The accumulation of motile cells at solid interfaces increases the rate of surface encounters and the likelihood of surface attachment, leading to surface colonization and biofilm formation. The cell density distribution in the vicinity of a physical boundary is influenced by the interactions between the microswimmers and their physical environment, including hydrodynamic and steric interactions, as well as by stochastic effects. Disentangling the contributions of these effects remains an experimental challenge. Here, we use a custom-made four-camera view microscope to track a population of motile puller-type Chlamydomonas reinhardtii in a relatively unconstrained three-dimensional (3D) domain. Our experiments yield an extensive sample of 3D trajectories including cell-surface encounters with a planar wall, from which we extract a full description of the dynamics and the stochasticity of swimming cells. We use this large data sample and combine it with Monte Carlo simulations to determine the link between the dynamics at the single-cell level and the cell density. Our experiments demonstrate that the near-wall scattering is bimodal, corresponding to steric and hydrodynamic effects. We find, however, that this near-wall dynamics has little influence on the cell accumulation at the surface. On the other hand, we present evidence of a cell-induced surface-directed rotation leading to a vertical orbiting behavior and hopping trajectories, consistent with long-range hydrodynamic effects. We identify this long-range effect to be at the origin of the significant surface accumulation of cells.
As a novel volumetric particle image velocimetry technique, single-camera light-field PIV (LF-PIV) is able to reconstruct three-dimensional flow fields with a single camera. The merits of LF-PIV lie in its concise hardware setup and minimum optical access requirement, its capability has been proved in many flow scenarios. In this study, LF-PIV is used to measure a self-similar adverse pressure gradient turbulent boundary layer (APG-TBL). Experiments were performed in a large water tunnel at the Laboratory for Turbulence Research in Aerospace and Combustion (LTRAC), Monash University. 20 independent batches of light-field PIV images were captured for both inner and outer flow, each consisting of 250 instantaneous image pairs. Instantaneous 3D velocity fields were reconstructed with the GPU accelerated DRT-MART and 3D cross-correlation methods and compared with two-dimensional PIV (2D-PIV) results. Initial results show that though limited by the experiment conditions and PIV algorithms developed in 2016, we still can have similar accuracy to 2D-PIV near and above the boundary layer. With the volumetric calibration method that compensates optical distortions caused by lens defect and misalignment between the micro-lens array (MLA) and image sensor, the resolution of LF-PIV is sure to have a large improvement.
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