Flexible pressure sensors have great potential in varieties of applications, such as human motion monitoring, human–machine interfaces and e‐skins. Through the integration of novel materials and innovative structural designs, substantial efforts have been devoted to augmenting the sensitivity, detection range, and operational stability of flexible pressure sensors for targeted application scenarios. However, in specific application domains such as robotic tactile systems, intelligent prosthetics, and wearable medical devices, sensors are required to concurrently exhibit both an extensive detection range and heightened sensitivity—a combination that remains unattainable for current flexible pressure sensors. Therefore, inspired by bamboo, a piezoresistive sensor composed of multiwalls carbon nanotubes and polydimethylsiloxane (PDMS/MWCNTs) films based on special surface morphology of ridges structure was fabricated through a facile and cost‐effective way. Thanks to the ridges structure, the sensor displayed a high sensitivity of 11.68 kPa −1 under pressure range up to 23 kPa and a wide detecting range from 116 Pa to 126 kPa. Besides, due to the hierarchical ridges structure, the sensor showed excellent linearity under three different pressure ranges ( R 2 > 0.92). Moreover, a series of studies have been made to demonstrate the practical application in human motion monitoring and muscular movement detection.

Smart microfluidic biosensor with polyamine saccharide-GluOx-modified LIG electrodes and real-time ML signal deconvolution for glucose monitoring.

Highly sensitive sensors for the simultaneous determination of imidacloprid, fenitrothion, and glyphosate pesticides in real samples constructed by functional buckyball nanoarchitectures based on fullerene-like nanoparticles.

Multi-objective optimization approach for eddy current displacement sensor’s performance based on a coupling analysis model

Development of an Eddy Current Sensor for Orthotropic Steel Decks Based on the Halbach Array

Protocol for contactless and instantaneous line-current data exchange between MATLAB and a drone-deployable sensor on overhead transmission lines.

Abstract The eddy current method can be applied to in situ nano-scale metal film thickness measurements with a high precision. Generally, the lift-off distance should be kept constant in the measurement process and its variation would significantly affect the accuracy of an eddy current sensor. However, it is quite difficult to control the lift-off distance precisely in practice. Therefore, how to evaluate the influence of micro-scale lift-off distance variation on the measurement accuracy quantitatively is a critical issue which should be addressed especially in the field of in-situ nano-scale detection. In this study, a simulation model of copper film thickness measurement using the eddy current method was established, which couples an electromagnetic field and an LC circuit module, with a film thickness range of up to 1500 nm. The lift-off benchmarks were set at 1, 2 and 3 mm, and the maximum vibration amplitude was 150 μm. Based on the established model, the coil parameters under each lift-off benchmark were optimized first for a good sensitivity. Then, coil impedance and output voltage in each lift-off vibration state were calculated sequentially. According to the calculation results, the influence of lift-off benchmark and variation amplitude on the thickness measurement error, as well as the sensitivity and linearity of output voltage, were revealed respectively. And a quantitative relationship between the measurement error and lift-off distance variation was further proposed. Meanwhile, a series of experiments have been carried out to verify the above theoretical analysis and a quantitative evaluation method was established by nonlinear surface fitting. Finally, it was demonstrated that the thicker the measured copper film, the more sensitive it was to lift-off variations. Specifically, a lift-off variation of 1 μm would result in a thickness error of approximately 6 nm under the experiment conditions.

This paper introduces an advanced control method for a Shunt Active Power Filter (SAPF), engineered specifically for the compensation of non-active current and power management in DC-powered systems. Non-active current components frequently arise in practical DC systems due to power electronics and dynamic loads. Their presence leads to increased current draw from the source, higher losses, and accelerated deterioration of DC energy providers, such as fuel cells and batteries. The proposed SAPF control strategy is based on the concept of an equivalent conductance signal, which dynamically reflects the load’s active power consumption and the SAPF’s internal losses. A key feature of this method is the derivation of the conductance signal primarily from the DC-link capacitor voltage, effectively eliminating the need for additional current or power sensors and thereby simplifying the control hardware and software. This methodology enables efficient buffering of energy flow through user-defined time constants, significantly reducing both the average value and the variability range of the current required to transmit the demanded power (as measured by the RMS parameter and standard deviation of the source current, respectively). As a result, the degradation process of energy sources can be mitigated. Furthermore, the conductance signal’s ability to assume negative values allows for effective management of generative loads, enabling power flow back into the system or directing it to specific loads. The flexibility of tuning the SAPF’s functionality—by adjusting the time constant and imposing limits on the conductance signal’s variation range—is demonstrated in the presented results. Simulation examples, including the potential for direct energy exchange with the DC-link capacitor without affecting the upstream source, validate the effectiveness and versatility of the proposed control method in improving power quality and extending the lifespan of DC energy storage systems.

