Performance Characteristics Of Sensors Research Articles

Ultra-sensitivity of surface plasmon resonance sensor using halide perovskite FASnI3 and 2D materials on Cu thin films

This paper studies a novel surface plasmon resonance (SPR) biosensor using a BK7 glass prism, a copper (Cu) metal plasmonic layer, which combine a halide perovskite (FASnI3) with two-dimensional (2D) materials such as phosphorus black, graphene and TMDC (MoS2, MoSe2, WS2, WSe2) for the detection of breast cancer cells. We have optimized the thickness of each layer in order to obtain maximum sensitivity. A numerical study mainly uses the transfer matrix principle, while the attenuation total reflection method involves examining the reflection properties. The evaluation of SPR biosensor configurations serves to obtain optimal performance. The simulation results indicate that the integration of halide perovskite (FASnI3) and 2D materials into the BK7/Cu/medium sensing structure significantly improves the sensitivity and figure of merit (ZT). The outstanding results in terms of sensor performance characteristics are observed in the BK7/Cu (48 nm)/FASnI3 (5 nm)/BP (0.53 nm) configuration. The figure of merit and sensitivity estimated at 123.11 RIU−1 and 459.28°/RIU, with a notable improvement of 338.45 %.

Principles and Applications of ZnO Nanomaterials in Optical Biosensors and ZnO Nanomaterial-Enhanced Biodetection.

Significant research accomplishments have been made so far for the development and application of ZnO nanomaterials in enhanced optical biodetection. The unparalleled optical properties of ZnO nanomaterials and their reduced dimensionality have been successfully exploited to push the limits of conventional optical biosensors and optical biodetection platforms for a wide range of bioanalytes. ZnO nanomaterial-enabled advancements in optical biosensors have been demonstrated to improve key sensor performance characteristics such as the limit of detection and dynamic range. In addition, all nanomaterial forms of ZnO, ranging from 0-dimensional (0D) and 1D to 2D nanostructures, have been proven to be useful, ensuring their versatile fabrication into functional biosensors. The employment of ZnO as an essential biosensing element has been assessed not only for ensembles but also for individual nanomaterials, which is advantageous for the realization of high miniaturization and minimal invasiveness in biosensors and biodevices. Moreover, the nanomaterials' incorporations into biosensors have been shown to be useful and functional for a variety of optical detection modes, such as absorption, colorimetry, fluorescence, near-band-edge emission, deep-level emission, chemiluminescence, surface evanescent wave, whispering gallery mode, lossy-mode resonance, surface plasmon resonance, and surface-enhanced Raman scattering. The detection capabilities of these ZnO nanomaterial-based optical biosensors demonstrated so far are highly encouraging and, in some cases, permit quantitative analyses of ultra-trace level bioanalytes that cannot be measured by other means. Hence, steady research endeavors are expected in this burgeoning field, whose scientific and technological impacts will grow immensely in the future. This review provides a timely and much needed review of the research efforts made in the field of ZnO nanomaterial-based optical biosensors in a comprehensive and systematic manner. The topical discussions in this review are organized by the different modes of optical detection listed above and further grouped by the dimensionality of the ZnO nanostructures used in biosensors. Following an overview of a given optical detection mode, the unique properties of ZnO nanomaterials critical to enhanced biodetection are presented in detail. Subsequently, specific biosensing applications of ZnO nanomaterials are discussed for ~40 different bioanalytes, and the important roles that the ZnO nanomaterials play in bioanalyte detection are also identified.

UWB distance estimation errors in (non-)line of sight situations within the context of 3D analysis of human movement

