Sensor Characteristics Research Articles

Design and Comparative Characterization of Water Level IDE Sensors at Resonant Frequencies

Background: This paper reports the design and characterization of three Interdigital electrode (IDE) water-level sensors at resonant frequencies. The geometries of the proposed IDE sensors are comb type, circular type, and Archimedean spiral type. These IDE sensors have been fabricated by the printed circuit board technology. The sensor’s performance has been evaluated on both tap and distilled water. Methods: The multiple resonant frequencies are investigated for the frequency span of 40 Hz to 110 MHz using a 4294A impedance analyzer. The peak of the projected admittance graph appeared at the first resonant frequency. This first resonant frequency is chosen here for the characterization of the proposed sensors. Results: The study asses that the variations in resonant frequency are caused by both the sensor's geometry and the water under test. The resonant frequency subtly states that sensors can be presented as lumped element equivalent series RLC circuits. In this work, an attempt has been made to show that the change in capacitance plays a pivotal role in estimating the resonant frequency. It is found that the sensor’s sensitivity decreases with water elevation and always be negative. Conclusion: The circular and Archimedean spiral sensors have comparable sensitivity performance, while the comb IDE sensor is found to be the most sensitive. The IDE sensor features the highest sensitivity at 1 cm of water elevation. The circular and spiral IDE sensor more closely follows the reference resonant frequency fr α 1/(√C) when compared with the comb IDE sensor.

Advancing oil and gas pipeline monitoring with fast phase fraction sensor

Abstract In the oil and gas sector, the design of monitoring equipment usually prioritizes durability and long-term reliability. However, such equipment does not provide resolution for scientific research, where capturing transient and dynamic events is crucial to enhancing flow understanding. This work describes the development of a capacitive sensor system optimized for phase fraction measurements in oil-gas industrial environments. The sensor features high sensitivity and temporal resolution to meet flow measurement investigative requirements. The measurement technique is based on the electrical capacitance variations of the flowing media and was validated with reference equipment. Six sensors were deployed across multiple test stations to analyze the slug flow regime and its evolution along the pipe. The data collected from these experiments were processed, and flow parameters were compared with a model that describes the elongated bubble shape found in the slug flow pattern. Results show a good agreement between the experimental data and the model, validating its capability to track the fast-changing phases of multiphase flow. The uncertainty analysis revealed a maximum absolute uncertainty of 1.65% for the gas fraction measurements. Further, the gas flow rate was evaluated with a good agreement against the reference gas flow meter, ensuring the sensor's reliability in dynamic multiphase flow environments. By providing accurate experimental data from real-world industrial conditions, the developed sensor can significantly enhance the precision of flow models, thereby improving the understanding of complex flow phenomena.

Effect of sensor noise characteristics and calibration errors on the choice of IMU-sensor fusion algorithms

This paper focuses on accurate and precise orientation estimation with consumer-grade MEMS-IMUs for ‘slow’ orientation change and ‘short’-time applications. A simulation platform is developed to predict a suitable algorithm for a MEMS-IMU of known noise specifications, improving similar works. Experimentally measured noise characteristics of two commercial grade IMUs (MPU9250 and BNO055) are used in the simulation platform to generate simulated data and evaluate some popular orientation estimation algorithms along with two new Kalman filter-based algorithms. Real experiments are conducted with the same IMUs using an electromagnetic tracker as reference sensor. The output orientation results for two new improved algorithms are compared with other algorithms in simulations and real experiments. We show that the choice of the ‘best’ algorithm varies with the noise characteristics of individual sensors within the sensor module. The two new best-performing algorithms tested achieve<1˚ RMS angle error for the two low-cost consumer-grade IMUs.

