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This article presents the possibility of controlling/managing the frequency selection ability of membrane-based broadband frequency sensors (MB2FS), exploiting systematic selection of membrane stiffness. MB2FS is a bio-inspired system mimicking the geometry and functionality of the basilar membrane (BM) in the mammalian cochlea. The actual BM is tapered in geometry (both length wise and thickness wise), which makes the stiffness of the membrane uniformly varied over its length. Because of varied stiffness, different locations of the BM show resonance deflection at different frequency inputs, which allow the BM to select/sense the entire sonic frequency band within its 35 mm length. While actual BM and conventional MB2FS possess homogeneous stiffness over the domain length, in this article, a comprehensive insight is provided of how the frequency selection ability of the sensors can be manipulated and controlled, predictively, using functionally graded structural stiffness. Therefore, this work is not intended to develop an artificial BM, rather is focused on developing frequency sensors inspired by the membrane stiffness of BM, which plays a vital role in the spatial selection of acoustic frequencies. The study is performed using a numerically validated predictive model developed in a semi-analytical interface to explain the effects of MB2FS stiffness variations. Based on biological occurrence of stiffness in natural BM, three functions (logarithmic, linear, and exponential) are assumed to predict the FSP. While a random sonic frequency band of 10–12 kHz is targeted in this study to demonstrate the stiffness grading principle of MB2FS, a similar process (e.g., choosing the appropriate stiffness distribution of the beam) can be used to develop both sonic and ultrasonic frequency sensors. This study presents a detailed framework of how the sensing parameters of a specific frequency band (e.g., sensing location of band start and end frequencies and membrane segment width necessary to sense the entire frequency band) are dependent on the function coefficients. Finally, a comprehensive guideline is provided to predictively determine the function coefficients for user-defined frequency selection parameters. While existing state-of-the-art only allows designing MB2FS for a specific frequency band, the work presented in this study will open the opportunity to select multiple frequency bands of an MB2FS without altering its geometric configuration. [ABSTRACT FROM AUTHOR]

Anomalous Hall effect (AHE) sensor has attracted significant attention in recent years due to its simpler structure and better sensitivity as compared to semiconductor-based Hall sensors. However, up to now, most of the work has been focused on its basic functionalities, with very little attention given to optimizing its performance for practical applications. In this work, we systematically investigated how the lateral dimension affects the performance of CoFeB-based AHE sensors. By adjusting the sensor width while keeping the length and other parameters constant, it is found that although the output signal amplitude decreases with increasing the sensor width, the noise and power consumption also decrease simultaneously, leading to an overall enhancement of the sensor performances with a sensitivity, detectivity, and power efficiency of 8960 Ω/T, 205 nT / Hz @ 1 Hz , and 2009 V/WT, respectively. To illustrate the potential applications of AHE sensors, we demonstrate a proof-of-concept experiment to showcase the potential AHE sensor in pulse detection. [ABSTRACT FROM AUTHOR]

Four types of barrier detectors based on a type II InAs/InAsSb superlattice with a wide-gap barrier made of a solid AlInAsSb lattice matched to the GaSb buffer were compared. The tested detectors differed in the type of doping of the active layer and the level and type of doping of the contact layer at the barrier. The epitaxial layers were deposited on GaAs (100) substrates using the molecular beam epitaxy method. The spectral and current–voltage characteristics of the analyzed detectors were compared. The highest current responsivities were observed in the structure with a p-type absorber (p+BpN+). Detectors with an n-type absorber (p+Bnn+, n+Bnn+, and nBnn+) show an increase in the current responsivity with an increase in the reverse bias voltage due to the reduction in the undesirable barrier in the valence band. Arrhenius characteristics for the dark current show that only in nBnn+ detectors, it was possible to limit the generation–recombination current. These detectors at 150 K were characterized by the highest normalized detectivity of approximately 3 × 1011 cm · Hz1/2/W. The obtained results were compared with literature data, showing that the parameters of type II superlattice photodetectors are close to those of HgCdTe photodiodes according to the "Rule 07" and "Rule 22" principles. [ABSTRACT FROM AUTHOR]

Transition-edge sensors (TESs) have the potential to perform electron spectroscopic measurements with far greater measurement rates and efficiencies than can be achieved using existing electron spectrometers. Existing spectrometers filter electrons by energy before detecting a narrow energy band at a time, discarding the vast majority of electrons available for measurement. In contrast, TESs have intrinsic energy sensitivity and so do not require prior filtering to perform energy-resolved measurements. Despite this fundamental advantage, TES electron spectroscopy has not, to our knowledge, previously been reported in the literature. We present the results of a set of proof-of-principle experiments demonstrating TES electron spectroscopy experiments using Mo/Au TESs repurposed for electron calorimetry. Using these detectors, we successfully measured the electron spectrum generated by an electron beam striking a graphite target with energies between 750 and 2000 eV, at a noise-limited energy resolution of 4 eV. Based on the findings of these experiments, we suggest improvements that could be made to TES design to enhance their electron detection capabilities through the use of a dedicated electron absorber in the device with integrated electron optics. [ABSTRACT FROM AUTHOR]

