Given that traditional cutting vibrations negatively impact machining quality and tool durability, there is a critical need to enhance vibration energy harvesting efficiency and provide reliable power solutions for wireless monitoring sensors. This study develops a 2-DOF electromechanical coupling model for cutting tools to simulate and analyze the influence of structural parameters on energy harvesting performance. Variable gap frequency modulation technology is used to achieve wide-band regulation of resonant frequency covering 38.8 Hz to 49.3 Hz and 0.27 mW output power. On the tool vibration test platform, the U-shaped Piezoelectric vibration Energy Harvester (U-PVEH) not only has power of 0.19 mW, but also maintains a continuous power supply to the wireless sensing nodes.

Theoretical models are essential for performance analysis and structure optimization design of large-scale piezoelectric micromachined ultrasonic transducers (PMUT) arrays. However, current models have rarely incorporated the inter-element crosstalk and oversimplified the electro-mechanical-acoustic coupling, leading serious discrepancies with experimental results and limiting the array optimization design and performance improvement. To address this, a novel electro-mechanical-acoustic coupling model and a spatial acoustic field modeling approach are proposed for PMUT arrays, incorporating distributed deformation functions of individual element and mutual acoustic impedance to analyse key performance metrics such as transmission power, frequency response, focal length, and beamwidth. Its accuracy is validated through finite element simulations, demonstrating small deviations of less than 3%. Parametric studies reveal that increasing the filling ratio from 20% to 60% improves transmission power and bandwidth but significantly increases crosstalk, reducing focusing efficiency. Enlarging the array size results in proportional increases in acoustic output power and focal pressure, while simultaneously reducing beamwidth, thereby improving directivity. As for array arrangements, circular array achieves higher focal pressure than square array, albeit with shorter focal lengths. Annular array, with its distinct mainlobe and ring-shaped sidelobes, demonstrates superior focal pressure at longer distances, ideal for extended-range applications. The theoretical models are further validated by experimental results from fabricated square, hexagonal, circular, and annular PMUT arrays. This study proposes an accurate theoretical model for PMUT arrays, enabling accurate and reliable prediction of key acoustic performance metrics in large-scale arrays, and facilitating the array structure optimization design and performance enhancement of PMUT.

Currently, space-variable, capacitive multi-axis force/torque sensors have limited detection accuracy in the measurement of complex multi-axis loads owing to their inherent nonlinearity and coupling errors in the full range. The nonlinearity and coupling of the conventional capacitance differential equation were experimentally verified for a pre-developed space-variable capacitive six-axis force/torque sensing chip. An inverse capacitance differential decoupling equation was practically applied to the chip to suppress the inherent nonlinearity and coupling errors in the full range (2.5 N and 12.5 N & sdot; mm) under multi-axis loads. The results of complex multi-axis coupled loading tests align with the theoretical analysis. When the inverse decoupling equation is adopted, the maximum nonlinearities of 18.59% full scale (FS) and coupling errors of 254.1%FS for the conventional equation can be reduced to 1.05%FS and 10.90%FS, respectively. The efficient decoupling structure combined with the inverse capacitance differential equation can provide critical theoretical guidance for developing high-accuracy capacitive multi-axis force/torque sensors.

With the development of smart grid, many wireless sensor nodes (WSN) used in monitoring grid equipment need continuous power supply. This work propose a multi-frequency array piezoelectric vibration energy harvester (PVEH) powering WSN based on the grid transformers vibration of 100, 200 and 300 Hz. The PZT bimorph with U shaped mass sturcture is design and opitimized by finite element simulation. The bonding method of epoxy conductivity and insulation is studied for PZT bimorph and aluminum packaged PVEHs. The equivalent circuit modeling and interface circuit of PVEHs are studied in LTspice simulation. Through the whole system design of the array PVEHs powered WSN circuit with LTC3331 chip, the WSN can run continuously in simultation and experimental verification. The feasibility of multi-frequency PVEH powered WSN is verified on the 500 kV transformer in filed operation. This research has important application value to the design of WSN self-power supply for smart grid.

