@misc{schladitz_geometric_modelling_2024, 
author={Schladitz, K.,Jung, C.,Flenner, S.,Godehardt, M.,Grevelhörster, B.,Greving, I.,Klein, P.,Konchakova, N.,Redenbach, C.,Visser, P.,Zaninović, J.},
title={Geometric modelling of corrosion inhibitor pigments in active protective coatings based on SR-nano-CT images},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.porgcoat.2024.108762},
abstract = {This paper reports on an essential step towards accelerating the development of new, environmentally friendly active protective coatings by structure optimization. The complex microstructure of the pigment particles within a coating have been observed non-destructively in 3D by nano-computed tomography using synchrotron radiation. For the first time, a stochastic geometry model is fitted based on spatial geometric features of the particles observed in the 3D images. The typical cell of a random Gibbs-Laguerre tessellation is used to model the particles' polyhedral shapes as well as the observed joint size and aspect ratio distributions.},
note = {Online available at: \url{https://doi.org/10.1016/j.porgcoat.2024.108762} (DOI). Schladitz, K.; Jung, C.; Flenner, S.; Godehardt, M.; Grevelhörster, B.; Greving, I.; Klein, P.; Konchakova, N.; Redenbach, C.; Visser, P.; Zaninović, J.: Geometric modelling of corrosion inhibitor pigments in active protective coatings based on SR-nano-CT images. Progress in Organic Coatings. 2024. vol. 197, 108762. DOI: 10.1016/j.porgcoat.2024.108762}}