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An advanced energy autonomous system that simultaneously harnesses and stores energy on the same platform offers exciting opportunities for the near-future self-powered miniature electronics. However, achieving optimal synchronization between the power output of an energy harvester and the storage unit or integrating it seamlessly with real-time microelectronics to build a highly efficient energy autonomous system remains challenging. Herein, a unique bimetallic layered double hydroxide (LDH) based tribo-positive layer is introduced for a high-voltage sliding triboelectric nanogenerator (S-TENG) with an output voltage of ≈1485 V and power output of 250 µW, respectively. To demonstrate the potential of a self-charging power system, S-TENG is integrated with on-chip micro-supercapacitors (MSCs) as a storage unit. The MSC array effectively self-charged up to 4.8 V (within 220s), providing ample power to support micro-sensory systems. In addition, by utilizing the high-voltage output of the S-TENG, the efficient operation of electrostatic actuators and digital microfluidic (DMF) systems driven directly by simple mechanical motion is further demonstrated. Overall, this work can provide a solid foundation for the advancement of next-generation energy-autonomous systems.

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A multiple self-powered sensor-integrated mobile manipulator (MSIMM) system was proposed to address challenges in existing exploration devices, such as the need for a constant energy supply, limited variety of sensed information, and difficult human-computer interfaces. The MSIMM system integrates triboelectric nanogenerator (TENG)-based self-powered sensors, a bionic manipulator, and wireless gesture control, enhancing sensor data usability through machine learning. Specifically, the system includes a tracked vehicle platform carrying the manipulator and electronics, including a storage battery and a microcontroller unit (MCU). An integrated sensor glove and terminal application (APP) enable intuitive manipulator control, improving human-computer interaction. The system responds to and analyzes various environmental stimuli, including the droplet and fall height, temperature, pressure, material type, angles, angular velocity direction, and acceleration amplitude and direction. The manipulator, fabricated using 3D printing technology, integrates multiple sensors that generate electrical signals through the triboelectric effect of mechanical motion. These signals are classified using convolutional neural networks for accurate environmental monitoring. Our database shows signal recognition and classification accuracy exceeding 94%, with specific accuracies of 100% for pressure sensors, 99.55% for angle sensors, and 98.66, 95.91, 96.27, and 94.13% for material, droplet, temperature, and acceleration sensors, respectively.

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In recent years, wearable sensor devices with exceptional portability and the ability to continuously monitor physiological signals in real time have played increasingly prominent roles in the fields of disease diagnosis and health management. This transformation has been largely facilitated by materials science and micro/nano-processing technologies. However, as this technology continues to evolve, the demand for multifunctionality and flexibility in wearable devices has become increasingly urgent, thereby highlighting the problem of stable and sustainable miniaturized power supplies. Here, we comprehensively review the current mainstream energy technologies for powering wearable sensors, including batteries, supercapacitors, solar cells, biofuel cells, thermoelectric generators, radio frequency energy harvesters, and kinetic energy harvesters, as well as hybrid power systems that integrate multiple energy conversion modes. In addition, we consider the energy conversion mechanisms, fundamental characteristics, and typical application cases of these energy sources across various fields. In particular, we focus on the crucial roles of different materials, such as nanomaterials and nano-processing techniques, for enhancing the performance of devices. Finally, the challenges that affect power supplies for wearable electronic products and their future developmental trends are discussed in order to provide valuable references and insights for researchers in related fields.

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Volatile organic compound (VOC) sensors have a broad range of applications including healthcare monitoring, product quality control, and air quality management. However, many such applications are demanding, requiring sensors with high sensitivity and selectivity. 2D materials are extensively used in many VOC sensing devices due to their large surface-to-volume ratio and fascinating electronic properties. These properties, along with their exceptional flexibility, low power consumption, room-temperature operation, chemical functionalization potential, and defect engineering capabilities, make 2D materials ideal for high-performance VOC sensing. Here, a 2D MoS2/Te heterojunction is reported that significantly improves the VOC detection compared to MoS2 and Te sensors on their own. Density functional theory (DFT) analysis shows that the MoS2/Te heterojunction significantly enhances the adsorption energy and therefore sensing sensitivity of the sensor. The sensor response, which denotes the percentage change in the sensor's conductance upon VOC exposure, is further enhanced under photo-illumination and zero-bias conditions to values up to ≈7000% when exposed to butanone. The MoS2/Te heterojunction is therefore a promising device architecture for portable and wearable sensing applications.

