Search Results (582)

The triboelectric nanogenerator (TENG), which converts mechanical energy into electrical energy through the coupled effect of triboelectrification and electrostatic induction, has garnered significant interest among researchers due to its portability and self-powered characteristics. Despite its evident development potential, TENG continues to face challenges, including the necessity to enhance its triboelectric performance through the optimization of structures, materials, and manufacturing techniques to improve energy conversion efficiency. Additionally, its environmental stability and durability also need to be improved. TENGs designed inspired by non-human animals and plants offer feasible solutions to address these limitations. These bio-inspired TENGs optimize the structural design of TENGs and the materials of the triboelectric layers by imitating the structures, functions, and behaviors of organisms, thereby further improving the energy conversion efficiency, sensitivity, wear resistance, adaptability to special environments, biocompatibility, and wearing comfort of TENGs. This paper expounds on the progress of TENGs inspired by non-human animals and plants applied in environmental energy harvesting, human health and motion monitoring. It also discusses the current challenges, with a view to providing insights for the interdisciplinary integration and development of bionics and TENGs. Full article

Real-time monitoring of marine ecosystems is crucial for global climate change research. In extreme marine environments such as the westerly regions in the Arctic and Antarctic, monitoring buoys and platforms often suffer from severe challenges, including insufficient energy supply, limited battery life, and difficult maintenance. Triboelectric nanogenerators (TENGs) offer a promising strategy for self-powered marine sensing. However, conventional tubular liquid–solid triboelectric nanogenerators (LS-TENGs) suffer from low efficiency of interfacial charge transfer due to limited contact area and excessive internal resistance, which restricts their output. In this study, a multi-tube nested liquid–solid triboelectric nanogenerator (MLS-TENG) is proposed, and the suitable filling ratio is determined through comparative experiments on structural parameters. This design significantly increases the effective contact area, reduces internal resistance, and improves synergistic charge transfer at multiple interfaces. Experimental results demonstrate that the MLS-TENG exhibits substantially improved electrical output compared with the corresponding single-tube structures. When integrated with a power management module, the capacitor charging efficiency is improved by approximately 120 times. In real sea trials, an array composed of MLS-TENG units successfully drives a self-powered sensing system, achieving stable 4G transmission of environmental parameters. This work provides a scalable structural optimization strategy for constructing high-performance blue energy-harvesting self-powered nodes for the marine Internet of Things. Full article

Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact–separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network–gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2× rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary. Full article

This comprehensive review aims to cover the surface tribology and triboelectric properties of additively manufactured (AM) natural biopolymers, including cellulose, chitosan (CS) and silk fibroin (SF), in biomedical interface engineering. While these sustainable materials exhibit innate biocompatibility and tribopositivity, their baseline triboelectric performance demands targeted surface engineering. We synthesize key physical mechanisms governing charge generation, emphasizing how controlled surface roughness, hierarchical porosity and nanoscale architectures maximize contact electrification. Furthermore, distinct dielectric and polarity modulation strategies are evaluated across the biopolymer families: cellulose relies heavily on chemical functionalization to overcome weak native polarity; chitosan utilizes ionic coordination and fillers to elevate its relatively low charge density; and silk fibroin achieves exceptional power outputs via highly porous three-dimensional nanocomposite aerogels. AM technologies afford unprecedented spatial control over these biointerfaces but introduce severe processing constraints. Techniques such as those based on extrusion impose strict shear-thinning rheology and rapid crosslinking for cellulose and chitosan, while SF frequently suffers from crystallization-induced nozzle clogging, necessitating photocurable derivatives. Full article

Polyvinyl alcohol (PVA)-based hydrogels suffer from insufficient mechanical strength, while aramid nanofibers (ANF) have intrinsic insulation that limits their sensing applications, and the synergistic effect of composite fillers remains underexplored. This study aims to develop a multifunctional PVA/ANF/NaCl composite organohydrogel for high-performance flexible sensors. The gel was fabricated via freeze–thaw crosslinking, solvent exchange and NaCl impregnation, with systematic investigations of its microstructure, mechanical, electrical and multifunctional sensing properties, and a corresponding triboelectric nanogenerator (TENG) and self-powered handwriting recognition system were constructed. Results show that 2% ANF significantly enhances the gel’s mechanical performance, 0.5 M NaCl achieves optimal mechanical-electrical balance, the gel-based sensor exhibits excellent distance, pressure and strain sensing with high cyclic stability, the TENG delivers stable electrical output, and the recognition system achieves 95% accuracy on the test set. This work provides a new material and design strategy for advanced flexible electronic devices. Full article

