ABSTRACT Real‐time monitoring of subtle muscle deformation remains of considerable importance for cooperative human‐exoskeleton control. Highly integrated flexible triboelectric nanogenerators (TENGs), owing to their self‐powered operation and high sensing resolution, are well suited for continuous physiological monitoring and human‐robot interaction (HRI). A flexible self‐powered wearable sensor (FSWS) based on a triboelectric nanogenerator is presented for real‐time monitoring of muscle‐induced strain on the thigh. By optimizing a three‐channel interdigitated electrode architecture, the device achieves a strain resolution as low as 0.025% and demonstrates durability beyond 600,000 cycles over a strain range of 0%–5%, enabling precise extraction of gait‐related features for exoskeleton cooperative control. An long short‐term memory (LSTM)‐based mapping network between muscle‐induced strain and real‐time gait is established, and the accuracy of lower‐limb motion trajectory recognition exceeds 95%. The FSWS is further integrated with a simulator‐based full‐drive control strategy to realize human‐exoskeleton collaborative adaptive control of a lower‐limb rehabilitation exoskeleton under different motion modes. Compared with adaptive admittance control, the proposed method shortens the response time by approximately 17 ms, reduces the control error by more than twofold, and decreases the human‐exoskeleton antagonistic torque by about fivefold. This work advances compliant and intelligent exoskeleton control and provides a practical reference for flexible TENG‐enabled HRI in clinical applications.
ABSTRACT The evolution of wearable and implantable electronics has redefined human‐machine interaction and clinical diagnostics. However, critical bottlenecks, including sensor performance, interfacial adaptation, and sustainable energy supply, etc., continue to hinder their widespread practical integration. Triboelectric nanogenerators (TENGs) have emerged as a promising platform, leveraging their unique working mechanism, inherent material universality, and self‐powered capabilities. This review synthesizes advancements in TENGs, encompassing architectural diversity, ultra‐high sensitivity to subtle mechanical deformations, innovations in chip‐less self‐powered wireless sensing and non‐contact perception, alongside triboelectric encoders to ensure high‐precision and stable wearable sensing. Furthermore, the frontiers of active bio‐interfacial interventions, including precision neuromodulation and therapeutic electrocatalysis, are explored. This review aims to provide an in‐depth summary of TENGs' unique properties and advantages, thereby facilitating the transition of wearable/implantable electronics from laboratory prototypes to commercial products.
ABSTRACT Robotic bionic tactile skins (RBTSs), as crucial components of next‐generation robotic systems, have attracted significant attention in recent years. By enabling robots to achieve human‐like tactile perception and interact effectively with their surroundings, RBTSs play an essential role in enhancing robotic intelligence. These skins can detect diverse tactile stimuli, including pressure, texture, temperature, and vibration, thereby providing robots with improved flexibility and sensory feedback. This review first discusses the fundamental principles of RBTSs, with a particular focus on key performance parameters such as sensitivity, response speed, and sensing range. It then systematically examines various design strategies, including material selection, biomimetic structural design, and manufacturing techniques, which have contributed to significant advances in tactile perception. Particular emphasis is placed on recent developments in bio‐inspired structures and multifunctional sensing capabilities, which have substantially improved the performance of bionic skins. Furthermore, this review explores diverse applications of RBTSs in human–robot interaction, dexterous manipulation, prosthetic tactile feedback, and AI‐enabled robotic systems. Finally, the current challenges and future directions in this field are discussed, with an emphasis on the integration of RBTSs into robotic platforms and the development of systems capable of simulating human tactile sensations for various future scenarios, thereby improving interactions with the physical world. This review aims to provide valuable insights for researchers and engineers in robotics and to offer a strategic roadmap for the further advancement of RBTSs.
