Active particles in explicit solvent: Dynamics of clustering for alignment interaction.

Area of Science:

• Soft Matter Physics
• Active Matter Systems
• Computational Physics

Background:

• Active particles in explicit solvents exhibit complex clustering dynamics.
• Understanding these dynamics is crucial for various applications, from materials science to biology.
• Hydrodynamic interactions play a significant role in the collective behavior of active matter.

Purpose of the Study:

• To investigate the dynamics of clustering in active particle systems immersed in an explicit solvent.
• To quantify the effects of particle activity and hydrodynamic interactions on clustering.
• To explore the different cluster growth mechanisms and their corresponding growth laws.

Main Methods:

• Hybrid simulation combining molecular dynamics (MD) and multiparticle collision dynamics (MPCD).
• Utilized modified Lennard-Jones potentials for inter-particle interactions.
• Incorporated Vicsek-like alignment rules for self-propulsion to induce clustering.

Main Results:

• Identified switching growth mechanisms: particle diffusion, diffusive coalescence, and ballistic aggregation.
• Demonstrated that active and hydrodynamic interactions modulate cluster growth and mobility.
• Observed distinct cluster morphologies at low active particle densities near the vapor-coexistence curve.

Conclusions:

• Multiparticle collision dynamics (MPCD) is effective for studying hydrodynamic phenomena in phase-separating active matter.
• The interplay between activity and hydrodynamics dictates the emergent clustering behavior.
• Results provide insights into the fundamental mechanisms governing self-organized structures in active systems.