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Trapping aligning self-propelled particles into static clusters.

Xinwei Zheng1,2, Yongge Li1,2, Jürgen Kurths3,4

  • 1Northwestern Polytechnical University, School of Mathematics and Statistics, Xi'an 710072, China.

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Summary
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Researchers controlled active particle clusters using Gaussian potentials. Adjusting potential parameters regulates cluster scale and number, offering insights into motility-induced phase separation and particle system manipulation.

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Area of Science:

  • Physics
  • Soft Matter Physics
  • Statistical Mechanics

Background:

  • Active particles, far from equilibrium, form dynamic clusters.
  • Controlling cluster dynamics and properties is crucial for applications.
  • External fields can suppress excessive dynamics in active particle systems.

Purpose of the Study:

  • Investigate cluster formation by aligning self-propelled particles in a Gaussian potential.
  • Discover methods to regulate the scale and number of static clusters (SCs).
  • Explore how potential parameters influence SC characteristics.

Main Methods:

  • Simulated self-propelled particles within a Gaussian potential.
  • Analyzed cluster formation and stability using order parameters on a connection graph.
  • Varied self-propulsion velocity, local density, and potential parameters.

Main Results:

  • Gaussian potential traps particles into stable clusters (SCs).
  • Increased self-propulsion velocity or local density causes partial/complete SC escape.
  • Adjusting potential parameters effectively regulates SC scale and number, creating diverse structures.

Conclusions:

  • Demonstrated a strategy to control SC scale and number by tuning potential parameters.
  • Findings offer new perspectives for controlling motility-induced phase separation.
  • Opens avenues for multitask manipulation in active particle systems.