Dual-energy imaging represents a versatile and evolving technology with wide-ranging applications in medicine and beyond. Recent technological developments increased the potential for improved diagnostic accuracy and expanded imaging capabilities across various fields. The purpose of this work is to design and develop an energy-integrating multilayer detector, known as a sandwich detector, aimed at single-shot dual-energy imaging tasks such as material discrimination and contrast cancellation. The sandwich detector uses two complementary metal oxide semiconductor advanced pixel sensors of 50 μm pixel size. The top and bottom sensors detect low-energy (LE) and high-energy (HE) photons, with sensors coupled with 250 and 600 μm scintillators, respectively. For better spectral separation between layers without excessively affecting the detected statistic in the bottom layer, the insertion of a 0.25-mm Cu filter between the layers was found to be the optimal choice, from among the tested 0-, 0.25-, and 0.5-mm filter options. The thickness selection for scintillator and intermediate Cu filter was carried out through a dual-energy simulation model. The experiments confirmed the model's reliability in selecting the optimal thicknesses of the intermediate Cu filter, thereby providing reassurance also on the choice of the top scintillator. [ABSTRACT FROM AUTHOR]

Miniaturized photoionization detectors (PIDs) are used in conjunction with gas chromatography systems to detect volatile compounds in gases by collecting the current from the photoionized gas analytes. PIDs should be inexpensive and compatible with a wide range of analyte species. One such PID is based on the formation of a He plasma in a dielectric barrier discharge (DBD), which generates vacuum UV (VUV) photons from excited states of He to photoionize gas analytes. There are several design parameters that can be leveraged to increase the ionizing photon flux to gas analytes to increase the sensitivity of the PID. To that end, the methods to maximize the photon flux from a pulsed He plasma in a DBD-PID were investigated using a two-dimensional plasma hydrodynamics model. The ionizing photon flux originated from the resonance states of helium, He(3P) and He(21P), and from the dimer excimer He2*. While the photon flux from the resonant states was modulated over the voltage pulse, the photon flux from He2* persisted long after the voltage pulse passed. Several geometrical optimizations were investigated, such as using an array of pointed electrodes. However, increasing the capacitance of the dielectric enclosing the plasma chamber had the largest effect on increasing the VUV photon fluence to gas analytes. [ABSTRACT FROM AUTHOR]

In the semiconductor industry, virtual metrology (VM) is a cost-effective and efficient technique for monitoring the processes from one wafer to another. This technique is implemented by generating a predictive model that uses real-time data from equipment sensors in conjunction with measured wafer quality characteristics. Before establishing a prediction model for the VM system, appropriate selection of relevant input variables should be performed to maintain the efficiency of subsequent analyses considering the large dimensionality of the sensor data inputs. However, wafer production processes usually employ multiple sensors, which leads to cost escalations. Herein, we propose a variant of the sparse principal component analysis (PCA) called true sparse PCA (TSPCA). The proposed method uses a small number of input variables in the first few principal components. The main contribution of the proposed TSPCA is reducing the number of essential sensors. Our experimental results demonstrate that compared to the existing sparse PCA methods, the proposed approach can reduce the number of sensors required while explaining an approximately equivalent amount of variance. [ABSTRACT FROM AUTHOR]

A novel mode-localized acceleration sensor employing an electrostatically coupled resonator and integrating a lever with proof mass is micromachined using standard silicon on insulator (SOI) technology. In order to determine the linear dynamic range of the sensor, a reduced order model is developed while assuming that the resonators vibrate below the critical amplitude. Then, open-loop and closed-loop testing platforms are established to measure the performance of the linearly operating accelerometer in a vacuum environment (less than 5 Pa). Moreover, the corresponding amplifier circuit based on the capacitive detection principle is designed in order to extract and amplify the current signal from the resonators. The obtained results show that the accelerometer sensitivity can be increased by three orders of magnitude when using the relative shift of amplitude ratio as the output metric instead of the relative shift of frequency, and the experimental measurements are consistent with the theoretical predictions. Remarkably, the Allan standard deviation of the mode-localized acceleration sensor obtained from the closed-loop testing circuit is around 5.03 μg. [ABSTRACT FROM AUTHOR]

In this work, we studied the free-carrier transport properties and space-charge formation/polarization in a CdZnTe bar-shaped radiation detector using the Laser-Induced Transient Current technique. We found out that a steady-state space charge ranging from 8 × 108 to 2.1 × 109 cm−3 is formed throughout the detector at about 0.5 s following biasing. The measured current waveforms were modeled by Monte Carlo simulations after taking into account the electric and weighting fields inside the detector and shielding box. Modeling of the unpolarized waveforms revealed an exceptionally high electron mobility-lifetime product μ e τ e ≥ 0.095 c m 2 V − 1 . The observed formation of positive space charge in the biased detector and linear scaling of the current waveform shapes on applied bias revealed that the detector polarization is attributed to carrier injection at the anode. Measurements in pulsed and DC bias in modified electrode geometry proved the surface-charge formation. [ABSTRACT FROM AUTHOR]

