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Title: Atomistically informed stochastic multiscale model to predict the behavior of carbon nanotube-enhanced nanocomposites

Journal Article · · Carbon

A comprehensive, point-information-to-continuum-level analysis framework is presented in this paper to accurately characterize the behavior of carbon nanotube (CNT)-enhanced composite materials. Molecular dynamics (MD) simulations are performed to study sub-nanoscale interactions of the CNT with the polymeric phase of the nanocomposite. The effect of cross-linking between the epoxy resin and the hardener on the mechanical properties of the polymer is investigated; furthermore, the effect of CNT weight fraction on the probability distribution of polymer cross-linking degree is also studied through stochastic models. The stochastic distributions obtained from MD simulations provide a basis to simulate local variations in the matrix properties in the continuum model at the microscale. The inclusion of an atomistically informed elastic-plastic model at the microscale reveals a significant deviation of the mechanical properties from those obtained based on classical homogenization approaches. Microstructural variability arising from heterogeneous cross-linking degree in the polymer phase and variations in fiber geometry and spacing is also found to cause deviations in the mechanical response when compared to the assumption of a perfectly ordered fiber-matrix microstructure.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
U.S. Department of the Navy
DOE Contract Number:
AC02-05CH11231
OSTI ID:
1581153
Journal Information:
Carbon, Vol. 94, Issue C; ISSN 0008-6223
Publisher:
Elsevier
Country of Publication:
United States
Language:
English

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