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.

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