Effect of pore structure, randomness and size on effective mass diffusivity
Open accessAbstract
The effective mass diffusivity 〈 D m 〉 of large specific surface area catalytic porous coatings is analyzed using 2‐D network models of connecting arms and verified experimentally for a multiple pore length scale coating layer. The network model includes effects of variation in the lattice randomness (Voronoi tessellation in the form of Delaunay lattice triangulation), pore coordination number, pore size (Knudsen effect), and pore‐size distribution on the predicted 〈 D m 〉. The effect of pore poisoning, resulting in a pore blockage, is analyzed. Correlations for the porosity and pore‐blockage dependency of 〈 D m 〉, as well as relationships for the pore size (low‐dimensionality) and multiple pore length scale effects, are also discussed. An experiment performed on a catalytic converter washcoat segment (represented by three pore length scales) placed on an otherwise impermeable wall of an electrochemical sensor shows a good agreement with the predicted 〈 D m 〉 based on a multiple pore length scale medium with parallel diffusion paths.
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Detailed models of mass diffusion through solid porous media as well as experiments using regular solids like glass spheres, sands, foams or catalytic materials always indicate diffusion resistance factors less than 1.
“Detailed models of mass diffusion through solid porous media as well as experiments using regular solids like glass spheres, sands, foams or catalytic materials always indicate diffusion resistance factors less than 1 (Mezedur et al., 2002).”
From Frosting modeling on a cold flat plate: Comparison of the different assumptions and impacts on frost growth predictions (2016) · cites this paper as Mezedur et al., 2002
The Ordered and Random Network Models section normalizes effective diffusivity by bulk diffusivity, and the Conclusion (Table 1; page unavailable) reports lower predicted and measured diffusivities for a porous catalytic washcoat than for the open reference. The paper does not report experiments on glass spheres, sands, or foams, or establish that diffusion resistance factors are always less than 1 across such materials. (LLM, conf=0.85)
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Wen, D., Herrmann, A.-K., Borchardt, L., Simon, F., Liu, W., Kaskel, S., & Eychmüller, A. (2014) · Journal of the American Chemical Society · doi:10.1021/ja412062e · Cited by 146 · see citing works
Analysis of the frost growth on a flat plate by simple models of saturation and supersaturation
Lee, Y. B., & Ro, S. T. (2005) · Experimental Thermal and Fluid Science · doi:10.1016/j.expthermflusci.2004.11.001 · Cited by 100 · see citing works
Brèque, F., & Nemer, M. (2016) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2016.06.010 · Cited by 70 · see citing works
- Authors
- Mezedur, M. M., Kaviany, M., & Moore, W.
- Affiliations
- University of Michigan (US)
- Aptiv (United States) (US)
- Corresponding author
- Kaviany, Massoud
- ORCID
- Kaviany, Massoud
- Venue
- AIChE Journal
- Publisher
- Wiley
- Published
- 2002-01
- Volume
- 48
- Issue
- 1
- Pages
- 15-24
- ISSN
- 0001-1541 (ISSN-L)
- 1547-5905
- OpenAlex
- W1984758683
- Cited by
- 138
- References
- 0
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 6 · 2023: 5 · 2022: 6 · 2021: 7 · 2020: 6 · 2019: 6 · 2018: 7 · 2017: 7 · 2016: 10 · 2015: 10 · 2014: 7 · 2013: 4 · 2012: 8
- FWCI
- 3.29
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- AIChE Journal (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Computational Mechanics › Heat and Mass Transfer in Porous Media
- Physical Sciences › Chemistry › Spectroscopy › Adsorption, diffusion, and thermodynamic properties of materials
- Physical Sciences › Materials Science › Materials Chemistry › Catalytic Processes in Materials Science
- Keywords
- effective diffusion coefficient, pore structure, Voronoi tessellation, Delaunay triangulation, pore coordination number, Knudsen effect, pore size distribution, pore blocking, porosity, network models, electrochemical sensor
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