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Polymer nanocomposite

About: Polymer nanocomposite is a research topic. Over the lifetime, 8977 publications have been published within this topic receiving 297599 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, electrical conductivity of poly(methyl methacrylate) and carbon nanofibers (CNF) was investigated in a low-shear chaotic mixer.
Abstract: Electrically conductive composites of poly(methyl methacrylate) and carbon nanofibers (CNF) were prepared in a low-shear chaotic mixer. These materials showed a percolation threshold of approximately 2 wt.% CNF compared to 6 wt.% for materials prepared in an internal mixer under comparable conditions of mean shear rate. It was found in materials prepared by chaotic mixing that nanofibers were pulled out of the bundles and oriented along the flow directions to produce electrically conductive networks. Electrical conductivity showed great sensitivity to mixing time around percolation threshold and remained almost unchanged with prolonged chaotic mixing above the percolation threshold. Thermal, thermo-mechanical and mechanical properties of the composites were investigated.

94 citations

Journal ArticleDOI
TL;DR: In this paper, a facile and easy way to prepare styrene-(ethylene-co-butylene)-styrene tri-block copolymer/polypropylene (SEBS/PP) blends filled with boron nitride nanosheets was reported.

94 citations

Journal ArticleDOI
TL;DR: In this article, the Maxwell-Wagner-Sillars (MWS) mechanism is considered to be the source of the observed high dielectric constant for this class of nanocomposites.

93 citations

Journal ArticleDOI
TL;DR: In this article, different types of interatomic potentials can be used for the modeling of graphene, hexagonal boron nitride (h-BN) and corresponding nanocomposites, and further elaborates on developments and challenges associated with the classical mechanics-based approach along with synergic effects of these nano reinforcements on host polymer matrix.
Abstract: Due to their exceptional properties, graphene and hexagonal boron nitride (h-BN) nanofillers are emerging as potential candidates for reinforcing the polymer-based nanocomposites. Graphene and h-BN have comparable mechanical and thermal properties, whereas due to high band gap in h-BN (~5 eV), have contrasting electrical conductivities. Atomistic modeling techniques are viable alternatives to the costly and time-consuming experimental techniques, and are accurate enough to predict the mechanical properties, fracture toughness, and thermal conductivities of graphene and h-BN-based nanocomposites. Success of any atomistic model entirely depends on the type of interatomic potential used in simulations. This review article encompasses different types of interatomic potentials that can be used for the modeling of graphene, h-BN, and corresponding nanocomposites, and further elaborates on developments and challenges associated with the classical mechanics-based approach along with synergic effects of these nano reinforcements on host polymer matrix. For further resources related to this article, please visit the WIREs website.

93 citations

Journal ArticleDOI
TL;DR: In this article, a review of the latest researches on modified halloysite nanotubes as an efficient flame retardant for various polymer nanocomposites and their influence on the mechanical properties and thermal stability is presented.

93 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023165
2022391
2021661
2020726
2019630
2018674