Abstract Toroidal eddy currents induced within the tokamak vacuum vessel play a critical role in plasma startup, volt-second consumption, and magnetic field configuration. However, the presence of strong background magnetic fields—generated by the central solenoid (CS) and poloidal field (PF) coils, of order of few T, generated by currents often exceeding seraval mega-ampere-turns—poses a significant challenge for direct and accurate measurement of these currents. This paper presents a novel dual-loop fiber optic current sensor (FOCS) system developed specifically for the EXL-50U spherical tokamak to directly measure toroidal eddy currents. The diagnostic setup includes an inner FOCS loop dedicated to measuring the plasma current Ip , and an outer loop for detecting the total enclosed toroidal current, which comprises contributions from the plasma, all external coils, and the eddy currents. A specially designed hardware compensation coil physically cancels the dominant magnetic flux generated by the CS leads in real time, significantly enhancing the signal-to-noise ratio. Experimental results demonstrate that the system is capable of measuring eddy currents even under strong background fields. The measured waveforms show good agreement with numerical simulations, validating both the diagnostic approach and the electromagnetic model of the device. The proposed diagnostic system offers a robust and reliable tool for optimizing plasma startup scenarios in spherical tokamaks.

The Automatic Fault Detection and Isolation System for Electrical Grids increase the reliability and efficiency of modern power distribution networks. Real-time fault detection using sensors and microcontrollers in the proposed system helps to identify faults such as short circuits, over current, and voltage abnormalities. Then, it isolates the section containing the fault through circuit breakers or relays to ensure a continuous power supply to the rest of the network. The proposed system incorporates several hardware and software components: current sensors, voltage sensors, microcontrollers such as Arduino or ESP32, and the software algorithms that it runs to monitor grid parameters continuously. Real-time data acquisition will enable the system to interpret the fault conditions correctly and act accordingly without any human interference. A user interface is also provided to display the status of the system and fault alerts for quick response by grid operators. It minimises fault detection and response time, which in turn reduces equipment damage, power losses, and downtime. It ensures operational safety, thereby improving load management and supporting grid resilience. Besides, it contributes to efficient maintenance and long-term grid sustainability.

ABSTRACT Compared with magnitude-based measurements, the phase response of an eddy current sensor is less sensitive to lift-off effects. This paper explores a tilted coil configuration to further reduce the lift-off effects in phase measurements. Although tilted coils have been used in eddy current testing previously and analytical models were established, the utilisation of its phase for lift-off effects reduction has not been explored. Furthermore, an intuitive physical interpretation of the utilisation of tilted coils is presented based on the interaction between magnetic flux and the material under test. An analytical model of tilted coils is employed to evaluate their impedance changes across different lift-offs in response to a planar structure. Numerical results demonstrate that the tilted coil effectively reduces lift-off effects, with optimal performance at a tilt angle of 90° (horizontal). A new quantitative criterion, Inter-Lift-off Phase Area (ILPA), is established in frequency-sweeping measurements to characterise lift-off effects, validated by experiments across multiple materials. The results show that the 90° coil (horizontal) provides an average improvement of 26.17% in phase stability compared to the regular 0° coil (vertical). A ferrite-core configuration was also evaluated and showed reductions in phase variation and ILPA, achieving an average improvement of 39.17% in phase stability across all tested materials, confirming the effect of tilt angle on phase stability.