For piezoresistive pressure sensor, sensing performance is typically ensured by compensating primarily for the temperature-induced drift. However, for high-precision differential pressure measurements in high static pressure scenarios, the measurement deviation caused by the static pressure cannot be ignored. Therefore, this study proposed a compact two-parameter compensation system for differential pressure sensors. First, a novel structure was proposed for synchronous acquisition of static pressure, temperature, and differential pressure. In addition, a two-layer microcontroller unit (MCU) compensation hardware was designed considering the nonlinear errors caused by temperature and static pressure, which ensures acquisition accuracy through 16-bit analog-to-digital (AD) and digital-to-analog (DA) converter circuits. Furthermore, a back propagation (BP) neural network based on the improved grey wolf optimal algorithm was employed to model the coupling relationship between temperature, static pressure, and difference pressure, thereby overcoming the limitations of polynomial fitting and achieving high-precision difference pressure sensing under multitemperature and high-static pressure. Calibration experiments were conducted to validate the proposed system, and the results compared with those of typical compensation methods. The maximum error of the compensated differential pressure sensor within the temperature range of -40 to 80 degrees C and static pressure range of 0-30 MPa was within 0.28%FS (% of full scale), demonstrating that the proposed system significantly reduced the error influence caused by static pressure.

Capacitive micromachined ultrasonic transducers (CMUTs) are considered promising alternatives to traditional transducers owing to their compact size, high electromechanical coupling coefficient, and ease of integration with circuits. However, their limited transmission performance and high operating voltage hinder applications in advanced fields such as, intracavitary ultrasonography, portable ultrasound imaging, human-machine interfaces, and long-term non-destructive testing. This study presents an innovative CMUTs design through a combination of annular electrodes and membrane grooves. The annular electrodes partially adjust the membrane stiffness with electrostatic stiffness softening effect, while the grooves release stress in the membrane edge and convert the fully clamped membrane boundary into a hinge-like boundary. By leveraging these effects, this combined configuration achieves synergistic improvement in multiple performances metrics, especially, enhancing transmission amplitude and reducing collapse voltage. Finite elemental analysis is used to evaluate the influence of annular electrodes and grooves on crucial performance parameters. These results reveal maximum increases of 327%, 23%, 305% and 17% in average displacement, electromechanical coupling coefficient, transmitting vibration amplitude and receiving sensitivity, respectively, while maximum reduction of 19% in collapse voltage. Comprehensive analysis indicates that an optimal annular electrode coverage of 40% to 70%, along with a groove-to-post ratio of 90%, delivers superior overall performances. Moreover, the fabricated CMUTs chips are used to validate performance improvements with the structural design. The proposed CMUTs exhibit low collapse voltage, high transmission performance, and a simple membrane structure, demonstrating great promise for advanced ultrasound applications.

Surface-enhanced Raman spectroscopy (SERS), empowered by the rapid development of advanced micro/ nanostructured substrates, has shown increasing promise in diverse applications. Graphene-Au nanopyramid (GAuNP) substrate is a promising SERS platform with high sensitivity, and can be fabricated through low-cost colloidal lithography. However, the fabrication processes remain underexplored and limit investigations into nanopyramid arrays with diverse dimensions. Here, three types of highly uniform and ultra-sensitive GAuNP SERS substrates with diverse dimensions were fabricated through advanced colloidal lithography technology. A novel Langmuir-Blodgett method and a poly (methyl methacrylate)/paraffin bilayer-enabled method were introduced to fabricate two-dimensional polystyrene colloidal crystals and achieve large-area, clean graphene transfer. Optimal micro/nanofabrication methods and parameters were comprehensively identified. Relative standard deviations of 3.3 % for nanopyramid size and 9.1 % for spectral intensity demonstrate excellent structural and spectral uniformity. Theoretical simulations and experimental results demonstrated the ultrasensitivity, achieving a maximum analytical enhancement factor of 1.6 x 1010. Graphene contributes a 19fold chemical enhancement effect and improves quantitative analysis capabilities. Machine learning enabled the classification of various substances with exceptional performance, achieving 100 % sensitivity, over 96.3 % specificity, and over 97.4 % accuracy. This method demonstrates significant potential for diverse applications, such as cytological diagnosis and chemical detection.

