摩擦电效应
材料科学
纳米发生器
图层(电子)
活动层
可穿戴计算机
纳米技术
卷积神经网络
光电子学
计算机科学
人工智能
复合材料
嵌入式系统
薄膜晶体管
压电
作者
Hao Zhang,Dongzhi Zhang,Ruiyuan Mao,Lina Zhou,Chunqing Yang,Yan Wu,Yukun Liu,Yuncheng Ji
出处
期刊:Nano Energy
[Elsevier BV]
日期:2024-05-18
卷期号:127: 109753-109753
被引量:158
标识
DOI:10.1016/j.nanoen.2024.109753
摘要
Self-powered sensing technology and smart perception technology have broad application prospects in flexible and wearable electronics. In this work, a flexible triboelectric nanogenerator (RMP-TENG) based on a room-temperature vulcanized silicone rubber (RTV)@(Molybdenum disulfide (MoS2)/Polyvinyl chloride (PVC)) functional layer is developed using a layer-by-layer self-assembly and material doping strategy. The RTV@(MoS2/PVC) functional layer is divided into a charge-generating layer (RTV/PVC) and a charge-trapping layer (RTV/MoS2). The synergistic effect of PVC and MoS2 has improved the surface roughness and charge transfer efficiency of RMP-TENG, doubling its output performance to 1055 V and 112 μA. In order to further improve the tactile sensing accuracy of RMP-TENG, a deep learning model based on Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) is developed. It predicts the type of contact material based on the features of tactile signals, achieving a prediction accuracy of 93.975%. Additionally, by combining mobile smart terminals, the CNN-GRU model, and RMP-TENG, a wireless access control system based on self-powered tactile sensing and intelligent material recognition is developed. Through the optimization of these experiments and algorithms, RMP-TENG has achieved real-time material recognition capabilities. This demonstrates the broad application prospects of RMP-TENG in wearable energy supply, intelligent sensing, human-computer interaction, and other areas.
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