Directional Moisture-Wicking Triboelectric Materials Enabled by Laplace Pressure Differences.

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.

Coaxial Flexible Fiber-Shaped Triboelectric Nanogenerator Assisted by Deep Learning for Self-Powered Vibration Monitoring.

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.

Environmentally Robust Triboelectric Tire Monitoring System for Self-Powered Driving Information Recognition via Hybrid Deep Learning in Time-Frequency Representation.

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.

Enhanced Sensitivity in Photovoltaic 2D MoS2/Te Heterojunction VOC Sensors.

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.

Nanofibrous PAN-PDMS Films-Based High-Performance Triboelectric Artificial Whisker for Self-Powered Obstacle Detection.

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.

Advanced Applications of Porous Materials in Triboelectric Nanogenerator Self-Powered Sensors.

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.

Research Progress in Enzyme Biofuel Cells Modified Using Nanomaterials and Their Implementation as Self-Powered Sensors.

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.

Hydrovoltaic Nanogenerators for Self-Powered Sweat Electrolyte Analysis.

Human sweat comprises various electrolytes that are health status indicators. Conventional potentiometric electrolyte sensors require an electrical power source, which is expensive, bulky, and requires a complex architecture. Herein, this work demonstrates an electric nanogenerator fabricated using silicon nanowire (SiNW) arrays comprising modified carbon nanoparticles. The SiNW arrays platform is demonstrated as an effective self-powered sensor for sweat electrolyte analysis. It has been shown that an evaporation-induced water flow in nanochannels can yield an open-circuit voltage (Voc ) of 0.45 V and a short-circuit current of 10.2 µA at room temperature as a result of overlapped electric double layers. The electrolyte in the water flow results in a Voc decrease due to the charge shielding effect. The Voc is inversely proportional to the electrolyte concentration. The fabricated hydrovoltaic device shows the capability for sensing electrolytes in human sweat, which is useful in evaluating the hydration status of volunteers following intense physical exercise. The device depicts a novel response mechanism compared to conventional electrochemical sensors. Furthermore, the hydrovoltaic device shows a maximum output power of 1.42 µW, and as such has been successfully shown to drive various electronic devices including light-emitting diodes, a calculator, and an electronic timer.

Carbon Dots-Based Ultrastretchable and Conductive Hydrogels for High-Performance Tactile Sensors and Self-Powered Electronic Skin.

Smart tactile sensing materials have excellent development prospects, including wearable health-monitoring equipment and energy collection. Hydrogels have received extensive attention in tactile sensing owing to their transparency and high elasticity. In this study, highly crosslinked hydrogels are fabricated by chemically crosslinking polyacrylamide with lithium magnesium silicate and decorated with carbon quantum dots. Magnesium lithium silicate provides abundant covalent bonds and improves the mechanical properties of the hydrogels. The luminescent properties endowed by the carbon dots further broaden the application of hydrogels for realizing flexible electronics. The hydrogel-based strain sensor exhibits excellent sensitivity (gauge factor 2.6), a broad strain response range (0-2000%), good cyclicity, and durability (1250). Strain sensors can be used to detect human motions. More importantly, the hydrogel can also be used as a flexible self-supporting triboelectric electrode for effectively detecting pressure in the range of 1-25 N and delivering a short-circuit current (ISC ) of 2.6 µA, open-circuit voltage (VOC ) of 115 V, and short-circuit transfer charge (QSC ) of 29 nC. The results reveal new possibilities for human-computer interactions and electronic robot skins.

Scalable Fabrication of MXene-PVDF Nanocomposite Triboelectric Fibers via Thermal Drawing.

In the data-driven world, textile is a valuable resource for improving the quality of life through continuous monitoring of daily activities and physiological signals of humans. Triboelectric nanogenerators (TENG) are an attractive option for self-powered sensor development by coupling energy harvesting and sensing ability. In this study, to the best of the knowledge, scalable fabrication of Ti3 C2 Tx MXene-embedded polyvinylidene fluoride (PVDF) nanocomposite fiber using a thermal drawing process is presented for the first time. The output open circuit voltage and short circuit current show 53% and 58% improvement, respectively, compared to pristine PVDF fiber. The synergistic interaction between the surface termination groups of MXene and polar PVDF polymer enhances the performance of the fiber. The flexibility of the fiber enables the weaving of fabric TENG devices for large-area applications. The fabric TENG (3 × 2 cm2 ) demonstrates a power density of 40.8 mW m-2 at the matching load of 8 MΩ by maintaining a stable performance over 12 000 cycles. Moreover, the fabric TENG has shown the capability of energy harvesting by operating a digital clock and a calculator. A distributed self-powered sensor for human activities and walking pattern monitoring are demonstrated with the fabric.

