Jie Wang

Triboelectric nanogenerators (TENGs) offer transformative potential for self-powered systems, yet their real-world applicability faces a key bottleneck as their performance and efficiency suffer dramatic degradation below 5 V that the operational threshold for most electronics when integrated with conventional power management circuits. Here, we overcome this limitation through the multi-stage buck strategy that synergistically combines dual-stage voltage conversion circuit with TENG’s output characteristic by the Q-V curve, enabling precise voltage regulation at critical nodes. The strategy achieves approximately 80% circuit efficiency at the low-voltage range, with 90.9% in the primary circuit and 93.9% in the secondary circuit. Concurrently, the current and power density reach 5.19 A/m ² and 9.70 W/m ² at 1.87 V, which is nearly an order of magnitude improvement over best prior work. Demonstrated in self-powered hydrogen production system, this approach achieves a record gas yield of 16.5 mL/(min·m ² ), resolving the challenge of low-voltage inefficiency in self-powered systems. Additionally, it is capable of powering a mobile phone. Our work establishes a foundational framework for implementing efficient TENG-powered devices in Internet of Things networks and industrial applications, bridging the gap between energy harvesting technologies and actual energy demands.

A comprehensive voltage theory combined with parameter sensitivity regulation enables a durable ultra-high voltage output while suppressing V – Q curve flattening to improve charge utilization efficiency.

Tribovoltaic nanogenerator (TVNG) offers self‐powered, low impedance, and high direct current transient response, making it highly suitable for robotic sensing. However, the poor performance and lack of intelligent sensing terminals in the solid–solid TVNG of the contact separation mode have limited its advanced applications. We present a self‐powered liquid TVNG sensor (LTVNGS) coupling sliding and contact‐separation modes, integrated with deep learning for robotic tactile and gustatory dual‐mode sensing system. The low‐resistance aqueous solution at the metal‐semiconductor interface promotes the charge transport efficiency of LTVNG, and the sensitivity has been improved from the nA to the µA level. The working mechanism of LTVNG was revealed, and the principle of enhancing sensitivity in the solid–solid noncontact LTVNGS through the qualitative and quantitative analysis of the GO dispersion solution was explained. Besides, LTVNGs achieve prediction of water droplet height. Furthermore, LTVNG achieves tactile material and gustatory liquid recognition with an average identification accuracy exceeding 98%, assisted by deep learning models through the perception of different materials and liquids. This work provides a scientific framework for multimodal TVNG and its application in intelligent robots, offers an innovative approach for robot liquid analysis, and enhances the ability to identify hazardous liquids and the HMI.

Origami‐ and Kirigami‐inspired structures have emerged as transformative strategies for enhancing the performance and versatility of triboelectric nanogenerators (TENGs). Their folding mechanisms facilitate efficient for contact‐separation TENGs, as well as their geometric patterns provide essential stretchability for complex interfaces. This review emphasizes that the core mechanism of these architectures lies in their ability to bridge mechanical deformation and electrical output of TENGs. On this basis, we summarize the representative origami and kirigami configurations and their mechanical characteristics. More importantly, we propose a general design framework to clarify how these structural strategies adapt to different operating conditions by leveraging their inherent mechanical characteristics. Typical applications include blue energy harvesting, vibration and biomechanical energy harvesting for micro/nano energy systems, self‐powered sensing for environmental and health monitoring, tactile sensing, and wearable electronics that benefit from the stretchability and deformability of kirigami structures. Finally, the current challenges and outline emerging opportunities toward deeper functional integration and scalable implementation of origami‐ and kirigami‐inspired TENGs are concluded.

Triboelectric nanogenerators (TENGs), as a mechanical harvesting technology that combines a wide range of material selection, high economy, portability, and low‐frequency efficiency, have a significant influence on related research fields such as the utilization of various environmental mechanical energy harvesting and self‐powered systems. This review elaborates in detail the technical principles and working mechanisms related to TENGs, and introduces in detail the key studies in the research process of high‐performance TENGs through three themes: material research, structural design, and charge excitation. Subsequently, the high‐performance TENG research on different energy harvesting (wind energy, ocean wave energy, and other energy) was summarized and analyzed. Furthermore, the recent progress in related fields was discussed through the gradient summary method from self‐powered electrochemistry (clean fuels, degrading pollutants, and recycling‐protection) and other power applications (high‐voltage source, passive IoT nodes, and other power systems). Finally, the rational summary of the relevant obstacles and challenges existing in the aforementioned research fields, and then provide reasonable prospects for the future development of high‐performance energy harvesting TENGs in a targeted manner. Based on this, the high‐performance energy harvesting TENG will be comprehensively discussed, and it is hoped to promote the rapid development and commercial application of TENG.