Issue 56, 2018

Revealing the deformation mechanism of amorphous polyethylene subjected to cycle loading via molecular dynamics simulations

Abstract

Despite tremendous efforts being devoted to the study of the deformation behavior of polyethylene, the deformation mechanism of an amorphous polyethylene polymer under cycle shear-loading remains largely unknown. Here, we report the cycle shear deformation mechanism of an amorphous polyethylene polymer using molecular dynamics (MD) simulations. The stress–strain behaviors, including the elastic, yield, strain hardening, and strain softening regions, are qualitatively in agreement with the previous results. The values of the yield stress, Young's modulus and ultimate strength obtained from MD simulations are consistent with the previous data. The effects of the shear strain rate, temperature, and cycle shear-loading number on the stress–strain behaviors are investigated. Higher strain rate and a lower temperature result in a higher strength in the amorphous polyethylene polymer, attributed to the agglomeration of high local strains. With the increase of the cycle shear-loading number, the high strain region gradually expands from the upper and lower surface to the interior of the polyethylene polymer matrix, which provides the origin of crack initiation. The energy contributions are used in elucidating the inherent deformation mechanisms within the elastic, yielding, strain hardening, and strain softening regions, and the variation trend of energy is consistent with the stress–strain response.

Graphical abstract: Revealing the deformation mechanism of amorphous polyethylene subjected to cycle loading via molecular dynamics simulations

Article information

Article type
Paper
Submitted
10 Jul 2018
Accepted
05 Sep 2018
First published
18 Sep 2018
This article is Open Access
Creative Commons BY license

RSC Adv., 2018,8, 32377-32386

Revealing the deformation mechanism of amorphous polyethylene subjected to cycle loading via molecular dynamics simulations

Q. Fang, Y. Tian, H. Wu and J. Li, RSC Adv., 2018, 8, 32377 DOI: 10.1039/C8RA05868G

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