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Dependence of Dielectric Properties and Percolative Behavior on Phase Separation Structure Induced by Heterogeneous Carbon Nanofiber Distribution in Polymer Blend Nanocomposites
Author(s) -
Sun LiLi,
Zhao Yan,
Zhong WeiHong
Publication year - 2011
Publication title -
macromolecular materials and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 96
eISSN - 1439-2054
pISSN - 1438-7492
DOI - 10.1002/mame.201100037
Subject(s) - materials science , high density polyethylene , composite material , dielectric , nanocomposite , polymer blend , phase (matter) , polyethylene , polymer , ternary operation , carbon nanofiber , carbon nanotube , copolymer , chemistry , optoelectronics , organic chemistry , computer science , programming language
Abstract Many thermoplastics currently used in industry are in fact polymer blends and there is a pressing need to understand the dependence of the dielectric properties and percolative behaviors of the multi‐phase polymers with heterogeneous nanofiller distributions. When nanofillers distribution occurs in a polymer blend with phase separation, the dielectric properties and percolative behaviors have been shown to be more complex, and very sensitive to the distribution of the nanofillers. As a basis, the dielectric properties and alternating current (AC) conductivities of the binary carbon nanofiber (CNF)/high density polyethylene (HDPE) composite system were first characterized. Subsequently the properties of the ternary CNF/ultra‐high molecular weight polyethylene (UHMWPE)/HDPE composites were compared and analyzed. Combined with the evidence showing the phase separation of UHMWPE and HDPE and the CNFs exclusively dispersed in HDPE phase, it was inferred that UHMWPE acting as a non‐conductive additive, dramatically changed the uniform CNF presence in the matrix into a heterogeneous distribution. As a result, the dependencies of dielectric properties and conductivities on frequency were strongly affected, and in particular the percolative characteristics showed significantly increased dependencies.