材料科学
复合材料
双环戊二烯
复合数
热稳定性
碳纳米管
环氧树脂
聚合物
热导率
化学工程
聚合
工程类
作者
Naveen Veeramani,S. Raja,Abhijit P. Deshpande,Sheril Varghese,Vinutha Moses
出处
期刊:International Polymer Processing
[De Gruyter]
日期:2023-06-14
卷期号:38 (4): 483-495
标识
DOI:10.1515/ipp-2022-4320
摘要
Abstract Three different microcapsules, namely dicyclopentadiene (DCPD)-urea formaldehyde (UF) based single-walled microcapsules, DCPD-UF-Siloxane (DCPD-UF-Si) based double-walled microcapsules and DCPD-Carbon nanotubes-UF based dual-core microcapsules were synthesized, and their corresponding self-healing composites were prepared. This paper mainly focuses on the synthesis procedure of various microcapsules and a comparative study on the effect of microcapsules over the final composite properties. The core content of the microcapsules was measured and compared with theoretical calculations. DSC & TGA analyses have shown that the novel microcapsules (DCPD-UF-Si, DCPD-CNT-UF) and their composites have better thermal stability compared to DCPD-UF microcapsules. Epoxy-carbon fiber (2 wt.%) composite specimens with three different microcapsules were tested for surface morphology, mechanical, thermal and electrical properties. SEM analysis has shown that the microcapsules have a rough outer surface and smooth inner surface. The average diameter and shell thickness of the microcapsules were measured for all types of microcapsules. Addition of double-walled and dual-core microcapsules has reduced the glass transition temperature of the composites by 10 °C. Also, SHC with DCPD-UF-Si and DCPD-CNT-UF microcapsules have shown better thermal stability (300 °C) compared to DCPD-UF microcapsules (220 °C). The incorporation of CNT based microcapsules inside the composite has also improved the electrical conductivity by 2.2 times, without compromising on self-healing efficiency (78 %). Therefore, these novel microcapsules can be potential candidates for making multifunctional polymer composites for aerospace, windmills and automotive applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI