Squirmer hydrodynamics near a periodic surface topography

Front Cell Dev Biol. 2023 Apr 13:11:1123446. doi: 10.3389/fcell.2023.1123446. eCollection 2023.

Abstract

The behaviour of microscopic swimmers has previously been explored near large-scale confining geometries and in the presence of very small-scale surface roughness. Here, we consider an intermediate case of how a simple microswimmer, the tangential spherical squirmer, behaves adjacent to singly and doubly periodic sinusoidal surface topographies that spatially oscillate with an amplitude that is an order of magnitude less than the swimmer size and wavelengths that are also within an order of magnitude of this scale. The nearest neighbour regularised Stokeslet method is used for numerical explorations after validating its accuracy for a spherical tangential squirmer that swims stably near a flat surface. The same squirmer is then introduced to different surface topographies. The key governing factor in the resulting swimming behaviour is the size of the squirmer relative to the surface topography wavelength. For instance, directional guidance is not observed when the squirmer is much larger, or much smaller, than the surface topography wavelength. In contrast, once the squirmer size is on the scale of the topography wavelength, limited guidance is possible, often with local capture in the topography troughs. However, complex dynamics can also emerge, especially when the initial configuration is not close to alignment along topography troughs or above topography crests. In contrast to sensitivity in alignment and topography wavelength, reductions in the amplitude of the surface topography or variations in the shape of the periodic surface topography do not have extensive impacts on the squirmer behaviour. Our findings more generally highlight that the numerical framework provides an essential basis to elucidate how swimmers may be guided by surface topography.

Keywords: cell motility; confinement; low Reynolds number flow; microswimming; surface topography.

Grants and funding

KI acknowledges JSPS-KAKENHI (18K13456, 21H05309), JSPS Overseas Research Fellowship (29-0146), Kyoto University Hakubi Project, Kyoto University Supporting Program for Interaction-Based Initiative Team Studies (SPIRITS), MEXT Leading Initiative for Excellent Young Researchers (LEADER), and JST, PRESTO Grant Number JPMJPR 1921, Japan. Elements of the numerical simulations were performed within the cluster computer system at the Research Institute for Mathematical Sciences (RIMS) and Institute for Information Management and Communication (IIMC), Kyoto University. DS acknowledges the EPSRC grant EP/N021096/1.