Millimeter-thick methylammonium lead tribromide (MAPbBr3) single crystal x-ray detectors have recently raised attention due to their high x-ray attenuation efficiency and good charge transport properties. However, an intriguing feature of the photocurrent response of MAPbBr3 detectors has been largely overlooked in the literature. After biasing, transient sensitivity is measured under x rays at short-circuit (bias = 0 V), thus revealing a large remnant electric field that builds up under bias. Here, we exploit the x-ray sensitivity of MAPbBr3 detectors at zero-bias in order to probe the internal built-in field, as well as to investigate the charge transport properties of the perovskite material. Our model derived from the Hecht equation is able to fully rationalize the response of the detectors both at short-circuit and under moderate applied bias. Moreover, we provide a method for the estimation of the internal electric field, and for the sum of the electrons and holes mobility–lifetime products μ e τ e + μ h τ h. This general method could extend to any perovskite-based x-ray detector exhibiting transient sensitivity at zero-bias. [ABSTRACT FROM AUTHOR]

We propose and analyze the performance of terahertz (THz) room-temperature bolometric detectors based on the graphene channel field-effect transistors (GC-FET). These detectors comprise the gate barrier layer (BL) composed of the lateral hexagonal-boron nitride black-phosphorus/hexagonal-boron nitride (h-BN/b-P/h-BN) structure. The main part of the GC is encapsulated in h-BN, whereas a short section of the GC is sandwiched between the b-P gate BL and the h-BN bottom layer. The b-P gate BL serves as the window for the electron thermionic current from the GC. The electron mobility in the GC section encapsulated in h-BN can be fairly large. This might enable a strong resonant plasmonic response of the GC-FET detectors despite relatively lower electron mobility in the GC section covered by the b-P window BL. The narrow b-P window diminishes the Peltier cooling and enhances the detector performance. The proposed device structure and its operation principle promote elevated-temperature GC-FET THz detector responsivity values and other characteristics, especially at the plasmonic resonances. [ABSTRACT FROM AUTHOR]

Analytical instruments or scientific instruments are indispensable for scientific research and industry. The analytical instruments require a detector that converts physical quantities to be measured (measurands) to electric signals. This Tutorial describes the basics of quantum and thermal detectors, the operation principles of superconductor detectors, and the ultimate performance of state-of-art analytical instruments with superconductivity. We still face fundamental issues, such as the classical Fano factor, the relation between energy gap and mean carrier creation energy, quasiparticle dynamics, and the intermediate state in the middle of superconducting transition; and engineering issues, such as the small sensitive area and the spatially nonuniform response. Nevertheless, enormous efforts have matured superconductor detectors, which enables us to solve the inherent problems of conventional analytical instruments. As an example of the analytical results, we describe x-ray spectroscopy and mass spectrometry at our institute by using three detector types: superconductor tunnel junction, transition edge sensor, and superconductor strip. Microwave kinetic inductance and metallic magnetic calorimetric types are also described. The analytical results may contribute to a wide range of fields, such as dentistry, molecular biology, energy-saving society, planetary science, and prebiotic organic molecules in space. [ABSTRACT FROM AUTHOR]

Recent studies have provided conclusive evidence for the existence of a liquid–liquid critical point in numerical models of water. Such a scenario implies the competition between two local molecular arrangements of different densities: a high-density liquid (HDL) and a low-density liquid (LDL). Within this context, the development of accurate structural indicators to properly characterize the two interconverting local structures is demanded. In a previous study, we introduced a reliable energy-based structural descriptor that properly discriminates water molecules into tetrahedrally arranged molecules (T molecules) and distorted molecules (D molecules). The latter constitute defects in terms of hydrogen bond (HB) coordination and have been shown to represent a minority component, even at high temperatures above the melting point. In addition, the D molecules tend to form high-quality HBs with three T molecules and to be surrounded by T and D molecules at further distances. Thus, it became evident that, while the LDL state might consist of a virtually pure T state, the HDL state would comprise mixed molecular arrangements including the D molecules. Such a need to abandon the single-molecule description requires the investigation of the degree of structural information to be incorporated in order to build an appropriate multi-molecule indicator. Hence, in this work, we shall study the effect of the local structural constraints on the water molecules in order to discriminate the different molecular arrangements into two disjoint classes. This will enable us to build a multi-molecule structural indicator for water whose performance will then be investigated within the water's supercooled regime. [ABSTRACT FROM AUTHOR]

Photon-number resolving transition-edge sensors (TESs) with near unity system detection efficiency enable novel approaches to quantum computing, for example, heralding robust Gottesman–Kitaev–Preskill qubit states. Increasing the speed of the detectors increases the rate at which these states can be heralded. In addition, depending on the details of the scheme, faster detectors can reduce the complexities of the hardware implementation. In previous work, we demonstrated that adding a small amount of gold between the tungsten film and silicon substrate can increase thermal conductance and reduce detector recovery time. In that study, the readout electronics imposed limitations on stable biasing conditions of the TES detector, and the TES could only be biased at higher than ideal values. In this report, we demonstrate the operation of the TES illuminated by a heavily attenuated pulsed laser running at 1 MHz repetition rate and examine the limits to adding gold to speed up device recovery times using a higher bandwidth readout system. The best performance was achieved by combining a 15 × 15 μ m 2 tungsten TES with 5 μ m 3 of gold, which resulted in a recovery time faster than 250 ns, with an energy resolution of 0.25 eV full-width at half maximum at 0.8 eV photon energy. [ABSTRACT FROM AUTHOR]