Abstract Integrated Ultrawideband (UWB) and Magnetic Inertial Measurement Unit (MIMU) sensors are becoming popular for indoor localization applications, as a higher accuracy can be achieved than with just MIMU sensors. These integrated sensors could extend stability and accuracy in the field of 3D analysis of human movement (3D AHM) if they can deliver position estimates with an accuracy close to 1 cm. Achieving this high accuracy of 1 cm remains challenging, with most studies reporting position estimation errors around 5 cm, often due to Non-Line of Sight (NLOS) conditions and systematic UWB sensor distance estimation errors. Studying the distance error characteristic of UWB in situations of 3D AHM is essential to deal with these errors. While research on UWB distance errors in Line of Sight (LOS) and NLOS situations exists, few studies focus on the NLOS errors caused by the human body and were not in the relevant scenarios of 3D AHM. Therefore, this article examines UWB sensor performance and distance error characteristics in LOS and NLOS situations typical for the 3D AHM. Both the LOS and NLOS situations were studied in the typical 3D AHM distance range of 0.2 m to 2 m. The NLOS situations were studied first with a human subject as NLOS causing object and then with simulated human body segments (PVC pipes filled with water) of varying diameters. In LOS situations, consistent systematic bias errors were observed, along with incidental errors at specific positions in the room. In NLOS scenarios caused by the human and simulated body segments, a consistent and reproducible overestimation of distances was found. The reproducibility of these errors based on relative node and object positions suggests that systematic mitigation methods could significantly reduce errors, enabling more accurate and reproducible 3D human movement analysis.

What Exactly Can Bionic Strategies Achieve for Flexible Sensors?

Flexible sensors have attracted great attention in the field of wearable electronic devices due to their deformability, lightness, and versatility. However, property improvement remains a key challenge. Fortunately, natural organisms exhibit many unique response mechanisms to various stimuli, and the corresponding structures and compositions provide advanced design ideas for the development of flexible sensors. Therefore, this Review highlights recent advances in sensing performance and functional characteristics of flexible sensors from the perspective of bionics for the first time. First, the "twins" of bionics and flexible sensors are introduced. Second, the enhancements in electrical and mechanical performance through bionic strategies are summarized according to the prototypes of humans, plants, and animals. Third, the functional characteristics of bionic strategies for flexible sensors are discussed in detail, including self-healing, color-changing, tangential force, strain redistribution, and interfacial resistance. Finally, we summarize the challenges and development trends of bioinspired flexible sensors. This Review aims to deepen the understanding of bionic strategies and provide innovative ideas and references for the design and manufacture of next-generation flexible sensors.

Fluorinated polyaniline-based sensors with enhanced NH3 sensitivity

Poly(2-fluoroaniline) films were prepared by electrochemical oxidation of 2-fluoroaniline in perchloric acid solutions. These films had a characteristic globular structure, but low thickness and conductivity. For these reasons, alternative polymer films were prepared from electrolytic solutions with different aniline:2-fluoroaniline ratios. The physicochemical properties of these polymer films strongly evolved with the ratio since they were thicker and more conductive when the proportion of aniline increased while their morphology also varied significantly. The electrodeposited polymer films were then used as sensitive layers of gas sensors for ammonia detection. The addition of 2-fluoroaniline improved the performance characteristics of gas sensors for the detection of ammonia at room temperature and the poly(aniline/2-fluoroaniline)-based sensors responded to ammonia gas with good repeatability, good sensitivity (0.44 %/ppb), a very low detection limit (4 ppb), and a low dependence on humidity variations.

Numerical investigation into impact of halide perovskite material on the optical performance of prism-loaded hybrid surface plasmon resonance biosensor: A strategy to increase sensitivity

The technology of surface plasmon resonance (SPR) is widely recognized and valued for its ability to rapidly and sensitively investigate biomolecular interactivities in real-time. Herein, we numerically investigate the collective influence of metal/ transition metal dichalcogenide (TMDC)/halide perovskite (HP)/2D carbon (C) and phosphorus (P) allotropes on the functionality of an SPR biosensor deploying Kretschmann configuration. The incident light wavelength is held constant at 633 nm, and radiative properties of the hybrid structure are determined using the attenuated total reflection and transfer matrix techniques. Crucial performance metrics such as quality factor (QF), figure of merit (FoM), sensitivity, and detection accuracy are calculated. The comparison is conducted and evaluated against the current literature using performance outcomes in terms of several prisms such as BK7, BAK1, BAF10, SF5, SF10, SF11, 2S2G, CaF2, and CsF, several TMDCs such as WS2, MoS2, WSe2, MoSe2, and PtSe2, several HPs such as CsPbI3, KSnI3, CsSnI3, and FASnI3, and 2D C/P allotropes such as Graphene, MXene, Black phosphorene (BP), and Blue phosphorene (BlueP) in order to search optimum parameters, and then we implement the best one in each layer of this biosensor design. It is noticed that the SPR heterostructure based on BAK1 prism, plasmonic metal Ag, tungsten disulfide (WS2) TMDC, formamidinium tin iodide (FASnI3) HP and 2D BP exhibits outstanding performance with regard to sensor performance characteristics. The observed FoM and sensitivity are 48.2/RIU and 402°/RIU, respectively. The investigation of the electric field distribution within this biosensor along the normal to the interface is also conducted using the finite difference time domain (FDTD) approach to demonstrate the unique contribution of FASnI3. The findings presented in this study are anticipated to play a key role in the improvement of plasmonic resonance-based biosensing domains like DNA hybridization or formalin detection by employing halide perovskite as an additional layer in SPR biosensors.

