X-ray microtomography and serial block face scanning electron microscopy are used to reveal independent clusters of inorganic particles embedded within a polymer. These clusters are interpenetrating, of varying size, and have fractal dimensions that strongly influence transport and structure-property relations. This interpretation forms a baseline for designing hybrid materials for applications in self-healing, drug delivery, and membranes.

Pitting corrosion is associated with the distribution and composition of intermetallic (IM) particles. However, quantitatively studying the relationship between alloy corrosion and IM particle property remains a challenging topic. In this paper, a computational method is presented for IM particle characterisation and reconstruction based on backscattered scanning electron micrographs of aluminium alloy AA2024-T3.The reconstructed mapping of IM particles provides a 2D map of the intermetallic distribution that conforms to empirical statistical data but is generated randomly. This enables a range of statistically identical virtual microstructures which are generated in order to determine variability in pitting models as well as for systematic variation of input parameters in a sensitivity analysis (e.g., concentration of a given alloying element) used to deduce new microstructural maps for modified compositions. IM particle spatial distribution patterns are analysed based on the reconstruction maps to study the clustering properties of different types of IM particles. The presented approach provides a quantitative tool for studying the relationship between alloy corrosion and the distribution and composition of a range of IM particles.