writer：Jianwen Chen, Hua Li, Qizhou Yu, Yanming Hu, Xihua Cui, Yutian Zhu, Wei Jiang
keywords：可拉伸导电聚合物复合材料, 应变传感行为, 填料维度, 电学性能, 碳纳米管, 炭黑
source：期刊
specific source：Composites Science and Technology, 2018, 168, 388-396
Issue time：2018年

摘要：本文研究了异戊橡胶（IR）基导电复合材料的应变传感行为对填料维度的依赖性。研究发现，炭黑（CB）/IR复合材料表现出超高应变灵敏度和良好回复性，因为CB网络在拉伸时易断裂、释放时快速重建；但CB/IR复合材料的缺点是电逾渗阈值较高（8.01 phr），导致加工复杂、力学性能差且成本高。相比之下，碳纳米管（CNTs）/IR复合材料具有较低的逾渗阈值（1.44 phr），但灵敏度和回复性较差，因为CNT网络在应变下更稳定。有趣的是，将零维CB和一维CNTs结合构建杂化CNT-CB网络，可有效克服CB网络和CNT网络的缺点，使可拉伸CNTs/CB/IR复合材料兼具低逾渗阈值、高应变灵敏度和良好回复性。演示实验表明，可拉伸CNTs/CB/IR复合材料可用于检测人体运动和情绪表达。该研究加深了对不同维度导电填料可拉伸导电聚合物复合材料应变传感行为的理解，有助于设计应变传感材料。

Abstract：Herein, we investigate the dependence of the strain sensing behaviors of isoprene rubber (IR) based conductive composites on filler dimensionality. It is found that carbon black (CB)/IR composites display ultrahigh strain sensitivity and good recoverability since CB-networks are easily broken under stretching and fast rebuilt under releasing. However, the drawback of CB/IR composites is the high electrical percolation threshold (8.01 phr), leading to the complex processing, poor mechanical properties, and high cost. In contrast, carbon nanotubes (CNTs)/IR composites possess low percolation threshold (1.44 phr) but also low sensitivity and poor recoverability because CNT-networks are more stable under strain. Interestingly, it is observed that combining zero-dimensional CB and one-dimensional CNTs to construct the hybrid CNT-CB networks is an effective route to overcome the drawbacks of CB-networks and CNT-networks, which endows the stretchable CNTs/CB/IR composites with low percolation threshold, high strain sensitivity and good recoverability. Moreover, the demonstration experiments show that the stretchable CNTs/CB/IR composites could be used to detect human motions and emotional expressions. This study provides a deeper understanding of the strain sensing behaviors of the stretchable conductive polymer composites loaded with different dimensional conductive fillers, which helps to design strain sensing materials.

论文链接：https://doi.org/10.1016/j.compscitech.2018.10.025