Eco-friendly triboelectric nanogenerator based on degradable rape straw powder for monitoring human movement.

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.

Recent Progress in Self-Powered Wireless Sensors and Systems Based on TENG.

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.

Advancements in Triboelectric Nanogenerators (TENGs) for Intelligent Transportation Infrastructure: Enhancing Bridges, Highways, and Tunnels.

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.

Fish-Wearable Data Snooping Platform for Underwater Energy Harvesting and Fish Behavior Monitoring.

Conventional approaches to studying fish kinematics pose a great challenge for the real-time monitoring of fish motion kinematics. Here, a multifunctional fish-wearable data snooping platform (FDSP) for studying fish kinematics is demonstrated based on an air sac triboelectric nanogenerator (AS-TENG) with antibacterial coating. The AS-TENG not only can harvest energy from fish swimming but also serves as the self-powered sensory module to monitor the swimming behavior of the fish. The peak output power generated from each swing of the fishtail can reach 0.74 mW, while its output voltage can reflect the real-time behavior of the fishtail. The antibacterial coating on the FDSP can improve its biocompatibility and the elastic texture of the FDSP allows it to be tightly attached to fish. The wireless communication system is designed to transmit the sensory data to a cell phone, where the detailed parameters of fish motion can be obtained, including swing angle, swing frequency, and even the typical swing gestures. This FDSP has broad application prospects in underwater self-powered sensors, wearable tracking devices, and soft robots.

Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning.

With the rapid development of human-machine interfaces, artificial acoustic sensors play an important role in the hearing impaired. Here, an ultrathin eardrum-like triboelectric acoustic sensor (ETAS) is presented consisting of silver-coated nanofibers, whose thickness is only 40 µm. The sensitivity and frequency response range of the ETAS are closely related to the geometric parameters. The ETAS endows a high sensitivity of 228.5 mV Pa-1 at 95 dB, and the ETAS has a broad frequency response ranging from 20 to 5000 Hz, which can be tuned by adjusting the thickness, size, or shape of the sensor. Cooperating with artificial intelligence (AI) algorithms, the ETAS can achieve real-time voice conversion with a high identification accuracy of 92.64%. Under good working property and the AI system, the ETAS simplifies signal processing and reduces the power consumption. This work presents a strategy for self-power auditory systems, which can greatly accelerate the miniaturization of self-powered systems used in wearable electronics, augmented reality, virtual reality, and control hubs for automation.

High-Efficiency Poly(Vinylidene Fluoride-Co-Hexafluoropropylene) Loaded 3D Marigold Flower-Like Bismuth Tungstate Triboelectric Films for Mechanical Energy Harvesting and Sensing Applications.

Triboelectric nanogenerators (TENGs) are one of the most trending energy harvesting devices because of their efficient and simple mechanism in harvesting mechanical energy from the environment into electricity. Herein, ferroelectric and dielectric bismuth tungstate (Bi2 WO6 (BWO)) with a marigold flower-like structure is prepared via a hydrothermal method, which is embedded in poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), forming a PVDF-HFP/BWO composite polymer film (CPF) to fabricate TENGs. Generally, the ferroelectric materials exhibit a large piezoelectric coefficient, high electrostatic dipole moment, and high dielectric constant. The prepared PVDF-HFP/BWO CPF reveals a high polar crystalline ß-phase which leads to enhanced piezoelectric and ferroelectric properties of the CPF, thus resulting in the increased electrical performance of the fabricated TENG. The electrical output performance of the proposed TENG is systematically investigated by varying the amount of BWO material embedded in the PVDF-HFP polymer. The fabricated PVDF-HFP/2.5 wt% BWO CPF-based TENG device exhibits the highest electrical output performance. Additionally, the robust test of the TENG device is conducted to investigate the electrical performance for long-term durability and mechanical stability. Finally, the proposed TENG is operated as a self-powered sensor, harvesting mechanical energy from daily life human activities, and powering various low-power portable electronics.

Self-Powered Low-Cost UVC Sensor Based on Organic-Inorganic Heterojunction for Partial Discharge Detection.