(1) Background: Gait analysis technologies have advanced; however, traditional systems like optical motion capture are lab-bound and costly, limiting rehabilitation monitoring. This cross-sectional study evaluates self-powered triboelectric nanogenerator (TENG) insoles combined with IMU sensors to assess gait asymmetry, plantar pressure signatures, age effects and injury history in rehabilitation patients, aiming to enable portable, battery-free phenotyping. (2) Methods: Fifty-three patients (22 females, 31 males; age, 29 ± 26 years) from Astana clinics with trauma histories (e.g., spine, ankle, fractures) and 10 healthy references underwent a 2 min walk test (2MWT). TENG insoles captured plantar loading; ankle/knee IMUs measured spatiotemporal parameters (cadence, asymmetry). The data were normalized; the analyses used an ANOVA and correlations (Python 3.14.3). (3) Results: The TENG sensors showed force/frequency linearity (up to 10 V at 20 N). The cadence averaged 101 ± 10 steps/min, declining with age (r = −0.31, p = 0.03) and fractures (r = −0.23, p = 0.04). The asymmetry varied (−54% to +31%) without category differences. Flatfoot (55%) was linked to lateral loading shifts; condition-specific waveform signatures emerged (e.g., lateral heel in ankle issues). (4) TENG-IMU systems feasibly capture gait phenotypes in heterogeneous cohorts, supporting out-of-lab monitoring for personalized rehabilitation without batteries. Prospective validation is required for further practical implications. Full article

To address dependence on external power and the limited capability of conventional hydroelectric units to detect low-amplitude vibrations, this work introduces a self-contained, highly accurate monitoring device. The design incorporates a magnetically levitated configuration, with triboelectric films placed on both the upper and lower faces of the floating magnet. Under minor oscillations, magnetic repulsion increases the relative displacement between the friction layers, producing a substantial voltage that permits low-level vibration sensing. A surrounding induction coil responds to the levitated pole’s vertical motion; this motion intersects the magnetic flux, generating a current that provides stable energy for wireless data transmission. Experimental outcomes confirm a detection limit of 0.1 mm. At an amplitude of 1 mm and a load of 1000 Ω, the system achieves a maximum output of 9 mW and a power density of 1.587 W/m², ensuring reliable power. This configuration provides a new pathway for monitoring vibrations in hydroelectric turbine generators. Full article

Against the backdrop of global energy structure decarbonization, distributed transformation, and the rapid development of low-power electronic devices and sensor networks, micro-energy supply and intelligent sensing have emerged as critical bottlenecks limiting their large-scale application. Triboelectric nanogenerators (TENGs), leveraging advantages such as compatibility with diverse materials and adaptability to flexible and miniaturized fabrication, can efficiently harvest widely available low-frequency, low-amplitude distributed mechanical energy in the environment. Additionally, they exhibit self-powered sensing characteristics, where output signals are directly correlated with external physical quantities, demonstrating unique strengths in the fields of micro-/nano-energy and intelligent monitoring. This article systematically reviews the research progress in TENGs; elucidates their working modes and power generation principles; summarizes material design, structural optimization, and performance enhancement strategies for efficient energy harvesting; and outlines the current state of self-powered sensing technologies. It highlights their engineering applications in intelligent monitoring scenarios such as drones, marine environments, infrastructure, and wearable devices. Addressing the existing technical bottlenecks and theoretical challenges in integrated energy harvesting–sensing–monitoring systems, the paper envisions future trends toward high performance, integration, and intelligence, providing valuable insights for fundamental research on and engineering applications of TENGs in micro-energy supply and intelligent monitoring. Full article

