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A microwave sensor working at around 2.4 GHz Wi-Fi frequency is proposed for rapid detection of arsenite/arsenate ions in water. The sensor consists of a planar folded complementary circular ring resonator (FCRR) etched on the top of the single sided copper clad substrate material, with a semi-cylindrical groove in the centre of the FCRR. The liquid material under test (MUT), filled within a cylindrical tube is placed in the groove. The key concept is the interaction of the EM wave with the material of different conductivity (As concentration) which results in change in reflection coefficient at a particular frequency. The dielectric constant varies negligibly for different concentrations of arsenic in the water hence, the change in the value of the reflection coefficient at a particular frequency is used to determine the arsenic content in the water sample. A reference set is generated by recording the variation of reflection coefficient indicating different arsenic concentrations. The sensor dimension is 40 mm X 40 mm and, the MUT is filled in a cylindrical tube with volume of approximately 4.83mm3 which is placed within the groove. The sensor possesses a sensitivity of 3.9 ~ 4dB/0.05 ppm change in concentration. [ABSTRACT FROM AUTHOR]

Abstract The concept of permittivity properties of dialysate allows the use of electromagnetic sensing techniques in hemodialysis treatment. In this study, we have introduced a method for assessing the adequacy of dialysis, which is based on the dialysate approach. The dialysate-based method offers several advantages, including preventing blood contamination, the absence of the need for the patient’s blood, and convenient application within laboratory settings. The dielectric properties of the dialysis fluid were analyzed using the open-ended coaxial probe technique to investigate the impact of various urea levels. The findings revealed a direct correlation between fluctuations in complex permittivity measurement and urea concentration levels. The measured results can be used to design invasive and non-invasive microwave sensors. However, further practical trials on dialysis fluid are needed.

In this paper, a novel realization of an ink-on-glass microwave sensor for biomedical applications is proposed. The Aerosol Jet Printing (AJP) technology is leveraged to implement a compact single-layer coplanar waveguide sensor featuring arc-shaped interdigital fingers that can accommodate a droplet of the Material-Under-Test (MUT). Such geometry provides a high sensitivity to even a very small deviation of MUT's electrical properties when placed as a superstrate. An application towards the detection of trace amounts of glucose in saliva, which is a biomarker for diabetes, is showcased. The design and fabrication process of an exemplary sensor is discussed in detail. A circular geometry feature is introduced that helps a droplet to lie over the sensitive region due to wettability difference of glass substrate and silver ink. Sensor operating in K-band is developed providing a tradeoff between circuit size and droplet volume. The study is conducted for an artificial saliva requiring roughly a 0.5 µL droplet where changes in mixture content are proportional to relative changes of sensor's transmission coefficient in a broad frequency range for occupied vs. empty states. The obtained results show that 10 mg of glucose per 100 ml of saliva can be easily distinguished in a frequency range of 20–30 GHz, whereas a monotonical change is visible for frequencies 20–26 GHz, which indicates the applicability of this sensor towards the detection of saliva-glucose levels and potential application in the detection of small amounts of other substances in liquids. [ABSTRACT FROM AUTHOR]

This paper comprehensively explores the development of a standalone and compact microwave sensing system tailored for automated radio frequency (RF) scattered parameter acquisitions. Coupled with an emitting RF device (antenna, resonator, open waveguide), the system could be used for non-invasive monitoring of external matter or latent environmental variables. Central to this design is the integration of a NanoVNA and a Raspberry Pi Zero W platform, allowing easy recording of S-parameters (scattering parameters) in the range of the 50 kHz– 4.4 GHz frequency band. Noteworthy features include dual recording modes, manual for on-demand acquisitions and automatic for scheduled data collection, powered seamlessly by a single battery source. Thanks to the flexibility of the system's architecture, which embeds a Linux operating system, we can easily embed machine learning (ML) algorithms and predictive models for information detection. As a case study, the potential application of the integrated sensor system with an RF patch antenna is explored in the context of greenwood hydration detection within the field of smart agriculture. This innovative system enables non-invasive monitoring of wood hydration levels by analyzing scattering parameters (S-parameters). These S-parameters are then processed using ML techniques to automate the monitoring process, enabling real-time and predictive analysis of moisture levels. [ABSTRACT FROM AUTHOR]