Partial discharge (PD) is an important early indicator of insulation degradation in high-voltage equipment, and its reliable detection is of great significance for equipment condition monitoring and fault warning. Ultrasonic detection offers favorable electrical isolation and strong immunity to electromagnetic interference; however, conventional bulk piezoelectric transducers remain limited in miniaturization, array implementation, and system integration. Piezoelectric micromachined ultrasonic transducers (PMUTs) provide a promising solution for ultrasonic PD detection because of their high-level miniaturization, batch-fabrication compatibility, and capability for multi-source localization. However, the existing PMUTs detection circuits still encounter limitations in bandwidth, noise performance, and multi-channel scalability, causing their insufficient acquisition of the weak PD signals. This paper presents a wideband four-channel analog front-end (AFE) interface circuit for PMUTs-array-based ultrasonic PD detection. The proposed circuit converts weak PMUTs output signals into differential outputs. Simulation results show that the circuit achieves a -6 dB bandwidth from 20 kHz to 3 MHz and an average input-referred noise density of $4.78 \text{nV} / \sqrt{ } \text{Hz}$. The experimental measurement of a printed circuit board prototype matched with the simulated performance and demonstrated a single-channel gain of approximately 42.17 dB. Furthermore, a PD detection platform is established to realize synchronized acquisition of PMUTs ultrasonic signals, thereby verifying the feasibility of the proposed AFE circuit for ultrasonic PD localization and detection.

Constructing hydrogel tactile sensors with high sensitivity, broad range, fast response, long-term stability, and scalable manufacturing is challenging because of their viscoelasticity, dehydration, and incompatibility with existing processes. This work proposes a structure-process synergy strategy for gelatin methacryloyl (GelMA)-based capacitive pressure sensors, which fuse highly-ordered porous dielectric microstructures with 3D printing technology to balance the device performance and scalability. The porous GelMA matrix fundamentally maximizes continuous compressibility while minimizing viscoelasticity, resolving the sensitivity-range conflicts and hysteresis issues. Performance-robust GelMA ink and a tailored 3D printing process are developed to implement consistent batch-to-batch fabrication of the porous microstructure. Compared to surface microstructures, the enlarged contact area and decreased contact stress between the porous dielectric layer and electrode interface, as well as the anti-drying GelMA, synergistically enhance the durability and long-term stability. The resultant pressure sensors show ~3 times higher sensitivity, 6.7 times broader sensing range, and ultrafast response time of 30 ms than previous sensors. It also demonstrates unprecedented durability of ≥5000 cyclic loading, long-term stability of ≥7 days, batch-to-batch consistency of ≤3.7% capacitance variation, and excellent scalable manufacturing and customization capability. Continuous detection of human physiological signals validates its substantial potential in practical biomonitoring.

Chip-scale quantum magnetometers featuring both ultra-high sensitivity and uniform spin polarization are highly desired for practical applications and have been diligently pursued. However, the fulfillment of such capabilities for quantum magnetometers typically necessitates a separate heating unit, bulky reflector, and beyond, severely impeding on-chip integration and batch fabrication of these quantum devices. Herein, we present a novel paradigm for the wafer-level fabrication of ultra-sensitive chip-scale quantum magnetometer, which is enabled by integrating a highly reflective mirror and a temperature-controlled component on the optically transparent windows of the MEMS atomic vapor cell, thereby providing a genuinely all-in-one atomic vapor cell with a temperature stability better than ±5 mK at up to 200°C as well as a reflectivity of 95

Artificial nociceptors are valuable for constructing human-like neural network systems capable of perceiving injury and exhibit significant application potential in medical treatment, prosthetics, and humanoid robotics. Currently, the conventional strategy for constructing artificial nociceptors involves connecting flexible sensors with synaptic devices to detect pain signals. However, this approach inevitably increases system complexity and is therefore unfavorable for large-scale integration. In this study, an artificial nociceptor with an integrated design based on an organic electrochemical transistor was proposed, in which a suspended-gate structure enabled a single device to detect pain signals. In addition, an ionic hydrogel was employed as the electrolyte layer to detect pain signals with different intensities. The device can stably detect pain signals and successfully emulate four key characteristics of biological nociceptors: threshold, relaxation, no adaptation, and sensitization. Experimental results verify that pressure sensing and synaptic functionalities are co-implemented in a single device, underscoring its promise for constructing compact and high-performance neuromorphic sensory systems.