Design and application of supramolecular based solid-contact ion-selective electrode for selective green determination of tenofovir disoproxil fumarate

This work describes the fabrication of solid-contact potentiometric sensor to determine the antiviral drug; tenofovir disoproxil fumarate. Screen-printed carbon electrodes have been selected as being a disposable substrate material. Ion sensing membrane is based on Polyvinyl chloride (PVC) polymer that was impregnated with calix [6] arene as being an ionophore for facilitating transferring the drug of interest from the sample phase into the membrane phase through decreasing Gibbs free energy of transfer. We applied a graphene nanocomposite interlayer between the carbon substrate and the polymeric membrane for overcoming potential drift, which is commonly encountered in solid-contact potentiometric sensors. As a result, the graphene nanocomposite layer enhanced the sensor performance and stabilized the potential signal as compared to the control sensor. The sensor performance characteristics were studied according to International Union of Pure and Applied Chemistry (IUPAC) recommendations, and linear range has been 0.01 M - 10 μM with limit of detection (LOD) 7.3 μM. We utilized the sensor for inline determination of the release of tenofovir disoproxil fumarate from its tablet pharmaceutical formulation without any separation or sample pre-treatment steps. In an attempt to be eco-friendly through evaluating the suggested method regarding its greenness, the method has been found to be excellent green according to the eco scale method.

Design and Performance Evaluation of Machine Learning-based Terahertz Metasurface Chemical Sensor.

This paper presents a terahertz metasurface based sensor design incorporating graphene and other plasmonic materials for highly sensitive detection of different chemicals. The proposed sensor employs the combination of multiple resonator designs - including circular and square ring resonators - to attain enhanced sensitivity among other performance parameters. Machine learning techniques like Random Forest regression, are employed to enhance the sensor design and predict its performance. The optimized sensor demonstrates excellent sensitivity of 417 GHzRIU-1 and a low detection limit of 0.264 RIU for ethanol and benzene detection. Furthermore, the integration of machine learning cuts down the simulation time and computational requirements by approximately 90% without compromising accuracy. The sensor's unique design and performance characteristics, including its high-quality factor of 14.476, position it as a promising candidate for environmental monitoring and chemical sensing applications. Moreover, it also demonstrates potential for 2-bit encoding applications through strategic modulation of graphene chemical potential values. On the other hand, it also shows prospects of 2-bit encoding applications via the modulation of graphene chemical. This work provides a major advancement to the terahertz sensing application by proposing new materials, structures, and methods in computation in order to develop a high-performance chemical sensor.

Modelling and analysis of fiber Bragg grating temperature sensor for Internet of things applications (FBG-4-IoT)

The integration of Fiber Bragg Grating (FBG) sensors into the Internet of Things (IoT) has garnered significant attention in recent years because of their immunity to electromagnetic and radio frequency interference, small size and weight, and corrosion resistance. This paper aims to enhance the performance characteristics of FBG sensors for temperature measurement by proposing a specific design of their parameters, thus facilitating their implementation in IoT applications. The FBG temperature sensor is designed to operate in the 1500–1600 nm wavelength range. The outcomes display a high sensitivity of 0.61 nm/°C with a Full Width Half Maxima (FWHM) of 7.893 nm and a Figure of Merit (FOM) of 7.72 x 10−2/°C. The calculated Quality Factor (Q) of the sensor was 195.67. When compared with previous studies in the literature, our obtained results confirm the enhanced performance of the proposed design of the FBG sensor, which render it suitable for utilization in most industrial use cases, especially in harsh environments.