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Porous materials possess advantages such as rich pore structures, a large surface area, low relative density, high specific strength, and good breathability. They have broad prospects in the development of a high-performance Triboelectric Nanogenerator (TENG) and self-powered sensing fields. This paper elaborates on the structural forms and construction methods of porous materials in existing TENG, including aerogels, foam sponges, electrospinning, 3D printing, and fabric structures. The research progress of porous materials in improving TENG performance is systematically summarized, with a focus on discussing design strategies of porous structures to enhance the TENG mechanical performance, frictional electrical performance, and environmental tolerance. The current applications of porous-material-based TENG in self-powered sensing such as pressure sensing, health monitoring, and human-machine interactions are introduced, and future development directions and challenges are discussed.

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Wearable sensors are experiencing vibrant growth in the fields of health monitoring systems and human motion detection, with comfort becoming a significant research direction for wearable sensing devices. However, the weak moisture-wicking capability of sensor materials leads to liquid retention, severely restricting the comfort of the wearable sensors. This study employs a pattern-guided alignment strategy to construct microhill arrays, endowing triboelectric materials with directional moisture-wicking capability. Within 2.25 s, triboelectric materials can quickly and directionally remove the droplets, driven by the Laplace pressure differences and the wettability gradient. The directional moisture-wicking triboelectric materials exhibit excellent pressure sensing performance, enabling rapid response/recovery (29.1/37.0 ms), thereby achieving real-time online monitoring of human respiration and movement states. This work addresses the long-standing challenge of insufficient moisture-wicking driving force in flexible electronic sensing materials, holding significant implications for enhancing the comfort and application potential of electronic skin and wearable electronic devices.

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Noncontact sensors have demonstrated significant potential in human-machine interactions (HMIs) in terms of hygiene and less wear and tear. The development of soft, stable, and simply structured noncontact sensors is highly desired for their practical applications in HMIs. This work reports on electret-based self-powered noncontact sensors that are soft, transparent, stable, and easy to manufacture. The sensors contain a three-layer structure with a thickness of 0.34 mm that is fabricated by simply stacking a polymeric electret layer, an electrode layer, and a substrate layer together. The fabricated sensors show high charge-retention capability, keeping over 98% of the initial surface potential even after 90 h, and can accurately and repeatedly sense external approaching objects with impressive durability. The intensity of the detected signal shows a strong dependence on the distance between the object and the sensor, capable of sensing a distance as small as 2 mm. Furthermore, the sensors can report stable signals in response to external objects over 3000 cycles. By virtue of the signal dependence on distance, an intelligent noncontact positioning system is developed that can precisely detect the location of an approaching object. Finally, by integrating with eyeglasses, the transparent sensor successfully captures the movements of blinks for information translation. This work may contribute to the development of stable and easily manufactured noncontact soft sensors for HMI applications, for instance, assisting with communication for locked-in syndrome patients.

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Enhancing the output performance of triboelectric nanogenerators (TENGs) is essential for increasing their application in smart devices. Oxygen-vacancy-rich BiO2-x nanosheets (BiO2-x NSs) are advanced-engineered nanomaterials with excellent piezoelectric properties. Herein, a stretchable unsymmetrical BiO2-x NSs deposited-hydrogel made of polyacrylamide (PAM) as a multimodal TENG is rationally fabricated, and the performance of TENG can be tailored by controlling the BiO2-x NSs deposition amount and spatial distribution. The alteration of resistance caused by the Poisson effect of PAM/BiO2-x composite hydrogel (H-BiO2-x) can be used as a piezoresistive sensor, and the piezoelectricity of BiO2-x NSs can effectively enhance the density of transfer charge, thus improving the output performance of the H-BiO2-x-based TENG. In addition, the chemical cross-linking between the BiO2-x NSs and the PAM polymer chain allows the hydrogel electrode to have a higher tensile capacity (867%). Used for biomechanical motion signal detection, the sensors made of H-BiO2-x have high sensitivity (gauge factor = 6.93) and can discriminate a range of forces (0.1-5.0 N) at low frequencies (0.5-2.0 Hz). Finally, the prepared TENG can collect biological energy and convert it into electricity. Consequently, the improved TENG shows a good application prospect as multimodal biomechanical sensors by combining piezoresistive, piezoelectric, and triboelectric effects.

