Elastic property prediction of single-walled carbon nanotube buckypaper/polymer nanocomposites: stochastic bulk response modeling.

In this study, we investigated the statistical relationship between nanostructure variations of carbon nanotube buckypaper-polymer (BPP) composites and their resulting elastic properties. A statistical simulation was developed to predict the elastic properties of a single-layer BPP lamina and extrapolated to the resultant bulk composite part. The stochastic characteristics of BPP composite nanostructure were quantified from experimental observations and used to generate the input for each simulation set performed. The Mori-Tanaka method was used to calculate the stiffness tensor within the buckypaper-polymer region, and a Monte-Carlo simulation was applied to generate the probability distribution for the effective stiffness tensor within each BPP lamina. Classical laminate theory was then employed to predict the effective elastic response for a multi-layered BPP composite laminate. The theoretical predictions were compared with experimental data, and the resulting trends for the effective tensile modulus between experimental and theoretical corresponded well with each other.