Zhiyi Wu

Wave energy is a highly promising marine renewable energy source. However, the complex and variable marine environment, along with the low‐frequency and impact characteristics of waves, poses severe challenges to efficient energy capture. This paper proposes a compact indirectly driven hybrid triboelectric‐electromagnetic generator (LTEG) based on magnetic repulsion for the direct capture of shore‐based impact wave energy. This device integrates two TENG modules and two EMG modules. Based on a contact‐separation triboelectric nanogenerator, it adopts a triboelectric‐electromagnetic composite power generation strategy. The output performance of the device is regulated by the coordinated coupling of wave impact force, magnetic repulsion and gravity, which can efficiently convert wave impact kinetic energy into the reciprocating sliding of the slider. By optimizing the parameters of the TENG and EMG units, the output performance of the entire device is further enhanced, providing a feasible technical solution for achieving self‐sufficient power supply for marine environment monitoring sensors.

Gesture recognition based on the Internet of Things and artificial intelligence holds significant importance in human–computer interaction. Different from array-type hydrogel sensors, this research has developed a one-piece flexible hydrogel sensor based on an ion-cross-linked three-dimensional network structure. Through the design of the hydrogel components and its network structure, the Young’s modulus spanning from soft tissues to hard materials has been achieved. The hydrogel exhibits excellent output stability, surface adhesion, and skin adaptability. The test results show that the gesture recognition sensor prepared from this hydrogel has a minimum detection limit of only 0.04% and has excellent cyclic stability. On this basis, combined with the long short-term memory network (LSTM) deep learning algorithm, a complete intelligent gesture recognition system is constructed. This system can precisely recognize complex dynamic gestures and provide real-time feedback while simplifying the hardware connections and data flows. It offers an efficient solution for the field of intelligent care.

Flexible self-powered devices can operate without external power supplies and are therefore attractive for wearable health monitoring. Here, cocamidopropyl betaine (CAPB), LiCl, and ZnO nanoparticles were incorporated into a poly(vinyl alcohol)/polyacrylamide (PVA/PAM) double-network matrix to form a highly conductive and stretchable hydrogel. An all-hydrogel, fully flexible integrated piezoelectric sensor was then fabricated by sequential casting and stepwise crosslinking. The optimized CAPB/LiCl/ZnO/PVA/PAM (CLZPP) hydrogel achieved a tensile stress of 116.41 kPa and a tensile strain of 1083.76%. Its toughness and ionic conductivity reached 0.66 MJ/m³ and 16.19 S/m, respectively. It also exhibited sensitive strain responses and reliable cycling stability. As a wearable sensor, the hydrogel detected motions of the finger, wrist, knee, and neck, together with weak physiological signals associated with speech. As a bioelectrode, it recorded electromyographic (EMG), electrocardiographic (ECG), and electrooculographic (EOG) signals with performance comparable to commercial electrodes and higher signal-to-noise ratios. The integrated piezoelectric sensor generated stable voltage through the piezoelectric response of ZnO, converting deformation-induced mechanical energy into electrical energy for self-powered sensing. Piezoelectric signatures produced by contact with different materials were further combined with machine learning to enable rapid material classification. This work provides a strategy for jointly optimizing the mechanical, electrical, and piezoelectric properties of hydrogels and supports their use in self-powered wearable health monitoring and intelligent human-machine interfaces.

Shore‐based water wave energy represents a vast and underexploited renewable resource. This work reports a non‐inertial driven hybridized nanogenerator with coil spring (CS‐HG), which can convert the water wave energy to electricity by the triboelectric nanogenerator (TENG) and the electromagnetic generator (EMG). Different from the previous works, the CS‐HG has a driving board that can be directly excited by the wave, which omits the steps in the traditional design that energy must first be transferred through the outer shell. Besides, the coil spring converts the single‐wave excitation into the multi‐cycle energy output of the TENG unit. The energy conversion efficiency has been significantly improved based on the effect of the driving board and the coil spring. Under operating conditions at 1 Hz, the TENG and EMG units achieve maximum peak power outputs of 5.80 and 7.89 mW, respectively. The CS‐HG can harvest the wave energy and be a power supply for self‐powered wireless temperature and humidity sensing systems. This work not only presents an effective strategy for wave energy harvesting but also opens up new possibilities for the development of sustainable marine monitoring systems.

In modern manufacturing and engineering, angular displacement sensors are crucial for motion control and feedback systems in Electromechanical equipment. Traditional sensors like resolvers, capacitive, and photoelectric encoders, though high in precision and resolution, face limitations in size, weight, and power supply. In this paper, we report a self‐powered angular displacement sensor (SPADS) based on the triboelectric nanogenerator principle and time‐grating technology. SPADS features a compact structure composed of a stator and a rotor. The rotor is equipped with a single row of dual‐sinusoidal copper electrodes. At the same time, the stator is made of annular fan‐shaped copper electrodes covered with a layer of PTFE material. The electrical signals generated by the friction between the stator and different rotor electrodes are modulated with high‐frequency excitation pulses to obtain signals with phase containing angular displacement information. High‐frequency time pulses serve as the measurement standard to realize the phase detection, and the angular displacement is measured by counting the time pulses. Through simulation and experimental tests, the sensor can achieve a theoretical resolution of 5.18“ and a measurement accuracy within the range of ±716”. This paper has its significance for reference to miniaturized, efficient, and reliable sensors in the field of intelligent equipment.

