Evolving Motility of Active Droplets Is Captured by a Self-Repelling Random Walk Model

Area of Science:

• Physics of soft matter
• Biophysics
• Fluid dynamics

Background:

• Microorganisms navigate complex environments using chemical gradients.
• Understanding self-propulsion and trail-following is crucial for microbial ecology.
• Previous models often simplify complex hydrodynamic interactions.

Purpose of the Study:

• To investigate swimmer-trail interactions using a model system.
• To develop a quantitative model for droplet motility.
• To understand memory effects and collective behavior in active matter.

Main Methods:

• Utilized swimming droplets as a model system.
• Combined experimental observations with theoretical modeling.
• Developed a non-Markovian model to capture droplet dynamics.

Main Results:

• The non-Markovian droplet model quantitatively describes droplet motility.
• Identified two key parameters: effective temperature from hydrodynamics and propulsion coupling strength.
• Observed and explained phenomena like droplet hovering and enhanced collective motion.

Conclusions:

• The developed framework provides a general approach to study active matter motility.
• Hydrodynamic interactions and self-generated trails significantly influence microswimmer behavior.
• This model offers insights into memory effects and emergent collective dynamics.