In the present work, a microwave sensor is proposed for detection of conductivity of the material. The sensor consists of a planar complementary circular ring structure etched on the top of the single sided copper clad substrate material and a shallow groove machined at the bottom surface coinciding with the ring structure. The conducting material under test (MUT), curved in the form of a split ring is placed in the groove. The proposed microwave sensor is particularly designed to work at 5.2 GHz Wi-Fi frequency. The key concept is the interaction of the EM wave with the material of different conductivity which results in change in reflection coefficient owing to different depth of penetration at a particular frequency. A reference set is generated by recording the variation in reflection coefficient for different materials, which is the main parameter in distinguishing between materials of different conductivities. The sensor dimension is 4 cm X 4 cm (0.083277 λg), λg being the guide wavelength, the MUT is a wire of length 4 cm with thickness ≤ 1 mm placed in form of circular split ring within the groove. The sensor corresponds to sensitivity of 3.6 dB/unit change in electrical conductivity. The proposed sensor facilitates rapid and convenient detection of the conductivity of the material. [ABSTRACT FROM AUTHOR]

This research focuses on investigating glucose meters utilizing metamaterial microwave sensors. The metamaterial microwave sensor is designed with a strip line loaded with a complementary split ring. The sensor is designed to conduct Ansys high‐frequency structure simulator and uses conductor material coated on a hydrocarbon ceramic laminate (Roger RO4232) substrate, with a sweep frequency range of 1–6 GHz. The signal of the metamaterial microwave sensor depends on the change in glucose permittivity and conductivity when the glucose concentration changes. The research involves designing a simulation model to explore the impact of complementary split ring size on the sensor's response to changes in glucose permittivity. Additionally, experiments are conducted using the proposed sensor to measure glucose concentration in solution, aiming to analyze trends in sensor response to varying concentrations of glucose and evaluate its sensitivity to changes in glucose concentration. The experimental results indicate that the metamaterial microwave sensor is able to respond to variations in glucose level, a sensitivity of the proposed sensor is 0.0345 dB (mg dL−1)−1 in range of 0–110 mg dL−1 with R2 0.9628. [ABSTRACT FROM AUTHOR]

The development of chemical sensor devices operating in non-contact mode is of primary interest due to the demand from various industries for a fast, simple and inexpensive determination of chemical composition in different media in a non-invasive way. One of the promising directions for the development of analytical devices with such characteristics is the use of high-frequency electrical signals. The paper discusses the evolution of high-frequency contactless conductometry method, likewise other methods and devices operating on similar physical principles (dielectric spectroscopy, microwave sensors, C4D detectors). [ABSTRACT FROM AUTHOR]

This paper investigates the performance of coplanar waveguide (CPW) structures loaded with symmetric circular and polygonal split-ring resonators (SRRs) for microwave and RF applications, leveraging their unique electromagnetic properties. These properties make them suitable for metamaterials, sensors, filters, resonators, antennas, and communication systems. The objectives of this study are to analyze the impact of different SRR shapes on the transmission characteristics of CPWs and to explore their potential for realizing compact and efficient microwave components. The CPW-SRR structures are fabricated on a dielectric substrate, and their transmission properties and spectrogram are experimentally characterized in the frequency range of 4 GHz to 10 GHz with the rotation angles of the SRR gap. The simulation results demonstrate that the resonant frequencies and magnitude of the transmission coefficient of the CPW-SRR structures are influenced by the geometry of the SRR shapes and the rotation angles of the SRR gap, with certain shapes exhibiting enhanced performance characteristics compared to others. Moreover, the symmetric circular and polygonal SRRs offer design flexibility and enable the realization of miniaturized microwave components with improved performance metrics. Overall, this study provides valuable insights into the design and optimization of CPW-based microwave circuits utilizing symmetric SRR shapes, paving the way for advancements in the miniaturization and integration of RF systems. [ABSTRACT FROM AUTHOR]

Metallic nanoscale particles attract a growing interest in several fields, thanks to their unique bonding characteristics; applications are appearing in the literature in the fields of, for example, sensor coatings and biochemical compound detection. However, the controlled fabrication of such nanopowders is often cumbersome, especially because their characterization is normally slow, involving procedures such as electron microscopy. On the other hand, microwave sensors based on near-field effects on materials are being developed with high sensitivity and show promising characteristics. In this paper, the authors show how a microwave sensor based on a Square Spiral Resonator can be used to characterize paraffin dispersions of nanoparticles conveniently and cost-effectively. [ABSTRACT FROM AUTHOR]

