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Automatic Mode Transition Enabled Robust Triboelectric Nanogenerators
128
Citations
43
References
2015
Year
Electrical EngineeringEnergy HarvestingEngineeringFlexible ElectronicsEnergy EfficiencyNanotechnologyNanoelectronicsEnergy ConversionApplied PhysicsNano Electro Mechanical SystemEnergy GenerationAdvanced Energy TechnologyEnergy StoragePiezoelectric NanogeneratorsTriboelectric NanogeneratorTechnologyDevice RobustnessAmbient Energy Harvesting
Although the triboelectric nanogenerator (TENG) has been proven to be a renewable and effective route for ambient energy harvesting, its robustness remains a great challenge due to the requirement of surface friction for a decent output, especially for the in-plane sliding mode TENG. Here, we present a rationally designed TENG for achieving a high output performance without compromising the device robustness by, first, converting the in-plane sliding electrification into a contact separation working mode and, second, creating an automatic transition between a contact working state and a noncontact working state. The magnet-assisted automatic transition triboelectric nanogenerator (AT-TENG) was demonstrated to effectively harness various ambient rotational motions to generate electricity with greatly improved device robustness. At a wind speed of 6.5 m/s or a water flow rate of 5.5 L/min, the harvested energy was capable of lighting up 24 spot lights (0.6 W each) simultaneously and charging a capacitor to greater than 120 V in 60 s. Furthermore, due to the rational structural design and unique output characteristics, the AT-TENG was not only capable of harvesting energy from natural bicycling and car motion but also acting as a self-powered speedometer with ultrahigh accuracy. Given such features as structural simplicity, easy fabrication, low cost, wide applicability even in a harsh environment, and high output performance with superior device robustness, the AT-TENG renders an effective and practical approach for ambient mechanical energy harvesting as well as self-powered active sensing.
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