The rapid development of wearable electronic devices and virtual reality technology has revived interest in flexible sensing and control devices. Here, we report an ionic hydrogel (PTSM) prepared from polypropylene amine (PAM), tannic acid (TA), sodium alginate (SA), and MXene. Based on the multiple weak H-bonds, this hydrogel exhibits excellent stretchability (strain >4600%), adhesion, and self-healing. The introduction of MXene nanosheets endows the hydrogel sensor with a high gauge factor (GF) of 6.6. Meanwhile, it also enables triboelectric nanogenerators (PTSM-TENGs) fabricated from silicone rubber-encapsulated hydrogels to have excellent energy harvesting efficiency, with an instantaneous output power density of 54.24 mW/m2. We build a glove-based human-computer interaction (HMI) system using PTSM-TENGs. The multidimensional signal features of PTSM-TENG are extracted and analyzed by the HMI system, and the functions of gesture visualization and robot hand control are realized. In addition, triboelectric signals can be used for object recognition with the help of machine learning techniques. The glove based on PTSM-TENG achieves the classification and recognition of five objects through contact, with an accuracy rate of 98.7%. Therefore, strain sensors and triboelectric nanogenerators based on hydrogels have broad application prospects in man-machine interface, intelligent recognition systems, auxiliary control systems, and other fields due to their excellent stretchable and high self-healing performance.

Ultrastretchable, Self-Healing Conductive Hydrogel-Based Triboelectric Nanogenerators for Human-Computer Interaction.

The building sector, including building operations and materials, was responsible for the emission of ∼11.9 gigatons of global energy-related CO2 in 2020, accounting for 37% of the total CO2 emissions, the largest share among different sectors. Lowering the carbon footprint of buildings requires the development of carbon-storage materials as well as novel designs that could enable multifunctional components to achieve widespread applications. Wood is one of the most abundant biomaterials on Earth and has been used for construction historically. Recent research breakthroughs on advanced engineered wood products epitomize this material's tremendous yet largely untapped potential for addressing global sustainability challenges. In this review, we explore recent developments in chemically modified wood that will produce a new generation of engineered wood products for building applications. Traditionally, engineered wood products have primarily had a structural purpose, but this review broadens the classification to encompass more aspects of building performance. We begin by providing multiscale design principles of wood products from a computational point of view, followed by discussion of the chemical modifications and structural engineering methods used to modify wood in terms of its mechanical, thermal, optical, and energy-related performance. Additionally, we explore life cycle assessment and techno-economic analysis tools for guiding future research toward environmentally friendly and economically feasible directions for engineered wood products. Finally, this review highlights the current challenges and perspectives on future directions in this research field. By leveraging these new wood-based technologies and analysis tools for the fabrication of carbon-storage materials, it is possible to design sustainable and carbon-negative buildings, which could have a significant impact on mitigating climate change.

Emerging Engineered Wood for Building Applications.

A review of single electrode triboelectric nanogenerators

The Artificial Intelligence of Things (AIoT) connects everything with intelligence, while the increase in energy consumption generated by numerous electronic devices puts forward an impending demand on the power supply. Energy harvesting technology has emerged as a compelling innovation technology for the net zero emissions of the power supply for the AIoT. Although significant advances have been witnessed in energy harvesting, some issues such as poor electrical output, weak environmental adaptability, and low reliability are difficult to satisfactorily resolve. Mechanical intelligent energy harvesting can be defined as the system identifying the external excitation or its own state and reacting to it, rather than relying on electrical sensing elements or a central controller for certain adaptive or programmed functions. The adaptive and programmed functions exhibit great potential in solving the above-mentioned issues that seriously restrict the development of the energy harvesting technology. Here, a generalized definition of mechanical intelligent energy harvesting is given critically and the design methodology is elaborated. The typical reported energy harvesting systems with the characteristics of mechanical intelligence are reviewed. The key research directions in mechanical intelligent energy harvesting are discussed. The mechanical intelligence is expected to revolutionize the development of the energy-harvesting technology and pave the way for applications. 

Mechanical Intelligent Energy Harvesting: From Methodology to Applications

The rapid rise of triboelectric nanogenerators (TENGs), which are emerging energy conversion devices in advanced electronics and wearable sensing systems, has elevated the interest in high‐performance and multifunctional triboelectric materials. Among them, cellulosic materials, affording high efficiency, biodegradability, and customizability, are becoming a new front‐runner. The inherently low dielectric constant limits the increase in the surface charge density. However, owing to its unique structure and excellent processability, cellulose shows great potential for dielectric modulation, providing a strong impetus for its advanced applications in the era of Internet of Things and artificial intelligence. This review aims to provide comprehensive insights into the fabrication of dielectric‐enhanced cellulosic triboelectric materials via dielectric modulation. The exceptional advantages and research progress in cellulosic materials are highlighted. The effects of the dielectric constant, polarization, and percolation threshold on the charge density are systematically investigated, providing a theoretical basis for cellulose dielectric modulation. Typical dielectric characterization methods are introduced, and their technical characteristics are analyzed. Furthermore, the performance enhancements of cellulosic triboelectric materials endowed by dielectric modulation, including more efficient energy harvesting, high‐performance wearable electronics, and impedance matching via material strategies, are introduced. Finally, the challenges and future opportunities for cellulose dielectric modulation are summarized.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/advs.202206243

Fabrication of Advanced Cellulosic Triboelectric Materials via Dielectric Modulation

With the rapid development of the Internet of Things, artificial intelligence, and big data, the smart home has played a critical role in human life and smart cities, where large amounts of distributed sensors should be applied. Here, we report a natural wood-based triboelectric self-powered sensor (WTSS) for building the smart home system. Based on an effective and simple treatment strategy for natural wood, the WTSS shows superior sensitivity, flexibility, stability, and thinness. Owing to the extensive use of wood materials in home construction, the WTSS is integrated with household facilities and applied in three real-time human-machine interfaces, including a smart home control system, a smart password gate control system, and a smart floor monitoring system, with advantages of low cost, easy operation, and eco-friendliness. This work promotes the development of wood-based flexible electronics and shows potential applications in the construction of smart homes and future cities.