A novel wireless microstrip-based RF sensor designed for detecting changes in the ionic content of water and the addition of solid contaminant objects is proposed and demonstrated for the purpose of water conservation and green cleaning. The sensor can be installed on the exterior wall of dielectric containers and customized according to the material of the container (such as porcelain) to enable wireless sensing inside the container. Its operation within the lower microwave frequency range (670–730 MHz) serves to minimize signal attenuation in water and streamline circuitry design. The most significant feature of this sensor is its unique design, rendering it impervious to its surrounding environment. This not only shields it from environmental noise but also maximizes its sensitivity by efficiently utilizing incoming power for sensing purposes. The sensor exhibits remarkable sensitivity, capable of detecting solute concentrations as low as 3.125 $ \times$ 10-3 M in water inside the container. It can also detect the insertion of foreign solid objects into the container from the exterior wirelessly and distinguish them from liquids being added. As a proof-of-concept demonstration, the sensor in this study was built for a porcelain wall of 10-12 mm thickness. The sensor's small size and the materials used for its fabrication make it an ideal choice for various smart bathroom applications, where accurate and reliable water use monitoring is essential for efficient water conservation and green cleaning. The sensor's ability to distinguish between the added solid objects and liquid electrolytes in the container provides the necessary sensing data for running water-saving and efficient washing mechanisms in bathrooms.

Non-melanoma skin cancer (NMSC) is among the most prevalent forms of cancer originating in the top layer of the skin, with basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) being its primary categories. While both types are highly treatable, the success of treatment hinges on early diagnosis. Early-stage NMSC detection can be achieved through clinical examination, typically involving visual inspection. An alternative, albeit invasive, method is a skin biopsy. Microwave imaging has gained prominence for non-invasive early detection of various cancers, leveraging distinct dielectric properties of healthy and malignant tissues to discriminate tumors and categorize them as benign or malignant. Recent studies demonstrate the potential of terahertz (THz) spectroscopy for detecting biomarkers by aligning electromagnetic wave frequencies in the low THz range (0.1 to 10 THz) with resonant frequencies of biomolecules, such as proteins. This study proposes an innovative microscale biosensor designed to operate in the THz range for the high-sensitivity and efficient diagnosis of non-melanoma skin cancer. By incorporating meticulously designed metamaterial layers, the sensor's absorption properties can be controlled, a critical aspect for discriminating between normal and NMSC-affected skin. In particular, the interaction between skin and THz waves, influenced by dielectric properties and unique vibrational resonances of molecules within tissue, is crucial for wave propagation and scattering. Extensive numerical studies showcased the suitability of the proposed biosensor for NMSC diagnosis, illustrated through specific case studies. These findings hold the potential to pave the way for further development of non-invasive microwave-imaging-based techniques for detecting NMSC and other types of skin cancer.

A dual-band fractal metamaterial absorber is proposed as a promising alternative for sensing applications. A preliminary prototype, useful to validate the proposed configuration, is designed to operate in the Ultra-High Frequency (UHF) range. The inherent miniaturization skills of fractal geometries are effectively exploited to design and fabricate multiband/broadband absorbers with a small lattice size ( $\le \lambda _{0}$ /2 at the smaller operating frequency $f_{0}$ ) and a very thin profile ( $\le \lambda _{0}$ /100). Two pairs of Minkowski fractal patches, alternately arranged in four different quadrants and properly sized to achieve two distinct absorption peaks, are assumed for the absorber-sensor configuration. In the framework of dielectric material diagnostics, the MA structure shows an average relative sensitivity of 4.6% and a quality factor equal to 36. Very high absorption peaks (>99%) and quite good stable absorption rates versus incidence angle variations ( $\ge 90$ % for TE polarization and $\ge 97$ % for TM polarization at both frequencies) are demonstrated both numerically and through experimental validations, thus proving the applicability of the proposed absorber sensor in low-frequency sensing applications.

Cytotoxicity assays are crucial for assessing the efficacy of drugs in killing cancer cells and determining their potential therapeutic value. Measurement of the effect of drug concentration, which is an influence factor on cytotoxicity, is of great importance. This paper proposes a cytotoxicity assay using microwave sensors in an end-point approach based on the detection of the number of live cells for the first time. In contrast to optical methods like fluorescent labeling, this research uses a resonator-type microwave biosensor to evaluate the effects of drug concentrations on cytotoxicity by monitoring electrical parameter changes due to varying cell densities. Initially, the feasibility of treating cells with ultrapure water for cell counting by a microwave biosensor is confirmed. Subsequently, inhibition curves generated by both the CCK-8 method and the new microwave biosensor for various drug concentrations were compared and found to be congruent. This agreement supports the potential of microwave-based methods to quantify cell growth inhibition by drug concentrations.