Abstract: The reliability and efficiency of modern power distribution systems are paramount for economic stability and quality of life. Substation feeders, critical components of this infrastructure, are often monitored through manual inspections or legacy SCADA systems, which can be slow, expensive, and lack comprehensive real-time analytics. This paper presents the design and implementation of a real-time substation feeder monitoring and auditing system leveraging Internet of Things (IoT) architecture. The proposed system utilizes high-accuracy voltage and current sensors interfaced with an ESP32 microcontroller for data acquisition. This data is transmitted via Wi-Fi and the MQTT protocol to a cloud platform for continuous monitoring, power quality auditing, and predictive fault detection. Key objectives include enabling continuous feeder monitoring, calculating key performance indicators like power factor and total harmonic distortion (THD), and identifying anomalies such as overloads and potential faults. Expected outcomes from system deployment demonstrate a significant enhancement in operational visibility, a reduction in energy losses through detailed power auditing, and improved grid reliability via early fault detection, offering a cost-effective and scalable alternative to traditional systems.

Abstract Tactile perception is about capturing, processing, and interpreting tactile signals using tactile sensors to accurately understand the user's intentions, enabling more natural and efficient interaction. However, to achieve high resolution and high precision perception, current tactile sensors still pose challenges including complex signal decoupling and data redundancy. In this study, an adaptable paradigm based on Hilbert curves is used for an inverse‐design tactile (AHIT) sensor, which achieves tactile perception by hash mapping and contributes the function of self‐information storage. By using the fractal properties of Hilbert curves, the perceptive area and precision of AHIT sensors can traverse from low to high, accompanied by 1D signals and high resolution. AHIT sensors are therefore tailored to meet the requirements of versatile application scenarios such as multifunctional human‐machine interfaces, multi‐dimensional encryption and intention transmission. It is hoped that AHIT sensors demonstrate potential to minimize the interface between sensors and communication devices, improve data compression and reduce computational complexity, which is expected to drive rapid development in the field of intelligent tactile perception.

Icing phenomena occur on aircraft and unmanned aerial vehicles (UAVs) under extreme weather conditions. Ultrasonic detection technology is an effective method for measuring ice formation while maintaining the shape of the structure. However, current ultrasonic sensors, which are large and inflexible, are unsuitable for irregular UAV bodies, limiting their applications in real scenarios. For the detection of icing on curved structure, this study proposes a novel flexible ultra-thin ultrasonic transducer (FUTUT). The transducer exhibits excellent flexibility, making it suitable for use on high-curvature wings. Firstly, the FUTUT was designed based on the material properties of the airframe and the sensitivity requirements for ice detection, following the design guidelines for 1-3 type piezocomposites. The fabrication process for the FUTUT was then investigated, and its flexibility and low-temperature resistance were tested. Finally, icing detection experiments were conducted in an icing wind tunnel (IWT), where the FUTUT of 9.82 MHz demonstrated an ice-thickness-detection sensitivity of 0.29 mm. Experimental results indicate that the FUTUT possesses superior flexibility and exhibits excellent stability in low-temperature environments. These results underscore the FUTUT’s promise for applications in ice detection on curved structures.

As global concern for food security continues to grow, modern monitoring technologies are playing a pyramidally crucial role in the agricultural sector. However, in the face of complex and fluctuating light requirements during crop growth, the further development of environmental monitoring technology is constrained by both the complexity and variability of environmental conditions and the limited accuracy and functionality of current light sensors. Herein, a self-powered all-inorganic tin-lead (Sn-Pb) perovskite photodetector (PD) is reported, and a novel all-in-one engineering approach utilizing benzenesulfonyl hydrazide (BSH) is incorporated to effectively enhance the photodetection performance of the PD. The BSH molecule plays a pivotal role in balancing and mitigating crystallization and grain growth processes of Sn-Pb perovskite, while also inhibiting the oxidation of Sn2+ and the formation of Sn vacancy defects in perovskite film. Consequently, the optimized champion PD reaches a responsivity of 0.36 A W-1 and a detectivity of 1.74 × 1013 Jones at 650 nm. Benefitting from its excellent performance, the prototype of a light sensor employing PDs achieves specific detection of red and blue light in a simulated lighting environment required for plants development. This research not only presents a feasible strategy to improve photodetection performance of Sn-Pb perovskite PDs but also provides novel insights for designing monitoring and feedback systems in intelligent agriculture applications.