Power outages caused by the aging of high-voltage power facilities can cause significant economic and social damage. To prevent such problems, it is necessary to implement a widespread and sustainable monitoring system. Partial discharge (PD) is a preliminary symptom of power equipment aging accompanying the light, typically in the UV range. UVC (200-280 nm) is more useful than UVA and UVB because of low interference from the environment owing to its solar-blindness by the stratosphere. Therefore, to realize a wide-range and durable diagnosis system, it is necessary to develop sensors that can selectively detect UVC, while enabling mass production at low-cost and low power consumption. Here, a solution-processable photodiode sensor that is inexpensive, mass-producible, and self-powered with selective UVC detection is developed. The optoelectronic characteristics of photodiode consisting of organic p-polymer and inorganic n-ZnO nanoparticles are systematically studied to determine the optimum p-type polymer and its thickness. The device shows high-performance: fast response time (rise/fall time: 36.6/37.0 ms) and high spectral response in the UVC region (maximum responsivity of 20 mA W-1 ) under self-powered operation. Furthermore, the practical application of the device to detect PD signals with a visual alarm system under UVC release conditions is demonstrated.

System Implementation Trade-Offs for Low-Speed Rotational Variable Reluctance Energy Harvesters.

Low-power energy harvesting has been demonstrated as a feasible alternative for the power supply of next-generation smart sensors and IoT end devices. In many cases, the output of kinetic energy harvesters is an alternating current (AC) requiring rectification in order to supply the electronic load. The rectifier design and selection can have a considerable influence on the energy harvesting system performance in terms of extracted output power and conversion losses. This paper presents a quantitative comparison of three passive rectifiers in a low-power, low-voltage electromagnetic energy harvesting sub-system, namely the full-wave bridge rectifier (FWR), the voltage doubler (VD), and the negative voltage converter rectifier (NVC). Based on a variable reluctance energy harvesting system, we investigate each of the rectifiers with respect to their performance and their effect on the overall energy extraction. We conduct experiments under the conditions of a low-speed rotational energy harvesting application with rotational speeds of 5 rpm to 20 rpm, and verify the experiments in an end-to-end energy harvesting evaluation. Two performance metrics-power conversion efficiency (PCE) and power extraction efficiency (PEE)-are obtained from the measurements to evaluate the performance of the system implementation adopting each of the rectifiers. The results show that the FWR with PEEs of 20% at 5 rpm to 40% at 20 rpm has a low performance in comparison to the VD (40-60%) and NVC (20-70%) rectifiers. The VD-based interface circuit demonstrates the best performance under low rotational speeds, whereas the NVC outperforms the VD at higher speeds (>18 rpm). Finally, the end-to-end system evaluation is conducted with a self-powered rpm sensing system, which demonstrates an improved performance with the VD rectifier implementation reaching the system's maximum sampling rate (40 Hz) at a rotational speed of approximately 15.5 rpm.

Cellulose II Aerogel-Based Triboelectric Nanogenerator.

Cellulose-based triboelectric nanogenerators (TENGs) have gained increasing attention. In this study, a novel method is demonstrated to synthesize cellulose-based aerogels and such aerogels are used to fabricate TENGs that can serve as mechanical energy harvesters and self-powered sensors. The cellulose II aerogel is fabricated via a dissolution-regeneration process in a green inorganic molten salt hydrate solvent (lithium bromide trihydrate), where. The as-fabricated cellulose II aerogel exhibits an interconnected open-pore 3D network structure, higher degree of flexibility, high porosity, and a high surface area of 221.3 m2 g-1. Given its architectural merits, the cellulose II aerogel-based TENG presents an excellent mechanical response sensitivity and high electrical output performance. By blending with other natural polysaccharides, i.e., chitosan and alginic acid, electron-donating and electron-withdrawing groups are introduced into the composite cellulose II aerogels, which significantly improves the triboelectric performance of the TENG. The cellulose II aerogel-based TENG is demonstrated to light up light-emitting diodes, charge commercial capacitors, power a calculator, and monitor human motions. This study demonstrates the facile fabrication of cellulose II aerogel and its application in TENG, which leads to a high-performance and eco-friendly energy harvesting and self-powered system.

Tactile UV- and Solar-Light Multi-Sensing Rechargeable Batteries with Smart Self-Conditioned Charge and Discharge.

A tactile, UV- and solar-light multi-sensing smart rechargeable Zn-air battery (SRZAB) with excellent cell performance, self-conditioned charge/discharge, and reliable environmental responsivity is made by using multi-scale conjugated block-copolymer-carbon nanotube-polyurethane foam assemblies as both a self-standing air electrode and a sensing unit. Multiscale engineering fully exploits the multi-synergy among components to endow the newly designed metal-free multi-sensing air electrode (MSAE) with bifunctional oxygen reduction and evolution activities, pressure sensitivity, and photothermal and photoelectric conversion functions in a single electrode, enabling effective regulation of interface properties, electronic/ionic transport, or redox reactions in SRZAB upon various stimulations and establishing multiple working principles. MSAE-driven SRZAB can be used as compressible power sources, self-powered pressure and optical sensors and light-to-electrochemical energy systems.