This study introduces an innovative high-Quality factor (Q-factor) double negative (DNG) metamaterial sensor designed for textile fabric and fabric moisture sensing applications in the dynamic realm of textile innovation. The sensor is specifically designed to detect the dielectric properties and moisture content of different textile fabrics. The high Q-factor of this metamaterial structure ensures heightened sensitivity and accuracy in fabric sensing, facilitating precise detection of even subtle changes in fabric properties. By measuring frequency shifting and analyzing S21 values, the sensor provides crucial information about the fabric's dielectric characteristics. Sensing experiments conducted on various fabrics, including cotton, denim, corduroy, organza, and polyester unveil distinctive patterns of frequency shifting and Q-factors, establishing a nuanced link between fabric structure and sensor performance. The proposed sensor is capable of detecting fabrics with a very low dielectric constant variation of 0.05. In the experiment, the high-dielectric fabric denim (1.7) exhibited frequency shifting and Q-factor of 6970 and 834.87, respectively. Moreover, it is worth noting that the low-dielectric fabric organza (1.03) exhibits frequency shifting and Q factors of 2190 and 1367.03, respectively. Experimental results affirm the prominent efficacy of the proposed sensor in fabric and fabric moisture sensing. Its high Q-factor empowers the sensor to accurately detect and monitor fabric properties, rendering it highly suitable for critical tasks such as quality control, energy efficiency optimization, and process enhancement within the textile industry. The proposed metamaterial sensor (MMS) can significantly contribute to the development of a smart textile sensing technology and pave the way for innovative applications in the textile industry. [ABSTRACT FROM AUTHOR]

This research introduces the conceptualization and examination of a microwave sensor incorporated with a microstrip band stop filter. The microwave sensor's design and assessment are based on the microstrip's parallel coupled lines, employing a band stop filter configuration at 2.45 GHz on an FR4 substrate. This study encompasses the evaluation of soil moisture spanning from 20 to 80%. The measurement procedure involved a network analyzer, specifically the KEYSIGHT model E5063A, operating within the frequency range of 100 kHz to 4.5 GHz. This investigation centers around scrutinizing the frequency response of the insertion loss (S21) across this spectrum. The outcomes of the experimentation unveiled notable disparities in frequency shifts. The resultant frequency values, labeled as (f0-f1), manifested at 0, 18, 60, 89, 145, and 200 MHz, sequentially. Remarkably, the correlation between the percentage representation of the frequency shift in the transmission coefficient and the frequency itself emerged distinctly, even as the range of tested samples was finetuned. [ABSTRACT FROM AUTHOR]

A novel electrophoretic technique to improve metasurface sensing capabilities of charged particles in solution is presented. The proposed technique may improve the ability of metasurfaces to sense charged particles in solution in a manner not possible using the current standard of particle deposition (which allows particles to sediment randomly on a metasurface under evaporation) by inducing an external, nonuniform electric field through the metasurface apertures. Such a technique may be useful in various sensing applications, such as in biological, polymer, or environmental sciences, where low concentration particles in solution are of interest. The electrophoretic technique was simulated and experimentally tested using latex nanoparticles in solution. The results suggest that, using this technique, one may theoretically increase the particle density within the metasurface regions of greatest sensitivity by nearly 1900% in comparison to random sedimentation due to evaporation. Such an increase in particle density within the regions of greatest sensitivity may facilitate more precise material property measurements and enhance identification and detection capabilities of metasurfaces to particles in solution which constitute only a few hundred parts per million by mass. It was experimentally determined that the electrophoretic technique enhanced metasurface sensing capabilities of 333 parts per million by mass latex nanoparticle solutions by nearly 1700%. [ABSTRACT FROM AUTHOR]

In this paper, a novel design of a near-field dipole antenna sensor array for breast tumor detection is presented. The proposed sensor consists of four electrically small dipole antennas fed by a single port. Due to the proven fact that breast tumors have higher dielectric properties than the surrounding normal tissues, the proposed sensor is utilized for detecting breast tumors by evaluating the variations of the sensor’s response of two cases, normal and abnormal, of the breast tissues. A simulation study is performed using both normal and abnormal numerical breast phantoms with different sizes of tumors inserted at different locations. Simulation results show the proposed sensor detected the inserted tumors at various locations inside the normal breast phantom due to an increased area of sensitivity of the sensor by using multiple sensors array. An experimental study is conducted on breast chicken meat that mimics a healthy breast and two cases of tumors including tumors made of oil and gelatin mixture and conductive spheres with different sizes inserted at different locations inside the chicken meat. Experimental results show that the proposed sensor has higher sensitivity for detecting different sizes of breast tumors placed at multiple locations.

