Suppr超能文献

界面设计策略用于制造高拉伸应变传感器。

Interface Design Strategy for the Fabrication of Highly Stretchable Strain Sensors.

机构信息

Department of Macromolecular Science and Engineering , Case Western Reserve University , 2100 Adelbert Road , Cleveland , Ohio 44106-7202 , United States.

出版信息

ACS Appl Mater Interfaces. 2018 Oct 24;10(42):36483-36492. doi: 10.1021/acsami.8b14573. Epub 2018 Oct 15.

Abstract

Simultaneously achieving high piezoresistive sensitivity, stretchability, and good electrical conductivity in conductive elastomer composites (CECs) with carbon nanofillers is crucial for stretchable strain sensor and electrode applications. Here, we report a facile and environmentally friendly strategy to realize these three goals at once by using branched carbon nanotubes, also known as the carbon nanostructure (CNS). Inspired by the brick-wall structure, a robust segregated conductive network of a CNS is formed in the thermoplastic polyurethane (TPU) matrix at a very low filler fraction, which renders the composite very good electrical, mechanical, and piezoresistive properties. An extremely low percolation threshold of 0.06 wt %, currently the lowest for TPU-based CECs, is achieved via this strategy. Meanwhile, the electrical conductivity is up to 1 and 40 S/m for the composites with 0.7 and 4 wt % CNS, respectively. Tunable piezoresistive sensitivity dependent on CNS content is obtained, and the composite with 0.7 wt % filler has a gauge factor up to 6861 at strain ε = 660% (elongation at break is 950%). In addition, this strategy also renders the composites' attractive tensile modulus. The composite with 3 wt % CNS shows 450% improvement in Young's modulus versus neat TPU. This work introduces a facile strategy to fabricate highly stretchable strain sensors by designing CNS network structures, advancing understanding of the effects of polymer-filler interfaces on the mechanical and electrical property enhancements for polymer nanocomposites.

摘要

在具有碳纳米填料的导电弹性体复合材料(CECs)中同时实现高压阻灵敏度、拉伸性和良好的导电性对于可拉伸应变传感器和电极应用至关重要。在这里,我们报告了一种简单且环保的策略,通过使用支化碳纳米管,即碳纳米结构(CNS),一次实现这三个目标。受砖墙结构的启发,在热塑性聚氨酯(TPU)基体中形成了一种非常坚固的 CNS 分离导电网络,其在非常低的填料分数下赋予了复合材料非常好的电、机械和压阻性能。通过这种策略,实现了极低的渗流阈值,仅为 0.06wt%,这是目前基于 TPU 的 CEC 中的最低值。同时,复合材料的电导率分别高达 1 和 40 S/m,其 CNS 含量分别为 0.7 和 4wt%。获得了依赖于 CNS 含量的可调压阻灵敏度,其中填充 0.7wt%填料的复合材料在应变 ε=660%(断裂伸长率为 950%)时的应变系数高达 6861。此外,该策略还赋予了复合材料有吸引力的拉伸模量。与纯 TPU 相比,含有 3wt%CNS 的复合材料的杨氏模量提高了 450%。这项工作通过设计 CNS 网络结构,引入了一种制备高可拉伸应变传感器的简单策略,推进了对聚合物-填料界面影响的理解,这对聚合物纳米复合材料的机械和电性能增强具有重要意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验