材料科学
碳纳米管
石墨烯
复合数
复合材料
渗流阈值
氧化物
色散(光学)
热导率
热稳定性
纳米复合材料
渗透(认知心理学)
聚合物
纳米技术
电阻率和电导率
化学工程
工程类
物理
神经科学
光学
冶金
电气工程
生物
作者
Jiajia Meng,Jianan Song,Xi Zhang,Jiaqi Wang,Songjun Li
标识
DOI:10.1016/j.coco.2023.101693
摘要
Carbon nanotube (CNT) is an important filler for preparing poly(dimethylsiloxane) (PDMS)-based composite sensors with high thermal conductivity. However, CNT encounters challenges in terms of dispersion within the polymer matrix. In this work, a combined strategy was proposed to improve the dispersion of CNT, involving surface modification of CNT, CNT-reduced graphene oxide (rGO) hybridization and in-situ cross-linking of PDMS in a solution. The in-situ cross-linking of PDMS contributed to an increase in elongation at break, coupled with a reduction in the modulus of the resulting in-situ crosslinked PDMS/m-CNT@rGO (S-PDMS/m-CNT@rGO) composites. Through the implementation of this strategy, the dispersion of CNT within the PDMS matrix was enhanced, simultaneously facilitating the establishment of filler networks. At the filler content of 10.0 wt%, the thermal conductivity of the S-PDMS/m-CNT@rGO composite increased to 1.06 W/(m·K) and the electrical conductivity increased to 4.51 × 10−3 S/cm. The S-PDMS/m-CNT@rGO composite had a low percolation threshold which was 0.35 wt%. When utilized as a strain sensor, the S-PDMS/m-CNT@rGO composite exhibited high sensitivity, good repeatability and stability in monitoring human motion.
科研通智能强力驱动
Strongly Powered by AbleSci AI