ABSTRACT Ocean wave energy has enormous potential for sustainable power generation but conventional technologies often face challenges in efficiency, durability, and adaptability to specific sites. Triboelectric nanogenerators (TENGs) are able to convert irregular and low frequency water motion into electrical energy, but their performance depends on the mechanical interface that transmits the motion. In this study, we introduce a site‐specific strategy for wave energy harvesting, in which floating platform geometry is selected to enhance TENG activation under the dominant wave conditions of the intended deployment region. To systematically evaluate this effect, three rolling‐ball TENG architectures (planar, concave, and lateral) were integrated into three floating platforms with distinct hull geometries shapes (half‐sphere, half‐cylinder, and trapezoidal prism) and tested under scaled wave conditions representative of the Portuguese coast. The results show that platform geometry strongly influences the mechanical motions acting on the TENGs, selectively enhancing the energy captured from specific wave frequencies without modifying the devices. Among the tested configurations, the lateral TENG achieved the highest outputs, generating approximately 70 V, 62 μA, and 11 μW when integrated into the half‐cylinder platform. These findings reveal that efficient wave energy harvesting depends on the combined effects of platform motion and TENG design, thus pointing to a paradigm shift, where optimization is achieved by adapting floating platforms to local wave dynamics, enabling robust, efficient, and scalable energy generation. This strategy opens new pathways for hybrid and distributed ocean energy systems and supports the practical, site‐specific deployment of TENG based wave energy technologies.
ABSTRACT The development of sustainable high‐performance bio‐hybrid neuromorphic electronics is essential for the next generation of intelligent human–machine interfaces. However, achieving systemic biocompatibility while maintaining low power consumption and long‐term stability remains a formidable challenge. Here, we report a high‐performance artificial transmission nerve based on a gelatin–starch (GS) nanoparticle ion–gel dielectric, optimized through a synergistic dual‐annealing protocol. The starch incorporation strengthens the intermolecular hydrogen‐bonding network, whereas the tailored annealing optimizes the electric double‐layer interface, yielding a benchmark energy consumption of 2.00 fJ per synaptic event and exceptional cycling stability (> 10 4 cycles). Leveraging these characteristics, we demonstrated a low‐power Morse‐code‐based reservoir computing (RC) system capable of 98.25% recognition accuracy for the full A−Z alphabet. Furthermore, by integrating these transistors with bio‐composite sensors and actuators, we constructed a self‐contained artificial reflex arc. This mainly bio‐composite system faithfully emulates the hierarchical perception and spatiotemporal response dynamics of human skin, where electrode‐length‐modulated sensitivity gradients trigger distinct motor behaviors. This work provides a robust framework for eco‐friendly neuromorphic hardware and paves the way for advanced soft robotics and intelligent prosthetics with bio‐realistic environmental interaction capabilities.
ABSTRACT Electrically driven hydrogels convert ion migration, water transport, and polymer network deformation into mechanical outputs, offering a soft and responsive platform for actuation. Recent progress in this field has advanced from macroscopic electroosmotic turgor actuators to micrometer‐scale hydrogel cilia arrays. Membrane‐confined polyelectrolyte gels retain osmotic pressure and transform swelling into large blocking stress, while electroosmotic flow accelerates water uptake through charged polymer meshes. In comparison, two‐photon‐printed gel microcilia with nanometer‐scale hydrogel networks shorten ion migration distance and generate low‐voltage bending, rotational motion, and reprogrammable collective actuation through microelectrode arrays. This News & Views examines how structural design regulates the output of hydrated charged polymer networks from load‐bearing actuation to dynamic fluid manipulation, highlighting the significance of electrically driven hydrogel actuators for soft robotics, microfluidics, and biomimetic micromachines.
ABSTRACT Cutaneous haptic interfaces have demonstrated substantial potential in human–machine interaction, enabling applications such as immersive experiences, robotic teleoperation, and sensory transfer in prosthetics. By conveying rich haptic cues such as indentation, stretching, vibration, and temperature, cutaneous feedback improves presence, realism, task performance, and the stability of two‐way interaction loops. This article introduces the fundamental concept of cutaneous haptic interfaces and reviews recent advances in cutaneous feedback modalities and device paradigms from skin‐integrated patches to fingertips and whole‐hand wearable devices. It highlights progress in spatiotemporal programmability for each feedback modality, as well as in combined multimodal feedback. Cutaneous adaptability designs for haptic feedback devices are also discussed, with an emphasis on maintaining natural interaction and achieving personalized haptic feedback. In addition, the integration of haptic feedback devices with sensing units has emerged as a popular trend, facilitating closed‐loop control for more accurate and stable haptic interaction. Finally, the article concludes by underscoring a complete workflow spanning coordinated visual‐haptic sensing, encoding, rendering, and feedback to support dexterous haptic interaction and enable more lifelike, responsive, and dependable performance in virtual or teleoperation scenarios.