Considering the depletion of fossil energy, the development of clean energy is a promising solution. Water wave energy is one of the most potential blue energy sources. This work reports a non-inertial driven large-scale hybridized nanogenerator (NID-HNG) combined with the triboelectric nanogenerator (TENG) and the electromagnetic generator (EMG), which can convert the water wave energy to electricity and be a power supply for wireless monitoring systems. Different from the previous works, the NID-HNG has a driving board that can be directly excited by the wave, rather than being excited by the shell driven by the wave first, which improves the efficiency of the energy conversion. Besides, the materials of the NID-HNG are selected according to the requirements, which have excellent stiffness, corrosion resistance, and impact toughness. By optimizing materials, structure, and number of zones divided of the TENG and connecting method of the EMG unit, they have the maximum peak power of 5.69 mW and 21.3 mW. The NID-HNG can harvest the wave energy and be a power supply of self-powered wireless temperature and humidity sensing systems. This work exhibits a wave harvester, providing an innovative strategy for energy harvesting and broadening the thoughts of prospective offshore monitoring systems.

With increasing multifunctional requirements for wearable electronic devices, higher requirements have been placed on the battery life of such devices. Humans generate a large amount of mechanical energy in daily life; efficiently converting this mechanical energy into electrical power to drive sensors is an important approach to addressing the issue of limited battery life. In this study, a hybrid energy harvester combining a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) was developed to collect human limb motion energy and provide continuous power for wearable devices and sensors. The WH-HG (triboelectric-electromagnetic hybrid generator) consists of a central eccentric rotor, copper coils at the top and bottom, and a TENG section at the top. When driven by human limb movement, the eccentric rotor rotates. In the EMG unit, the rotation of the magnets inside the rotor changes the magnetic flux through the surrounding coils, generating electric energy via electromagnetic induction. In the TENG unit, rotation of the eccentric rotor drives periodic contact and separation between polycarbonate (PC) villi and a fluorinated ethylene propylene (FEP) film, producing electrical energy through triboelectrification and electrostatic induction effects. When the energy harvester was worn on a tester’s wrist and tested at a running speed of 160 steps per minute, the WH-HG generated 10.61 mW, which was sufficient to light up over 100 LEDs and, after energy storage in capacitors, power a temperature–humidity sensor and a calculator. This research promotes the advancement of human-motion energy harvesting and provides an important reference for further efficient harvesting of human motion energy.

Acute wounds present a significant global health challenge. While traditional dressings provide passive protection, they lack active intervention capabilities. Electrical stimulation (ES), which mimics endogenous bioelectric fields, shows promise in modulating cell migration and angiogenesis. However, wound healing is a dynamic process with continuously shifting microenvironments, and existing ES dressings often deliver a single output mode, failing to adapt to different healing stages. To address this, a dual‐mode ES dressing is developed by integrating a triboelectric nanogenerator (TENG) and Ag/Zn battery on a nonwoven fabric substrate. This design leverages dynamic wound conditions: exudate in early stages acts as an electrolyte to activate the Ag/Zn battery for direct current stimulation. As the wound dries, the reduced humidity facilitates efficient TENG operation, converting mechanical energy into pulsed electrical signals. In rat models, this dressing significantly enhanced healing, achieving 89.7% wound closure on day 10, significantly outperforming single‐mode controls and demonstrating synergistic healing enhancement.

As a critical hardware component for machines to intelligently perceive physical interactions, pressure tactile sensors have achieved remarkable breakthroughs in recent years, driven by advancements in flexible electronics, new materials, and artificial intelligence. This review systematically summarizes the research progress in the field, covering sensing mechanisms, performance optimization, and application scenarios. In terms of sensing principles, this review introduces the working mechanisms, advantages, and limitations of mainstream technologies such as piezoresistive, capacitive, piezoelectric, and triboelectric sensing, and highlights the trend of multi‐principle integration for enhancing perceptual dimensions. Regarding performance improvements, groundbreaking progress in key metrics such as high sensitivity, wide linear range, multi‐dimensional force sensing, and miniaturization integration is summarized, emphasizing strategies such as micro/nano structural design, material modification, and system integration. In applications, the focus is placed on innovative uses in human–computer interaction, smart healthcare, and the Internet of Things, including robotic fine manipulation, wearable health monitoring, and smart environmental perception. Finally, this review outlines future development trends toward multifunctional, intelligent, and integrated tactile sensing systems. It aims to provide a comprehensive reference for researchers in the field and promote the innovative development of intelligent tactile perception technology.