Tessellation-based stochastic modelling of 3D coating structures imaged with FIB-SEM tomographyShow others and affiliations
2021 (English)In: Computational materials science, ISSN 0927-0256, E-ISSN 1879-0801, Vol. 197, article id 110611Article in journal (Refereed) Published
Abstract [en]
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. © 2021 The Author(s)
Place, publisher, year, edition, pages
Elsevier B.V. , 2021. Vol. 197, article id 110611
Keywords [en]
FIB-SEM tomography, Gaussian random field, Laguerre tessellation, Paperboard coatings, Permeability, Stochastic modelling
National Category
Manufacturing, Surface and Joining Technology
Identifiers
URN: urn:nbn:se:ri:diva-55217DOI: 10.1016/j.commatsci.2021.110611Scopus ID: 2-s2.0-85107658403OAI: oai:DiVA.org:ri-55217DiVA, id: diva2:1578320
Note
Funding details: 2019-01295; Funding details: Technische Universität Kaiserslautern, TU KL; Funding details: VINNOVA, 2018-00424; Funding details: Vetenskapsrådet, VR, 2016-03809, VR 2018-03986; Funding text 1: This work was financially supported by Vinnova (project number 2018-00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986 and 2016-03809) and the Swedish Research Council for Sustainable Development (2019-01295). The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC). The authors would like to thank Chris Bonnerup of StoraEnso and Magnus ?stlund of TetraPak for providing the coating samples used in this paper and for their helpful comments. The authors would also like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern.; Funding text 2: This work was financially supported by Vinnova (project number 2018-00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986 and 2016-03809) and the Swedish Research Council for Sustainable Development (2019-01295). The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC).
2021-07-062021-07-062023-05-26Bibliographically approved