摩擦电效应
材料科学
导电体
杰纳斯
纳米技术
触觉传感器
触觉知觉
仿生学
电阻式触摸屏
计算机科学
信号(编程语言)
接近传感器
电子皮肤
柔性电子器件
可穿戴计算机
可穿戴技术
人工智能
导电的
仿生材料
图层(电子)
接口(物质)
人机交互
适应性
软机器人
作者
Xuelian Zou,Tao Liu,Huiya Zhang,Jin-long Wang,Kang Yu,Qiguan Luo,Wenxia Zhai,Siyi Qin,Xiaochen Pan,Zewen Dang,Shuangfei Wang,Shuangxi Nie,Zhiwei Wang
标识
DOI:10.1002/adfm.202526356
摘要
Abstract Triboelectric tactile sensors enable precise recognition of diverse objects within a single sensing unit, opening a new pathway for the advancement of robotic intelligence. However, these sensors often suffer from limitations such as poor environmental adaptability (e.g., humidity), susceptibility to interface shedding, and a lack of advanced data interpretation capabilities. This study, utilizing an evaporation‐induced strategy, develops a biomimetic hierarchical Janus triboelectric material (HJTM). Its skin‐like structure simultaneously integrates superhydrophobic protection, conductive sensing, and virtual machine learning computing. The HJTM's superhydrophobic surface (contact angle = 163 ± 0.5°) effectively shields against environmental interferences such as humidity, while the underlying conductive network layer enhances charge storage and transfer. As a result, the output voltage is 6.7 times higher than that of pure CNF film, while maintaining 95.32% performance at 99% relative humidity. Furthermore, combined with multiple machine learning algorithms, the system achieves high‐precision recognition (≥ 95.0%) of various objects, including plastic boxes, plastic balls, and glass bottles. This study provides a new pathway toward achieving stable tactile sensing with a single sensing unit under complex environmental conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI