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Planar microwave sensors have become increasing developed in recent decades, especially in material characterization (solid/liquid) as they provide regions highly sensitive to the surrounding medium. However, when it comes to deciphering the content of practical biological analytes or chemical components inside a host medium, even higher sensitivities are required due to their minute concentrations. This review article presents a comprehensive outlook on various methodologies to enhance sensitivity (e.g., coupling resonators, channel embedding, analyte immobilization, resonator pattern recognition, use of phase variation, using coupled line section, and intermodulation products), resolution (active sensors, differential measurements), and robustness (using machine learning) of arbitrary sensors of interest. Some of the most practical approaches are presented with prototype examples, and the main applications of incorporating such procedures are reported. Sensors with which the proposed techniques are implemented exhibit higher performance for high-end and real-life use.

Electronic sensor foils only 2 μm thick are extremely light, 27-fold lighter than office paper, durable and flexible and conform to curvilinear surfaces for many innovative applications. Feather-light unbreakable plastic electronics Flexible electronics is emerging as a mainstream technology for smart, mobile, wearable devices and also for biomedical applications. Kaltenbrunner et al . break new ground by fabricating light-as-a-feather virtually imperceptible and unbreakable electronic foils that can conform to any desired shape. The foils consist of organic transistors with an ultra-dense oxide gate dielectric, itself only a few nanometres thick, deposited on ultra-lightweight plastic films, for an overall thickness of just two micrometres. They can withstand repeated severe bending and stretching, can crumple like paper, and work at elevated temperatures and in wet environments. The authors demonstrate that the flexible electronic foil can act as a tactile sensor on a model of the upper human jaw, illustrating the potential for this technology in health care and monitoring. Electronic devices have advanced from their heavy, bulky origins to become smart, mobile appliances. Nevertheless, they remain rigid, which precludes their intimate integration into everyday life. Flexible, textile and stretchable electronics are emerging research areas and may yield mainstream technologies 1 , 2 , 3 . Rollable and unbreakable backplanes with amorphous silicon field-effect transistors on steel substrates only 3 μm thick have been demonstrated 4 . On polymer substrates, bending radii of 0.1 mm have been achieved in flexible electronic devices 5 , 6 , 7 . Concurrently, the need for compliant electronics that can not only be flexed but also conform to three-dimensional shapes has emerged 3 . Approaches include the transfer of ultrathin polyimide layers encapsulating silicon CMOS circuits onto pre-stretched elastomers 8 , the use of conductive elastomers integrated with organic field-effect transistors (OFETs) on polyimide islands 9 , and fabrication of OFETs and gold interconnects on elastic substrates 10 to realize pressure, temperature and optical sensors 11 , 12 , 13 , 14 . Here we present a platform that makes electronics both virtually unbreakable 4 and imperceptible. Fabricated directly on ultrathin (1 μm) polymer foils, our electronic circuits are light (3 g m −2 ) and ultraflexible and conform to their ambient, dynamic environment. Organic transistors with an ultra-dense oxide gate dielectric a few nanometres thick formed at room temperature enable sophisticated large-area electronic foils with unprecedented mechanical and environmental stability: they withstand repeated bending to radii of 5 μm and less, can be crumpled like paper, accommodate stretching up to 230% on prestrained elastomers, and can be operated at high temperatures and in aqueous environments. Because manufacturing costs of organic electronics are potentially low, imperceptible electronic foils may be as common in the future as plastic wrap is today. Applications include matrix-addressed tactile sensor foils for health care and monitoring, thin-film heaters, temperature and infrared sensors, displays 15 , and organic solar cells 16 .

Intracranial pressure (ICP) refers to the pressure inside the skull. It is influenced by the complex interactions between the volume of brain tissue, cerebrospinal fluid (CSF), and blood. Maintaining a normal ICP is crucial for normal brain function, as elevated ICP can restrict blood flow to the brain, potentially resulting in severe health issues. Because of this, there is significant interest in non-invasive methods for monitoring ICP. In this paper, a Machine Learning (ML) driven, non-invasive, and quantitative microwave method and setup are proposed for ICP monitoring in human subjects. The proposed method is independent of the type of microwave sensors and is carefully devised for accurate measurements based on two-level feature extraction, including advanced signal attributes. Six thin, small, lightweight microwave sensors are evaluated with different placement strategies for accurate ICP monitoring. The proposed method was tested on a realistic human phantom model developed exclusively for this study. The phantom model corresponds to the dielectric properties and hydrodynamics of a human head. A unique data set creation module and Ordered Selection Scheme (OSS) are also proposed to ensure real-time operation with a lightweight ML algorithm. In addition, the quantitative method is devised using weighted regression on signal attributes selected from OSS. It is deduced from numerous trials that the proposed microwave system can even detect minute changes in ICP, and its response is analogous to pressure values measured by invasive sensors used as a ground-truth device. The proposed microwave-based setup is potentially suitable for wearable applications, enabling safe and prolonged usage.

