Aggregation and disaggregation processes in clusters of particles: simple numerical and theoretical insights of the competition in 2D geometries

TL;DR

This paper investigates how clusters of particles grow or break apart under flow in 2D, using simulations and a theoretical energy-based model to understand the power-law relationship between cluster size and adhesion strength.

Contribution

It introduces a simple energy-based model that explains the power-law scaling of cluster size with adhesion number, linking it to cluster fractal dimension, supported by simulations.

Findings

Cluster size follows a power law with adhesion number.

The model predicts the power-law exponent based on fractal dimension.

Simulation results agree with theoretical predictions.

Abstract

Aggregation and disaggregation of clusters of attractive particles under flow are studied from numerical and theoretical points of view. Two-dimensional molecular dynamics simulations of both Couette and Poiseuille flows highlight the growth of the average steady-state cluster size as a power law of the adhesion number, a dimensionless number that quantifies the ratio of attractive forces to shear stress. Such a power-law scaling results from the competition between aggregation and disaggregation processes, as already reported in the literature. Here, we rationalize this behavior through a model based on an energy function, which minimization yields the power-law exponent in terms of the cluster fractal dimension, in good agreement with the present simulations and with previous works.