Numerous applications of wireless sensor networks (WSNs) highly depend on the node location, such as maritime rescue, agriculture, and hazardous environments. GPS-enabled sensors are not cost-effective or energy efficient. Henceforth, the precise location of sensor nodes significantly impacts the performance of WSNs. Finding the position of a target node (an unknown node) is known as node localization. Gaussian noise and RSSI are cost-effective approaches for estimating the location of a target node. In this paper, the Seagull optimization algorithm and its enhanced versions are applied to increase the NL accuracy of localized nodes. To enhance the accuracy and improve the randomness of the seagull optimization algorithm (SOA)., levy flight and a chaotic map are employed in this work to enhance the seagull optimization algorithm Furthermore, the chaotic map-based SOA (C-SOA) and the Levy flight-based SOA (LF-SOA) are used for node location in WSNs. The performance evaluation and result comparison of SOA, C-SOA, and LF-SOA show that LF-SOA is better than C-SOA and SOA. [ABSTRACT FROM AUTHOR]

Summary: Many optimal sensor placement (OSP) techniques have been developed basing on known external loads. However, it is often difficult to obtain excitation measurements. Therefore, the development of OSP under unknown inputs (OSP‐UI) is desirable. In this paper, based on modal Kalman filter (MKF), an OSP‐UI approach (MKF‐OSP‐UI) is proposed for optimally determining the number and locations of multitype sensors with the aim of minimizing the reconstructed responses errors. An MKF‐based approach previously developed by the authors is first employed for estimating multiscale structural responses and unknown loads. Then, an error covariance matrix is defined as a measure of the differences between the reconstructed responses and the corresponding actual ones. By using the covariance matrix of measurement noise for normalization, the ill‐conditioning problem caused by data fusion of multiscale responses is avoided. The sensors that have few contributions to the reconstructed responses are removed from the candidate set during iteration procedure. The sensor placement is finally determined when the estimation errors are below the preset level. Numerical results show that the sensor configuration determined by the proposed approach has a better performance on the joint estimation of multiscale responses and unknown inputs, as compared with that determined by experience. [ABSTRACT FROM AUTHOR]

MXene quantum dots (MQDs), an emerging zero‐dimensional nanomaterial, have garnered significant attention from researchers due to their distinctive physical and chemical properties. In this study, cysteine‐functionalized Ti3C2 MQDs were synthesized using a facile hydrothermal methods, resulting in the functionalized Ti3C2 MQDs exhibiting intense blue fluorescence attributed to size‐dependent effects and surface defects. Furthermore, the cysteine‐functionalized Ti3C2 MQDs exhibit excitation wavelength‐dependent emission behavior and serve as a highly sensitive fluorescent probe for Ag+ detection with an impressive low limit of detection (LOD) of 0.015 μM. Moreover, they demonstrate exceptional sensitivity and selectivity in determining Ag+. This study presents a novel approach for the detection of Ag+ and highlights the immense potential of cysteine‐functionalized Ti3C2 MQDs in environmental applications. [ABSTRACT FROM AUTHOR]

ZnFe (PBA)@Mo3C2Tx is prepared by in‐situ sonication method using ZnFe Prussian blue analogue infused with Mo3C2Tx (MXene) to use as a non‐enzymatic glucose sensor owing to its low cost and biocompatibility. The synthesized ZnFe (PBA)@Mo3C2Tx is characterized for its physical and chemical characterization by XRD, Raman, XPS, EDAX, and FESEM analyses, revealing a functionalized multiple‐layered structure with a cubic nano‐hybrid arrangement. This sensor has undergone electroanalytical investigation, including cyclic voltammetry and chronoamperometry analysis. The electrochemical performance of ZnFe(PBA)@Mo3C2Tx exhibits an excellent analytical performance with a sensitivity of 818.285 μA mM−1 cm−2 and the limit of detection (LOD) of 1.6 μM (S/N=3). The analysis of glucose in human sweat samples, compared with their corresponding blood glucose values, yield a relative standard deviation (RSD) of 2.98 %. [ABSTRACT FROM AUTHOR]

The present work reports for the first time the design of an electrochemical sensor functionalized with green nanoparticles based on Hyphaene thebaica for amoxicillin quantification. Based on a simple one‐pot bio‐reduction reaction, lead oxide PbO coated with Hyphaene thebaica was synthesized. Ultraviolet‐visible spectroscopy (UV), fourier transform infrared (FITR), transmission electron microscopy (TEM) and X‐ray diffraction (XRD) were used to control optical, structural, morphological, and physicochemical properties of the elaborated nanoparticles. Results demonstrated a good dispersion with a spherical morphology, which is in the order 8 nm. Regarding the good properties of nanoparticles, they are integrated to design an electrochemical sensor for amoxicillin detection. Cyclic voltammetry and square wave voltammetry were used to follow up the sensor modification and the electrochemical sensor response versus different amoxicillin concentrations. Under optimal conditions, the electrochemical sensor modified with the nanoparticles in question provides a linear detection in the range 50–10000 nM, with a detection limit of 0.105 nM. The proposed sensor also exhibits good sensitivity and selectivity against several antibiotic analogues and has been successfully applied to real samples. Aside from its power in several fields including antibacterial, antifungal, enzyme‐inhibiting and antioxidant, green nanoparticles based on Hyphaene thebaica have demonstrated an effectiveness as a sensor for the electrochemical detection of amoxicillin, highlighting the possibility of adopting these sensors as routine test for the environment monitoring. [ABSTRACT FROM AUTHOR]

Numerous approaches are explored to achieve precise position registry of microparticles (MPs) with minimal defects; however, MP assembly in a periodic pattern or an arbitrary manner has been a challenging issue over the past several decades. Utilizing the position‐registered conductive MPs, polymer composites of the MPs are used as anisotropic conductive film (ACF) and soft interfacing. One of the remaining challenges is maintaining the MP positions while producing or utilizing the ACF. This study proposes a simple strategy to produce a stretchable ACF (S‐ACF) by mechanical rubbing, without disturbing the MP positions during the production and use. A practical means of precise MP positioning on a ultraviolet (UV)‐patternable soft template is investigated first. This study investigates, through both experiment and finite element method calculation, the relationship between local adhesion of the template and mechanical rubbing variables (pressure, rubbing velocity, and MP size). Based on this exploration, a fast and simple method to fabricate large‐area S‐ACF is presented. This study demonstrates that the S‐ACF can be used for electronic interfacing in stretchable devices and for ionic interfacing to remove the effect of external mechanical force in ionic sensors. [ABSTRACT FROM AUTHOR]

The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors' data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset's utility and reliability. [ABSTRACT FROM AUTHOR]

MXene quantum dots (MQDs), an emerging zero‐dimensional nanomaterial, have garnered significant attention from researchers due to their distinctive physical and chemical properties. In this study, cysteine‐functionalized Ti3C2 MQDs were synthesized using a facile hydrothermal methods, resulting in the functionalized Ti3C2 MQDs exhibiting intense blue fluorescence attributed to size‐dependent effects and surface defects. Furthermore, the cysteine‐functionalized Ti3C2 MQDs exhibit excitation wavelength‐dependent emission behavior and serve as a highly sensitive fluorescent probe for Ag+ detection with an impressive low limit of detection (LOD) of 0.015 μM. Moreover, they demonstrate exceptional sensitivity and selectivity in determining Ag+. This study presents a novel approach for the detection of Ag+ and highlights the immense potential of cysteine‐functionalized Ti3C2 MQDs in environmental applications. [ABSTRACT FROM AUTHOR]

Due to its excellent durability and steady mechanical qualities, three‐dimensional porous polyurethane foam (PUF) presents a wide range of possibilities for flexible piezoresistive sensors. Its extreme flammability, poor electrical conductivity, and susceptibility to outside factors present serious difficulties, though. In this study, a waterborne polyurethane‐coated flexible PUF sensor that incorporates reduced graphene oxide (RGO) and polyaniline (PANI) through a methodical, step‐by‐step dip‐coating methodology is successfully developed. The final product has a water contact angle of 133°, which improves its ability to adapt to a variety of environmental circumstances. Flexible graphene sheets are incorporated to improve heat resistance and flame retardancy, and PANI and RGO provide strong bonding to the PUF framework, ensuring outstanding structural stability even after 1500 cycles. The flexible foam sensor shows promise for use in flexible piezoresistive sensors and electronic skin due to its remarkable strain monitoring range of up to 70%, quick response time of 0.39 s in sensitivity experiments, and adaptability to different physical activities like walking and gesturing. [ABSTRACT FROM AUTHOR]

This paper explores the optical limiting (OL) characteristics of an input probe field within a closed-loop asymmetric coupled quantum well (ACQW) system. Our research reveals that the application of Terahertz (THz) coupling laser fields can induce the OL behavior within the THz domain in the ACQW. The study demonstrates that revers saturable absorption arises through cross-Kerr nonlinearity, contributing to the emergence of OL behavior. Additionally, it is shown that the self-defocusing is induced concurrently within the system, further enhancing nonlinear refractive OL effects. Furthermore, it is revealed that the properties of induced OL can be manipulated by adjusting the characteristics of the applied fields. The discovered outcomes hold potential utility in safeguarding sensors and detectors operating within the THz band. [ABSTRACT FROM AUTHOR]