Virtual Tools for Testing Autonomous Driving: A Survey and Benchmark of Simulators, Datasets, and Competitions

Traditional road testing of autonomous vehicles faces significant limitations, including long testing cycles, high costs, and substantial risks. Consequently, autonomous driving simulators and dataset-based testing methods have gained attention for their efficiency, low cost, and reduced risk. Simulators can efficiently test extreme scenarios and provide quick feedback, while datasets offer valuable real-world driving data for algorithm training and optimization. However, existing research often provides brief and limited overviews of simulators and datasets. Additionally, while the role of virtual autonomous driving competitions in advancing autonomous driving technology is recognized, comprehensive surveys on these competitions are scarce. This survey paper addresses these gaps by presenting an in-depth analysis of 22 mainstream autonomous driving simulators, focusing on their accessibility, physics engines, and rendering engines. It also compiles 35 open-source datasets, detailing key features in scenes and data-collecting sensors. Furthermore, the paper surveys 10 notable virtual competitions, highlighting essential information on the involved simulators, datasets, and tested scenarios involved. Additionally, this review analyzes the challenges in developing autonomous driving simulators, datasets, and virtual competitions. The aim is to provide researchers with a comprehensive perspective, aiding in the selection of suitable tools and resources to advance autonomous driving technology and its commercial implementation.

Flexible, Breathable and Hydrophobic SnO2–SnS2–SiO2/SiO2 All‐Inorganic Self‐Supporting Nanofiber Membrane for Ultralow‐Concentration NO2 Sensing Under High Humidity

AbstractInorganic semiconductor gas sensors, being widely utilized in gas‐sensing applications, face significant challenges in attaining mechanical flexibility and humidity resistance in wearable sensing fields. Herein, a highly flexible, breathable, and hydrophobic all‐inorganic self‐supporting nanofiber (NF) gas sensor is developed using electrospinning combined with thermal sulfidation approach. This innovative sensor features a bilayer configuration, with an amorphous SiO2 nanofiber substrate layer and an interwoven SiO2 and SnO2–SnS2 nanofiber active layer. The relatively low elastic modulus of the amorphous SiO2 nanofibers, combined with the three‐dimensional network interwoven structure, endow the SnO2–SnS2–SiO2/SiO2 sensor with superior mechanical flexibility. The sensor exhibits excellent sensitivity, selectivity, moisture resistance, and cycling stability (&gt;10 000 cycles at 140° bending) to both high and low concentration NO2. Notably, an excellent flexible detecting capability of the sensor to NO2, an asthma‐related biomarker, is demonstrated at ultralow concentrations (≈25 ppb) in simulated exhaled breath environments. The enhanced moisture resistance is attributed to the effective inhibition of hydrogen bond formation from H2O molecules by the Sn─S bonds formed through sulfidation of SnO2 nanofibers. This work represents a substantial advancement in the universal fabrication of flexible, breathable and moisture‐resistant inorganic semiconductor sensors for wearable breath sensing applications.

Effect of radiofrequency bias power on transmission spectrum of flat-cutoff sensor in inductively coupled plasma

Real-time monitoring of plasma parameters at the wafer plane is important because it significantly affects the processing results, yield enhancement, and device integrity of plasma processing. Various plasma diagnostic sensors, including those embedded in a chamber wall and on-wafer sensors, such as flat-cutoff sensors, have been developed for plasma measurements. However, to measure the plasma density on the wafer surface in real-time when processing plasma with bias power, such as in the semiconductor etching process, one must analyze the transmission spectrum of the flat-cutoff sensor in an environment with bias power applied. In this study, the transmission-spectrum and measured plasma-density characteristics of an electrode-embedded flat-cutoff sensor are analyzed via electromagnetic simulations and experiments under applied bias power. Our findings indicate that the flat-cutoff sensor accurately measures the plasma density, which is equivalent to the input plasma density under low bias power. Conversely, under high bias power, the plasma density measured by the sensor is lower than the input plasma density. Also, a thick-sheath layer is formed owing to the high bias power, which may complicate the measurement of plasma parameters using the flat-cutoff sensor. Plasma diagnostics using a flat-cutoff sensor in thick-sheath environments can be achieved by optimizing the flat-cutoff sensor structure. Our findings can enhance the analysis of plasma parameters on-wafer surfaces in processing environments with bias power applied.

Miniaturized Antenna Design for Wireless and Powerless Surface Acoustic Wave Temperature Sensors.

