复合材料
材料科学
导电体
电导率
纳米颗粒
极限抗拉强度
热导率
纳米技术
化学
物理化学
作者
Xiao Hou,Fangming Shen,Mingzhou Chen,Lina Song,Quan Liu,Yongyuan Ren,Xiaoli Zhan,Qinghua Zhang
出处
期刊:ACS applied bio materials
[American Chemical Society]
日期:2024-09-02
卷期号:7 (9): 6297-6305
标识
DOI:10.1021/acsabm.4c00905
摘要
Thermal conduction for electronic devices has attracted extensive attention in light of the development of 5G communication. Thermally conductive materials with high thermal conductivity and extensive mechanical flexibility are extremely desirable in practical applications. However, the construction of efficient interconnected conductive pathways and continuous conductive networks is inadequate for either processing or actual usage in existing technologies. In this work, spherical copper nanoparticles (S-CuNPs) and urchin-inspired fractal-growth CuNPs (U-CuNPs), thermally conductive metal fillers induced by ionic liquids, were fabricated successfully through the electrochemical deposition method. Compared to S-CuNPs, the U-CuNPs shows larger specific surface contact area, thus making it easier to build a continuous conductive pathway network in the corresponding U-CuNPs/liquid silicone rubber (LSR) thermally conductive composites. The optimal loading of CuNP fillers was determined by evaluating the rheological performance of the prepolymer and the mechanical properties and thermal conductivity performances of the composites. When the filler loading is 150 phr, the U-CuNPs/LSR produces optimal mechanical properties (e.g., tensile strength and modulus), thermal conductivity (above 1000% improvement compared to pure LSR), and heating/cooling efficiency. The enhanced thermal conductivity of U-CuNPs/LSR was also confirmed through the finite element analysis (FEA) overall temperature distribution, indicating that U-CuNPs with larger specific surface contact areas exhibit more advantages in forming a continuous network in composites than S-CuNPs, making U-CuNPs/LSR a promising and competitive alternative to traditional flexible thermally interface materials.
科研通智能强力驱动
Strongly Powered by AbleSci AI