材料科学
磁滞
可穿戴计算机
压力传感器
信号(编程语言)
步态
智能材料
卷积神经网络
人工神经网络
可穿戴技术
计算机科学
工作(物理)
拓扑(电路)
压力(语言学)
动压
堆栈(抽象数据类型)
自愈
离子液体
航程(航空)
压缩传感
能量(信号处理)
生物系统
声学
网络拓扑
电压
离子键合
纳米技术
软机器人
耐久性
作者
Hongnan Zhu,Yicong Wang,Liang Zheng,Zhouyang Hu,Q. X. Zhang,Jiangrui Gao,Senyun Yang,Jun He Yang,Sanwei Hao,Jia‐Long Wen,Feng Xu,Jing Rao,Caofeng Pan
摘要
ABSTRACT Flexible plantar pressure sensors require soft ionic materials that can withstand large deformation, suppress hysteresis, and maintain reliable signal transduction under dynamic loading, yet these properties are rarely integrated in one material platform. Here, we report a water‐induced topological ionogel (WTI) enabled by competitive hydrogen‐bond regulation in an acrylic acid/acrylamide/[BMIM]Cl/H 2 O system. Water weakens rigid polymer‐ionic liquid associations and drives the transition from aggregated polymer clusters to a dynamically adaptive topological network, thereby promoting elastic recovery and reducing energy dissipation. The optimized WTI exhibits a compressive stress of 1.02 MPa at 90% strain, a hysteresis ratio of 8.3% at 50% strain, and an ionic conductivity of about 270 mS m −1 . As a flexible pressure sensor, it delivers a response time of about 10 ms, a sensing range from 62.3 Pa to 200 kPa, and stable operation over 20,000 loading‐unloading cycles. Integrated into a wearable plantar pressure sensing system, it enables high‐resolution spatiotemporal pressure mapping and recognition of nine locomotor patterns with 99.18% accuracy through convolutional neural network analysis. This work provides a topology‐engineering strategy for low‐hysteresis ionogels for wearable biomechanical monitoring and intelligent healthcare.
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