This study explores the influence of MXene solution as an interfacial liquid on the output performance of a Cu/n-Si-based direct current triboelectric nanogenerator (DC-TENG) system. The ${\mathrm{Ti}}_3{\mathrm{AlC}}_2$ MAX phase was successfully transformed into ${\mathrm{Ti}}_3{\mathrm{C}}_2{\mathrm{T}}_{\mathrm{x}}$ MXene through selective etching and was confirmed by scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) and X-ray diffraction (XRD) analyses, which revealed an increase in d-spacing from 8.99 to 9.58 Å and a transition from dense layered grains to delaminated, sheet-like structures. Electrochemical impedance spectroscopy (EIS) demonstrated a pronounced reduction in impedance with the introduction of MXene solution, indicating enhanced interfacial conductivity and charge transfer capability. The presence of MXene in deionized (DI) water led to the formation of an electrical double layer (EDL) at the Cu/n-Si interface, contributing to additional interfacial capacitance and more efficient charge relaxation dynamics. As a result, the DC-TENG output was significantly enhanced with the incorporation of MXene into the system, exhibiting a markedly higher current compared to the dry contact condition. Moreover, the MXene solution helped suppress charge decay compared to dry interfaces, highlighting its role as an effective liquid medium for stabilizing surface charge and improving interfacial electron transport in DC-TENG systems. Full article

Triboelectric nanogenerators (TENGs) exhibit great application potential in the fields of intelligent sensing and Internet of Things terminal devices due to their advantages of self-powering, simple structure, and high sensitivity. A self-powered alarm sensor for smart manhole covers is proposed to realize real-time monitoring of water immersion and abnormal displacement without external power supply. Experimental results show that the sensor can generate distinguishable voltage signals under water immersion and different displacement states, enabling rapid recognition of potential hazards such as manhole cover offset and accumulated water. On this basis, a reliable intelligent alarm system is constructed, which can receive, analyze, and warn of abnormal signals in real time. Therefore, it can even directly replace commercial manhole covers, demonstrating the broad application prospects of TENG in the field of intelligent monitoring. With the continuous advancement of TENG technology, the functions of this manhole cover alarm will be further expanded and optimized in the future, providing stronger support for the construction of smart cities. Full article

Seismocardiography (SCG) is a promising noninvasive modality for cardiovascular monitoring. By capturing subtle chest wall vibrations induced by the mechanical pumping activity of the heart at the body surface, SCG is of considerable value for blood pressure-related cardiovascular risk assessment and cardiac function monitoring. However, continuous SCG monitoring in daily life settings still relies predominantly on rigid accelerometers, and reports on flexible acquisition systems remain scarce. This is mainly because SCG signals are characterized by low frequency, low amplitude, and high sensitivity to the sensor-skin interface, requiring the sensor to achieve stable, high-fidelity acquisition of weak chest wall mechanical vibrations while maintaining conformal contact and wearing comfort. To address this challenge, this study proposes a flexible pressure sensor based on the triboelectric effect. The sensor adopts a single-electrode contact-separation structure and is composed of a polymer material capable of achieving a high negative charge density and a nickel foil electrode. The sensor exhibits a sensitivity of 3.76 V/N within a small force range of 0–200 mN, shows good frequency response over the 0.5–25 Hz band, and maintains stable output after approximately 5300 cycles. The sensor was attached to the lower-middle segment of the sternum to capture weak vibration signals generated by cardiac mechanical activity and transmitted through the chest wall, thereby enabling continuous SCG monitoring. This study presents a feasible approach for flexible SCG acquisition in daily life scenarios and provides experimental evidence supporting the application of flexible sensors in home-based health monitoring. Full article

As a green energy technology, triboelectric nanogenerators (TENGs) convert mechanical energy into electricity and have gained significant attention in response to growing global environmental concerns. However, the widespread use of petroleum-based polymers as triboelectric materials in high-performance TENGs raises concerns over plastic pollution. In this work, we report a high-performance biodegradable TENG utilizing chitosan/laser-induced graphene (LIG) composite films as triboelectric layers. Modified chitosan substrates were first converted into LIGs via a convenient one-step CO₂ laser engraving, subsequently incorporated into chitosan matrices to form homogeneous composite films. A TENG device was designed by pairing the LIG/chitosan composite film with the fluorinated ethylene propylene (FEP) film, and copper electrodes. The introduction of LIG effectively strengthens charge storage and dielectric properties of the chitosan matrix, thereby significantly boosting the triboelectric output performance. Experimental results demonstrate that the as-assembled TENG with an LIG concentration of 1 wt.% achieves a peak open-circuit voltage of 196 V and short-circuit current of 2.1 μA, with a maximum power density of 295 mW/m². It can drive LED lights and small low-power electronic devices. Furthermore, the designed TENG device exhibits good biodegradability, flexibility, and stability, serving as a self-powered sensor for monitoring human joint movements. This work provides a simple and scalable strategy for integrating laser-induced graphene with biomass-based polymers, offering new insights into the design of high-performance, biobased triboelectric materials. Full article

