Modeling fractal aggregates of polydisperse particles with tunable dimension

Abstract

A generalized non-kinetic off-lattice algorithm to construct stochastic fractal clusters of polydisperse particles with tunable cluster parameters including dimension, is presented. The model based on a hierarchical procedure extends the previous studies in this area to the general case of the cluster-cluster aggregation and, in contrast to the previous kinetic models, makes it possible to generate clusters with a continuous change in the structure, in particular, covering the full range of natural mass fractal dimensions between one and three. An example of the morphological study of numerically generated clusters based on the correlation analysis in both direct and reciprocal spaces is given. In the latter case, it is demonstrated that the use of the developed fast algorithm gives an accurate and self-consistent description of the small-angle scattering data.