Tensile modulus prediction of carbon nanotubes-reinforced nanocomposites by a combined model for dispersion and networking of nanoparticles | Zendy

Yasser Zare | Zendy; Kyong Yop Rhee | Zendy

Open Access

Tensile modulus prediction of carbon nanotubes-reinforced nanocomposites by a combined model for dispersion and networking of nanoparticles

Author(s) -

Yasser Zare,

Kyong Yop Rhee

Publication year - 2019

Publication title -

journal of materials research and technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.832

H-Index - 44

eISSN - 2214-0697

pISSN - 2238-7854

DOI - 10.1016/j.jmrt.2019.10.025

Subject(s) - materials science , nanocomposite , composite material , percolation threshold , carbon nanotube , volume fraction , modulus , interphase , ultimate tensile strength , dispersion (optics) , percolation (cognitive psychology) , young's modulus , polymer , polymer nanocomposite , elastic modulus , physics , optics , engineering , neuroscience , biology , electrical engineering , genetics , electrical resistivity and conductivity

In this work, two models for the tensile modulus of composites and blends are joined, assuming the dispersion and networking of carbon nanotubes (CNTs) and the interphases around CNTs in polymer nanocomposites after the percolation threshold. Equations are given to express the percolation threshold, the network fraction, and the fractions of interphases in the nanocomposites. The suggested model predicts the tensile modulus in several samples, and the roles and efficiencies of all parameters in the nanocomposite modulus are determined. CNT radius (R) and interphase thickness (t) as well as the modulus (EiN) and volume fraction ( ϕ i N ) of the interphase surrounding the CNT network have the most important influences on the modulus; R = 10 nm and t = 35 nm produced a 400% improvement in the modulus of nanocomposite compared to the neat polymer matrix.

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