Ultra-stretchable triboelectric touch pad with sandpaper micro-surfaces for Transformer-assisted gesture recognition

摩擦电效应 材料科学 砂纸 手势识别 变压器 纳米发生器 手势 电子皮肤 计算机科学 纳米技术 电气工程 人工智能 电压 工程类 压电 复合材料 冶金
作者
He Liu,Deliang Li,Haoxiang Chu,Yong Ding,Zhiwei Fu,Xinan Yao,Jiayi Zhu,Jiaqi Yang,Ruonan Liu,Tao Xu,Simian Fu,Yiying Liu,Yixuan Han,Yanpeng Wang,Yue Zhao,Xiaoyu Cui,Ye Tian
出处
期刊:Nano Energy [Elsevier]
卷期号:130: 110110-110110 被引量:36
标识
DOI:10.1016/j.nanoen.2024.110110
摘要

Touch pad based on triboelectric nanogenerator are attracting attention in the field of wearable electronics and human-machine interaction. However, it is still a challenge to realize touch pads combining large-area metamorphic stretchability, high power triboelectric sensing, intelligent free-sliding recognition and availability in extreme environments. Here, we fabricate an ultra-stretchable triboelectric touch pad by integrating liquid metal and high performance hydrogel-based triboelectric sensor arrays, which achieves Transformer-assisted gesture recognition for drone flight direction control. The internal hydrogel electrode has great stretchability, electrical conductivity and anti-freeze properties. Encapsulated in Ecoflex with sandpaper micro-surfaces, it endows high triboelectric power density and pressure sensitivity. With screen-printed liquid metal, the integrated touch pad is fully ultra-stretchable and large-area strain stability. Combining Internet of Things, we build a Transformer-assisted human machine interface. Notably, slide gesture signal peak deviation is reduced by integral processing. The random free-sliding gesture signals are parsed by the Transformer algorithm with 96.83 % accuracy. Multi-threaded signal processing improves the response speed and throughput of the system. The accurate real-time gesture recognition for drone flight direction control in extreme environment is realized. This human machine interface can facilitate development of next generation intelligent remote interactive platforms.
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