摩擦电效应
材料科学
微电子
纳米发生器
触觉传感器
压阻效应
液态金属
稳健性(进化)
纳米技术
多孔性
复合材料
自愈
电压
物联网
接触面积
小型化
机器人学
造型(装饰)
机械工程
平版印刷术
胶粘剂
夹持器
接触力
接触电阻
数码产品
聚合物
计算机科学
电接点
CMOS芯片
可靠性(半导体)
航空航天
电极
3D打印
作者
Jiahong Yang,Yao Xiong,Rui Gu,Yang Liu,Liang Wei,Chao Liu,Zhong Lin Wang,Qijun Sun
摘要
ABSTRACT With the rapid expansion of the Internet of Things (IoT) and artificial intelligence (AI), developing flexible self‐powered electronic skins with high sensitivity and mechanical robustness has become a critical research priority. However, traditional metal‐polymer composites often face challenges such as mechanical mismatch and complex molding processes. To address these issues, we report an innovative elastic liquid‐metal‐silicone‐based foam (LMSF) for self‐powered triboelectric sensing and intelligent tactile recognition. A facile and environmentally friendly sugar‐template strategy was adopted to fabricate the LMSF with a 3D interconnected porous architecture that effectively encapsulates liquid metal networks within polymer matrices. This structure significantly amplifies the effective specific surface area and electron‐trapping capability while resolving long‐standing LM leakage and molding difficulties. The LMSF‐based triboelectric nanogenerator (LMSF‐TENG) delivers an outstanding electrical output, achieving an open‐circuit voltage ( V OC ) of 48.48 V, a short‐circuit current ( I SC ) of 0.36 µA, and a transferred charge ( Q SC ) of 15.72 nC in single‐electrode mode. In non‐contact mode, it maintains superior performance with the V OC of 38.81 V, the I SC of 0.29 µA, and the Q SC of 13.51 nC. Furthermore, the device demonstrates exceptional long‐term reliability for over 24,000 continuous cycles. Assisted by the ResNet‐34 deep learning algorithm, the sensing array achieves high‐accuracy recognition of complex tactile patterns with a precision of 95.83%. This work provides a low‐cost, multifunctional platform for next‐generation intelligent robotic skins, self‐powered human–machine interfaces, and flexible microelectronic systems.
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