2 citations · 2 across the 4 of their papers we have counts for
4 papers
Predicting air flow in calendered paper sheets from -CT data: combining physics with morphology
Phillip Gräfensteiner, Andoni Rodriguez, Peter Leitl +10
Predicting the macroscopic properties of thin fiber-based porous materials from their microscopic morphology remains challenging because of the structural heterogeneity of these ma…
Quantifying local heterogeneities in the 3D morphology of X-PVMPT battery electrodes based on FIB-SEM measurements
L. Dodell, M. Neumann, M. Osenberg +5
Organic electrode-active materials (OAMs) not only enable a variety of charge and storage mechanisms, but are also safer for the environment and of lower cost compared to materials…
Data-driven stochastic 3D modeling of the nanoporous binder-conductive additive phase in battery cathodes
Phillip Gräfensteiner, Markus Osenberg, André Hilger +5
A stochastic 3D modeling approach for the nanoporous binder-conductive additive phase in hierarchically structured cathodes of lithium-ion batteries is presented. The binder-conduc…
Stochastic 3D modeling of nanostructured NVP/C active material particles for sodium-ion batteries
Matthias Neumann, Tom Philipp, Marcel Häringer +3
A data-driven modeling approach is presented to quantify the influence of morphology on effective properties in nanostructured sodium vanadium phosphate $\mathrm{Na}_3\mathrm{V}_2(…