Ultra-reliable triboelectric nanogenerator based on dynamic perception self-adjustment strategy and collaborative-stability strategy

Abstract

Triboelectric nanogenerator (TENG) is suitable for the construction of sensor networks. However, TENG is greatly influenced by the external environment and its own state. Herein, we proposed a TENG using dynamic perception self-adjustment strategy and collaborative stability strategy. The dynamic perception self-adjustment strategy allows the TENG to directly access sensor networks. Unlike simply accessing the network to transmit sensing results, this strategy allows the TENG to access other sensors to gain dynamic perception of its own surrounding environment. Subsequently, the TENG can directly adjust its sensing results based on the dynamic perception results. Furthermore, TENG's own state, such as charge loss and material aging, can also cause interference. We have established multiple models regarding TENG's own state, which can easily eliminate these adverse factors through self-regulation function. In addition, the stability of TENG itself is also worth noting. Unlike previous single stability strategies, we proposed a collaborative stability strategy for the first time. This strategy has superior and comprehensive anti-interference performance compared with a single strategy. Excellent and comprehensive performance achieved under various reliability tests: different weather tests (99.7 %), ultraviolet irradiation tests (100 %), temperature tests (99.6 %), humidity tests (100 %), wear tests (99.3 %), and charge loss tests (99.8 %). Finally, we demonstrated the application of the TENG based wireless sensing devices. This work is comprehensive and unprecedented in improving TENG based sensors, and will drive the practical process of TENG.