Modeling Biodegradable Free Chlorine Sensor Performance Using Artificial Neural Networks

AbstractElectrochemical sensors are used to measure target analytes in water, meat, fruits, or vegetables, to ensure their safety, security, and integrity for human use. In this paper, a solution‐based fabrication process is presented for a biodegradable electrochemical free chlorine sensor using asparagine that is functionalized onto graphene oxide (GO). An ink solution of the GO functionalized with asparagine is synthesized, and then deposited onto a screen‐printed carbon electrode (SPCE) using a spin coater. The sensor shows high a sensitivity of 0.30 µA ppm−1 over a linear range of 0–8 ppm with a hysteresis‐limited resolution of 0.2 ppm after achieving a steady state at 50 s. From the development and testing of the free chlorine sensor, over 9000 datapoints are collected and used for training an artificial neural network (ANN) model to quantify and characterize the factors affecting the free chlorine sensor's performance, and model its degradation characteristics. The model reports a low mean absolute error (MAE) of 0.1603 and a high model accuracy with a Pearson correlation coefficient (PCC) of 0.9950, demonstrating that these degradation characteristics can be modeled and be used to compensate the degraded performance characteristics of the free chlorine sensors.

Efficiently Range-Coupled Position Estimation for an Aerial Swarm With the Confidence Evaluation of Onboard Sensing

This work proposes an efficient range-coupled localization approach for aerial swarms considering the variance of onboard sensors in cluttered environments. First, a reciprocal bond estimation algorithm is proposed to estimate the position; it constructs an optimization framework based on the range-coupled observability analysis. Subsequently, considering the variable performance characteristics of onboard sensors in cluttered environments, a moving confidence evaluation algorithm is proposed to improve the resilience of the position estimation system by assessing the concurrent reliability of all sensors. Mathematically, the aforementioned two algorithms are integrally formulated using a nonlinear least-squares equation. Notably, solving this nonlinear problem is typically a low-efficiency process that deteriorates with the scale of the swarm. To overcome this issue, a gradient-aware Levenberg–Marquardt algorithm is herein proposed to enhance the computational efficiency of this system to solve this nonlinear least-squares problem. Finally, swirling experiments involving four drones are carried out to verify the performance of the proposed methods. The results demonstrate that the time cost of optimization in each servo period is only approximately 7.15 ms, and the computational efficiency exhibits at least a 2.78 times improvement over the existing methods. Meanwhile, even in a smoky environment, the estimation precision can be as great as 8 cm, which is comparable to results obtained using state-of-the-art methods.

Wildfire Smoke Monitoring for Agricultural Safety and Health in Rural Washington

ABSTRACT Objectives This study aimed to evaluate the performance of a low-cost smoke sampling platform relative to environmental and occupational exposure monitoring methods in a rural agricultural region in central Washington state. Methods We co-located the Thingy AQ sampling platform alongside cyclone-based gravimetric samplers, a nephelometer, and an environmental beta attenuation mass (E-BAM) monitor during August and September of 2020. Ambient particulate matter concentrations were collected during a smoke and non-smoke period and measurements were compared across sampling methods. Results We found reasonable agreement between observations from two particle sensors within the Thingy AQ platform and the nephelometer and E-BAM measurements throughout the study period, though the measurement range of the sensors was greater during the smoke period compared to the non-smoke period. Occupational gravimetric sampling methods did not correlate with PM2.5 data collected during smoke periods, likely due to their capture of larger particle sizes than those typically measured by PM2.5 ambient air quality instruments during wildfire events. Conclusion Data collected before and during an intense wildfire smoke episode in September 2020 indicated that the low-cost smoke sampling platform provides a strategy to increase access to real-time air quality information in rural areas where regulatory monitoring networks are sparse if sensor performance characteristics under wildfire smoke conditions are understood. Improving access to spatially resolved air quality information could help agricultural employers protect both worker and crop health as wildfire smoke exposure increases due to the impacts of climate change. Such information can also assist employers with meeting new workplace wildfire smoke health and safety rules.

