4.5 Article Proceedings Paper

Determination of the positions and orientations of concentrated rod-like colloids from 3D microscopy data

Journal

JOURNAL OF PHYSICS-CONDENSED MATTER
Volume 27, Issue 19, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/0953-8984/27/19/194109

Keywords

rod-like particles; image processing; 3D reconstructions

Funding

  1. European Research Council under European Unions Seventh Framework Programme/ERC [291667]
  2. Material Properties of the Materials innovation institute (M2i) [M62.7.08SDMP25]

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Confocal microscopy in combination with real-space particle tracking has proven to be a powerful tool in scientific fields such as soft matter physics, materials science and cell biology. However, 3D tracking of anisotropic particles in concentrated phases remains not as optimized compared to algorithms for spherical particles. To address this problem, we developed a new particle-fitting algorithm that can extract the positions and orientations of fluorescent rod-like particles from three dimensional confocal microscopy data stacks. The algorithm is tailored to work even when the fluorescent signals of the particles overlap considerably and a threshold method and subsequent clusters analysis alone do not suffice. We demonstrate that our algorithm correctly identifies all five coordinates of uniaxial particles in both a concentrated disordered phase and a liquid-crystalline smectic-B phase. Apart from confocal microscopy images, we also demonstrate that the algorithm can be used to identify nanorods in 3D electron tomography reconstructions. Lastly, we determined the accuracy of the algorithm using both simulated and experimental confocal microscopy data-stacks of diffusing silica rods in a dilute suspension. This novel particle-fitting algorithm allows for the study of structure and dynamics in both dilute and dense liquid-crystalline phases (such as nematic, smectic and crystalline phases) as well as the study of the glass transition of rod-like particles in three dimensions on the single particle level.

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