The current investigation theoretically presents a one-dimensional phononic crystal (PnC) as a fluidic sensor. The sensor under consideration aims to distinguish the concentration of acetic acid. The primary configuration of the proposed sensor is constructed with lead, epoxy, and a defect layer in the middle of the structure, that is filled with acetic acid (vinegar). As a result of the rise in density and decline in the speed of sound at a 100% concentration of acetic acid in comparison to pure water, the peak frequency of the output has shifted towards lower frequencies. Given that the maximum permissible concentration of acetic acid in water for vinegar is above 30%, sensor simulations were conducted within the concentration range of 25–35% with a step size of 1%. Interestingly, the sensitivity of the sensor exhibits a polynomial change in response to the concentration of acetic acid. Consequently, the highest level of sensitivity, which corresponds to the lowest concentration of vinegar, is recorded as 48.44 × 106 (Hz). The proposed system exhibits a remarkable value of the quality factor of 2802.91. Furthermore, the optimal figure of merit (FOM) is achieved when the concentration is at its lowest, with a value of 94.00. Furthermore, the temperature effects are taken into account for a wide range between 10 and 60 °C. A pronouncing sensitivity is obtained for all temperatures changes and the highest one reached the value of 1.57 × 106 (Hz/°C) at a temperature of 25 °C. Considering the present circumstances, the suggested sensor configuration has the potential to cater to a diverse array of other fluids, specifically their concentration and temperature, thereby offering a broad scope of applications. [ABSTRACT FROM AUTHOR]

A modified carbon paste sensor based on N,N′-(((ethane-1,2-diylbis(oxy))bis(2,1-phenylene))bis(methanylylidene))bis(pyridine-2-amine; BPA Schiff base as Cr(III) selective carrier was fabricated and studied in this work. The proposed sensor homogenization and mechanism of action was studied by infra-red (IR) and scanning electron microscope (SEM) with energy dispersive X-ray (EDX) tools. The sensor covered 1.0 × 10−7–1.0 × 10–1 mol L−1 linear range and a detection limit of 7.22 × 10–8 mol L−1 for Cr(III) with 20.17 ± 0.13 mV decade−1 Nernstian slope. 5 s was the response time of the prepared sensor and it was reproducible and stable for 3 months. The working pH range was 3.3–6.0 and it also works well to determine Cr(III) ion in presence of water miscible solvents up to 12.5% content of the methanol and 17.5% of ethanol. The electrode's selectivity was studied using separate and mixed solution methods for selectivity coefficients determination and the sensor showed good selectivity relative to a variety of metal ions (selectivity coefficients = 1.01 × 10−5–8.57 × 10−3). In addition, the practical analysis value of the sensor was demonstrated by measurement of Cr(III) quantitatively in mineral water, supplement and also as an indicator electrode in Cr(III) against EDTA potentiometric titration with good reproducibility (RSDs of 0.91–2.15%). [ABSTRACT FROM AUTHOR]

Predicting stratified ground consolidation effectively remains a challenge in geotechnical engineering, especially when it comes to quickly and dependably determining the coefficient of consolidation (cv${c}_{\mathrm{v}}$) for each soil layer. This difficulty primarily stems from the time‐intensive nature of the consolidation process and the challenges in efficiently simulating this process in laboratory settings and using numerical methods. Nevertheless, the consolidation of stratified ground is crucial because it governs ground settlement, affecting the safety and serviceability of structures situated on or in such ground. In this study, an innovative method utilizing a physics‐informed neural network (PINN) is introduced to predict stratified ground consolidation, relying solely on short‐term excess pore water pressure (PWP) data collected by monitoring sensors. The proposed PINN framework identifies cv${c}_{\mathrm{v}}$ from the limited PWP data set and subsequently utilizes the identified cv${c}_{\mathrm{v}}$ to predict the long‐term consolidation process of stratified ground. The efficacy of the method is demonstrated through its application to a case study involving two‐layer ground consolidation, with comparisons made to an existing PINN method and a laboratory consolidation test. The results of the case study demonstrate the applicability of the proposed PINN method to both forward and inverse consolidation problems. Specifically, the method accurately predicts the long‐term dissipation of excess PWP when cv${c}_{\mathrm{v}}$ is known (i.e., the forward problem). It successfully identifies the unknown cv${c}_{\mathrm{v}}$ with only 0.05‐year monitoring data comprising 10 data points and predicts the dissipation of excess PWP at 1‐year, 10‐year, 15‐year, and even up to 30‐year intervals using the identified cv${c}_{\mathrm{v}}$ (i.e., the inverse problem). Moreover, the investigation into optimal PWP monitoring sensor layouts reveals that installing sensors in areas with significant variations in excess PWP enhances the prediction accuracy of the proposed PINN method. The results underscore the potential of leveraging PINNs in conjunction with PWP monitoring sensors to effectively predict stratified ground consolidation. [ABSTRACT FROM AUTHOR]

