材料科学
碳纳米管
压阻效应
复合材料
制作
模数
压力传感器
造型(装饰)
热塑性聚氨酯
挤压
灵敏度(控制系统)
压缩成型
纳米技术
机械工程
弹性体
电子工程
医学
替代医学
病理
模具
工程类
作者
Qing-wen Yuan,Zhenyu Gao,Kang‐Wei Xia,Mengman Weng,Zan Huang,Rui Liu,Ting Wu,Jinping Qu
标识
DOI:10.1002/adfm.202512249
摘要
Abstract Flexible pressure sensors hold significant promise in wearable health monitoring due to their superior conformability and mechanical adaptability. However, conventional designs often struggle to achieve both high sensitivity and a wide detection range simultaneously. Herein, inspired by biological gradient structures, a scalable polymer molding method that combines non‐isothermal extrusion compression molding and chemical etching is proposed for fabricating thermoplastic polyurethane (TPU)/carbon nanotubes (CNTs)/carbon black (CB) pressure sensors with gradient modulus and conductivity. Gradient‐oriented pores and CNTs distributions are formed via gradient temperature and shear fields during the extrusion compression molding process, enabling synergistic gradient modulus and conductivity distribution. As expected, the as‐prepared mechanical‐electrical dual‐gradient TPU/CNTs/CB pressure sensor has a dual piezoresistance effect with both positive and negative piezoresistance, exhibiting an ultra‐wide working range (1.5 MPa) and high sensitivity (1.25 kPa −1 ). Furthermore, the TPU/CNTs/CB foam also exhibits exceptional triboelectric sensitivity (1.69 V kPa −1 ). Consequently, the mechanical‐electrical dual‐gradient TPU/CNTs/CB foam is assembled into a system of self‐generated electrical sensing and piezoresistive sensing for recognizing different gaits assisted by machine learning algorithms. The proposed scalable fabrication method and structure‐function synergy offer a promising pathway for next‐generation intelligent sensing technologies.
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