To address the issue of insufficient output voltage of the self-powered unit of intelligent bearings under low-amplitude working conditions, a piezoelectric–friction composite energy harvester driven by rotating magnetic force is proposed based on the multi-physical field coupling and synergy of magnetoelectric, piezoelectric and triboelectric effects, which effectively enhances the voltage output in low-amplitude vibration environments. The intelligent bearing adopts an extended structure, consisting of an outer ring sleeve, an inner ring extension ring, magnetic poles and a composite energy harvester. The outer ring sleeve is nested on the outer ring of the bearing and fixes the composite energy harvester, while the inner ring extension ring is fixed on the inner ring of the bearing and installs the magnetic poles. The composite energy harvester adopts a magnetic double-mass block single-crystal piezoelectric simply supported beam structure and integrates a contact-separation type triboelectric nanogenerator in the vibration direction, achieving the collaborative power supply of the piezoelectric and triboelectric units. A mechanical-electrical coupling dynamic model of the composite energy harvester is developed. Using COMSOL software, the effects of various structural dimensions and magnetic pole configurations on the output voltage are analyzed. Experimental validation confirms the model’s effectiveness. The results demonstrate that the energy harvester operates effectively under varying bearing rotational speeds. The rotational speed of the magnetic poles has little influence on the output voltage amplitude but primarily affects its frequency. Under the condition that the rotational speed is within 600 r/min, the piezoelectric module stably outputs a peak voltage of approximately 16.6 V, and the triboelectric unit stably outputs a peak voltage of approximately 4.4 V, which can effectively meet the self-driving requirements of intelligent bearings. Full article

Continuous monitoring of vehicle engine vibration is a key enabler of real-time diagnostics, yet conventional accelerometers require an external power supply and fit poorly into the distributed sensor networks envisioned for next-generation vehicles. Triboelectric nanogenerators offer an attractive self-powered alternative, but their direct application to the vibration of a running passenger vehicle engine, and the explicit link between sensor design parameters and individual engine operating states, remains largely unexplored. Here, we address this gap by co-tuning the air gap and the substrate rigidity of a contact-separation triboelectric vibration sensor to the vibration spectrum of an automotive engine. A systematic 3 × 3 design sweep across three gap distances and three substrate types identifies a single configuration that simultaneously resolves the low-frequency idle band and the higher-frequency acceleration band of a four-cylinder gasoline engine. A frequency-amplitude response map confirms that the real engine operating points fall within the sensitive region of the optimized device, and an on-vehicle test demonstrates clean discrimination of all seven operating states, from ready to shut-down, without any external power. The results establish design guidelines for source-matched triboelectric vibration sensors and outline a practical path toward self-powered, wireless-ready engine health monitoring in future vehicles. Full article

Triboelectric nanogenerators (TENGs) offer a promising route for self-powered microscale energy harvesting, yet their design optimisation remains empirically challenging due to the complex interplay of material surface physics, device geometry and operating mode. In this work, we present an integrated framework that combines atomic force microscopy (AFM) characterisation, COMSOL Multiphysics 6.0 finite element simulation and physics-informed conditional variational autoencoder (cVAE) to predict and optimise TENG output performance. Four polymer dielectric materials, HDPE, LDPE, TPU, and PMMA, were characterised via Kelvin Probe Force microscopy (KPFM) for work function, surface potential and surface roughness. Surface charge density was calculated from measured KPFM potential using the parallel plate capacitor model and used as a boundary condition in COMSOL Multiphysics simulations for contact-separation and lateral sliding TENG mode for dielectric film thicknesses of 50 µm and 100 µm. The simulated open circuit voltage (Voc) and short circuit charge (Qsc) across gap distances up to 150 mm formed the training dataset for a cVAE model with eight physicochemical condition features. The trained model demonstrated strong reconstruction accuracy (R² ≥ 0.94) and enables generative prediction across unseen design spaces. Results reveal that the LDPE/TPU pair at 50 µm thickness consistently achieves the highest electric outputs in both modes, and the sliding mode yields 25–30% higher voltages than the contact separation mode across all material pairs. This study provides a transferable data-efficient methodology for accelerating TENG material and geometry optimisation. Full article