Several unknowns remain surrounding marine Carbon Dioxide Removal (mCDR) monitoring, reporting, and verification (MRV) practices and capabilities. Current in-situ sensor technology is limited (primarily pH and p CO 2 ), requiring calculations and assumptions to estimate changes in carbonate chemistry parameters, including total alkalinity (TA). Considering that cost, energy consumption, and accuracy of commercial sensors can vary by orders of magnitude, understanding how well existing sensors perform in an mCDR context is important for this emerging community. Likewise, documenting sensor limitations and how relatively simple models can optimize sensor deployments will improve MRV efforts and support protocol development. Here we (1) compare performance a variety of commercially available sensors in a blind mesocosm experiment simulating ocean alkalinity enhancement (OAE), and how sensor performance impacted carbonate chemistry estimates; (2) evaluate if sensors can distinguish the OAE signal from natural variability during a small scale OAE field test in Sequim Bay, WA, USA, and (3) use an idealized ocean biogeochemistry model to explore optimal sensor network design based on (1) and (2). Our mesocosm results indicate that correctly constraining pH uncertainty will be critical for accurate TA estimates with current sensor technology compared to the less impactful variation caused by uncertainty in p CO 2 (pH data that are presented throughout are reported on the total scale (pH T ) unless otherwise noted). Our pilot field test demonstrated that sensors were capable of distinguishing mCDR signatures from natural variability under optimal real-world conditions. Idealized modeling simulations of the field test showed that a range of sparse and dense (3 to 100) sensors sampling areas of detectable increases will underestimate the net change in surface pH by at least 35–55%, at both realistic and highly elevated alkalinity input levels. We also highlight the limitations of current sensing technology for MRV, and the importance of ocean biogeochemistry models as critical tools for predicting when and where mCDR signals will be detectable using available sensors. Overall, our findings suggest that commercially available p CO 2 sensors and some pH sensors will form an important backbone for mCDR MRV tasks, though complete MRV characterization will require these data to be used in combination with other tools.

ABSTRACT Flexible pressure sensors hold transformative potential in personalized healthcare and motion‐aware electronics. However, constrained by a single conduction mechanism, current sensors still face significant challenges in simultaneously achieving high sensitivity, wide range, and robust stability. Herein, a gradient doping hierarchical microstructure flexible piezoresistive sensor with multi‐path conduction mechanisms is developed. The synergistic combination of micro‐engineered surfaces and spatially graded doping enables significant resistance variation at low pressures, yielding a high sensitivity of 101.1 kPa −1 . Multi‐path conduction mechanisms (including surface resistance, interlayer electrode resistance, interlayer contact resistance, interlayer tunneling resistance, and bulk resistance) enable tunable resistivity under high loads, extending the sensing range from 0.32 Pa to 3.6 MPa (a span of seven orders of magnitude). Moreover, the integrated full‐carbon nanotubes/polydimethylsiloxane design shows high stability, durability (over 5000 cycles), and fast response/recovery time (10/58 ms). As a proof of concept, the sensor's application for broad‐range biomechanical monitoring has been validated, spanning from subtle pulse waveform detection to high‐intensity plantar pressure monitoring. This work advances next‐generation wearables for simultaneous high‐fidelity physiological tracking and extreme‐force kinematic analysis.

Highly sensitive fiber-optic direct current electric field sensor using Michelson interferometry and constant strain cantilever beam

We present a novel Se(IV)-mediated etching protocol to control the etching orientation and geometrical evolution of bare gold nanorods (AuNRs) and exploit it as a highly sensitive surface-enhanced electrochemiluminescence (ECL) sensor. The initial etching orientation was intimately governed by the concentrations of Se(IV) and cetyltrimethylammoniumbromide(CTAB). Interestingly, an extraordinary lateral etching was preferentially observed in the Se(IV)/KI/CTAB system, leading to the formation of quasi-rectangular AuNRs with increased aspect ratio. This etching process afforded clear geometrical transformation, enabling the efficient synthesis of cubic gold nanoparticles and quasi-rectangular nanorods with an enhanced electric-field enhancement factor. The etched AuNRs immobilized on a glassy-carbon electrode produced a markedly enhanced ECL signal 4.42-fold higher than that of the unetched AuNRs. A detection limit as low as 9.24 pM was achieved for the p53 biomarker carrying a codon-249 mutation. Moreover, the method yielded a lower selectivity factor than previously reported strategies, highlighting its high selectivity and potential for discriminating mutant p53 DNA. Our study significantly advanced current p53 sensor capabilities and highlighted the power of etched plasmonic metasurfaces for sensitive optical detection.

Material-based-flexibilization of eddy current gap sensor system