This paper presents the introduction, design, and experimental validation of two small helical antennae. These antennae are a component of the surface acoustic wave (SAW) sensor interrogation system, which has been miniaturized to operate at 915 MHz and aims to improve the performance of wireless passive SAW temperature-sensing applications. The proposed antenna designs are the normal-mode cylindrical helical antenna (CHA) and the hemispherical helical antenna (HSHA); both designed structures are developed for the ISM band, which ranges from 902 MHz to 928 MHz. The antennae exhibit resonance at 915 MHz with an operational bandwidth of 30 MHz for the CHA and 22 MHz for the HSHA. A notch occurs in the operating band, caused by the characteristics of the SAW sensor. The presence of this notch is crucial for the temperature measurement by aiding in calculating the frequency shifting of that notch. The decrement in the resonance frequency of the SAW sensor is about 66.67 kHz for every 10 °C, which is obtained by conducting the temperature measurement of the system model across temperature environments ranging from 30 °C to 90 °C to validate the variation in system performance.

Design and on-orbit performance evaluation of Ethiopian earth observation satellite multispectral optical imaging payload

The Ethiopian Earth observation micro-satellite was successfully launched into a sun-synchronous orbit equipped with an optical multispectral imaging payload system. This optical multispectral imaging payload camera weighs 1.4 kg with four spectral bands: RGB and NIR, each having a unique spectral range. Furthermore, it has a field of view of 7.4°×0.3°, a relative F-number of 9.8°, and a spectral range of 0.45∼0.9μm. The present article covers the design and on-orbit performance analysis of the ETRSS-1 electro-optical imaging payload system, which is based on the COTS compact and unobscured off-axis three-mirror anastigmatic system for high-resolution imaging. Additionally, selecting an appropriate imaging sensor, optomechanical architecture, and performance characteristics for optical instruments is investigated to evaluate spatial, spectral, and radiometric requirements and the payload’s on-orbit performance and capability.

Temperature-based energy changes in gold nanowire sensors for flow rate detection and failure prediction

This study delves into the dynamic operational states of nanowire sensors within microfluidic channels for flow velocity detection, classifying these states into decline, steady, and failure states. It conducts a comparative analysis of the steady-state operational characteristics of nanowire sensors across various voltages and inlet flow rates, alongside examining the interplay between nanowire resistivity and temperature. This investigation identifies an optimal working condition for the sensor at a 1 V operating voltage and a nanowire dimension of 150 × 150 nm. Employing both theoretical and experimental approaches, the research elucidates the convective heat transfer mechanism that underpins the functionality of the nanowire sensor for flow rate detection. It unveils the pattern of nanowire temperature changes during inlet flow rate measurement within a range from 10 to 50 μL/min range and establishes standard values of temperature and calorimetric differences for various flow velocities. Furthermore, the study achieves the prediction of the time to reach the steady and failure states under given operational conditions for the nanowire-based sensor. This advancement will enhance the reading precision of the signal output from the nanowire sensor, mitigate the risk of sensor failure, and contribute to prolonging the operational lifespan of equipment.

Mechanoluminescence of ZnS: Cu@Al2O3 enabled optical fiber microlens passive tactile sensor for hardness recognition.

We propose an optical fiber microlens (OFM) passive tactile sensor (OFMPTS) for hardness recognition. The sensor features a core-shell structure, with an OFM as the core and an elastic mechanoluminescence (ML) matrix shell, which is composed of ZnS: Cu@Al2O3 doped with 10 nm SiO2 particles and polydimethylsiloxane (PDMS). Utilizing the Hertz model, the ML intensity of the sensor is correlated to the elastic modulus of the sample, which enables precise hardness detection. The microlens fiber structure significantly enhances photon collection efficiency, thereby allowing for effective coupling of the ML signal. In press mode, OFMPTS differentiates between five PDMS hardness levels. It can also operate in scan or tap mode, identifying hidden foreign bodies and tissue masses through response curve analysis. The sensor, which requires no external light source, expands the capabilities of optical hardness measurement.

Establishing Healthy Breath Baselines With Tin Oxide Sensors: Fundamental Building Blocks for Noninvasive Health Monitoring.