Room-temperature ammonia (NH3) detection is crucial for environmental safety and human health. In this study, a ternary PANI@Au-TiO2 ammonia-sensitive composite was synthesized via in situ polymerization of polyaniline (PANI) with simultaneous reduction of chloroauric acid to form Au nanoparticles, followed by ultrasonic compounding with TiO2 nanoparticles. The structural and morphological characterization confirmed the uniform distribution of Au and TiO2 nanoparticles in the PANI matrix. Gas sensing experiments demonstrated that the PANI@Au-TiO2 sensor exhibited markedly enhanced NH3 response, achieving a high sensitivity of 0.0527/ppm compared to PANI, PANI@Au, and PANI-TiO2 counterparts. Moreover, the PANI@Au-TiO2 ternary composite sensor displayed excellent linearity within the NH3 concentration range of 3-30 ppm, along with a low detection limit, good repeatability, and high selectivity toward ammonia. The enhanced performance is attributed to the synergistic effects of the p-n heterojunction, Schottky junction, and catalytic activity of Au nanoparticles, which facilitate efficient charge transfer and amplify the interaction with NH3 molecules. These findings demonstrate that the hybrid sensing film based on PANI@Au-TiO2 ternary composites exhibits excellent ammonia detection performance at room temperature, thereby offering a promising pathway for the development of advanced ammonia sensors.

We investigated the significant obstruction of ultrasound waves by the skull in ultrasound neuromodulation, to avoid the cranial window surgery in ultrasound neurotherapy, aimed for fully leveraging the non-invasive nature of ultrasound. The exponential attenuation of ultrasound in single-layer biological tissues is analyzed through finite element simulation, and a multi-layer tissue model is established, revealing the critical influence of interfacial acoustic impedance matching on ultrasonic reflection and transmission. An experimental platform is constructed, using pork fat and chicken breast to simulate human adipose and muscle tissue, respectively, and Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) devices at a frequency of 160kHz. The results show that ultrasound exhibits exponential attenuation in both fat and chicken breast tissue types, with the acoustic attenuation coefficient of muscle tissue (0.45 dB /cm) being higher than that of adipose tissue (0.37 dB/cm). In two-layer structures combining fat and muscle with skull, the signal further attenuates, and the extent of attenuation is constrained by the signal level remaining after penetration through the preceding tissue layer.

In the context of compliant robotic grasping and safe physical human–robot interaction, accurate pre-contact approach speed sensing in real time at low speeds and short distances remains a critical challenge. This paper presents a PMUT-enabled ultrasonic Doppler sensing scheme that directly estimates dynamic approach speed via frequency-shift extraction, overcoming the limitations of conventional ranging-based methods. The proposed PMUT sensor operates in conjunction with a power spectral density (PSD)-based processing algorithm to achieve high-precision speed detection under short-distance (5–20 cm) and low-speed (0.01–0.1 m/s) conditions—a regime where traditional Fourier-transform techniques exhibit significant errors. Experimental result shows that the system maintains a detection error below 1% across the target speed range, with a latency of approximately 20 ms. Taking the advantage of enabling real-time, low-latency speed perception in close-proximity scenarios, this work provides both a hardware platform and an algorithmic foundation for embedding dynamic proximity sensing into robotic tactile systems, thereby facilitating safer and more responsive human-robot interaction through predictive control.

Precise viscosity measurement in liquid media remains a critical challenge for micromachined resonant sensors. This primarily results from the inherent coupling between viscosity and density in hydrodynamic interactions, which limits independent quantification of viscosity. This work presents an aluminum nitride (AlN) piezoelectric microresonator vibrating at in-plane lateral mode for direct viscosity sensing in liquids. The resonator features cantilevered dual-plate structure with a wide step to leverage width-dependent effects on resonant frequency and quality factor. Through fluid-structure interaction modeling, the resonator is optimized to enhance vibrational characteristics while increasing linearity with respect to liquid viscosity. In experiments, the resonator incorporates fully electrical interfaces by combining self-actuation and self-sensing capabilities under liquid immersion. Furthermore, a significantly linear relationship between the quality factor and liquid viscosity is demonstrated. This linearity enables direct viscosity quantification through simultaneously measuring the resonant frequency and quality factor, which eliminates the need for prior density calibration required by conventional methods. The fabricated resonator achieves a mean absolute relative deviation of 2.65% with a maximum stability deviation of 3.43%. These results establish microplate-based laterally vibrating resonators as promising solutions for high-precision viscosity determination in compact liquid monitoring systems.

Gas detection in microfluidic chips is significant for predicting flow characteristics, identifying channel blockage, and enhancing experimental stability. However, existing detection methods face challenges such as large device size, susceptibility to medium interference, and difficulties in integration. To address these issues, this paper proposes a non-invasive gas content detection method based on piezoelectric micromachined ultrasonic transducers (PMUTs). This method processes ultrasonic echo signals using the principle of ultrasonic pulse echo, combined with a two-stage random forest algorithm. Through two-dimensional finite element simulation analysis, the optimal ultrasonic operating frequency was determined, ensuring the stability of the detection system. Experimental results indicate that the fabricated PMUTs can effectively detect gas content ranging from 0% to 100% in a microfluidic chip with a channel width of 50 micrometers, achieving a detection accuracy of 100% for gas presence and absence discrimination, with a goodness of fit (R2) of 0.9935 for gas content regression prediction. This study provides an accurate, reliable, and practical new method for gas content detection in microfluidic chips.

