Sensor Performance Research Articles

Investigation of Fiber Bragg Grating Sensor Measurability in Concrete Beams under Static Load Conditions

Recent advances in construction materials and architecture have enhanced the safety of modern structures, which now feature higher, lighter, and more unique designs. Bridges, as critical infrastructure, face increasing load demands due to rising traffic volumes, leading to accelerated structural deterioration. This necessitates more frequent inspections and maintenance, resulting in increased costs and potential operational disruptions. Real-time built-in monitoring systems are thus essential for both new and aging structures. Fiber Optic Sensor (FOS) technology, particularly Fiber Bragg Grating (FBG) sensors, offers a reliable and stable solution for long-term Structural Health Monitoring (SHM). This study evaluates the performance and applicability of FBG sensors (FBGs) in comparison to traditional strain gauges (SGs) for capturing strains, loads, deflections, and temperature in full-scale beams under static loads. Four large-scale reinforced concrete (RC) and CFRP-strengthened beams were tested. Nonlinear finite element analysis (NLFEA) using VecTor2 was employed to simulate the behavior of these beams under static loading. Data from FBGs were compared to those from collocated electrical SGs. The results demonstrated the reliability and flexibility of FBGs in monitoring structural performance. Notably, FBGs continued to provide accurate readings even after the specimens reached their maximum load, showcasing their endurance and resilience compared to conventional SGs.

Engineering Steep Subthreshold Swings in High-Performance Organic Field-Effect Transistor Sensors.

Organic field-effect transistor (OFET)-based sensors have gained considerable attention for information perception and processing in developing artificial intelligent systems owing to their amplification function and multiterminal regulation. Over the last few decades, extensive research has been conducted on developing OFETs with steep subthreshold swings (SS) to achieve high-performance sensing. In this review, based on an analysis of the critical factors that are unfavorable for a steep SS in OFETs, the corresponding representative strategies for achieving steep SS are summarized, and the advantages and limitations of these strategies are comprehensively discussed. Furthermore, a bridge between SS and OFET sensor performance is established. Subsequently, the applications of OFETs with steep SS in sensor systems, including pressure sensors, photosensors, biochemical sensors, and electrophysiological signal sensors. Lastly, the challenges faced in developing OFET sensors with steep SS are discussed. This study provides insights into the design and application of high-performance OFET sensor systems.

Flexible highly-sensitive pressure sensor based on rGO/Fe nanowires composites for wearable human health detection

Flexible pressure sensors applied in wearable detection often face challenges, such as low sensitivity, large device size, poor flexibility, and long response time. This study aims to design and develop high-performance pressure-sensitive materials for wearable human detection applications. Using a sensitive layer composite and microstructural design, rGO/Fe nanowires (NWs) composites were proposed as the pressure-sensitive material. This approach yields a compact sensor with high flexibility, good mechanical properties, and excellent sensing performance. Firstly, rGO/Fe NWs composites were prepared by the Hummers method and an in situ reduction technique under a magnetic field. Secondly, the structural design, component construction, and sensing mechanism of the sensors were thoroughly investigated. Finally, the performance of the flexible pressure sensor was tested, and its application in the wearable field was explored. The results demonstrate that the sensor exhibits excellent performance with a good response to both large and small pressures within the range of 0–30 kPa, providing an effective method for wearable human health detection.

Enhancing Sensing Performance of Capacitive Sensors Using Kirigami Structures

Capacitive sensors have widespread applications in human-machine interaction, Internet of Things, and smart home systems due to their low cost, high sensitivity, and ease of integration. However, improving the sensitivity and sensing distance of capacitive sensors remains a challenging issue. This study proposes a novel capacitive sensor design method based on Kirigami structures, which enhances sensor performance by introducing specific cutting patterns into the conductive layer to leverage edge effects. Through experimental testing and statistical analysis, we systematically investigated the influence of Kirigami geometric parameters on sensor sensitivity and sensing distance. We designed and fabricated 12 different Kirigami structures, including circular flower patterns, array patterns, layered pointed flower patterns, and circular strip structures, and compared them with traditional non-cut structures. The results show that Kirigami structures significantly improved sensor performance. Compared to traditional sensors without Kirigami structures, optimally designed Kirigami capacitive sensors demonstrated approximately a 3-fold increase in sensitivity and up to 170 percent extension in sensing distance. Multivariate regression analysis and nonlinear models revealed complex relationships between Kirigami structural parameters and sensor performance. Notably, the circular strip (three-layer) structure exhibited the best performance, possibly due to its maximization of edge effects and optimization of electric field distribution. This study provides new design insights for developing high-performance capacitive sensors, with potential applications in improving smart home systems and indoor activity monitoring for solitary elderly individuals.

LIG-Based High-Sensitivity Multiplexed Sensing System for Simultaneous Monitoring of Metabolites and Electrolytes

With improvements in medical environments and the widespread use of smartphones, interest in wearable biosensors for continuous body monitoring is growing. We developed a wearable multiplexed bio-sensing system that non-invasively monitors body fluids and integrates with a smartphone application. The system includes sensors, readout circuits, and a microcontroller unit (MCU) for signal processing and wireless communication. Potentiometric and amperometric measurement methods were used, with calibration capabilities added to ensure accurate readings of analyte concentrations and temperature. Laser-induced graphene (LIG)-based sensors for glucose, lactate, Na+, K+, and temperature were developed for fast, cost-effective production. The LIG electrode’s 3D porous structure provided an active surface area 16 times larger than its apparent area, resulting in enhanced sensor performance. The glucose and lactate sensors exhibited high sensitivity (168.15 and 872.08 μAmM−1cm−2, respectively) and low detection limits (0.191 and 0.167 μM, respectively). The Na+ and K+ sensors demonstrated sensitivities of 65.26 and 62.19 mVdec−1, respectively, in a concentration range of 0.01–100 mM. Temperature sensors showed an average rate of resistance change per °C of 0.25%/°C, within a temperature range of 20–40 °C, providing accurate body temperature monitoring.

Multi-Electrode Extended Gate Field Effect Transistors Based on Laser-Induced Graphene for the Detection of Vitamin C and SARS-CoV-2.

Despite the clinical data showing the importance of ascorbic acid (AA or vitamin C) in managing viral respiratory infections, biosensors for their simultaneous detection are lacking. To address this need, we developed a portable and wireless device for simultaneous detection of AA and SARS-CoV-2 virus by integrating commercial transistors with printed laser-induced graphene (LIG) as the extended gate. We studied the effect of laser printing pass number and showed that with two laser printing passes (2-pass LIG), the sensor sensitivity and limit of detection (LOD) for AA improved by a factor of 1.6 and 12.8, respectively. Using complementary characterization methods, we attribute the improved response to a balanced interplay of crystallinity, defect density, surface area, surface roughness, pore density and diameter, and mechanical integrity/stability. These factors enhance analyte transport, reduce noise/variability, and ensure consistent sensor performance, making 2-pass LIG the most effective material in this work. Our sensors exhibit promising performance for detecting AA with a selective response in the presence of common salivary interfering molecules, with sensitivity and LOD of 73.67 mV/dec and 54.04 nM in 1× phosphate buffered saline and 81.05 mV/dec and 78.34 nM in artificial saliva, respectively. We also showed that functionalization of the 2-pass LIG gate with S-protein antibody enables the detection of SARS-CoV-2 protein antigens with an ultralow LOD of 52 zg/mL─an improvement of more than 10-fold compared to 1-pass LIG─and 4 particles/mL for virion mimics with a selective response against influenza virus and multiple human coronavirus strains. With low signal drift/hysteresis and wireless capabilities, the developed device holds great potential for improving at-home monitoring and clinical decision-making.