ABSTRACT With the widespread worldwide adoption of location‐based service technologies, accurate and reliable driving trajectories have become crucial. However, because of the inherent deficiencies of sensor devices, accurate road matching results may not always be obtained directly from trajectory data, which poses a challenge for many location and trajectory based services. Existing map‐matching techniques mainly focus on high‐sampling‐rate trajectory data while paying relatively less attention to low‐frequency trajectory data. Low‐sampling‐rate trajectory data have greater matching difficulties than high‐sampling‐rate data owing to the limited available information. Moreover, in the case of signal loss or interference, the accuracy of map‐matching algorithms can decrease significantly for low‐sampling‐rate data. To achieve accurate map‐matching results for low‐sampling‐rate trajectory data, this study proposes a map‐matching algorithm based on probability interpolation. First, the trajectory data are denoised to eliminate redundant trajectory points. Second, the concept of the probability truth value is introduced to handle the relationship between the interpolated virtual points and actual sampled trajectory points accurately. A higher probability truth value indicates a higher confidence level of the interpolation. Third, the denoised trajectory data are interpolated and a probability truth value is assigned based on the interpolation accuracy. Finally, a comprehensive probability composed of the probability truth value, emission probability, and transition probability is used to determine the correctly matched road segments. Experimental results on real trajectory datasets demonstrated that the proposed algorithm outperformed several advanced algorithms in terms of accuracy and performance. [ABSTRACT FROM AUTHOR]

Soft force sensors enable closed loop control or autonomous operation of compliant robot systems. A stretchable force sensing surface containing an array of independent sensor units is reported. This design allows for the measurement of local shear and normal forces at multiple locations, independently, providing real‐time, multi‐axis force information at each unit. The sensor array is based on capacitive strain sensing, using liquid metal electrodes and air microchannel for high sensitivity. Electromechanical interference between adjacent sensor units is addressed and eliminated through design optimization and the use of compliant electrical shield layers. A 1D sensor array is applied to gripping tasks, where the independent sensor readings enable detecting local and partial slipping. This study illustrates how the device can be used to explore the dynamics of local forces during the stages of pick up, slip, and release. [ABSTRACT FROM AUTHOR]

The current‐state of polymer‐based humidity sensors faces numerous limitations, including energy‐costly synthesis, low sensitivity, and slow response times. This study presents innovative approach to overcome these challenges, based on a robust all‐water‐borne in situ miniemulsion polymerization. The use of water throughout the entire process mitigates the negative environmental impact. Thiol‐ene polymers reinforced with reduced graphene oxide (rGO) with concentrations ranging from 0.2–1.0 wt% are selected to fabricate these chemoresistive sensors. The selected thiol‐enes present high hydrophobicity and a semicrystalline nature, suggesting resistance to early delamination even under prolonged exposure to humidity. Incorporating rGO not only imparts electrical conductivity but also enhances mechanical and water resistance of the composite films. The 0.6% rGO composite exhibits optimal resistance for humidity sensing, demonstrating rapid and consistent responses across three exposure cycles to water vapor concentrations ranging 800–5000 ppm. Moreover, the sensor exhibits remarkable selectivity toward water vapors over these of toluene, propanol, and 4‐methyl‐2‐pentanol, attributed to the high surface hydrophilicity and inherent porosity of the waterborne film, and network structuring of rGO platelets within the matrix. In summary, this study pioneers a novel approach to polymer‐based humidity sensing, addressing key limitations while offering enhanced sensitivity, rapid response times, and superior selectivity. [ABSTRACT FROM AUTHOR]

Sensors have become more versatile and sophisticated in recent years to fulfill the increasing demands for human health applications. Physiological information such as electrocardiogram, pulse rate, and respiration are essential indications of personal health, often collected as vitals, which are typically collected from medical‐grade electrocardiogram (ECG) machines. In‐textile sensors are a fast‐growing sub‐category of wearable sensors embedded in smart textiles to acquire physiological information and movement index and provide harmful chemical warnings without compromising the comfortable nature of clothing. Recent literature has shown that integrating new materials has greatly improved the stability, specificity, and selectivity of in‐textile sensors. For example, polyvinylidene fluoride nanofiber produced a highly stretchable sensor to measure ECG readings during movement without losing data quality. This review discusses a group of nanomaterial‐based in‐textile sensors for consumer use in the home, workplace, and healthcare environments. This review will focus on exploring and analyzing the latest developments in these nanomaterial‐based e‐textiles due to their ability to be more easily integrated for daily use and their great potential for medical applications. Future work will be necessary to incorporate recycled materials, improve the method of powering these sensors, and ultimately refine the designs to be appropriate for more sustainable use. [ABSTRACT FROM AUTHOR]

This paper presents a Cosine Similarity-Based Knowledge Distillation (CSKD) for robust, lightweight object detectors. Knowledge Distillation (KD) has been effective in enhancing the performance of compact models in image classification by leveraging deep CNN models. However, the complex and multifaceted nature of object detection, characterized by its modular design and multitasking requirements, poses significant challenges for traditional KD techniques. These challenges are further compounded by the conventional reliance on the Mean Squared Error (MSE) loss function and the limited application of enhanced feature representations to the training phase. Addressing these limitations, the proposed CSKD method combines cosine similarity guidance with MSE loss to facilitate a more effective knowledge transfer from the teacher model to the student model. This is achieved by distilling both intermediate features and prediction outputs, aided by an assistant prediction branch designed to learn directly from the teacher's predictions. This dual-faceted distillation strategy enables the student model to better mimic the teacher model's behavior, leading to improved performance. The proposed method demonstrates versatility and robustness across various object detector architectures without the need for additional feature enhancement layers during training. Notably, employing ResNet-50 as the teacher model and ResNet-18 as the student model, we achieve new benchmarks in KD for object detection across several architectures, including Faster-RCNN, RetinaNet, FCOS, and GFL, with respective mAP scores of 36.6, 35.2, 35.9, and 38.9. These results highlights the effectiveness of CSKD in advancing the state-of-the-art in KD for object detection, offering a compelling solution to the challenges previously faced by traditional KD methods in this domain. The code of the proposed CSKD is available at https://github.com/swkdn16/CSKD. [ABSTRACT FROM AUTHOR]

