Modeling complex motility patterns for autophoretic microswimmers

TL;DR

This paper introduces a high-accuracy numerical framework for modeling isotropic autophoretic microswimmers, capturing complex behaviors like disordered motion and chemotactic interactions through coupled chemical and flow fields.

Contribution

The work develops a novel pseudospectral numerical method that self-consistently models chemical gradients and flow fields without prescribed slip velocities, enabling detailed simulation of autophoretic microswimmer dynamics.

Findings

Reproduces experimentally observed disordered swimming at high viscosities

Captures chemotactic pairwise interactions among microswimmers

Validates the model against experimental data on active droplets

Abstract

Symmetry breaking is essential for biological microswimmers to achieve locomotion in viscous environments. Such asymmetry in the swimming mechanism enables the generation of directional forces that overcome fluid resistance, leading to efficient motion and complex interactions. As synthetic analogues, autophoretic microswimmers including isotropic active colloids and active droplets exhibit spontaneous symmetry breaking of a chemical field, which generates interfacial flows and drives persistent self-propulsion. Modeling these systems is challenging because the chemical concentration and flow fields are strongly coupled through nonlinear advective transport of the chemical species. In this work, we propose a new numerical framework for modeling isotropic autophoretic microswimmers whose propulsion arises solely from self-generated chemical gradients, without any imposed geometric or chemical anisotropy. The framework employs a high-accuracy pseudospectral method to solve the fully coupled advection diffusion Stokes equations, without prescribing any slip velocity model.Slip velocities emerge self-consistently from instantaneous concentration gradients at the particle surface, driving propulsion and inducing flow disturbances through a stresslet representation of force and torque free swimmers. This approach naturally captures nonlinear advection, chemo-hydrodynamic feedback, and many-particle interactions within a unified framework. We demonstrate that the model reproduces complex emergent behaviors observed in experiments, including disordered swimming at higher fluid viscosities and chemotactically guided pairwise interactions. At each stage, numerical predictions are quantitatively compared with independent experiments on active droplets, validating the proposed framework as a robust tool for studying autophoretic microswimmers.