Optimal design parameter estimation and analytical investigation of MEMS quadruple touch mode capacitive pressure sensor

Purpose Touch mode capacitive pressure sensors (TMCPS) offer superior sensitivity and linearity in comparison to normal mode CPS and have therefore seen substantial improvements in modeling and construction. This study aims to develop a sensor that is highly robust, with near-linear output characteristics, increased sensitivity and superior overload protection, making it an ideal choice for deployment in harsh industrial environments. Design/methodology/approach The proposed sensor design uses a substrate with a multi-step notch, introducing a new quadruple TMCPS and uses a small deflection model for mathematical analysis. Addition of a multi-step notch to traditional touch mode capacitive sensors results in quadruple touch regions which further enhances its operational range performance. Findings The simulation of diaphragm deflection in response to pressure is carried out by using COMSOL Multiphysics, whereas MATLAB is used for analytical simulations pertaining to variations in capacitance and capacitive sensitivity. Comparing with earlier models, there is a noticeable enhancement in capacitance, experiencing a fivefold increase. The achieved value stands at 50.1 pF, reflecting improved sensitivity for applied pressure ranging from 0 to 2 MPa. Originality/value In existing literature to improve the performance of the single TMCPS, a double-sided TMCPS has been developed. To enhance sensor performance, a substrate with a multi-step notch is proposed. The notch creates four touch regions with varying gap depths, resulting in increased capacitance and capacitive sensitivity.

Detection of Serratia marcescens and Mierococcus lysodeikticus Bacterial Cells Using Cerium Oxide/Transition Metal Dichalcogenides Heterostructure‐Based Surface Plasmon Resonance Sensor

This article explores a novel surface plasmon resonance sensor for detecting the Serratia marcescens and Mierococcus lysodeikticus bacteria cells employing the cerium oxide (CeO2) and transition metal dichalcogenides heterostructure. The proposed sensor is designed based on the Kretschmann configuration, where silver (Ag) is deposited over a prism's surface to excite the surface plasmons. The transfer matrix method and angular interrogation technique are exploited for analyzing the sensor's performance at a wavelength of 633 nm. Firstly, the optimization of the prism and metal film is analyzed by selecting the minimum reflectance, better sensitivity, and quality factor. Secondly, the influence of the proposed structure in the sensor is executed by the performances of different structures, which are made with defined layers. Thirdly, different sensing parameters are analyzed for the considered bacterial cells, resulting in the maximum attained parameters being a sensitivity of 369.40° RIU−1, QF of 151.35 RIU−1, and detection accuracy of 7.57. Finally, the comparative study also shows the noteworthy enhancement using the proposed sensor compared with existing work. Therefore, the proposed sensor can be used as a carrier for detecting the bacterial cells and establishing a new platform for biomolecular and biomedical applications.

Electrochemical Immunosensor for the Sensitive Determination of Human Papillomavirus (HPV) 16 L1 Capsid Protein: A Leap in Cervical Cancer Diagnosis

Human Papillomavirus (HPV) is the principal cause of cervical cancer, which is still a prime universal health concern, especially in underdeveloped nations where access to advanced screening techniques is often restricted. Herein, we propose an electrochemical immunosensor for the determination of HPV 16 L1 protein, a key biomarker associated with cervical carcinogenesis. The developed immunosensor, employing glassy carbon electrode (GCE) enhanced with gold nanoparticles, provides a highly sensitive, specific, and cost-effective approach for early screening of cervical cancer. An optimized stepwise fabrication process which includes electrode surface modification and antibody immobilization, was used to enhance sensor performance. Characterization studies confirmed the effective modification of electrodes and the selectivity of immunoreactions. With an impressive limit of detection (LOD) of 0.033 fg mL−1, the immunosensor showed a linear response to L1 protein concentrations ranging from 0.1 fg mL−1 to 1 ng mL−1. Additionally, the immunosensor exhibits excellent specificity, stability, reproducibility, and regeneration capabilities. The performance of the immunosensor was compared with the enzyme-linked immunosorbent assay (ELISA) by analyzing clinical samples (positive: n = 12; healthy: n = 5) showed satisfactory results. The findings indicated that the proposed sensing platform has the potential to be utilized for the early diagnosis of cervical cancer.

