Bioinspired Robust Aramid Triboelectric Aerogels with Vertically Oriented Architecture Enabled by Magnetization Effects

IF 19 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Mingchao Chi, Zixi Lin, Tao Liu, Jinlong Wang, Chenchen Cai, Kang Yu, Bin Luo, Shuangxi Nie
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引用次数: 0

Abstract

Many natural organisms utilize vertically oriented bristles to gain environmental information, and replicating these precisely oriented structures in sensing materials is crucial for improving sensing performance. Building ordered oriented architectures while maintaining the material's mechanical robustness remains challenging. Inspired by the vertically bristle structure of gecko toes, this study proposes a magnetic‐thermal synergistic strategy for fabricating robust aramid nanofiber aerogels with a vertically oriented spatial structure. Under the influence of magnetic torque and magnetic attraction, magnetic carbon nanotubes spontaneously align to form an ordered vertically oriented architecture (direction fit of 96%). This architecture enhances the sensing signal intensity of the aerogel by 64% by inducing surface charge migration. The thermally crosslinked effect enhances the bonding strength between aerogel fiber networks, enabling the aerogel to achieve a compressive strength of 682 kPa (80% compressive strain). This surpasses the compressive strength of aramid fiber aerogels reported to date. The vertically oriented aerogel is assembled into a self‐powered pressure sensor, achieving a signal recognition rate of 98.2% with machine learning assistance. This study proposes a non‐invasive spatial microstructure regulation strategy, offering new insights into the construction of anisotropic structural materials.
具有垂直导向结构的仿生坚固芳纶摩擦电气凝胶,由磁化效应实现
许多自然生物利用垂直定向的刚毛来获取环境信息,在传感材料中复制这些精确定向的结构对于提高传感性能至关重要。在保持材料的机械坚固性的同时,构建有序的面向结构仍然具有挑战性。受壁虎脚趾垂直刚毛结构的启发,本研究提出了一种磁-热协同策略,用于制造具有垂直定向空间结构的坚固芳纶纳米纤维气凝胶。磁性碳纳米管在磁转矩和磁引力的作用下,自发排列形成有序的垂直结构(方向拟合度达96%)。这种结构通过诱导表面电荷迁移,使气凝胶的传感信号强度提高了64%。热交联效应增强了气凝胶纤维网络之间的结合强度,使气凝胶的抗压强度达到682 kPa(80%压应变)。这超过了迄今为止报道的芳纶纤维气凝胶的抗压强度。垂直定向的气凝胶被组装成一个自供电的压力传感器,在机器学习的帮助下实现了98.2%的信号识别率。本研究提出了一种非侵入性的空间微观结构调控策略,为各向异性结构材料的构建提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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