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Designing a high-performing triboelectric novel material with eco-friendly, rapid, and cost-effective synthesis is the future of material research in triboelectric nanogenerators (TENG). We report a mechanochemical ball mill synthesis of a zeolitic tetrazolate framework (ZTF-8) that is isostructural with the well-known zeolitic imidazolate framework ZIF-8. ZTF-8 is extremely stable in water, 0.1 M aqueous acid/base solutions for 75 days at 25 °C, and boiling water (100 °C) for 7 days. Kelvin probe force microscopy and molecular electrostatic surface potential computational analysis exhibited that ZTF-8 has a very high positive surface potential. Atomic force microscopy and three-dimensional digital microscopy studies reveal the high roughness profile in the ZTF-8 film. The unique structure, exceptional acid/base stability, good dielectric property, and high roughness profile combined with the extremely electropositive nature of ZTF-8 make it a suitable candidate as a polymer-free triboelectric positive material in TENG with outstanding performance (power density of 720 mW/m2). High triboelectric output was further validated using the COMSOL Multiphysics simulation tool. Simple mechanical hand tapping of the ZTF-based TENG (ZTF-TENG) device generates high electric output, which was practically used to power numerous low-powered devices like tally counter, clinical thermometer, and digital clock and also illuminates 125 light-emitting diodes. In addition, the efficiency of ZTF-TENG was utilized as a self-powered device for a selective dopamine (DA) sensor with good sensitivity (377.76 mV/µM/cm2), wide range linearity (5-120 µM), and excellent limit of detection (0.42 µM).

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Developing a robust artificial intelligence of things (AIoT) system with a self-powered triboelectric sensor for harsh environment is challenging because environmental fluctuations are reflected in triboelectric signals. This study presents an environmentally robust triboelectric tire monitoring system with deep learning to capture driving information in the triboelectric signals generated from tire-road friction. The optimization of the process and structure of a laser-induced graphene (LIG) electrode layer in the triboelectric tire is conducted, enabling the tire to detect universal driving information for vehicles/robotic mobility, including rotation speeds of 200-2000 rpm and contact fractions of line. Employing a hybrid model combining short-term Fourier transform with a convolution neural network-long short-term memory, the LIG-based triboelectric tire monitoring (LTTM) system decouples the driving information, such as traffic lines and road states, from varied environmental conditions of humidity (10%-90%) and temperatures (50-70 °C). The real-time line and road state recognition of the LTTM system is confirmed on a mobile platform across diverse environmental conditions, including fog, dampness, intense sunlight, and heat shimmer. This work provides an environmentally robust monitoring AIoT system by introducing a self-powered triboelectric sensor and hybrid deep learning for smart mobility.

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Enzyme biofuel cells (EBFCs) can convert chemical or biochemical energy in fuel into electrical energy, and therefore have received widespread attention. EBFCs have advantages that traditional fuel cells cannot match, such as a wide range of fuel sources, environmental friendliness, and mild reaction conditions. At present, research on EBFCs mainly focuses on two aspects: one is the use of nanomaterials with excellent properties to construct high-performance EBFCs, and the other is self-powered sensors based on EBFCs. This article reviews the applied nanomaterials based on the working principle of EBFCs, analyzes the design ideas of self-powered sensors based on enzyme biofuel cells, and looks forward to their future research directions and application prospects. This article also points out the key properties of nanomaterials in EBFCs, such as electronic conductivity, biocompatibility, and catalytic activity. And the research on EBFCs is classified according to different research goals, such as improving battery efficiency, expanding the fuel range, and achieving self-powered sensors.

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Avoiding collisions is a key necessity for any autonomous mobile robot, and obstacle mapping enables them to maneuver in an uncharted area. In this era of the Internet of Things, with the emerging need for a multitude of sensors, adopting self-powered technologies is more practically viable than batteries for powering the same. Herein, with the fabrication of a triboelectric artificial whisker (TAW), a self-powered obstacle detection is demonstrated via tactile perception. The mechanical contact with the obstacle gives rise to an electrical signal from the TAW owing to the embedded triboelectric sensor. In addition, the triboelectric nanogenerator (TENG) based on electrospun polyacrylonitrile (PAN) nanofibers and polydimethylsiloxane film, which facilitates this self-powered artificial sensation, generates an output voltage of 720 V and current density of 5 mA m-2 with 1.7 W m-2 of maximum power delivery from a force of 10 N. The electro-spinning aided enhancement in contact area of the PAN is responsible for the remarkable improvement in the performance of the TENG, 3.4 times enhancement in power density, when compared to the nonsurface-modified ones. In addition, the TENG is able to charge commercial capacitors up to appreciable values and demonstrates powering different electronic gadgets such as calculators and thermometers.

