Aggregate Structure Evolution for Size-Dependent Aggregation by Means of Monte Carlo Simulations

Aggregation during crystallization and precipitation processes often leads to complex-shaped particle aggregates. As an alternative to low-dimensional deterministic population balance models, where assumptions on the particle shape must be made, stochastic or so-called Monte Carlo methods can be employed. In previous work a hierarchical characterization of aggregates has been proposed (Briesen, AIChE J., 52, 2436-2446, 2006), which allows the use of different levels of detail for modelling the different rate processes as primary particle growth or particle aggregation. With that hierarchical characterization, the detailed geometry of aggregates becomes accessible for rate process modelling and product characterization. Here, this framework is extended to investigate size-dependent collision rates and aggregation efficiencies. The results show that the aggregate structures can be modelled by the interplay of shear rate and the growth rate at the particle necks in a mechanistic way. Future work will address the comparison with experimental data and alternative model formulations.