ABSTRACT The rapid expansion of Internet of things (IoT) and cyber‐physical systems presents a formidable challenge for sustainably powering massive numbers of distributed sensors. Friction, a ubiquitous phenomenon typically viewed as a source of energy dissipation, offers a novel avenue for energy harvesting and in situ sensing. In this study, a self‐powered sensing system integrating a self‐lubricating p‐p heterojunction DC generator (SHDG) is constructed from the friction interface between a hydrogenated diamond‐like carbon coating (HDLC) and a p‐type gallium nitride (pGaN) wafer. The SHDG exhibits a peak power density of 2.1 kW m −2 and an 85% reduction in the wear rate compared to metal‐pGaN counterparts. Theoretical analysis revealed that material transfer can modulate the pGaN surface states attenuating the built‐in electric field and thus augmenting the tribo‐induced electric‐field‐dominated DC output. Furthermore, the SHDG is integrated into a bearing for the high‐precision monitoring of dynamic parameters, such as cage slip, exhibiting an average deviation of 0.0014 Hz from commercial sensors. Coupled with deep learning, self‐sensing signals were utilized for fault diagnosis achieving an average accuracy of 96.81% across various conditions. The successful deployment of a smart bearing in a transmission system featuring wireless monitoring and stable operation exceeding 12 h corroborated its feasibility and durability. This study establishes a new paradigm for developing high‐performance, long‐lifespan, and self‐powered sensing systems for next‐generation intelligent equipment and IoT terminals.
ABSTRACT Sustainable energy harvesting technologies require materials that combine high performance with environmental compatibility. Triboelectric nanogenerators (TENGs) provide a versatile platform for converting mechanical energy into electricity, yet the structure–property relationships governing bio‐derived materials remain insufficiently understood. Cellulose nanofibrils (CNFs), with their structure and tunable interfaces, offer a promising materials platform to address this challenge. In this study, CNF papers were engineered via controlled filtration, pressing, and ionic liquid (IL) posttreatment to systematically investigate the roles of surface morphology and crystallinity. Multiscale characterization using atomic force microscopy (AFM), scanning electron microscopy (SEM), X‐ray diffraction (XRD), and attenuated total reflectance Fourier transform infrared (ATR–FTIR) spectroscopy showed that reducing surface roughness from ∼50 to ∼18 nm enhanced the power density from ∼5.7 to 13 W m −2 by increasing the effective contact area. Further structural modulation via IL reduced roughness to ∼7 nm and crystallinity from ∼61% to ∼49%, and a partial polymorphic transition from cellulose I to cellulose II at the fibril level was induced, resulting in a pronounced performance enhancement. The optimized CNF‐based TENG achieved a power density of ∼80 W m −2 and could power 100 blue light‐emitting diodes under manual tapping. These results highlight the synergistic roles of interfacial smoothness, structural disorder, and cellulose polymorphism, providing design guidelines for high‐performance sustainable triboelectric energy devices.
ABSTRACT Triboelectric nanogenerators (TENGs) have emerged as a promising solution to the challenge of powering distributed sensor nodes in the Internet of Things by harvesting ambient mechanical energy. However, the conventional dependence on physical wiring severely constrains the scalable deployment of multinode sensing systems. In this work, we present an innovative self‐powered wireless sensing architecture that seamlessly merges TENG energy harvesting with localized radio frequency (RF)‐based wireless power transmission. A bulk‐effect‐based TENG is designed, achieving a maximum power density of 14.5 W m −2 . The captured energy is regulated by a silicon‐controlled rectifier and converted into 900 MHz RF signals via a voltage‐controlled oscillator, enabling wireless power transmission over a distance of up to 70 cm. The integration of a Dickson voltage multiplier rectifier and an ultraefficient power management unit at the receiver enables support for an energy‐accumulation‐driven vibration monitoring cycle, facilitating intermittent sensing operation without battery constraints. This work demonstrates a fully self‐sustained architecture for distributed sensing nodes, offering a wiring‐free power solution with potential for low‐power, duty‐cycled Internet of Things sensing applications.
ABSTRACT The field of tactile perception is transitioning from phenomenological analysis to integrated application and creation. To develop intelligent and embodied tactile capabilities, it is necessary to move beyond the traditional view of touch as a passive input channel and instead understand it as an active closed‐loop computational process. This requires the convergence of multiple disciplines, including materials science, neuroscience, robotics, and computer science, to establish a unified framework centered on active perception, predictive processing, and sensorimotor integration. This framework will guide the co‐design of intelligent devices, brain‐like algorithms, and scalable systems. Such advancements will drive the transformation of human–digital interaction, physical environment manipulation, and interpersonal connectivity, thereby enabling more natural and efficient human–machine collaboration.
