.png){kind=icon}
Return
Computational characterization techniques applied to pore network models by using a fast percolation algorithm
.png){kind=icon}
OA
AI
DOI：10.1016/j.ces.2022.117812.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Nitrogen Sorption, Mercury Porosimetry, and Nuclear Magnetic Resonance Cryoporometry are character-ization 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 rele-vant 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 condi-tions and invasion percolation considerations. Such simulation tools form the basis for a more compre-hensive treatment of experimental characteristic curves and the characterization of the properties of porous materials.(c) 2022 Elsevier Ltd. All rights reserved.
Keywords:
Nitrogensorption
Mercuryporosimetry
Cryoporometry
Porenetworkmodels
Computationalcharacterization
Gammaaluminasupports
Digitaltwin
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.3
Papers:
2.3W
Citations:
5.5W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSave
View more