Optical characterisation of subwavelength dielectric particles using particle tracking beyond the Stokes-Einstein relation
Licentiate thesis, 2021
The first method combines off-axis holographic nanoparticle tracking with deep learning (Paper I). By utilizing the optical signal, both size and refractive index of individual particles with a minimum size of R=150 nm were accurately determined using only five particle observations. The method was evaluated using particles of different sizes, refractive indices, surrounding media as well as for polystyrene nanoparticle clusters, for which reversible fluctuations of the number of monomers could be resolved while the fractal dimension remained constant.
The second method is based particles tethered to a laterally fluid supported lipid bilayer and quantification of their diffusivity and flow-induced motion (Paper II). By separating the friction contributions from the tethers and the particle, simultaneous measurement of size and diffusivity enabled a comparison with theory using partial slip as a fitting parameter. This was used to quantify the slip length for different lipid vesicles, and to clarify the size-dependent mechanistic aspects concerning the mobility of membrane-attached nanoparticles.
Chalmers, Physics, Nano and Biophysics
Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography
ACS Nano,; Vol. 15(2021)p. 2240-2250
Olsén, E., Jõemetsa, S., González, A., Joyce, P., Zhdanov, V. P., Midtvedt, D., Höök, F. Quantification of Diffusion for Lipid Vesicles Attached to a Supported Lipid Bilayer Suggests the Partial-Slip Boundary Condition
Areas of Advance
Nanoscience and Nanotechnology (SO 2010-2017, EI 2018-)
Atom and Molecular Physics and Optics
Chalmers University of Technology
PJ salen, Origo, vån 4, Fysikgården 2B, Chalmers Tekniska Högskola
Opponent: Stephan Block, Freie Universität Berlin, Germany