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Self-powered vibration sensor is highly desired for distributed and continuous monitoring requirements of Industry 4.0. Herein, a flexible fiber-shaped triboelectric nanogenerator (F-TENG) with a coaxial core-shell structure is proposed for the vibration monitoring. The F-TENG exhibits higher adaptability to the complex surfaces, which has an outstanding application prospect due to vital compensation for the existing rigid sensors. Initially, the contact characteristics between the dielectric layers, that related to the perceiving performance of the TENG, are theoretically analyzed. Such a TENG with 1D structure endows high sensitivity, allowing for accurately responding to a wide range of vibration frequencies (0.1 to 100 Hz). Even applying to the real diesel engine, the error in detecting the vibration frequencies is only 0.32% compared with the commercial vibration sensor, highlighting its potential in practical application. Further, assisted by deep learning, the recognition accuracy in monitoring nine operating conditions of the system achieves 97.87%. Overall, the newly designed F-TENG with the merits of high-adaptability, cost-efficiency, and self-powered, has offered a promising solution to fulfill an extensive range of vibration sensing applications in the future.

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Energy harvesting has become an increasingly important field of research as the demand for portable and wearable devices continues to grow. Skin-contact triboelectric nanogenerator (TENG) technology has emerged as a promising solution for energy harvesting and motion sensing. This review paper provides a detailed overview of skin-contact TENG technology, covering its principles, challenges, and perspectives. The introduction begins by defining skin-contact TENG and explaining the importance of energy harvesting and motion sensing. The principles of skin-contact TENG are explored, including the triboelectric effect and the materials used for energy harvesting. The working mechanism of skin-contact TENG is also discussed. This study then moves onto the applications of skin-contact TENG, focusing on energy harvesting for wearable devices and motion sensing for healthcare monitoring. Furthermore, the integration of skin-contact TENG technology with other technologies is discussed to highlight its versatility. The challenges in skin-contact TENG technology are then highlighted, which include sensitivity to environmental factors, such as humidity and temperature, biocompatibility and safety concerns, and durability and reliability issues. This section of the paper provides a comprehensive evaluation of the technological limitations that must be considered when designing skin-contact TENGs. In the Perspectives and Future Directions section, this review paper highlights various advancements in materials and design, as well as the potential for commercialization. Additionally, the potential impact of skin-contact TENG technology on the energy and healthcare industries is discussed.

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Green energy from the surrounding environment has great potential for reducing environmental pollution and sustainable development. Triboelectric nanogenerators (TENGs) are of great interest as they can easily harvest mechanical energy from the environment. Here, we present a triboelectric nanogenerator (RS-TENG) based on rape straw (RS), which was developed from a film composed of waste RS and polyvinyl alcohol (PVA). Due to the high content of carbonyl, hydroxyl and amino acid functional groups in RS, the ability of RS/PVA to lose electrons is increased. The proposed RS-TENG device with a size of 6.25 cm2exhibits open circuit voltage (78 V), short circuit current (5.3µA) performance under uniform external stress at a frequency of 3.5 Hz and 10 N in the cylinder motor. 104.5µW was obtained with a load resistance of 25 MΩ. Results obtained from degradability tests revealed that the RS/PVA film was able to degrade over a period of 30 d (In PBS solution). The RS-TENG produces a significantly high current signal under conditions of finger bending, elbow movements, and foot tapping. Practical tests of the RS-TENG have shown that it is a promising sensing device that will be widely used in the future.

