材料科学
复合材料
碳纳米管
复合数
导电体
热导率
皮克林乳液
电阻率和电导率
乳状液
化学工程
纳米技术
纳米颗粒
电气工程
工程类
作者
Songqing Hu,Bin Xu,Yang Zhao,Xudong Fu,Qingting Liu,Rong Zhang
标识
DOI:10.1016/j.compscitech.2022.109374
摘要
Conductive and thermal conductive polymer composites have significant advantages in corrosion resistance and mechanical and processing properties. To improve the integrity of the network structure of the conductive filler in a polypropylene (PP) matrix, [email protected] (Gr) with segregated single-network structure, [email protected](carbon nanotubes (CNTs)/Gr) with segregated double-network structure, and (x wt%-CNTs/PP)@Gr with segregated hybrid double-network structure were prepared by the Pickering emulsion method. The original irregular powder was converted into spherical shape by the Pickering emulsion method. Among these composites, the (2 wt%-CNTs/PP)@Gr composite had the highest conductivity and thermal conductivity. The electrical and thermal conductivity of the (2 wt%-CNTs/PP)@Gr composite reached 1.45 S/m and 0.82 W/m·K, respectively, at a Gr loading of 13.01 wt%, and the electrical conductivity was 3 and 0.5 times higher than that of [email protected] and [email protected](CNTs/Gr) composites, respectively. The CNTs acted as "bridges" to form a denser conductive network, and significantly improved the conductivity. The interfacial thermal resistance of the (2 wt%-CNTs/PP)@Gr composite was between 1.5×10-7 and 1×10-6 m2K/W according to the effective medium theory (EMT) fitting results. Additionally, the crystalline peaks of the [email protected] and [email protected](CNTs/Gr) composites showed a significant left shift, while the (2%-CNT/PP)@Gr composite showed a significant right shift, which indicated that the hybridization of CNTs with Gr caused a "bridge effect" and increased the thermal conductivity. This method provides a convenient and time-saving new approach for the study of segregated structural thermally conductive composites by encapsulating the filler on the matrix through a one-step process while meeting the requirements of green environment.
科研通智能强力驱动
Strongly Powered by AbleSci AI