The paper introduces the Oil-Slick Hub (OSH), a computational platform to facilitate the data visualization of a large database of petroleum signatures observed on the surface of the ocean with synthetic aperture radar (SAR) measurements. This Internet platform offers an information search and retrieval system of a database resulting from >20 years of scientific projects that interpreted ~15 thousand offshore mineral oil "slicks": natural oil "seeps" versus operational oil "spills". Such a Digital Mega-Collection Database consists of satellite images and oil-slick polygons identified in the Gulf of Mexico (GMex) and the Brazilian Continental Margin (BCM). A series of attributes describing the interpreted slicks are also included, along with technical reports and scientific papers. Two experiments illustrate the use of the OSH to facilitate the selection of data subsets from the mega collection (GMex variables and BCM samples), in which artificial intelligence techniques—machine learning (ML)—classify slicks into seeps or spills. The GMex variable dataset was analyzed with simple linear discriminant analyses (LDAs), and a three-fold accuracy performance pattern was observed: (i) the least accurate subset (~65%) solely used acquisition aspects (e.g., acquisition beam mode, date, and time, satellite name, etc.); (ii) the best results (>90%) were achieved with the inclusion of location attributes (i.e., latitude, longitude, and bathymetry); and (iii) moderate performances (~70%) were reached using only morphological information (e.g., area, perimeter, perimeter to area ratio, etc.). The BCM sample dataset was analyzed with six traditional ML methods, namely naive Bayes (NB), K-nearest neighbors (KNN), decision trees (DT), random forests (RF), support vector machines (SVM), and artificial neural networks (ANN), and the most effective algorithms per sample subsets were: (i) RF (86.8%) for Campos, Santos, and Ceará Basins; (ii) NB (87.2%) for Campos with Santos Basins; (iii) SVM (86.9%) for Campos with Ceará Basins; and (iv) SVM (87.8%) for only Campos Basin. The OSH can assist in different concerns (general public, social, economic, political, ecological, and scientific) related to petroleum exploration and production activities, serving as an important aid in discovering new offshore exploratory frontiers, avoiding legal penalties on oil-seep events, supporting oceanic monitoring systems, and providing valuable information to environmental studies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Applied pressure and fluid flow induce different modes of deformations on the membrane, which are electronically probed by an integrated microwave resonator. The flow changes the capacitance, and in turn resonance frequency, of the microwave resonator. By tracking the resonance frequency, liquid flow was probed with the device. In addition to responding to applied pressure by deflection, the membrane also exhibits periodic pulsation motion under fluid flow at a constant rate. The two separate mechanisms, deflection and pulsation, constitute sensing mechanisms for pressure and flow rate. Using the same device architecture, we also detected pressure-induced deformations by a gas to draw further insight into the sensing mechanism of the membrane. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Chipless radio-frequency identification (RFID) sensors are not yet widespread in practical applications because of their limited sensitivity and selectivity when compared to more mature sensing technologies. The search for a suitable material to perform the sensing function has often been focused on the most common materials used in electrochemical sensing approaches, but little work has been done to directly relate the performances of chipless or microwave sensors to the characteristics of the materials used to fabricate them. In this work we are simulating the impact of the substrate material on the performances of a chipless RFID sensor for humidity detection. The dielectric parameters of the substrate material turn out to be very important to maximize the sensor performances, in relation to the operative range of the sensor (based on the desired application) and to the effective dielectric properties of the sensitive material used, we verify the simulated results with measurements of real chipless humidity cells with Nafion 117 sensitive material. We show which types of substrate are preferable for low-humidity detection and which substrates' features are instead fundamental to operate in a wider humidity range. [ABSTRACT FROM AUTHOR]

A novel technique using a W-band metasurface for the purpose of transmissive fine powder layer sensing is presented. The proposed technique may allow for the detection, identification, and characterization of inhomogeneous ultrafine powder layers which are effectively hundreds of times thinner than the incident wavelengths used to sense them. Such a technique may be useful during personnel screening processes (i.e., at an airport) and in industrial manufacturing environments where early detection and quantization of harmful airborne particulates can be a matter of security or safety. The proposed sensing technique was experimentally and theoretically tested. The results suggest that, using this technique, one may identify, extract the effective complex dielectric properties, and measure the layer thicknesses of ultrafine powder layers present on a metasurface. Using this technique, it may be possible to identify and characterize diverse media in various physical, chemical, and biological metasurface sensing efforts at numerous bands of the electromagnetic spectrum. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article presents a novel concept for the implementation of electromagnetic encoders exhibiting very high data density per unit length (DPL), a figure of merit (FoM) of such systems. Encoding is based on a hybrid scheme that exploits both the frequency and time domains. The encoders consist of rows of inclusions (linear strips) of different sizes, periodically arranged to form a chain (with four columns). The bits corresponding to each row are read sequentially in a time-division multiplexing scheme, whereas the size of the inclusions provides frequency encoding. The main relevant aspect of the proposed system concerns the reader, based on a power splitter architecture with either two outputs (prototype A) or four outputs (prototype B). It is shown that the data capacity per row in one of the encoders read through prototype B is 8.78 bits, whereas the data density is as high as DPL = 29.26 bit/cm, an unprecedented value in this type of encoders. The proposed system can be used as a near-field synchronous chipless-radio frequency identification (RFID) system, or as a position and velocity sensor. In the latter case, the system is able to provide the absolute encoder position, provided the number of bits per row (or position) is enough to discern the different number of encoder positions (up to 440 different positions for prototype B, corresponding to the indicated number of bits). [ABSTRACT FROM AUTHOR]

