摩擦电效应
材料科学
纳米孔
静电纺丝
纳米技术
图层(电子)
纳米纤维
纳米发生器
电荷密度
光电子学
复合材料
聚合物
量子力学
压电
物理
作者
Kumar Shrestha,Gagan Bahadur Pradhan,Trilochan Bhatta,Sudeep Sharma,Sang‐Hyun Lee,Hyesu Song,Seonghoon Jeong,Jae Young Park
出处
期刊:Nano Energy
[Elsevier]
日期:2023-04-01
卷期号:108: 108180-108180
被引量:11
标识
DOI:10.1016/j.nanoen.2023.108180
摘要
Significant research has been conducted to find practical methods to increase the triboelectric charge density of friction surfaces and improve the TENG output performance. In this study, a double-layer nanofibrous-TENG is newly proposed, consisting of MXene/P(VDF-TrFE) as a charge-generating layer and Siloxene/cobalt-nanoporous carbon/P(VDF-TrFE) as a charge-trapping layer, fabricated via a facile electrospinning process. The charge-generating layer generates abundant surface charges owing to the high electronegativity and electron affinity of MXene. Similarly, Siloxene as a filler in the charge-trapping layer improves the dielectric property of the layer, whereas hierarchically porous structure with a large surface area of cobalt nanoporous carbon provides more active sites for charge storage. After utilizing the charge-trapping layer, the current density and surface potential of the double-layer nanofibrous TENG is two-fold higher than the single-layer nanofibrous TENG. Furthermore, the TENG with Nylon 6/6 nanofiber as a positive friction layer, delivers a power density of 19 W m-2, which shows superior output performance compared to the state-of-the-art works. Finally, the fabricated device is attached to the shoe insole, and the triboelectric sensor data is analyzed using cutting-edge deep learning technology, which exhibited an accuracy of 99% in user identification and user activity recognition. Thus, this study investigates the possibilities of using the electrospun double-layer nanofibrous mat to boost the TENG output performance and explores its applications in artificial intelligence and human activity recognition systems.
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