Metal Replacement in Aeronautics Applications Using Two‐Dimensional Multifunctional Composites

Carbon‐based composites have replaced metals in many structural components of modern airplanes; however, functional applications still require metal conductors and devices. Here, the production and integration in small‐scale airplane parts of electric devices based on metal‐free layered composites of graphene, boron nitride, and polymers are described. Thanks to their two‐dimensional structure, these materials feature excellent tunable thermoelectrical properties and high flexibility. We describe the production and performance of heaters and ice sensors installed on scaled NACA‐0012 airfoils to avoid ice formation, to remove ice or to detect the ice on the outer skin of the airfoil. We demonstrate that we can tune the electrical conductivity of the composite heating element from 105 to 103 S m−1 that is preserved even after 1000 bending cycles. The heaters successfully achieve anti‐icing and deicing in representative icing conditions and can sustain high‐power densities as required for electrothermal ice‐protection systems in aviation. The composite material can be readapted into a sensor able to detect ice formation in real time in an icing wind tunnel. Moreover, the possibility to use the heaters developed as heating molds to cure composite materials by out‐of‐oven curing, with a significant energy saving potential, is demonstrated.

Hierarchical Heterojunctions of Metal Sulfide WS2 Nanosheets/Metal Oxide In2O3 Nanofibers for an Efficient Detection of Formaldehyde

The construction of transition metal dichalcogenides (TMDs) heterojunctions for high-performance gas sensors has garnered significant attention due to their capacity to operate at low temperatures. Herein, we realize two-dimensional (2D) WS2 nanosheets in situ grown on one-dimensional (1D) In2O3 nanofibers to form heterostructures for formaldehyde (HCHO) gas sensors. Capitalizing on the p-n heterojunctions formed between WS2 and In2O3, coupled with the high surface-to-volume ratio characteristic of 1D nanostructures, the WS2/In2O3 NFs sensor demonstrated an elevated gas response of 12.6 toward 100 ppm HCHO at 140 °C, surpassing the performance of the pristine In2O3 sensor by a factor of two. Meanwhile, the sensor presents remarkable repeatability, rapid response/recovery speed, and good long-term stability. The superior sensing capabilities of WS2/In2O3 NFs heterojunction are attributed to the combined impact of the increased charge transfer and the presence of more sites for gas adsorption. The research endows a potent approach for fabricating TMD heterojunctions to significantly enhance the gas sensing properties of gas sensors at relatively low temperatures.

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 %.

Tailoring Strain Sensor Performance by Biwetting–Dewetting Assembly

Tailoring Strain Sensor Performance by Biwetting–Dewetting Assembly

Machine Learning for Improving Renewable Energy: Integrating Solar Power for Continuous Operation of Smart Sensors During Natural Calamities

This research tackles the critical issue of ensuring reliable data collection during natural disasters, such as floods, by calibrating and integrating smart sensors with renewable energy systems. Natural disasters often disrupt power supplies, posing significant challenges to the continuous operation and data availability of these sensors. To address this challenge, the study proposes leveraging renewable solar energy as a sustainable and reliable power source for smart sensors. By incorporating solar energy systems, the framework guarantees that sensors remain operational even in extreme conditions, ensuring that crucial environmental data is consistently accessible for rescue and recovery efforts. The research introduces an innovative approach that employs renewable energy to sustain the functionality of smart sensors during disasters. The framework includes models designed to manage uncertainties in disaster scenarios and optimize energy use for sensor operation. Additionally, the machine learning forecasting tool Prophet is utilized to improve the accuracy of predictions related to energy consumption and sensor performance. Prophet’s strength in handling time series data and generating reliable forecasts is vital for this application.

