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Computational Characterization Techniques Applied to Pore Network Models by Using a Fast Percolation Algorithm

Abstract : Nitrogen Sorption, Mercury Porosimetry, and Nuclear Magnetic Resonance Cryoporometry are characterization techniques used to obtain qualitative and quantitative information about the textural properties of porous materials. The physical phenomena exploited in each technique are related to mechanical and thermodynamic equilibria and are conditioned by pore blocking. The latter phenomenon becomes relevant in highly disordered solids with a broad pore size distribution and a multilevel organization. The techniques listed above contain topological information in the shape of their characteristic curves. In this work, it is shown how a pore network model can be characterized numerically by using computationally efficient algorithms for each characterization technique. These algorithms combine equilibrium conditions and invasion percolation considerations. Such simulation tools form the basis for a more comprehensive treatment of experimental characteristic curves and the characterization of the properties of porous materials.
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https://hal-ifp.archives-ouvertes.fr/hal-03748568
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Submitted on : Tuesday, August 9, 2022 - 4:38:15 PM
Last modification on : Friday, August 12, 2022 - 3:49:40 AM

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G. Ledezma, J.J. Verstraete, L. Sorbier, D. Leinekugel-Le Cocq, E. Jolimaitre, et al.. Computational Characterization Techniques Applied to Pore Network Models by Using a Fast Percolation Algorithm. Chemical Engineering Science, Elsevier, 2022, 260, pp.117812. ⟨10.1016/j.ces.2022.117812⟩. ⟨hal-03748568⟩

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