Search

Triboelectric nanogenerator (TENG) is regarded as an equally important mechanical energy harvesting technology as electromagnetic generator (EMG). Here, the input mechanical torques and energy conversion efficiencies of the rotating EMG and TENG are systematically measured, respectively. At constant rotation rates, the input mechanical torque of EMG is balanced by the friction resisting torque and electromagnetic resisting torque, which increases with the increasing rotation rate due to Ampere force. While the input mechanical torque of TENG is balanced by the friction resisting torque and electrostatic resisting torque, which is nearly constant at different rotation rates. The energy conversion efficiency of EMG increases with the increasing input mechanical power, while that of the TENG remains nearly constant. Compared with the EMG, the TENG has a higher conversion efficiency at a low input mechanical power, which demonstrates a remarkable merit of the TENG for efficiently harvesting weak ambient mechanical energy., Competing Interests: The authors declare no competing interests., (© 2021 The Author(s).)

The emerging triboelectric nanogenerator (TENG) network shows great potential in harvesting the ocean wave energy, which can help to achieve large-scale clean wave power generation. However, due to the lack of an effective networking strategy and theoretical guidance, the practicability of the TENG network is heavily restricted. In this paper, based on the typical spherical TENG, we investigated the networking design of TENGs. Four fundamental forms of electrical networking topology are proposed for large-scale TENG networks, and the influences of cable resistance and output phase asynchrony of each unit to the network output were systematically investigated. The research results show that the forms of electrical networking topology can produce an important influence on the output power of large-scale TENG networks. This is the first strategy analysis for the TENG network, which provides a theoretical basis and a universal method for the optimization design of large-scale power networks., Competing Interests: All authors confirm there are no competing interests., (© 2020 The Author(s).)