Fabrication of a textile-based triboelectric nanogenerator toward high-efficiency energy harvesting and material recognition

Abstract

Textile-based triboelectric nanogenerator (T-TENG) devices, particularly, narrow-gap mode, have been conceived and developed for obtaining energy harvesting and tactile sensing devices unaffected by the external environment. Enhancing the interfacial area of T-TENG materials offers exciting opportunities to improve the device output performance. In this work, a narrow-gap T-TENG was fabricated with a facile process, and a new strategy for improving the device output is proposed. The new structural sensor (polydimethylsiloxane (PDMS)-encapsulated electroless copper plating (EP-Cu) cotton) with multiple electricity generation mechanism was designed and fabricated for enhancing recognition accuracy. The result shows that only PDMS layer strain was established at an external stress of 1.24–12.4 kPa and the fibers laterally slip at a stress of 12.4–139 kPa; more importantly, the output performance of the TENG displayed a linear relationship under corresponding stress ranges. The as-fabricated device demonstrated the ability to convert different energies such as vibration, raindrops, wind and human motions into electrical energy with excellent sensitivity. Interestingly, the output signal of the as-fabricated TENG device is a combination of output signals from PDMS/EP-Cu and PDMS/recognition object devices. To be precise, there are two TENG devices (PDMS/EP-Cu and PDMS/recognition object) that work when the as-fabricated TENG device is under 12.4–139 kPa stress. Accompanied by unique characteristics, the generated TENG signals are capable of recognition of contact materials. Combining the TENG signal and deep learning technology, we explore a strategy that can enable the as-fabricated device to recognize 8 different materials with 99.48% recognition accuracy in the natural environment.