Hexagonal boron nitride-carbon nanotube hybrid network structure for enhanced thermal, mechanical and electrical properties of polyimide nanocomposites
This study suggests the simple and effective synthesis method of chemically interconnected hexagonal boron nitride (h-BN)–carbon nanotubes (CNTs) hybrid materials (BN–Fe-CNT) with aminosilane functionalized iron oxide nanoparticles (NH2–Fe) via amide bond formations. Synthesized BN-Fe-CNT was acting...
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Published in | Composites science and technology Vol. 188; p. 107977 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Barking
Elsevier Ltd
01.03.2020
Elsevier BV |
Subjects | |
Online Access | Get full text |
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Summary: | This study suggests the simple and effective synthesis method of chemically interconnected hexagonal boron nitride (h-BN)–carbon nanotubes (CNTs) hybrid materials (BN–Fe-CNT) with aminosilane functionalized iron oxide nanoparticles (NH2–Fe) via amide bond formations. Synthesized BN-Fe-CNT was acting as an effective filler that enhanced the mechanical, thermal, and electrical properties of polyimide (PI) nanocomposites and accelerated polycondensation reaction of poly(amic acid) (PAA) due to its high thermal conductivity and heat diffusivity. At a 2 wt% filler reinforcement, the in-plane thermal conductivity of the BN-Fe-CNT/PI reached 15 W m−1 K−1 at 200 °C, which represents an enhancement of approximately 11430% compared to that of pure PI. Moreover, thermal stability was enhanced from 400 °C to 570 °C. Furthermore, the connected CNTs between the individual h-BN produced electron pathways through the PI matrix, with the BN-Fe-CNT/PI exhibiting 106 times higher electrical conductivity than that of pure PI. The results in this study clearly suggested that the BN-Fe-CNT could be applicable as an effective multi-functional reinforcement in the fabrication of lightweight polymer nanocomposites with superior mechanical properties, high thermal properties, and high electrical conductivities. |
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ISSN: | 0266-3538 1879-1050 |
DOI: | 10.1016/j.compscitech.2019.107977 |