Tessellation-based stochastic modelling of 3D coating structures imaged with FIB-SEM tomography
Journal article, 2021
To facilitate printing, coatings are typically applied to paperboard used for packaging to provide a good surface for application. To optimise the performance of the coating, it is important to understand the relationship between the microstructure of the material and its mass transport properties. In this work, three samples of paperboard coating are imaged using combined focused ion beam and scanning electron microscope (FIB-SEM) tomography data appropriately segmented to characterise the internal microstructure. These images are used to inform a parametric, tessellation-based stochastic three-dimensional model intended to mimic the irregular geometry of the particles that can be seen in the coating. Parameters for the model are estimated from the FIB-SEM image data, and we demonstrate good agreement between the real and virtual structures both in terms of geometrical measures and mass transport properties. The development of this model facilitates exploration of the relationship between the structure and its properties.
Gaussian random field
Permeability
Laguerre tessellation
Paperboard coatings
FIB-SEM tomography
Stochastic modelling
Author
Philip Townsend
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
RISE Research Institutes of Sweden
Torben Nilsson Pingel
Chalmers, Physics, Nano and Biophysics
Niklas Lorén
RISE Research Institutes of Sweden
Chalmers, Physics, Nano and Biophysics
Tobias Gebäck
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Eva Olsson
Chalmers, Physics, Nano and Biophysics
Aila Särkkä
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Magnus Röding
RISE Research Institutes of Sweden
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Computational Materials Science
0927-0256 (ISSN)
Vol. 197 110611Subject Categories
Manufacturing, Surface and Joining Technology
Other Materials Engineering
Medical Image Processing
DOI
10.1016/j.commatsci.2021.110611