Dynamic Clustering and Scaling Behavior of Active Particles under Confinement

Area of Science:

• Physics, Soft Matter
• Computational Physics
• Chemical Physics

Background:

• Active particles exhibit complex collective behaviors, including dynamic clustering.
• Understanding these behaviors under confinement is crucial for applications in materials science and nanotechnology.
• Particle density and driving forces are key parameters influencing active matter dynamics.

Purpose of the Study:

• To systematically investigate the dynamic clustering of active particles under confinement.
• To determine the influence of particle density and active driving force on clustering behavior.
• To derive scaling laws describing the temporal evolution of cluster number and size.

Main Methods:

• Hybrid coarse-grained molecular dynamics simulations were employed.
• Systematic variation of particle density and active driving force was performed.
• Analysis focused on deriving scaling relationships for clustering dynamics.

Main Results:

• Power-law scaling relationships were derived for dynamic clustering time concerning particle density and driving force.
• Average cluster number (N¯) scales with time (t) as N¯∝t-m.
• Average cluster size (S¯) scales with time (t) as S¯∝tm.
• Up to four distinct dynamic clustering regions were identified, dependent on particle density.
• Increased active driving force accelerates aggregation; increased particle density alters dynamic procession.

Conclusions:

• The study establishes quantitative scaling laws for active particle clustering under confinement.
• Particle density and driving force are critical determinants of clustering dynamics and temporal evolution.
• Findings provide insights into the fundamental mechanisms governing self-organization in active matter systems.