Conjugated Polymer-Based Nanocomposites for Pressure Sensors.

Flexible sensors are the essential foundations of pressure sensing, microcomputer sensing systems, and wearable devices. The flexible tactile sensor can sense stimuli by converting external forces into electrical signals. The electrical signals are transmitted to a computer processing system for analysis, realizing real-time health monitoring and human motion detection. According to the working mechanism, tactile sensors are mainly divided into four types-piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. Conventional silicon-based tactile sensors are often inadequate for flexible electronics due to their limited mechanical flexibility. In comparison, polymeric nanocomposites are flexible and stretchable, which makes them excellent candidates for flexible and wearable tactile sensors. Among the promising polymers, conjugated polymers (CPs), due to their unique chemical structures and electronic properties that contribute to their high electrical and mechanical conductivity, show great potential for flexible sensors and wearable devices. In this paper, we first introduce the parameters of pressure sensors. Then, we describe the operating principles of resistive, capacitive, piezoelectric, and triboelectric sensors, and review the pressure sensors based on conjugated polymer nanocomposites that were reported in recent years. After that, we introduce the performance characteristics of flexible sensors, regarding their applications in healthcare, human motion monitoring, electronic skin, wearable devices, and artificial intelligence. In addition, we summarize and compare the performances of conjugated polymer nanocomposite-based pressure sensors that were reported in recent years. Finally, we summarize the challenges and future directions of conjugated polymer nanocomposite-based sensors.

Sensors Based on Nanoscale Silicon 1D Structures for Industrial, Environmental and Medical Monitoring

Article is devoted to the analysis of modern sensors based on silicon nanowires (SiNWs) to determine the influence of SiNWs synthesis parameters and their structural features on device characteristics. A modern trend in the development of electronic sensing devices is the use of various types of nanomaterials in order to increase sensor sensitivity and miniaturize of their size. 1D nanomaterials, namely SiNWs, have several advantages for sensor applications, such as a large surface-to-volume ratio and an increased rate of diffusion of the main charge carriers. Based on the literature analysis, an overview of modern SiNWs sensors was made. The advantages of silicon 1D structures were shown by comparison with other types of nanostructures. Also sensors were classified according to the methods of synthesis of SiNWs, sensor principle operation, kind of input value and types of applied modifiers. Silicon nanowires were most often synthesized by the method of metal-stimulated chemical etching, the advantages of which include the simplicity of implementation, low cost, and the ability to synthesize nanostructures with a high aspect ratio. The vapor-liquid-solid synthesis was also used, the advantages of which include the ability to be adapted to any technology of supplying a gas mixture with the target component and the possibility of obtaining nanowires with a diameter of 10 nm or less. According to the principle operation, the most of sensors developed on the basis of silicon nanowires are of electrical type (resistive, capacitive, electrochemical, diode or transistor type), optical sensors (fluorescent) are developed to a much lesser extent. Gas sensors (ethanol, oil vapor, formaldehyde, ammonia, nitrogen oxide, hydrogen, carbon dioxide,), liquid sensors (glucose, hydrogen peroxide, ethanol, heavy metal ions, pH), and physical values (humidity, temperature and illumination) have been developed on the basis of silicon 1D nanoscale structures. The following surface modifiers of nanowires were used to improve the performance characteristics: noble metal nanoparticles, metal-organic framework structures, carbon nanotubes, graphene, self-assembled monolayers, metal and metal oxide thin films. In particular, it was shown that the modification of the surface of the array of SiNWs with noble metals led to an increase in the sensitivity of the hydrogen sensor by 80%. Modification of formaldehyde sensor using reduced graphene oxide resulted in an improvement of sensor sensitivity by more than 2 times. The influence of SiNWs synthesis parameters on sensor performance characteristics was also determined. In particular, it was shown that increasing of SiNWs width from 20–30 nm to 500–600 nm led to an increase in the sensitivity of humidity sensor from 4.5 to 7.5%. Increasing the etching time caused the synthesis of longer nanowires, which improved the sensitivity of carbon dioxide sensors from 0.6 to 2.5%. Dependences established in this work will make it possible to develop the production technology of various types of sensors based on silicon nanowires with high sensitivity, selectivity, stability and operation speed.

