Previous experiments have shown that spherical colloidal particles relax to equilibrium slowly after they adsorb to a liquid–liquid interface, despite the large interfacial energy gradient driving the adsorption. The slow relaxation has been explained in terms of transient pinning and depinning of the contact line on the surface of the particles. However, the nature of the pinning sites has not been investigated in detail. We use digital holographic microscopy to track a variety of colloidal spheres—inorganic and organic, charge-stabilized and sterically stabilized, aqueous and non-aqueous—as they breach liquid interfaces. We find that nearly all of these particles relax logarithmically in time over timescales much larger than those expected from viscous dissipation alone. By comparing our results to theoretical models of the pinning dynamics, we infer the area per defect to be on the order of a few square nanometers for each of the colloids we examine, whereas the energy per defect can vary from a few kT for non-aqueous and inorganic spheres to tens of kT for aqueous polymer particles. The results suggest that the likely pinning sites are topographical features inherent to colloidal particles—surface roughness in the case of silica particles and grafted polymer “hairs” in the case of polymer particles. We conclude that the slow relaxation must be taken into account in experiments and applications, such as Pickering emulsions, that involve colloids attaching to interfaces. The effect is particularly important for aqueous polymer particles, which pin the contact line strongly.
Selective-plane illumination microscopy (SPIM) provides unparalleled advantages for the volumetric imaging of living organisms over extended times. However, the spatial configuration of a SPIM system often limits its compatibility with many widely used biological sample holders such as multi-well chambers and plates. To solve this problem, we developed a high numerical aperture (NA) open-top configuration that places both the excitation and detection objectives on the opposite of the sample coverglass. We carried out a theoretical calculation to analyze the structure of the system-induced aberrations. We then experimentally compensated the system aberrations using adaptive optics combined with static optical components, demonstrating near-diffraction-limited performance in imaging fluorescently labeled cells.
20 June 2019 in Computing in Science & Engineering
A holographic microscope captures interference patterns, or holograms, that encode three-dimensional (3-D) information about the object being viewed. Computation is essential to extract that 3-D information. By wrapping low-level scattering codes and taking advantage of Python's data analysis ecosystem, HoloPy makes it easy for experimentalists to use modern, sophisticated inference methods to analyze holograms. The resulting data can be used to understand how small particles or microorganisms move and interact. The project illustrates how computational tools can enable experimental methods and new experiments.