Designing LiDAR‐Detectable Dark‐Tone Materials with High Near‐Infrared Reflectivity for Autonomous Driving: A Comprehensive Review

AbstractAutonomous driving relies on the precise recognition of objects using light detection and ranging (LiDAR) technology, that operates at a specific wavelength of 905 nm. Black objects, such as carbon black used in vehicle coating, tend to absorb this specific wavelength significantly, which limits the performance of LiDAR sensors. To address this issue, researchers have explored creating dark‐toned materials that can be detected by LiDAR with high NIR reflectivity while maintaining a true blackness (L* < 20 based on the CIE color coordinates). These materials fall into two categories: organic and inorganic pigments. Organic pigments can be synthetically adjusted to achieve true blackness by manipulating their functional groups, but achieving high NIR reflectivity remains challenging, often requiring a bilayer structure with NIR‐reflective white base and an upper layer of organic black pigments. Additionally, the need for hydrophobic additives and resistance to degradation from sunlight further restricts their use. In the case of inorganic pigments, the desired LiDAR‐detectable properties can be obtained through careful control of their composition, structure, and morphology, allowing for single‐layer coatings with appropriate design. This review highlights recent advancements in developing organic and inorganic LiDAR‐detectable black pigments and outlines future material design strategies for autonomous vehicle systems.

Enhanced NO2 Gas Sensing in Nanocrystalline MoS2 via Swift Heavy Ion Irradiation: An Experimental and DFT Study.

Nanostructured transition metal dichalcogenides (TMDs) like MoS2 hold promise for gas sensing applications due to their exceptional properties. However, limitations exist in maximizing sensor performance, such as limited active sites for gas interaction and sluggish response/recovery times. This study explores swift heavy ion (SHI) irradiation as a strategy to address these challenges in MoS2-based NO2 gas sensors. MoS2 nanoflakes were fabricated and subsequently irradiated with 120 MeV silver (Ag) ions to induce structural and morphological modifications. Characterization techniques confirmed the formation of Mo and S vacancies within the MoS2 lattice due to irradiation. Significantly, SHI irradiation resulted in a remarkable enhancement of approximately 3 times improvement in sensing response compared to pristine MoS2 sensors. Additionally, the irradiated sensors exhibit substantial improvements in both response and recovery times for NO2 detection. SHI irradiation resulted in the formation of self-affine nanostructures and increased grain fragmentation as fluence rises. This enhanced surface area is hypothesized to promote gas-sensor response. To gain deeper insights into the underlying mechanism, first-principles calculations were employed. These calculations suggest that electron transfer occurs from the MoS2 surface to the NO2 molecule during interaction. Furthermore, the irradiation-induced vacancies facilitate stronger NO2 adsorption on the MoS2 surface compared to the pristine sample. This work demonstrates the effectiveness of SHI irradiation in engineering defects within MoS2 nanoflakes, leading to significantly improved NO2 gas-sensing performance. This approach offers a promising avenue for developing next-generation TMD-based gas sensors with enhanced sensitivity, response times, and stability.

Chemoresistive Gas Sensors Based on Electrospun 1D Nanostructures: Synergizing Morphology and Performance Optimization

Gas sensors are essential for safety and quality of life, with broad applications in industry, healthcare, and environmental monitoring. As urbanization and industrial activities intensify, the need for advanced air quality monitoring becomes critical, driving the demand for more sensitive, selective, and reliable sensors. Recent advances in nanotechnology, particularly 1D nanostructures like nanofibers and nanowires, have garnered significant interest due to their high surface area and improved charge transfer properties. Electrospinning stands out as a promising technique for fabricating these nanomaterials, enabling precise control over their morphology and leading to sensors with exceptional attributes, including high sensitivity, rapid response, and excellent stability in harsh conditions. This review examines the current research on chemoresistive gas sensors based on 1D nanostructures produced by electrospinning. It focuses on how the morphology and composition of these nanomaterials influence key sensor characteristics—sensitivity, selectivity, and stability. The review highlights recent advancements in sensors incorporating metal oxides, carbon nanomaterials, and conducting polymers, along with their modifications to enhance performance. It also explores the use of fiber-based composite materials for detecting oxidizing, reducing, and volatile organic compounds. These composites leverage the properties of various materials to achieve high sensitivity and selectivity, allowing for the detection of a wide range of gases in diverse conditions. The review further addresses challenges in scaling up production and suggests future research directions to overcome technological limitations and improve sensor performance for both industrial and domestic air quality monitoring applications.