Conventional Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) are typically fabricated on rigid silicon substrates, which limits their ability to achieve conformal contact with complex curved surfaces, thereby hindering their application in flexible sensing. To address this limitation, this paper reports the design and fabrication of a lead-free, fully flexible PMUTs array based on a Potassium Sodium Niobate (KNN)-on-SU-8 structure. Addressing the thermal incompatibility between high-temperature KNN crystallization and temperature-sensitive polymer substrates, a novel "top-down" wafer-level fabrication strategy is proposed. Finite Element Method (FEM) analysis was conducted to optimize the device geometry, predicting a resonant frequency of 197 kHz and high transmitting sensitivity (0.26 μm / V). Experimentally, high-quality KNN thin films were deposited and annealed at 750°C on a silicon carrier, followed by the integration of flexible SU-8 cavities and serpentine copper interconnects. The lithography-based cavity formation eliminates the micro-loading effects common in deep silicon etching. The device, released by completely removing the rigid substrate, exhibits a pure perovskite phase and superior mechanical flexibility with a bending radius of 5 mm. The agreement between simulation and experimental results supports the design strategy, providing a significant pathway for eco-friendly, conformal ultrasonic sensors.

Quantum current sensors require highly precise magnetic field measurements for power grid monitoring. As a core component, the magnetic field modulation coil must achieve miniaturization while maintaining high magnetic field uniformity. This study focuses on the design, fabrication, and testing of MEMS (Micro-Electro-Mechanical Systems)-based magnetic field modulation coils. The magnetic field produced by the coil was simulated through COMSOL as well as the coil was fabricated by using MEMS technology, and tested on a custom-built SERF magnetometer platform. Results show that the fabricated bi-planar coil achieves a magnetic field non-uniformity of only 2.1

The piezoelectric vibration energy harvester (PVEH) with multiple resonant frequency points can be used for self-powered sensing in wideband excitation scenarios such as train ride roughness, rotating equipment vibration, and overhead line wind-induced vibrations. However, it has the issue of being unable to operate simultaneously, leading to a waste of size and weight. This paper investigates the collision frequency broadening and energy transfer phenomena of two different resonant frequency piezoelectric actuators. Based on this, a dual T-shaped mass simply supported PVEH (T-S-PVEH) with a collision structure is proposed for broadband vibration energy harvesting. A finite element model of the T-S-PVEH is established, and the resonant frequency is controlled by adjusting the mass thickness. A lumped parameter model is provided for parameter identification. A two-degree-of-freedom electromechanical coupling equation for nonlinear collisions is established, and the impact of collision spacing stiffness damping the on voltage frequency response is simulated to achieve a wider frequency range and better energy transfer between the dual actuators. A prototype is fabricated to verify the effectiveness of the collision model through sweep frequency tests at different accelerations to validate the voltage frequency response curve. Finally, a management circuit designed for dual piezoelectric interfaces and under-voltage locking energy storage discharged is presented. Experiment results demonstrated the feasibility of using dual simply supported beam T-mass collision broadband vibration energy harvesting for self-powering wireless sensor nodes.

Precise force measurement is crucial for evaluating cell injury and optimizing operations in micropipette-based somatic cell microinjection. In this article, a robotic microscopy system with a micropipette-integrated microelectromechanical system (MEMS) capacitive nanoforce sensor was proposed. Utilizing a bionic swallow structure, the proposed sensor exhibited a high force sensitivity of 39.84 aF/nN with a remarkable linearity of 0.9996 over a large measurement range of 145.98 nN. A stable micropipette-medium interface is formed inside the open U-shaped medium channel of the proposed microchamber, whose force resolution and noise floor were reduced to below 4.88 nN and 1.28 nN/root Hz, respectively. Following the proposed moving-cell and immobile-sensor (MCIS) strategy, the nN-level microinjection forces under different speeds were precisely measured for mouse myoblast cells without interface interference, allowing for the analysis of cell injury at each interaction stage through the proposed force-based metrics. This indicates the great potential of this approach for somatic cell microinjection studies.