Volatile organic compounds (VOCs) in breath serve as a source of biomarkers for medical conditions relevant to warfighter health including Corona Virus Disease and other potential biological threats. Electronic noses are integrated arrays of gas sensors that are cost-effective and miniaturized devices that rapidly respond to VOCs in exhaled breath. The current study seeks to qualify healthy breath baselines of exhaled VOC profiles through analysis using a commercialized array of metal oxide (MOX) sensors. Subjects were recruited/consented through word of mouth and using posters. For each sample, breath was analyzed using an array of MOX sensors with parameters that were previously established. Data were also collected using a lifestyle questionnaire and from a blood test to assess markers of general health. Sensor data were processed using a feature extraction algorithm, which were analyzed through statistical approaches to identify correlations with confounding factors. Reproducibility was also assessed through relative standard deviation values of sensor features within a single subject and between different volunteers. A total of 164 breath samples were collected from different individuals, and 10 of these volunteers provided an additional 9 samples over 6 months for the longitudinal study. First, data from different subjects were analyzed, and the trends of the 17 extracted features were elucidated. This revealed not only a high degree of correlation between sensors within the array but also between some of the features extracted within a single sensor. This helped guide the removal of multicollinear features for multivariate statistical analyses. No correlations were identified between sensor features and confounding factors of interest (age, body mass index, smoking, and sex) after P-value adjustment, indicating that these variables have an insignificant impact on the observed sensor signal. Finally, the longitudinal replicates were analyzed, and reproducibility assessment showed that the variability between subjects was significantly higher than within replicates of a single volunteer (P-value = .002). Multivariate analyses within the longitudinal data displayed that subjects could not be distinguished from one another, indicating that there may be a universal healthy breath baseline that is not specific to particular individuals. The current study sought to qualify healthy baselines of VOCs in exhaled breath using a MOX sensor array that can be leveraged in the future to detect medical conditions relevant to warfighter health. For example, the results of the study will be useful, as the healthy breath VOC data from the sensor array can be cross-referenced in future studies aiming to use the device to distinguish disease states. Ultimately, the sensors may be integrated into a portable breathalyzer or current military gear to increase warfighter readiness through rapid and noninvasive health monitoring.

Silver-based bimetallic nanozyme fabrics with peroxidase-mimic activity for urinary glucose detection

The enhanced catalytic properties of bimetallic nanoparticles have been extensively investigated. In this study, bimetallic Ag-M (M = Au, Pt, or Pd) cotton fabrics were fabricated using a combination of electroless deposition and galvanic replacement reactions, and improvement in their peroxidase-mimicking catalytic activity compared to that of the parent Ag fabric was studied. The Ag-Pt bimetallic nanozyme fabric, which showed the highest catalytic activity and ability to simultaneously generate hydroxyl (•OH) and superoxide (O2•−) radicals, was assessed as a urine glucose sensor. This nanozyme fabric sensor could directly detect urinary glucose in the pathophysiologically relevant high millimolar range without requiring sample predilution. The sensor could achieve performance on par with that of the current clinical gold standard assay. These features of the Ag-Pt nanozyme sensor, particularly its ability to avoid interference effects from complex urinary matrices, position it as a viable candidate for point-of-care urinary glucose monitoring.Graphical

Smart and accurate detection of nanoplastics in aquatic environments by photoelectrochemical-electrochemical dual-mode portable sensor

The harmful effects of nanoplastics (NPs) on both human health and the ecosystem have gained global attention. This study develops a photoelectrochemical-electrochemical (PEC-EC) dual-mode portable sensor based on CdS/CeO2 heterojunction for the rapid detection of polystyrene nanoplastics (PS NPs) in aquatic environments. The interaction and aggregation between protein and PS NPs, facilitated by hydrophobic properties, influence electron transfer, thereby enabling the detection of PS NPs. Integration of the sensor with a portable EC workstation controlled by a smartphone streamlines the detection process, yielding rapid and clear results, and enhancing convenience for detection. The sensor exhibits the advantages of high sensitivity, good repeatability, and exceptional portability. A wide detection linear range of 0.5–800 μg/mL accompanied by the detection limit of 0.38 ng/mL can be achieved. The relative standard deviation of the sensor for the inter-day (intra-day) precision are determined ranging from 0.4 % to 2.97 % (0.94 % to 4.65 %) in real water samples. Furthermore, the sensor features a self-checking function, establishing it as a dual-mode system that introduces a novel approach for smart detection of PS NPs, with substantial potential for assessing PS NPs pollution in aquatic environments.

