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Active Brownian polymers exhibit distinct conformational and dynamical properties based on their driving mechanism. Multiparticle collision dynamics simulations reveal activity-induced temporal regimes, impacting polymer motion at various scales.

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Area of Science:

  • Soft Matter Physics
  • Polymer Physics
  • Computational Physics

Background:

  • Active Brownian polymers possess unique properties influenced by their propulsion or actuation mechanisms.
  • Understanding these properties is crucial for applications in soft robotics and biomaterials.
  • Existing simulation methods require adaptation for different active polymer driving mechanisms.

Purpose of the Study:

  • To implement and validate multiparticle collision dynamics (MPC) simulations for both self-propelled and actuated active Brownian polymers.
  • To investigate the distinct conformational and dynamical behaviors arising from different driving mechanisms.
  • To analyze the impact of activity on polymer dynamics across various length and time scales.

Main Methods:

  • Development of adapted MPC simulation schemes for self-propelled and actuated active Brownian polymers.
  • Comparison of MPC simulation results with Brownian dynamics simulations incorporating hydrodynamic interactions (Rotne-Prager-Yamakawa tensor).
  • Analysis of polymer properties using static and dynamic structure factors.

Main Results:

  • The adapted MPC method accurately captures the differences between self-propelled and actuated active polymers.
  • Dynamic structure factor reveals distinct activity-induced temporal regimes.
  • Small wave numbers show persistent diffusive motion; large wave numbers exhibit activity-enhanced internal dynamics.

Conclusions:

  • The implemented MPC approach is suitable for simulating active Brownian polymers with different driving mechanisms.
  • Activity significantly influences polymer dynamics, leading to scale-dependent behaviors.
  • Simulation results align with theoretical predictions, validating the model.