A novel triboelectric nanogenerator based on electrospun polyvinylidene fluoride nanofibers for effective acoustic energy harvesting and self-powered multifunctional sensing. (February 2019) - Chen, Fangqi; Wu, Yonghui; Ding, Zhenyu; Xia, Xin; Li, Shaoheng; Zheng, Haiwu; Diao, Chunli; Yue, Gentian; Zi, Yunlong
Abstract: Acoustic energy is mostly wasted without a proper energy harvesting approach. In this work, an integrated triboelectric nanogenerator (TENG) with a polymer tube is constructed to harvest acoustic energy from the environment, which can work stably in the frequency ranging from 20 Hz to 1000 Hz. The TENG is based on electrospun polyvinylidene fluoride (PVDF) nanofibers and two conductive fabrics. The unique structure design facilitates acoustic energy capturing and the enhancement of sound pressure. The TENG can deliver an open-circuit voltage and short-circuit current of 400 V and 175 µA, respectively, with instantaneous maximum output power density of 7 W/m 2 under a sound frequency of 170 Hz and sound pressure of 115 dB. The TENG can be used for audio frequency analysis and noise detection. Furthermore, self-powered active sensors are demonstrated for detecting sound source direction and motion velocity of an object making sounds. This work not only provides a simple, cost-effective approach for fabricating high performance TENG to recycle ambient noise energy into available electricity, but also enables self-powered sensing applications, with potential applications in military surveillance, artificial intelligence, Internet of Things, and jet engine noise reduction. Graphical abstract: This work not only systematically studied the effect of sound frequency and sound pressure on the output of TENG but also demonstrated that the acoustic driven-TENG can be used as multifunctional self-powered sensing. Highlights: A TENG integrated with a polymer tube is helpful for sound pressure enhancement and acoustic energy capture. A self-powered velocity sensing system for measuring the velocity of a moving object has been introduced. An acoustic sensor that can distinguish the sound signals of human and tuning fork is demonstrated.