A Novel Soft and Inflatable Strain-based Tactile Sensing Balloon for Enhanced Diagnosis of Colorectal Cancer Polyps Via Colonoscopy.

In this paper, with the goal of addressing the lack of tactile feedback in colorectal cancer (CRC) polyps diagnosis using a colonoscopy procedure, we propose the design and fabrication of a novel soft and inflatable strain-based tactile sensing balloon (SI-STSB). The proposed soft sensor features a unique stretchable sensing layer - that utilizes a liquid metal injected within spiral-shape microchannels of a stretchable substrate - and is integrated with a unique inflatable balloon mechanism. The proposed SI-STSB has been thoroughly characterized through different calibration experiments. Results demonstrate a phenomenal adjustable sensitivity with low hysteresis behavior under different experimental conditions for this sensor making it a great candidate for enhancing the existing diagnosis procedures.

An Object-Centric Hierarchical Pose Estimation Method Using Semantic High-Definition Maps for General Autonomous Driving.

To achieve Level 4 and above autonomous driving, a robust and stable autonomous driving system is essential to adapt to various environmental changes. This paper aims to perform vehicle pose estimation, a crucial element in forming autonomous driving systems, more universally and robustly. The prevalent method for vehicle pose estimation in autonomous driving systems relies on Real-Time Kinematic (RTK) sensor data, ensuring accurate location acquisition. However, due to the characteristics of RTK sensors, precise positioning is challenging or impossible in indoor spaces or areas with signal interference, leading to inaccurate pose estimation and hindering autonomous driving in such scenarios. This paper proposes a method to overcome these challenges by leveraging objects registered in a high-precision map. The proposed approach involves creating a semantic high-definition (HD) map with added objects, forming object-centric features, recognizing locations using these features, and accurately estimating the vehicle's pose from the recognized location. This proposed method enhances the precision of vehicle pose estimation in environments where acquiring RTK sensor data is challenging, enabling more robust and stable autonomous driving. The paper demonstrates the proposed method's effectiveness through simulation and real-world experiments, showcasing its capability for more precise pose estimation.

Development of a Plasma-Based Nanosensor Platform for Triage of Neurological Tumors

Neurological tumors have diverse etiologies and treatments. Presently, diagnostic technologies such as MRI or CT scans are limited by poor resolution, and thus imprecise identification of tumor classes. As a result, diagnostic methods rely on highly invasive intracranial biopsies for conclusive tumor identification. Development of non-invasive methods to accurately identify tumor class may lead to earlier and more accurate diagnoses, enabling prompt and targeted treatment strategies. To address this unmet clinical need, we report the development a molecular-recognition-based nanosensor array that can accurately identify a molecular fingerprint of glioma and meningioma from plasma. We developed this capability using sensor arrays of chemically modified carbon nanotubes that can transduce subtle differences in the physicochemical properties of molecules in biofluids via sensitive molecular binding interactions. Using high-throughput near-infrared fluorescence spectroscopy, we screened 23 chemically modified (6,5) carbon nanotubes sensors in 324 patient plasma samples. We trained machine learning models to classify sensor responses as coming from either glioma or meningioma tumors. The best performing models were able to achieve a positive predictive value of 0.75. Sensor feature analysis revealed a set of spectral features positively associated with class differentiation. This work has the potential to aid clinical care by facilitating the early triage of different types of tumors to provide better treatment options for patients.