In this paper, a complementary split-ring resonator (CSRR)-based patch antenna is proposed as a microwave sensor to measure the salt concentration of NaCl solution. The microwave sensor consists of an RF-4 substrate, where a small copper disc is attached on the top as the radiator, a larger copper disc integrated with two CSRRs is attached on the bottom side as the finite ground plane, and a coaxial feeding port is introduced at the ground plane center. During salt concentration sensing, only the top disc is immersed into NaCl solution. The results indicate that the proposed microwave sensor can measure salt concentrations ranging from 5‰ to 35‰ with a maximum sensitivity of 0.367 (kHz/(mg/L)). The proposed microwave sensor is low-cost, low-profile, electrically small, lightweight, and easy to fabricate, and it also can be applied to other solutions’ concentration sensing.

Industrial microwave-heating systems are pivotal in various sectors, including food processing and materials manufacturing, where precise temperature control and safety are critical. Conventional systems often struggle with uneven heat distribution and high fire risks due to the intrinsic properties of microwave heating. In this work, a fiber-optic-sensor-assisted monitoring system is presented to tackle the pressing challenges associated with uneven heating and fire hazards in industrial microwave systems. The core innovation lies in the development of a sophisticated fiber-optic 2D temperature distribution sensor and a dedicated fire detector, both designed to significantly mitigate risks and optimize the heating process. Experimental results set the stage for future innovations that could transform the landscape of industrial heating technologies toward better process quality.

A 2 μm wavelength band spot size converter (SSC) based on a trident structure is proposed, which is coupled to a lensed fiber with a mode field diameter of 5 μm. The cross-section of the first segment of the tapered waveguide structure in the trident structure is designed as a right-angled trapezoidal shape, which can further improve the performance of the SSC. The coupling loss of the SSC is less than 0.9 dB in the wavelength range of 1.95~2.05 μm simulated by FDTD. According to the experimental results, the lowest coupling loss of the SSC is 1.425 dB/facet at 2 μm, which is close to the simulation result. The device is compatible with the CMOS process and can provide a good reference for the development of 2 μm wavelength band integrated photonics.

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.

This study aims to present a low-cost, non-destructive microwave sensor implementation to monitor the real-time moisture content of rubber wood in industrial dehydration processes. The proposed sensor is based on the free-space measurement technique with magnitudes S11 and S21 only. The novelties of this study consist of the natural frequency determination of rubber wood and the design of a sensor system using devices available on the market with reasonable cost performance. The natural frequency was determined using a simulation and was equal to 1.25 GHz. It specified the sensor system design and device selection. The designed system was initially verified by measuring the moisture content of rubber wood in the laboratory. The measured S11 and S21 voltages correlating with moisture content percentages were obtained and programmed. The system was then installed to monitor the moisture content of rubber wood in the dehydration process. The measured results deviated from those obtained from a standard method in the range of 7.67–15.38%. The error compensation was analyzed to improve the measured results that provided the deviated moisture content in the range of 3.58–5.21%. It can be inferred that the proposed sensor system has the capability to be implemented in industrial dehydration processes.

The prevalence of chronic diseases and the rapid rise in the aging population are some of the major challenges in our society. The utilization of the latest and unique technologies to provide fast, accurate, and economical ways to collect and process data is inevitable. Industry 4.0 (I4.0) is a trend toward automation and data exchange. The utilization of the same concept of I4.0 in healthcare is termed Healthcare 4.0 (H4.0). Digital Twin (DT) technology is an exciting and open research field in healthcare. DT can provide better healthcare in terms of improved patient monitoring, better disease diagnosis, the detection of falls in stroke patients, and the analysis of abnormalities in breathing patterns, and it is suitable for pre- and post-surgery routines to reduce surgery complications and improve recovery. Accurate data collection is not only important in medical diagnoses and procedures but also in the creation of healthcare DT models. Health-related data acquisition by unobtrusive microwave sensing is considered a cornerstone of health informatics. This paper presents the 3D modeling and analysis of unobtrusive microwave sensors in a digital care-home model. The sensor is studied for its performance and data-collection capability with regards to patients in care-home environments.