Modeling Colloidal Particle Aggregation Using Cluster Aggregation with Multiple Particle Interactions

Abstract

In this study, we investigate the aggregation dynamics of colloidal silica by generating simulated structures and comparing them to experimental data gathered through scanning transmission electron microscopy (STEM). More specifically, diffusion-limited cluster aggregation and reaction-limited cluster aggregation models with different functions for the probability of particles sticking upon contact were used. Aside from using a constant sticking probability, the sticking probability was allowed to depend on the masses of the colliding clusters and on the number of particles close to the collision between clusters. The different models of the sticking probability were evaluated based on the goodness-of-fit of spatial summary statistics. Furthermore, the models were compared to the experimental data by calculating the structures' fractal dimension and mass transport properties from simulations of flow and diffusion. The sticking probability, depending on the interaction with multiple particles close to the collision site, led to structures most similar to the STEM data.

Coagulation-flocculation process on a lattice: Monte Carlo simulations

“…The concept of the DLA was initially introduced [27] as a discrete model of growth of dendritic clusters formed by irreversible aggregation of small particles. Since then, it became a paradigm in description of growth phenomena and pattern formation [28,29], in particular as a model of colloidal particle aggregation [30,31], growth of neuronal trees [32], retinal arterial and venous vessels [33], thin film nucleation growth process [34], growth of microbial colonies [35] etc.…”