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Super‐Durable, Low‐Wear, and High‐Performance Fur‐Brush Triboelectric Nanogenerator for Wind and Water Energy Harvesting for Smart Agriculture
Author(s) -
Chen Pengfei,
An Jie,
Shu Sheng,
Cheng Renwei,
Nie Jinhui,
Jiang Tao,
Wang Zhong Lin
Publication year - 2021
Publication title -
advanced energy materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.08
H-Index - 220
eISSN - 1614-6840
pISSN - 1614-6832
DOI - 10.1002/aenm.202003066
Subject(s) - triboelectric effect , nanogenerator , brush , materials science , abrasion (mechanical) , energy harvesting , relative humidity , wind speed , electrical engineering , windmill , renewable energy , wind power , automotive engineering , voltage , energy (signal processing) , composite material , engineering , meteorology , statistics , physics , mathematics
The triboelectric nanogenerator (TENG), as a promising energy harvesting technology, provides a new approach for the realization of the Internet of Things (IoTs). However, material abrasion severely limits its practical applications because of the deterioration in mechanical durability and electrical stability. Here, naturally available animal furs are introduced, owing to their superiorities of extremely low wear, high performance and humidity resistance. More than 10 times the electric output is observed relative to the conventional TENG, even at low driving torque. The transferred charge of fur‐brush TENG (FB‐TENG) exhibits only 5.6% attenuation after continuous operation for 300 000 cycles, maintaining high output performance even if the relative humidity increases up to 90%. Furthermore, a counter‐rotating structure is first designed to further increase the output by doubling the relative rotation speed. Based on this mechanism, a significantly elevated output current of 36.6% is obtained in ambient conditions. Finally, self‐powered automatic irrigation, weather monitoring and wireless water level warning multifunctional management systems are realized by collecting the wind and water flow energy. This work provides a strategy of reducing wear on the premise of high performance, which lays a foundation for effective environmental energy harvesting toward practical applications in big data and the IoTs.