A common-mode (CM) suppression-based passive microwave measurement system for microfluidic applications is proposed in this article. The proposed system contains three parts, including differential microwave microstrip sensor, phase shifter, and power divider. The differential structure of the proposed microstrip sensor is composed of two split-ring resonator (SRR)-based microstrip sensors and four 3-D metallic walls. Interdigital capacitances (IDCs) are inserted between two SRRs to enhance the density of electric field. Moreover, two 3-D metallic walls are erected on both sides of each IDC, which can increase the concentration of electric field further. Power divider, phase shifter, and differential structure constitute the measurement system. Assuming that a signal with frequency of ${f}_{{0}}$ is input into input port, and going through by power divider, the CM signals will be generated. Then, passing by phase shift, differential structure, and combiner to output port, theoretically, when the phase difference between two branches is 180° at ${f}_{{0}}$ , the corresponding magnitude of output signal will be zero at ${f}_{{0}}$. Therefore, the transmission coefficient will be infinitesimal at ${f}_{{0}}$ (CM signals are suppressed), and an ultrahigh ${Q}$ will be obtained. An equivalent circuit model is presented to reveal the operating principle of the sensor. The variations of relative frequency shift and normalized ${Q}$ are adopted to extract the complex permittivity of liquid sample. In the experiment, the sensitivity of detecting real permittivity is about 0.05%, and a high ${Q}$ of about 1432 is realized. All in all, the proposed microwave sensor has a huge superiority over some previously reported ones. [ABSTRACT FROM AUTHOR]

Human African Trypanosomiasis (HAT) is caused by the African trypanosome, a single-cell parasite that proliferates in the blood and cerebrospinal fluid of infected patients. Diagnostic measures for this pathogen are currently not sufficiently robust and reliable enough to permit effective disease control procedures. As a consequence, we suggested the development of a new sensor type, combining the selectivity of parasite-specific nucleic acid aptamers with the sensitivity of resonant electromagnetic devices to capture and detect the disease-causing organism. While we accomplished the detection of parasite cells in dehydrated specimens, here we summarize our recent progress toward electromagnetic sensors capable of uncovering parasites in liquid patient samples. We present a technique for the removal of blood cells from blood specimens and the deposition of trypanosome cells on glass microfiber membranes for dielectric spectrometry. Liquid suspensions of trypanosomes are characterized to determine the actual dielectric properties of single parasites and lastly, we present two sensor concepts optimized for the detection in liquids, along with a fabrication technique for the integration of microfluidic sample confinements. [ABSTRACT FROM AUTHOR]

A scheme for generating oscillations based on an exceptional point of degeneracy (EPD) is proposed in two-coupled resonators made of two coupled transmission lines terminated on balanced gain and loss, exhibiting a double pole. The EPD is a point in the parameter space of the system at which two or more eigenmodes coalesce in both their eigenvalues (here, resonance frequencies) and eigenvectors. We show that a finite-length single transmission line terminated with gain and loss possesses no degeneracy point, whereas second-order EPDs are enabled in two finite-length coupled transmission lines (CTLs) terminated with balanced gain and loss. We demonstrate the conditions for EPDs to exist for three different termination configurations with balanced gain and loss, and show the eigenfrequency bifurcation at the EPD following the fractional power expansion series related to the Puiseux series. We study the oscillatory regime of operation assuming the gain element is nonlinear, and the extreme sensitivity of the degenerate self-oscillation frequency to perturbations and how it compares with the sensitivity of the linear-gain case. Finally, we show that the sensitivity of the EPD-CTL resonator is much higher than the one of a single-TL resonator. The very sensitive EPD based oscillator can be used as sensors when very small variations in a system shall be detected.

