Triboelectric nanogenerators (TENGs) have gradually been applied in various practical scenarios, mainly focusing on core areas such as wearable motion monitoring devices, medical security systems, and natural resource exploration technology. However, they have the problem of low output energy and have not yet formed effective integration with mature commercially available products, which has hindered the industrialization process. This situation still significantly limits its global promotion and application. In this study, TENG was used as the sensing module for intelligent automotive airbags. We tested the voltage and current output characteristics of the system under different impact forces and frequency conditions. During the testing process, the electrical energy generated under different operating conditions is transmitted to the control system via Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) circuits. The system will quickly determine whether to trigger the airbag deployment based on the received electrical signals, and activate the ignition device when necessary to achieve rapid inflation and deployment of the airbag. Compared with traditional triggering mechanisms, the airbag system based on this designed sensor has higher sensitivity and reliability. The sensor can stably capture collision signals, and experiments have shown that as the collision speed increases, the slope of its open-circuit voltage gradually approaches infinity. Applying TENG to automotive airbags not only effectively improves the triggering efficiency and accuracy of airbags, but also provides more reliable safety protection for drivers and passengers. Finite element simulation of the automotive airbag was conducted to provide specific data support for evaluating its safety performance. With the continuous advancement of TENG technology and further expansion of its application scenarios, we believe that such innovative safety technologies will play a more critical role in the future automotive industry.

The Droplets Triboelectric Nanogenerator (DTENG) possess distinctive merits in harvesting ambient hydropower into usable electricity. Nevertheless, droplet spreading, contact separation behavior, and dynamic interfacial interactions on insulating film surfaces are extremely sensitive to external environmental factors, giving rise to complicated nonlinear output characteristics. Herein, this work reports a droplet-driven TENG based on fluorinated ethylene propylene (FEP) thin films. We systematically explore how electrode geometry, droplet falling height, substrate inclination angle, and droplet flow rate modulate electrical output performance, and further clarify the fluid-triboelectric electron transfer between droplet hydrodynamic evolution and electric signal generation. Notably, we identify the retraction current during droplet recession, a signal largely neglected in previous solid–liquid TENG research, which complements the fundamental mechanism of interfacial charge transfer. This work not only provides a systematic experimental basis for understanding the working mechanism of DTENG, but also lays a theoretical and practical foundation for developing efficient and controllable water energy collection and self-powered sensor systems.

Triboelectric nanogenerators (TENGs) exhibit great application potential in the fields of intelligent sensing and Internet of Things terminal devices due to their advantages of self-powering, simple structure, and high sensitivity. A self-powered alarm sensor for smart manhole covers is proposed to realize real-time monitoring of water immersion and abnormal displacement without external power supply. Experimental results show that the sensor can generate distinguishable voltage signals under water immersion and different displacement states, enabling rapid recognition of potential hazards such as manhole cover offset and accumulated water. On this basis, a reliable intelligent alarm system is constructed, which can receive, analyze, and warn of abnormal signals in real time. Therefore, it can even directly replace commercial manhole covers, demonstrating the broad application prospects of TENG in the field of intelligent monitoring. With the continuous advancement of TENG technology, the functions of this manhole cover alarm will be further expanded and optimized in the future, providing stronger support for the construction of smart cities.

Aiming at the technical pain points of traditional manhole covers with low intelligence high cost and excessive power consumption, this study designs a TENG-based alarm device to enhance the safety and maintenance efficiency of urban infrastructure. The device integrates a water immersion sensor and a displacement sensor enabling real-time status monitoring through a unique TENG mechanism. The solid–liquid mode water immersion sensor detects seepage through the triboelectrification effect. Water droplets contact electrodes on the surface of FEP film and generate electric energy to trigger the detection circuit. The displacement sensor adopts the independent layer mode of TENG and combines with a mechanical tumbler mechanism to realize displacement detection. External force-induced manhole cover displacement drives internal balls to roll and rub against electrodes. Electric energy is then generated to activate the detection circuit. On the basis of the two sensors, an efficient and reliable intelligent alarm system is constructed. The system receives and analyzes displacement and water immersion-sensing signals in real time. It rapidly identifies potential safety hazards including displacement offset water accumulation and leakage. Signal analysis and early warning prompts are completed synchronously. This system provides accurate and real-time data support for public facility monitoring, pipe network operation and maintenance, and regional security in smart cities. It helps achieve early detection and early disposal of hidden dangers and improves the intelligent and refined level of smart city monitoring.

Triboelectric nanogenerator (TENG) have gradually been applied in various practical scenarios, mainly focusing on core areas such as wearable motion monitoring devices, medical security systems, and natural resource exploration technology. However, it has the problem of low output energy and has not yet formed effective integration with mature commercially available products, which has hindered the industrialization process. This situation still significantly limits its global promotion and application. In this study, TENG was used as the sensing module for intelligent automotive airbags. We conducted tests on the voltage and current output characteristics of the system under different impact forces and frequency conditions. During the testing process, the electrical energy generated under different operating conditions is transmitted to the control system through Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) circuits. The system will quickly determine whether to trigger the airbag deployment based on the received electrical signals, and activate the ignition device when necessary to achieve rapid inflation and deployment of the airbag. Compared with traditional triggering mechanisms, the airbag system based on this designed sensor has higher sensitivity and reliability. The sensor can stably capture collision signals, and experiments have shown that as the collision speed increases, the slope of its open circuit voltage gradually approaches infinity. Applying TENG to automotive airbags not only effectively improves the triggering efficiency and accuracy of airbags, but also provides more reliable safety protection for drivers and passengers. The finite element simulation of vehicle airbags provides specific data support for safety performance evaluation. With the continuous advancement of TENG technology and further expansion of its application scenarios, we believe that such innovative safety technologies will play a more critical role in the future automotive industry.