3-D microstructure reconstruction of polymer nano-composite using FIB–SEM and statistical correlation function

Abstract

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] .