A RECIPE FOR IMAGE CHARACTERIZATION OF FRACTAL-LIKE AGGREGATES

Abstract

In the present paper a simple and straightforward recipe for characterizing the structural and fractal properties of aggregates from their projected images is presented. Starting from geometrical properties that are directly measured from the projected image—such as primary particle mean diameter, maximum projected length, projected area, and overlap coefficient—important threedimensional properties including number of primary particles in an aggregate, radius of gyration, aggregate surface, or fractal dimensions, D f and k g , can be inferred. Expressions proposed in the recipe to relate three dimensional with projected properties were obtained from an extensive investigation of the structure of numerically simulated cluster–cluster fractal-like aggregates. This involved the simulation of statistically significant populations of aggregates having appropriate fractal properties and prescribed numbers of primary particles per aggregate in order to characterize three-dimensional morphological properties of aggregates. Specific ranges of aggregate properties considered were as follows: number of primary particles per aggregate up to 512, fractal dimension, D f≈1.78, overlap coefficient in the range 0–0.33 and fractal pre factor between 1.5 and 3.1.