The strong association between hearing loss and cognitive decline has developed into a major health challenge that calls for early detection, diagnosis and prevention. Hearing loss usually results in severe health implications that include loss of mobility, communication problems and cognitive decline. This study provides an overview of the effects of hearing loss on cognition and progressive neurological disorders with a discussion on the future scope of microwave portable technologies in care homes arrangement. Moreover, the efficacy of hearing aids in reversing cognitive decline and dementia has been investigated. The interconnection between hearing loss, cognitive load and neurodegeneration is also explored. Furthermore, this study looks into the prospects of using portable microwave sensors for the detection and monitoring of cognitive load. For early detection of dementia, this study proposes the integration of microwave sensors with hearing aid devices. Implications and design challenges of portable antenna systems for neurodegeneration detection have also been considered. Future improvement areas regarding robust analysis and diagnosis, system accuracy and security, user-centricity and device privacy for a broader clinical implementation are also discussed.

This research introduces the conceptualization and examination of a microwave sensor incorporated with a microstrip band stop filter. The microwave sensor’s design and assessment are based on the microstrip’s parallel coupled lines, employing a band stop filter configuration at 2.45 GHz on an FR4 substrate. This study encompasses the evaluation of soil moisture spanning from 20 to 80%. The measurement procedure involved a network analyzer, specifically the KEYSIGHT model E5063A, operating within the frequency range of 100 kHz to 4.5 GHz. This investigation centers around scrutinizing the frequency response of the insertion loss (S21) across this spectrum. The outcomes of the experimentation unveiled notable disparities in frequency shifts. The resultant frequency values, labeled as (f0-f1), manifested at 0, 18, 60, 89, 145, and 200 MHz, sequentially. Remarkably, the correlation between the percentage representation of the frequency shift in the transmission coefficient and the frequency itself emerged distinctly, even as the range of tested samples was finetuned.

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. [ABSTRACT FROM AUTHOR]

In this article, a dual-functional microwave system with a single input port that can simultaneously be used for antenna and sensor applications is presented. The dual-functional ability of the proposed system is achieved by integrating a two-port microwave sensor and a Wi-Fi antenna with a novel frequency-selective multipath filter (FSMF). The FSMF ensures efficient system operation by not affecting the operational bandwidth of the communicating antenna in the presence of different sensed materials under test (MUTs) on top of the sensor. The proposed microwave sensor also has a unique capability of measuring one more sensing parameter in addition to the often used reflection and transmission coefficients. The additional parameter is the frequency distance of two closely spaced resonance frequencies of the microwave sensor in the presence of an MUT. Compared to existing state-of-the-art techniques, the additional sensing parameter (as done in this work) can be used as an alternative to transmission coefficient for characterization of different MUTs or as an additional parameter giving more degree of freedom. The entire system is designed in a single substrate with a common input source. The performance of the dual-functional system was tested using different MUTs and showed a good agreement with the measurement results. [ABSTRACT FROM AUTHOR]

Design optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This article proposes a novel methodology for rapid redesign and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using preoptimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry parameters and CSRR optimization over broad ranges of operating frequencies. The tuning process is arranged to precisely allocate the operating frequency while maximizing the quality factor of the circuit. The procedure is generic and characterized by an extremely low computational cost of up to two electromagnetic (EM) analyses of the circuit at hand (not counting the inverse model setup). The presented technique is demonstrated using a circular CSRR coupled to a microstrip transmission line (MTL) and optimized to operate between 5 and 20 GHz. The design optimized for 15 GHz is fabricated and experimentally validated using a vector network analyzer. The sensor works in the transmission mode and senses the shift in resonance frequency determined by the properties of the material under test (MUT). Furthermore, an inverse regression model is developed that allows for directly finding the unknown permittivity of the MUT based on the measured resonant frequencies of the sensor. The obtained results corroborate the design utility of the proposed optimization method, as well as the practical usefulness of the specific CSRR structure developed with the aid thereof. [ABSTRACT FROM AUTHOR]

Automation is a key technology for a sustainable and secure meat sector in the future, both in terms of productivity and work environment. New robotic technologies, such as the so-called “meat factory cell,” (MFC) aim to contribute to this goal, but they require new “smart” tools that provide sensor feedback, which enable robots to perform complex tasks. This article presents one such tool: the smart knife, which gives real-time feedback on its contact status with meat, as well as cutting depth. The tool and the system are described, and its operation evidenced via electromagnetic (EM) simulation using the Ansys High-Frequency Structure Simulator. Furthermore, the performance of the knife is validated using pork loin meat: in the worst case, knife is shown to have an error of 1.78% for contact detection, and a mean error of 7.66 mm (±1.45 mm) for depth detection. This article also presents brief discussion regarding eventual use of the knife as part of the MFC control system, in addition to future work to be performed. [ABSTRACT FROM AUTHOR]