ABSTRACT A self‐powered wireless sensing e‐sticker (SWISE), combining triboelectric and discharge breakdown effects, can serve as an all‐in‐one wireless sensing solution with minimal energy consumption compared to state‐of‐the‐art wireless sensing techniques. However, the environmental impacts of SWISE have never been clearly assessed. This study conducted a cradle‐to‐grave life cycle assessment (LCA) of SWISE using the software OpenLCA, modeling its whole cradle‐to‐grave lifecycle from raw material extraction, fabrication, and usage to end‐of‐life treatment, and comparing SWISE with prevalent sensing techniques. The results indicated that SWISE with PVC configuration emits 1.24 kg CO 2 per 1000 sensing units per year, which is 1–2 orders of magnitude lower than sensors equipped with flexible batteries. We also evaluated the SWISE‐based wireless power supplier (SWISE‐WPS) designed for wireless energy transmission. Its environmental impacts per kWh were benchmarked against other grid sources in Guangdong Province, and a techno‐economic analysis was performed to estimate the levelized cost of electricity (LCOE). Results showed that both environmental impacts and LCOE of SWISE‐WPS devices ($0.11 kWh −1 ) were slightly higher than those of prevalent renewable energies with great potential for further optimization in material selection, energy usage, fabrication methods, and structure design. Finally, a unified environmental and economic metric was proposed to evaluate the overall performance of various sensing and power supply techniques, providing insights for trade‐offs between environmental and economic perspectives, which may guide the optimizing direction for future development of SWISE‐based devices.
ABSTRACT Aiming to explore structurally stable and easily fabricable magneto‐optical (MO) platforms for potential refractive‐index‐sensing applications, this work investigates stacking‐number‐dependent low‐field‐enhanced polar magneto‐optical Kerr effect (P‐MOKE) in substrate/AlN buffer/[CoPt(3 nm)/AlN(22 nm)] N /CoPt(3 nm) multilayer structures. With increasing stacking number N , the magnetic hysteresis loops gradually evolved into pronounced step‐like behaviors, indicating the coexistence of two magnetically distinct regions with different coercivity ( H C ) values along the film thickness direction. Correspondingly, low‐field‐enhanced Kerr rotation ( θ K ) hysteresis loops were observed, where the θ K in the low‐field region exceeded that of the saturated state. To clarify the origin of this behavior, inverse MO Fresnel transfer matrix method analysis was performed by separating the multilayer structure into top and bottom CoPt regions with distinct magnetic reversal characteristics. The fitting results revealed that the two regions exhibit different complex Voigt vectors and contribute oppositely to the θ K hysteresis behavior. The observed low‐field‐enhanced P‐MOKE was interpreted as a consequence of the competition between opposite MO polarities and different H C values between these spatially separated magnetic regions along the film thickness direction. In addition, the extracted Voigt vector difference suggests that MO coupling may be influenced by the structural environment and residual‐stress‐related variations. Furthermore, the multilayer structures exhibited appreciable sensitivity to variations in the surrounding dielectric‐environment at 408 nm, indicating potential applicability in MO sensing.
ABSTRACT It has been anticipated that quantum computing (QC) would solve computational tasks involving quantum phenomena intractable for supercomputers based on digital technology. Concurrently, however, the vast development of artificial intelligence (AI) has resulted in systems targeting these real‐world problems with unprecedented progress including protein design for drug discovery and constituent optimizations for novel magnetic materials. Even climate simulation has welcomed the AI era. This “News and Views” intends to provide an analysis of QC for future applications and associated technological challenges. Our analysis leads to a scenario in which room‐temperature QC technology acts as an energy‐efficient processor for large‐system computations likely targeting markets for mobile systems. With this scenario, silicon nanofabrication would contribute indispensably to further advancing QC technology in all aspects.
In energy constrained application scenarios, self-powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High-entropy energy, such as micro-wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low-frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high-entropy distribution. This review outlines the basic concepts and recent developments of TENG-driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical high-entropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG-driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, low-altitude economy, mobile intelligent devices, and ocean sensing networks.
