to extract the dielectric permittivity of liquid materials with unknown dielectric properties. A good match between simulated and experimental results is obtained, as well as a high Q-factor, compact size, good sensitivity and high repeatability for use in sensing applications. Sensors like the one here presented could lead to promising solutions for characterizing materials, particularly in determining material properties and quality in the food industry, bio-sensing and other applications. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Instituto Tecnológico de Costa Rica: P15106, P13252, Universidad Tecnológica de Pereira