A new stochastic approach for the simulation of agglomeration between colloidal particles.

Area of Science:

• Multiphase flow dynamics
• Colloidal science
• Computational fluid dynamics

Background:

• Particle agglomeration is crucial in many industrial and natural processes.
• Existing models often simplify particle collision and adhesion dynamics.
• Accurate simulation requires detailed tracking of particle interactions.

Purpose of the Study:

• To develop a stochastic simulation approach for particle agglomeration.
• To extend previous work on particle interaction detection to agglomeration.
• To model the adhesion step using the Derjaguin and Landau, Verwey and Overbeek (DLVO) theory.

Main Methods:

• A two-step process: particle collision and adhesion.
• Lagrangian approach for tracking individual particle motions.
• DLVO theory to model inter-particle forces (van der Waals, electrostatic).
• Energy balance approach to couple collision and adhesion steps.

Main Results:

• The model accurately simulates particle agglomeration.
• Numerical results show good agreement with experimental data.
• The approach is applicable to a wide range of particle sizes, including nanoscopic particles.
• The model handles both attractive and repulsive inter-particle forces.

Conclusions:

• The stochastic approach provides a robust method for simulating particle agglomeration.
• The coupled collision-adhesion model is effective for diverse particle types and conditions.
• This work advances the understanding and prediction of particle aggregation phenomena.