Gas Sensor Based on ZnO Nanostructured Film for the Detection of Ethanol Vapor

In this paper, the ZnO<La> target was synthesized by the solid-state reaction method and a nanostructured thin film was deposited by the RF (radio frequency) magnetron sputtering method on a Multi-Sensor-Platform. The obtained ZnO<La> nanostructured film was investigated as the sensing material. Energy-Dispersive X-ray (EDX) analysis indicated the existence of La in the synthesized ZnO<La> material. Scanning Electron Microscope (SEM) images of the film showed the grain sizes in the range of 20–40 nm. Sensor performance characteristics such as a dynamic response, response and recovery times, and ethanol detection range were investigated at 50–300 °C. A sensitivity was observed at extremely low concentrations of ethanol (0.7 ppm). The minimum response and recovery times of the sensor corresponding to 675 ppm ethanol vapor concentration at 250 °C were found to be 14 s and 61 s, respectively. The sensor showed a high response, good selectivity, fast response/recovery behavior, excellent repeatability toward ethanol vapor, and low sensitivity toward humidity. These characteristics enable the use of a ZnO<La> based sensor for ethanol detecting applications.

Recent Trends in the Development of Carbon-Based Electrodes Modified with Molecularly Imprinted Polymers for Antibiotic Electroanalysis

Antibiotics are antibacterial agents applied in human and veterinary medicine. They are also employed to stimulate the growth of food-producing animals. Despite their benefits, the uncontrolled use of antibiotics results in serious problems, and therefore their concentration levels in different foods as well as in environmental samples were regulated. As a consequence, there is an increasing demand for the development of sensitive and selective analytical tools for antibiotic reliable and rapid detection. These requirements are accomplished by the combination of simple, cost-effective and affordable electroanalytical methods with molecularly imprinted polymers (MIPs) with high recognition specificity, based on their “lock and key” working principle, used to modify the electrode surface, which is the “heart” of any electrochemical device. This review presents a comprehensive overview of MIP-modified carbon-based electrodes developed in recent years for antibiotic detection. The MIP preparation and electrode modification procedures, along with the performance characteristics of sensors and analytical methods, as well as the applications for the antibiotics’ quantification from different matrices (pharmaceutical, biological, food and environmental samples), are discussed. The information provided by this review can inspire researchers to go deeper into the field of MIP-modified sensors and to develop efficient means for reliable antibiotic determination.

Electrical SPR biosensor with thermal annealed graphene oxide: Concept of highly sensitive biomolecule detection

(Reduced) graphene oxides as promising 2D materials have been explored extensively to improve the performance characteristics of SPR sensors. Herein, we demonstrate the tuning optical properties of SPR biochips by the combination of two strategies: (i) using gold/reduced graphene oxide (Au/rGO) interfaces prepared by thermal annealing of Au/GO, and (ii) applying external electrical bias via the solid-liquid interface during SPR measurements. We investigated this novel approach by studying a model biological interaction of prostate-specific antigen (PSA) with lectin Concanavalin A (Con A) based on glycan recognition, as the glycan motifs detection is increasingly requested due to the growing knowledge of the importance of glycans in various biological processes and their use as biomarkers. The thermally annealed Au/rGO as a functional layer of SPR chips provides higher signals and 10 times better LOD (limit of detection) compared to Au/GO case. This experimental finding was cross-verified by SPR simulations based on a model combining the optical indices (dielectric parameters) and thicknesses of the GO and rGO thin films obtained from ellipsometry characterizations. In addition, the unique optoelectrical properties of rGO thin films allowed for efficient tuning of the plasmonic intensities by applying an electrical bias at the Au/rGO interface, exploited here to improve the Con A LOD down to 10 ng/ml, what is by 1 order of magnitude better compared to the classic Au chip. The electrical SPR biosensor approach presents a proof-of-concept for future ultrasensitive SPR biosensor platforms.