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 ($\lvert S_{31} \lvert $) or its isolation level ($\lvert S_{41} \lvert $) 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 $\lvert S_{21} \lvert $ level of a microstrip line when loaded with different MUTs. Validation of the method is presented through measurements for both solid and liquid MUTs. [ABSTRACT FROM AUTHOR]

Progressive techniques that enable reagent-free detection and analysis of low-concentration and low-volume chemical samples are of great interest for scientific and technological investigations in biochemical and physiological areas. Highly sensitive microwave-based sensors are promising approaches among such techniques. In this work, we present a novel microwave-based noncontact sensing method to determine the concentration of standard bovine serum albumin (BSA) solution. It is demonstrated that the modal suppression technique can excite a split-ring resonator by two independent microstrip lines with reversed phase, resulting in high quality factor and resolution. The quality factor exceeding $5.5\times 10^{5}$ with lossy-liquid loaded can be achieved at $\sim 4.3$ GHz. The obtained high resolution in frequency is $\sim 20$ kHz for the concentration of BSA from 0 to 1 mg/mL. The measured concentration level ranges from 1 to 200 mg/mL in 0.9% sodium chloride, which covers most commercial standard BSA solutions. An equivalent circuit model is built to study and explain its working principle. Using the fit premeasurement data of standard solutions, the concentration and permittivity of an unknown BSA solution can be estimated. [ABSTRACT FROM AUTHOR]

The identification of different plastic materials in pellet form using a microwave negative-order-resonance sensor along with the evaluation of classification algorithms from machine learning is presented in this paper. Operation of the sensor is within the unlicensed ISM 2.5 GHz band, and identification of the materials is based on the measured resonant parameters from the sensor. Several classifiers are used to process the resonant parameters having uncertainty factors involved in pellet measurements (air gaps, pellet positions, dimensions and shapes), and performance comparison between the algorithms is carried out in terms of accuracy in the classification. Moreover, the presented measurement method is proposed as a fast, non-destructive, and low-power consumption way to identify plastic raw materials using a low-profile circuit having a high potential of being used in industrial processes. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

This article is the first in the periodic Breakthroughs in Microwaves series. This series is intended to highlight recent accomplishments, especially to those new to the field, by researchers in microwave engineering that hold promise for long-term impact in the field. The articles are written after a conversation with the author so that background information can be provided to understand the breakthrough more fully. This first article looks at the pioneering work of Dr. Aydin Babakhani from UCLA in the USA. Dr. Babakhani's work is a novel application based on oscillator injection locking to synchronize, in the RF domain, the transmit frequency from individual sensors in a sensor swarm so that the individual sensors' signals constructively add at the receiver to increase the overall swarm signal level. The article reviews the loss issues in the system, both path loss for the transmit-receive path as well as for wireless power transfer. The article also provides background on RF integrated circuit transceiver circuits so that the reader can more fully understand the novelty of the RF phase synchronization technique. Finally, the article concludes with a short conversation with Dr. Babakhani that provides further insight into this pioneering technique.

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.

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.

A novel W-band sensor for complex permittivity measurements of rod shaped samples based on reflectometer method is described. Characterization of dielectric materials around 100 GHz is quite a challenge. The main limitation is the requirements for the accuracy of the dimensions of the test sample and ensuring good contact with conductive surfaces. From this point of view, it seems interesting to use a cylindrical waveguide with the TE01 mode. The four linearly-polarized H10 fields of rectangular waveguides with equal amplitude and phase circumnavigate the cylindrical waveguide to jointly excite its TEnm circular modes with four-fold symmetry. This precludes the excitation of lower-order modes of the metallic cylindrical waveguide. TE01 mode is unique in that its field leads to zero on the surface of the walls of a metallic cylindrical waveguide. The main field interaction takes place on the sample surface. The calibration method uses calibration curves obtained by simulation for known values of complex permittivity of the samples. This eliminates the requirement for a precision calibration standards, which is the problematic to realize at millimeter wavelengths. Moreover, the complex field structure in the sensor makes it impossible to apply a standard calibration method. Simulation and measurements using these method have been performed in W-band (70–114 GHz). Measurement results demonstrate the robustness of this new sensor for characterizing rod shaped dielectric samples.

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. [ABSTRACT FROM AUTHOR]