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Title: Hydrodynamics of micro-swimmers in complex fluids and environments
Author: Mathijssen, Arnoldus J. Th. M.
ISNI:       0000 0004 6421 4868
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Both biological micro-organisms and synthetic micro-robots propel through viscous liquids to achieve their goal, be it to invade new territories or to deliver drugs to infected regions. Considerable attention is devoted to learning how to prevent or encourage these processes, and understanding the interactions between micro-swimmers and their complex environments is an essential part of this. In vivo conditions provide a challenge to model, although novel experimental, computational and theoretical techniques have provided clear insights into the continuous interplay between the effects of strong confinement, hydrodynamic interactions, and local activity that drives living systems out of equilibrium. To analyse the underlying mechanisms of micro-swimmer processes, we develop a hydrodynamic framework based on the fundamental solutions of the Stokes equations to compute swimmer-generated flow fields. These flows affect the motion of swimmers via reflections in surfaces, mix and enhance the uptake of nutrients, and enable cells to sense one another's presence. Hence, we study the accumulation of microbes on surfaces, which could be relevant for the initial stages of biofilm formation, and compute the strength required for externally imposed flows to detach them. Moreover, we evaluate the ability to swim upstream and uncover that viscoelasticity can provide a natural sorting mechanism for sperm cells. Other ecological effects are considered, including the transport of nutrients by micro-flows, the interaction with water-air interfaces, and the impact of thermal noise and biological fluctuations. To verify our results, we compare our theory to extensive simulations using a `Raspberry' swimmer model in combination with the Lattice-Boltzmann fluid solver algorithm. This allows us to determine previously unknown model parameters and hence make suggestions to improve micro-organism treatment and micro-robot design.
Supervisor: Yeomans, Julia M. Sponsor: European Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available