Issue 60, 2021, Issue in Progress

Preparation of graphene/polypropylene composites with high dielectric constant and low dielectric loss via constructing a segregated graphene network

Abstract

In this paper, a reduced graphene oxide/polypropylene (rGO/PP) dielectric composite with high dielectric constant and low dielectric loss at a low filler content was prepared via constructing a segregated moderately-reduced graphene network by encapsulation of GO on PP latex particles and subsequent in situ reduction of GO by hydrazine hydrate. GO/PP latex was prepared through artificial PP latex preparation in the presence of GO based on the solution-emulsification technique. As the emulsification proceeded, GO could self-assemble to become encapsulated on the surface of PP latex particles composed of PP and maleic-anhydride-grafted-PP because of the hydrogen bonding interaction between maleic-anhydride-grafted-PP and GO nanosheets. After reduction, the rGO encapsulated PP latex particles were obtained, and after coagulation and hot pressing, a segregated graphene network was achieved at a low content of rGO, demonstrated by TEM images. The dielectric constant at 1 kHz obviously increased from 3.28 for PP to 55.8 for the composite with 1.5 wt% rGO. The dielectric loss of the composite was retained at a low value (1.04). This study provides a new simple and effective strategy for preparing high-performance dielectric composites with high dielectric constant and low dielectric loss, facilitating the wide application of dielectric materials.

Graphical abstract: Preparation of graphene/polypropylene composites with high dielectric constant and low dielectric loss via constructing a segregated graphene network

Article information

Article type
Paper
Submitted
13 Aug 2021
Accepted
27 Oct 2021
First published
29 Nov 2021
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2021,11, 38264-38272

Preparation of graphene/polypropylene composites with high dielectric constant and low dielectric loss via constructing a segregated graphene network

L. Han, H. Wang, Q. Tang, X. Lang, X. Wang, Y. Zong and C. Zong, RSC Adv., 2021, 11, 38264 DOI: 10.1039/D1RA06138K

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