The field of compact optical microcavities has received significant research in the past decades, and a broad range of cavity‐based micromechanical sensors has been demonstrated. The present approach replaces the frequently employed, complex etched cantilever and membrane structures with a simple thin‐film system based on a compressible photonic microcavity to achieve pressure‐sensitive wavelength shifting of resonant modes. The effects of a topological dielectric mirror architecture on the light propagation in the system are extensively investigated. Topologically improved light‐matter interaction is experimentally demonstrated for systems where thin‐film devices are mounted on one side of the photonic cavity due to mechanical constraints. Coupled topological states are examined under the aspect of mode splitting and exhibit advantageous splitting tunability compared to non‐topological systems. The findings are complemented by the proposal of a simple spectral evaluation method allowing significant improvement in the precision of integrated Fabry‐Pérot sensors. The readout concept of the presented sensor allows a scalable improvement of the measurement precision by evaluating the resonant‐mode order in the deformable cavity. The experimental results and conceptual advancements provide pathways for significant improvements addressing the efficiency of light‐matter interaction in Fabry‐Pérot cavities and the readout precision of sensors incorporating thin‐film photodiodes in multimode photonic cavities. [ABSTRACT FROM AUTHOR]

In recent years, China has launched a number of Gaofen (GF) series earth observation satellites. It is crucial to understand the relationship between the data of the GF series of satellite sensors for the selection of sensor images for scientific research. Taking the same-day transit image pairs of three regions as the study data, this paper compares the consistency of the Top of Atmosphere (TOA) reflectance of GF-1 WFV4 and GF-6 WFV sensors by using the TOA mean comparison method, and discusses the differences in water body and vegetation extraction. The results indicate that the satellite signal intensity in different land cover types and areas differs significantly. In the bare soil-dominated region, GF-1 WFV4 has a larger signal strength than GF-6 WFV, while in the vegetation-dominated region, it turns out to be just the opposite. The difference between the two sensors is mainly related to the difference in the spectral response function and the radiometric resolution of the two satellites. In addition, the determination coefficient (R2) of the corresponding bands of the two sensors is all greater than 0.90, indicating that the two sensors have strong linear correlation and good complementarity. [ABSTRACT FROM AUTHOR]

The influence of grating filling factor on the spectral sensitivity of sensors, characterized by full width at half maximum (FWHM) and a figure of merit (FOM), operating on the principle of waveguide mode resonance in dielectric gratings formed on a substrate, has been investigated. Resonant wavelengths were determined for varying grating thicknesses and filling factors. Sensitivity values were obtained for normally and obliquely incident plane waves, as well as for Gaussian beams. Additionally, a scaling rule is presented, allowing determination of sensor parameters using a calculator based on identical grating parameters and corresponding resonant wavelengths. This method holds when linear dimensions of the grating and tested wavelengths are scaled proportionally. [ABSTRACT FROM AUTHOR]

To meet the demand for estimating actuator and sensor faults simultaneously in a class of repetitive nonlinear time‐delay systems, this paper proposes a novel fault estimation strategy based on an iterative learning scheme. Firstly, an iterative‐learning‐based fault estimation law is designed to estimate actuator faults while system is free of sensor failures. Both the fixed initial shift and random one are taken into consideration. Secondly, a novel sensor fault observer is proposed based on an augmented state variable which consists of original system state and sensor fault signal; output compensation strategy is also provided to ensure the iterative‐learning‐based actuator fault estimation method is effective considering the existence of sensor failures. In addition, theorems based on λ$$ \lambda $$‐norm and linear matrix inequality are provided to determine values or ranges of gain matrices and parameters in proposed sensor fault observer and iterative‐learning‐based actuator fault estimation law. Finally, two simulation examples are provided to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Under the influence of sensor saturation and packet dropout, this paper is concerned with the fault detection (FD) problem for a class of nonlinear systems with two additive time‐varying delay components. In the addressed measurement model, the sensor is assumed to have two communication channels, which can contribute to improving the probability of successfully delivering the measurements. A FD filter is designed to generate residual signals, and the sufficient criteria are established to ensure the stochastic finite‐time stability (SFTS) of the residual system with H∞$$ {H}_{\infty } $$ performance constraint by constructing new Lyapunov‐Krasovskii functionals. Based on the established criteria, the explicit expression of the desired FD filter is obtained via solving a set of linear matrix inequalities (LMIs). Finally, the usefulness of the proposed FD scheme is verified by a simulation example. [ABSTRACT FROM AUTHOR]