Improved the Sensitivity and Limit of Detection of Surface Alloying SERS Sensors by Controlling Mixing Ratio of Trimetallic (Ag-Au-Pd) Nanoparticles

In this study, three different types of hybrid structures SERS sensors made from different mixing ratio of trimetallic (Ag-Au-Pd) nanoparticles of [Au1: Ag1: Pd1] , [Au1: Ag2: Pd1] , [Au1: Ag2: Pd2] in surface alloying forms deposited on macro porous silicon (macroPsi) layer were created and extensively tested. By using a simple and fast immersion process, trimetallic (Ag-Au-Pd) nanoparticles were created utilizing ion reduction of numerous metallic salts on a macro porous silicon (macroPsi) layer. The macroPsi layers were created using a laser assisted etching (LAE) technique for 15 minutes with a constant density of approximately (28mA/c.m2). At a constant concentration (10-3 M) of HAu.Cl4, Ag.NO3 and Pd.Cl2 to synthesize Au-NPs, Ag-NPs and Pd-NPs, immersion processes with various mixing ratios were performed. The hybrid structures of SERS sensors were examined using XRD, FE-SEM, and Raman microscopes. The sensors were tested at different concentrations from 10-6 to 10-12 of MB target molecules. The SERS trimetallic sensors demonstrated a considerable reliance on hot spot zones among trimetallic nanoparticles. Higher enhancement factor with lower detection limit of Raman signal was obtained from [Au1: Ag2: Pd2] hybrid structures SERS sensor of about 1.5×1010 and 10-14 respectively, due to extra ordinary specific surface area and high surface density forming trimetallic nanoparticles . The variations of mixing ratio of trimetallic (Ag-Au-Pd) provide an effective pathway to develop the sensors performance towards detection of lower concentrations.

Performance of 3D trench silicon pixel sensors irradiated up to [formula omitted]

Tracking particles at extreme fluences requires the accurate measurement of the charged particle timing at the pixel level in order to cope with the increased occupancy of HL-LHC experiments. Maintaining this precision throughout the operational life of the detector is crucial. This work demonstrates that the 55×55μm2 wide 150μm thick 3D trench-type pixels, developed by the TimeSPOT Collaboration, maintain the performance of non-irradiated sensors even after exposure to fluences as high as 1⋅10171MeVneqcm−2. The preliminary results of a beam test characterization using minimum ionizing particles at the SPS North area beam facility reveal that the charge collection and the time resolution of the irradiated sensors are comparable to those of non-irradiated ones, by increasing the operational bias voltage. A minor reduction in detection efficiency, approximately 4%, is observed post-irradiation. Currently, 3D trench-type pixels are among the fastest pixel detectors available for tracking charged particles and hold significant promise for future tracking system upgrades. This preliminary evaluation suggests their suitability for use in even harsher radiation environments than High Luminosity Large Hadron Collider (HL-LHC) such as future experiments at the Future Circular Hadron Collider (FCC-hh).

MXene anchored fabric for room-temperature operated ammonia sensing

Low-cost and fast-response fabric sensors are highly desirable for shop floor worker daily monitoring and early trace ammonia leak detection. However, the difficulty is how to establish a high bonding capacity between the active material and the fabric to meet the needs of sensing performance on practical applications. Herein, MXene anchored fabric sensors have been fabricated by spray casting technology and the impacts of the preparation process on sensor performance have been investigated. When the casting concentration of MXene is 10 mg/mL and the fabric is spandex, the ammonia sensor exhibits the best sensing performance with a response time of 0.62 s for 100 ppm ammonia and a low limit of detection of 0.4 ppm. Notably, when the sensor used for detection ammonia in wafer cleaner volatiles, the responsivity was up to 96.61 %. This research offers an efficient route for developing MXene anchored fabric for room-temperature operated ammonia sensing.