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With the popularization of the Internet of Things, the application of chemical sensors has become more and more extensive. However, it is difficult for a single functional sensor to meet multiple needs at the same time. For the next generation of chemical sensors, in addition to rapid qualitative and quantitative detection, it is also necessary to solve the problem of a distributed sensor power supply. Triboelectric nanogenerator (TENG) and surface-enhanced Raman scattering (SERS) are two emerging technologies that can be used for chemical testing. The combination of TENG and SERS technology is proposed to be an attractive research strategy to implement qualitative and quantitative analysis, as well as self-powered detection in one device. Herein, the Ag nanoparticle (NP)@polydimethylsiloxane (PDMS) plasmonic cavity is demonstrated, which can be exploited not only as a SERS substrate for qualitative analysis of the target molecules but also as a TENG based self-powered chemical sensor for rapid quantitative analysis. More importantly, the as-designed plasmonic cavity enables prolonged triboelectric field generated by the phenomena of triboelectricity, which in turn enhances the "hot spot" intensities from Ag NPs in the cavity and boosts the SERS signals. In this way, the device can have good feasibility and versatility for chemical detection. Specifically, the measurement of the concentration of many analytes can be successfully realized, including ions and small molecules. The results verify that the proposed sensor system has the potential for self-powered chemical sensors for environmental monitoring and analytical chemistry.

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The development of triboelectric nanogenerators (TENGs) over time has resulted in considerable improvements to the efficiency, effectiveness, and sensitivity of self-powered sensing. Triboelectric nanogenerators have low restriction and high sensitivity while also having high efficiency. The vast majority of previous research has found that accidents on the road can be attributed to road conditions. For instance, extreme weather conditions, such as heavy winds or rain, can reduce the safety of the roads, while excessive temperatures might make it unpleasant to be behind the wheel. Air pollution also has a negative impact on visibility while driving. As a result, sensing road surroundings is the most important technical system that is used to evaluate a vehicle and make decisions. This paper discusses both monitoring driving behavior and self-powered sensors influenced by triboelectric nanogenerators (TENGs). It also considers energy harvesting and sustainability in smart road environments such as bridges, tunnels, and highways. Furthermore, the information gathered in this study can help readers enhance their knowledge concerning the advantages of employing these technologies for innovative uses of their powers.

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Hydrogels are three-dimensional polymer networks with excellent flexibility. In recent years, ionic hydrogels have attracted extensive attention in the development of tactile sensors owing to their unique properties, such as ionic conductivity and mechanical properties. These features enable ionic hydrogel-based tactile sensors with exceptional performance in detecting human body movement and identifying external stimuli. Currently, there is a pressing demand for the development of self-powered tactile sensors that integrate ionic conductors and portable power sources into a single device for practical applications. In this paper, we introduce the basic properties of ionic hydrogels and highlight their application in self-powered sensors working in triboelectric, piezoionic, ionic diode, battery, and thermoelectric modes. We also summarize the current difficulty and prospect the future development of ionic hydrogel self-powered sensors.

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Advanced interfacial engineering has the potential to enable the successful realization of three features that are particularly important for a variety of healthcare applications: wettability control, antimicrobial activity to reduce infection risks, and sensing of physiological parameters. Here, a sprayable multifunctional triboelectric coating is exploited as a nontoxic, ultrathin tactile sensor that can be integrated directly on the fingertips of surgical gloves. The coating is based on a polymer blend mixed with zinc oxide (ZnO) nanoparticles, which enables antifouling and antibacterial properties. Additionally, the nanocomposite is superhydrophobic (self-cleaning) and is not cytotoxic. The coating is also triboelectric and can be applied directly onto surgical gloves with printed electrodes. The sensorized gloves so obtained enable mechanical energy harvesting, force sensing, and detection of materials stiffness changes directly from fingertip, which may complement proprioceptive feedback for clinicians. Just as importantly, the sensors also work with a second glove on top offering better reassurance regarding sterility in interventional procedures. As a case study of clinical use for stiffness detection, the sensors demonstrate successful detection of pig anal sphincter injury ex vivo. This may lead to improving the accuracy of diagnosing obstetric anal sphincter injury, resulting in prompt repair, fewer complications, and improved quality of life.

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With the development of 5G, artificial intelligence, and the Internet of Things, diversified sensors (such as the signal acquisition module) have become more and more important in people's daily life. According to the extensive use of various distributed wireless sensors, powering them has become a big problem. Among all the powering methods, the self-powered sensor system based on triboelectric nanogenerators (TENGs) has shown its superiority. This review focuses on four major application areas of wireless sensors based on TENG, including environmental monitoring, human monitoring, industrial production, and daily life. The perspectives and outlook of the future development of self-powered wireless sensors are discussed.