摩擦电效应
纳米发生器
材料科学
复合材料
超细纤维
热塑性聚氨酯
压电
图层(电子)
纳米技术
分层(地质)
模数
阳极
压力(语言学)
聚合物
韧性
弹性模量
静电纺丝
电导率
光电子学
电容感应
电极
薄脆饼
智能材料
纳米纤维
磁滞
纳米柱
蜂巢
作者
Shiwei Xu,Pengfan Wu,Feng Qin,Endian Cui,Zhongyong Mo,Hengyu Guo,Xiaojing Mu,Hua Dong Yu
标识
DOI:10.1002/advs.202518027
摘要
Abstract With the growing demand for flexible self‐powered energy sources for wearable bioelectronics, triboelectric nanogenerator (TENG) have emerged as a promising technology for harvesting biomechanical energy. However, interfacial delamination between functional layers caused by mechanical mismatch has limited their practical application. Existing strategies struggle to balance bond strength, electrical conductivity, and stretchability. Inspired by molecularly continuous interfaces in biological systems, this study proposes a novel TENG construction strategy based on homologous polymer pairing. The triboelectric layer is a tailored thermoplastic polyurethane (TPU)/polyvinyl chloride (PVC)/ dibutyl adipate (DBA) gel (TPD‐gel) with high electronegativity and tunable plasticity, while the electrode consists of a carbon nanotube‐embedded TPU microfiber network that maintains stable conductivity under 200% strain. Both layers share a polyurethane matrix, enabling modulus matching (ratio < 2) and strain coordination, which fundamentally suppresses stress concentration. Through ultrasonic cavitation treatment, the interfacial toughness is significantly enhanced to 190 N m −1 , which is 3.2 times that of conventional PDMS‐based interfaces. The resulting TENG exhibits high triboelectric charge density, strain‐insensitive conductivity, and over 100% extensibility. Furthermore, a delamination‐resistant triboelectric sensor integrated with a deep learning algorithm achieves 97.8% accuracy in character recognition, demonstrating potential for wearable health monitoring and human–machine interaction.
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