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Inertial delay of self-propelled particles (1807.04357v1)

Published 11 Jul 2018 in cond-mat.soft

Abstract: The motion of self-propelled massive particles through a gaseous medium is dominated by inertial effects. Examples include vibrated granulates, activated complex plasmas and flying insects. However, inertia is usually neglected in standard models. Here, we experimentally demonstrate the significance of inertia on macroscopic self-propelled particles. We observe a distinct inertial delay between orientation and velocity of particles, originating from the finite relaxation times in the system. This effect is fully explained by an underdamped generalisation of the Langevin model of active Brownian motion. In stark contrast to passive systems, the inertial delay profoundly influences the long-time dynamics and enables new fundamental strategies for controlling self-propulsion in active matter.

Citations (124)

Summary

Inertial Delay of Self-Propelled Particles: Insights and Implications

The paper of self-propelled particles (SPPs) offers profound insights into the dynamics of active matter, where each individual particle is propelled by forces that arise from within, contrasting with passive particle systems driven by external forces. The paper, titled "Inertial Delay of Self-Propelled Particles," provides compelling empirical data and theoretical models to demonstrate the critical role that inertia plays in the dynamics of massive self-propelled particles. Departing from traditional models that often neglect inertial effects, this research sheds light on how inertia influences the orientation-velocity alignment in such systems and underscores its implications for motion control strategies.

Key Findings and Methodology

The authors conducted experiments using 3D-printed macroscopic vibrobots—simple self-propelled particles—driven by vibrational energy. These experiments focused on elucidating how inertia affects the dynamics of SPPs moving through gaseous environments. Notably, the paper identified a delayed response between particle orientation and velocity, a phenomenon attributed to inertial effects. This inertial delay is found to significantly alter the long-time trajectories of the particles, thereby impacting their diffusion characteristics.

To capture the inertial influence, the researchers advanced an underdamped generalization of the Langevin equation that includes rotational components. This model effectively accounts for translational-rotational coupling through a self-propulsion term.

In experimental setups, the paper demonstrates:

  • The temporal lag between a particle's actual orientation and its movement direction, quantified as of the order of 10-1 seconds.
  • The significant alteration in long-term diffusion coefficients in self-propelled systems compared to passive ones, directly tied to the moment of inertia.

Implications and Theoretical Insights

The paper's findings hold considerable implications for the understanding and control of active matter:

  • Dynamic Modulation: Through modulation of inertia, control over movement strategies can be enhanced. This knowledge is vital for designing artificial systems, such as microswimmers or robotic entities, where maneuvering precision and obstacle navigation are paramount.
  • Biological Parallels: The findings provide a plausible insight into biological systems where organisms may adjust their inertia (e.g., limb positioning in cheetahs) to optimize for speed or stability.
  • Enhanced Models: The revised Langevin model proposed integrates inertial effects, addressing a significant gap in the predictive modeling of large-scale SPP systems.

Future Directions

The research invites further exploration into the applications of inertial manipulation in active systems. Investigations could consider more complex geometries or environmentally interactive systems where external fields might be used to dynamically modulate the effective inertia of SPPs. Additionally, translating these insights into micro-scale biological and synthetic systems could yield new capabilities in swarm robotics, targeted drug delivery, or environmental sensing technologies.

In summary, the paper underscores the significance of incorporating inertia within the discourse on active particle dynamics, offering a nuanced view that bridges theoretical models with observable experimental behavior. This reconceptualization promotes a deeper understanding of movement within diverse scales and environments, holding promise for new technology and insights into natural phenomena.

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