Application of silicon nanowires in sensors of temperature, light and humidity

Resistive and capacitive types of sensors based on silicon nanowires (SiNWs) for measuring of physical quantities have been manufactured. Silicon nanowires were obtained through a two-step metal-assisted chemical etching (MACE) method. The surface morphology of the silicon nanowire array was investigated using atomic force microscopy (AFM) and scanning electron microscopy (SEM). The impact of SiNWs synthesis parameters on sensor sensitivity has been investigated. In particular, the influence of deposition time of AgNPs and etching time of silicon, as well as the content of H2O2 in the etchant, preliminary texturing of the substrate, and additional post-processing in isotropic/anisotropic etchant after the MACE process, on the characteristics of physical quantity sensors has been determined. Static and dynamic parameters were calculated for the obtained sensors. To compare the obtained sensors, physical sensors without SiNWs were manufactured. The highest response value for temperature sensors was 132, which is two orders of magnitude better than for sensors without SiNWs. The presence of SiNWs on the surface of the sensor led to an increase in the response value by about two orders of magnitude for all types of sensors. The speed of humidity sensors improved by 3–4 times, and for temperature and light sensors by an order of magnitude. Further device applications include of multi-parameter sensors, human breath sensors, and solar radiation power sensors.

Very High Temperature Hall Sensors in a Wafer‐Scale 4H‐SiC Technology

Abstract4H‐SiC is a key enabler for realizing integrated electronics operating in harsh environments, which exhibit very high temperatures. Through advances in 4H‐SiC process technology, different sensor and circuit types have been demonstrated to operate stable at temperatures as high as 800 °C, paving the way toward harsh‐environment immune smart sensors. In this work, for the first time the operation of ion‐implanted 4H‐SiC Hall sensors realized in a wafer scale Bipolar‐CMOS‐DMOS technology is demonstrated at a wide operation temperature range spanning room temperature up to 500 °C in addition to short‐term operation up to 600 °C. The temperature‐dependent sensor characteristics of 15–22 samples are evaluated in terms of sensitivity and noise. The small inter‐device variations reflect the stability of the used process for very high temperature Hall sensors. The noise‐limited detectivity is further evaluated, revealing a best value of 950 nT/ and a mean detectivity of 1 µT/ at 500 °C. This is the best value reported up to date for very high temperature Hall sensors, besides being the first demonstration of ion‐implanted wide‐bandgap Hall sensors. Overall, the results reflect the potential of the demonstrated Hall sensors for the next generation of integrated magnetic field sensors in harsh environments.

Lensless multi-spectral holographic interferometry for optical inspection

We explore the principles, implementation details, and performance characteristics of a lensless multi-spectral digital holographic sensor and demonstrate its potential for quality assurance in semiconductor manufacturing. The method is based on capturing multi-spectral digital holograms, which are subsequently utilized to evaluate the shape of a reflective test object. It allows for a compact setup satisfying high demands regarding robustness against mechanical vibrations and thus overcomes limitations associated with conventional optical inspection setups associated with lens-based white light interferometry. Additionally, the tunable laser source enhances the versatility of the system and enables adaptation to various sample characteristics. Experimental results based on a wafer test specimen demonstrate the effectiveness of the method. The axial resolution of the sensor is ±2.5 nm, corresponding to 1σ.

Fiber optic relative humidity and temperature sensor with the cascaded Vernier effect based on the C-shaped cavity structure.

The water-absorbent sensing film, coated on the surface of traditional optical fiber humidity sensors, often suffers from detachment issues. In this paper, we present what we believe to be a new fiber-optic cascaded Fabry-Perot interferometer sensor for detecting relative humidity (RH) and temperature, without the need for sophisticated instrumentation. The sensing structure comprises two sections of single-mode optical fibers and a C-shaped cavity between them. The C-shaped cavity is created by grinding the side of a hollow-core fiber with fiber optic abrasive paper. The Vernier effect arises from the cascaded interaction between the C-shaped cavity filled with ultraviolet optical glue (NOA61) and the subsequent single-mode fiber pigtail. The sensor exhibits a high RH sensitivity of 0.248 nm/%RH (35-95%RH) and an RH resolution of up to 0.08%RH. It also has high-temperature sensitivities of -1.091 nm/°C (25 - 65°C). Furthermore, simultaneous measurement of RH and temperature is achieved by establishing a dual parameter matrix, and the sensor's response time and recovery time for RH and temperature are within 300s. Therefore, this work provides a simple and cost-effective manufacturing process and the proposed RH and temperature sensor features a compact size, strong environmental adaptability, and significant potential for practical applications.