Flag-type hybrid nanogenerator utilizing flapping wakes for consistent high performance over an ultra-broad wind speed range

Fluttering of regular flags and flapping of inverted flags in the wind serve as the foundational principles of flag-type nanogenerators (FNGs). However, FNGs relying on a single aerodynamic behavior exhibit significant power output only within a limited spectrum of wind speeds, posing a challenge to their robustness in scenarios with intensely fluctuating wind. In this paper, we propose a novel hybrid scheme aimed at harnessing the synergistic potential of two aerodynamic behaviors to enhance the performance of FNGs and broaden their operational wind speed ranges. A flag-type triboelectric-piezoelectric hybrid nanogenerator (FTPNG) is developed with the integration of flapping piezoelectric flags (PEFs) and a fluttering triboelectric flag (TEF). To overcome the limited operational wind speed range, flapping PEFs are configured in an array format, optimized through fluid-solid coupled simulations. The rear TEF leverages the fluttering motion of a polytetrafluoroethylene (PTFE) membrane, which intermittently contacts and separates from conductive textiles positioned on the inner surface of the baffles. A noteworthy feature is the innovative “back-to-back” design, which utilizes the flapping wakes generated by PEFs to intensify the fluttering of the PTFE membrane, resulting in a remarkable boost in power generation of up to 132 times and achieving a maximum peak power output of 5400 μW. The FTPNG offers consistent high performance, with an average output of exceeding 200 μW over an ultra-broad wind speed range of 4.7–14.6 m/s, while the complete operational range is 3.7–15 m/s. It also attains a considerable average power output of 850 μW at 7.8 m/s, marking a significant advancement compared to other FNGs. Finally, in demonstration tests, the FTPNG can light 252 LEDs and showcases the capabilities of PEF array and TEF to independently power a wireless sensor node (WSN), highlighting its significant potential for applications in the Internet of Things and various self-powered systems.