Flexible Wood-Based Triboelectric Self-Powered Smart Home System.

Sleep quality plays an essential role in human health and has become an index for assessing physical health. Self-powered, sensitive, noninvasive, comfortable, and low-cost sleep monitoring sensors for monitoring sleep behavior are still in high demand. Here, a pressure-sensitive, noninvasive, and comfortable smart pillow is developed based on a flexible and breathable triboelectric nanogenerator (FB-TENG) sensor array, which can monitor head movement in real time during sleep. The FB-TENG is based on flexible and breathable porous poly(dimethylsiloxane) (PDMS) with a fluorinated ethylene propylene (FEP) powder and exhibits pressure sensitivity and durability. The electrical output of the FB-TENG is further optimized by modifying the porous structure and the FEP powder. Combining the FB-TENG and the flexible printed circuit (FPC), a self-powered pressure sensor array is fabricated to realize touch sensing and motion track monitoring. The smart pillow is formed by laying the self-powered pressure sensor array on an ordinary pillow to realize real-time monitoring of the head position in a static state and head movement trajectory in a dynamic state during sleep. Additionally, the smart pillow also has an early warning function for falling out of bed. This work not only provides a viable sensing device for sleep monitoring but also could be extended to real-time monitoring of some diseases, such as brain diseases and cervical spondylosis, in the future. It is expected to introduce a practical strategy in the real-time mobile healthcare field for disease management.

Smart Pillow Based on Flexible and Breathable Triboelectric Nanogenerator Arrays for Head Movement Monitoring during Sleep.

The force distribution in the oceans, which cover 71% of the Earth's surface, is relatively unknown compared to the cosmos between Earth and 13.8 billion light years away due to the lack of sensors that can operate over long periods in a harsh underwater environments. Herein, a self‐powered underwater force sensor (SUFS) is reported based on a T‐shaped triboelectric nanogenerator (T‐TENG) for simultaneous detection of normal and tangential forces of finger touching as well as water flow exerted on the underwater objects. The SUFS based on two coupled TENGs can detect normal and tangential forces working in different TENG modes. The T‐shaped structure and atmosphere of the airbag inside the SUFS are optimized for improved electrical outputs. Furthermore, simple method suitable for mass production is also proposed to achieve a superhydrophobic surface with an underwater anti‐interference function. The SUFS can effectively monitor the angle α, force, and frequency of the kayak paddle and finger touching, and is promising for self‐powered intelligent motion sensing, soft robotics, human–computer interaction, and ocean monitoring in general.

Self‐Powered Underwater Force Sensor Based on a T‐Shaped Triboelectric Nanogenerator for Simultaneous Detection of Normal and Tangential Forces

Acceleration sensors have wide applications in earthquake warning, human motion recognition, vehicle restraint system, etc. However, the existing commercial acceleration sensors have some limitations on needing an external power supply, high fabrication cost, and small signal when self‐powered. Here a grating‐structured freestanding triboelectric nanogenerator (GF‐TENG) capable of sensing displacements, velocities, and accelerations in real‐time is presented with self‐powered, low cost, and sufficiently large signal. The slider with grating‐structured electrodes of GF‐TENG sliding over the stator with another grating‐structured electrode generates the periodic open‐circuit voltage due to electrostatic induction. By recognizing the shape of open‐circuit voltage, it could sense the acceleration in real time even at scales down to hundred microns through systematic optimization of simulations and experiments. Furthermore, the acceleration sensing range could be expanded to the desired ranges, such as 5.0 to 45.0 m s–2, by assembling springs and GF‐TENG into a grating‐structured TENG‐based acceleration sensor (GTAS). Moreover, GTAS is demonstrated to sense the vehicle motion and be a part of the vehicle restraint system on a model car. This work reports a new self‐powered acceleration sensor with sufficiently large outputs for real‐time motion sensing and collision detection, which could be further applicated for robotics and human motion recognition.

Grating‐Structured Freestanding Triboelectric Nanogenerator for Self‐Powered Acceleration Sensing in Real Time

Contact electrification (CE), a common physical phenomenon, is worth discussing. However, there are few reports on the influence of atmosphere on CE, or on the performance of triboelectric nanogenerators (TENG), based on CE by encapsulating gas inside. Here, we propose physical processes of electron transfer to interpret the impact of the gaseous atmosphere on CE. An atmosphere-filled triboelectric nanogenerator (AF-TENG) encapsulated five different gas-components of air based on the vertical contact separation mode was prepared. The sensitivity (1.02 V·N−1) and the power density (9.63 μW·m−2) of the oxygen-atmosphere-filled AF-TENG were 229.03% and 157.81% higher than these (0.31 V·N−1 and 3.84 μW·m−2) of the nitrogen-atmosphere-filled AF-TENG. As the oxygen atom possesses more atomic energy levels than other atoms, this could act as a “bridge” for more electrons to directly transfer between the two materials. The device package under different atmospheres could not only strengthen understanding of CE and improve the performance of TENG, but also be potentially applicable to prevent and control unnecessary damage caused by static electricity.

Electron Transfer in Contact Electrification under Different Atmospheres Packaged inside TENG

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