Sensor for Meso-Scale Tissue Stiffness Characterization

Force sensing is fundamental for developing smart surgical devices capable of in-vivo tissue stiffness measurement. The sensing technique necessitates integration of micromachined force sensors at the end-effectors of tactile probes. We discuss fabrication and characterization of a small footprint silicon diaphragm-based force sensor with boron-doped piezoresistors connected in Wheatstone bridge configuration. The sensor performance characteristics for axial indentation experiments yield sensitivity 0.34 mV/mN, linearity > 0.99, and hysteresis 1.18% for force range 0–250 mN. To validate the utility of the force sensor for mechanical characterization of soft tissues, we perform indentation experiments on sheep tracheal tissues. The study involved two important mechanical characterization techniques: compression and stress relaxation. Tissue samples comprised of cartilage tissue from the cranial, middle, and caudal portions of the trachea and smooth muscle tissue. We record the hysteresis patterns of the tissue samples at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10 ~\mu \text{m}$ </tex-math></inline-formula> /s strain rate. The stiffness of cranial, middle, and caudal cartilage at 20% strain are 23±1.39 N/m,22.36±2.05 N/m, and 22.41±2.04 N/m. The cranial cartilage is innately stiffer than other tracheal segments; however, the results show no statistical variation (p ≥ 0.1488) in cartilage stiffness based on anatomical region. The stiffness of smooth muscle at 30% strain measures to be 14.02±0.76 N/m. The stress relaxation experiments reveal cartilage samples have faster relaxation time, and the smooth muscle tissues respond less rapidly to compression loads and have slower relaxation time. The feasibility of characterizing soft tissues at low contact force and small sensing area extends the utility of the sensor in airway diagnostic tools for localized stiffness measurement.

Novel contactless Hybrid Static Magnetostrictive Force-Torque (CHSMFT) sensor using Galfenol

This paper presents a novel Contactless Hybrid Static Magnetostrictive Force-Torque (CHSMFT) sensor using Galfenol. Initially, the sensor's design principles for measuring axial force and torque are outlined. The magneto-mechanical properties of the materials used, such as B-H curves and magnetic permeability, are determined and used in the finite element method when various mechanical preloads and magnetic fields are applied. The CHSMFT sensor is evaluated analytically using the equivalent circuit method and numerically using COMSOL Multiphysics® software based on the obtained experimental results. Afterward, the sensor is fabricated based on the results of the analytical and finite element method and experimentally validated for a range of electrical currents and excitation frequencies. The analytical and finite element method results are then compared to the experimental results. In force and torque measurements, sensitivity, precision, and linearity error are presented separately. Finally, the CHSMFT sensor's performance characteristics under optimal conditions are presented. Sensitivity is found to increase with rising electrical current (or magnetic field) and frequency. Maximum sensitivities are obtained at 0.7349 mV/kgf and 2.24 mV/Nm for axial load and torque measurements, respectively.

Piezoelectric Joint Sensors Shape to Sensor Response Characteristics by FEM Analysis and Measuring Result

After the huge earthquake many steel structures were constructed using frame welded joints of welded construction and welded base. Steel structures are considered earthquake resistance structures however, many steel structures are constructed using frame-welded joints of fillet welded construction and welded column bases. These weld joints could result to have low capacity to absorb energy during earthquakes. Therefore, the application of structural health monitoring to the maintenance of infrastructures is extensively expected for new technology. However, in order to achieve practical utilization of new sensors, both accumulation of data and evaluation method to derive information about structural conditions from the measured data is highly required. To solve such a problem, we would like to measure the structure by health monitoring using a piezoelectric sensor. In this paper, measurements output voltage because using piezoelectric joint sensors, we recorded the sensor characteristics during measuring robot measurement because of changes in the thickness and shape of the base plate of the piezo joint sensor. Structural FEM for sensor analysis is also introduced to evaluate the mechanism and influence of various environmental factors on the response of the structures. In other hand, the introduction of the sensor measurement robot has reduced the working hours required for measurement experiments of sensor characteristics to about 1/19, which is expected to boost the cycle of sensor improvements in the future significantly. We will use robotics to promote research on the performance characteristics of piezoelectric joint sensors for a safe society.