3-D Microstructure Reconstruction of Polymer Nano-Composite using FIB-SEM and Statistical Correlation Function

 http://www.sciencedirect.com/science/article/pii/S0266353813001012?np=y
Abstract

3-D
reconstruction of Halloysite nanotube (HNT) polypropylene composite has
been performed using two different methods. In the first method,
several slices of the composite material were obtained using focused ion
beam (FIB), and scanning electron microscopy (SEM). A representative
volume element (RVE) of the real material’s micro/nanostructures was
then constructed by stacking these morphological images using VCAT®
software. In the second method, SEM images of the nano-composite were
used to extract statistical two-point correlation function (TPCF), for
reconstruction of an RVE of the nano-composite.

The
resulting RVEs obtained from both methods were meshed for finite element
(FE) simulation of deformation under tension and shear loadings. The FE
results were then used to compute the stiffness tensor of the
nano-composite.

In the statistical approach, the TPCF
was obtained from a none-Eigen microstructure which can partially
reflect statistical information of the microstructure. The mechanical
constants obtained from statistical RVEs using FEM approach shows a 5.7%
error compared with those obtained from real RVE, which could be
attributed to the approximation using TPCF. [1]

It
is concluded that the statistical method using TPCF alone can produce
an approximate microstructure that should be modified using other
statistical descriptor such as two-point cluster function and lineal
path function to have better reconstruction of heterogeneous
nano-composites [2].