Upscaling the Poisson-Nernst-Planck equations for ion transport in weakly heterogeneous charged porous media

被引:2
|
作者
Klika, Vaclav [1 ]
Gaffney, Eamonn A. [2 ]
机构
[1] Czech Tech Univ, Dept Math, FNSPE, Trojanova 13, Prague 12000, Czech Republic
[2] Univ Oxford, Math Inst, Wolfson Ctr Math Biol, Radcliffe Observ Quarter, Andrew Wiles Bldg,Woodstock Rd, Oxford OX2 6GG, England
关键词
Poisson-Nernst-Planck equations; Non -periodic homogenisation; Swelling pressure; SWELLING PRESSURE; HOMOGENIZATION; MODEL;
D O I
10.1016/j.aml.2022.108482
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The Poisson-Nernst-Planck (PNP) equations govern the continuum level descrip-tion of ions in electrolytes and especially the impact of charged surfaces. In numerous applications such surfaces are complex, varying on a small lengthscale compared to the overall scale of the system, often prohibiting the direct prediction of the osmotic swelling pressures induced by ion behaviours in Debye layers near surfaces. With periodicity, upscaling techniques can be readily used to determine the behaviour of the swelling pressure on large lengthscales without solving the PNP equations on the complex domain, though generalising to cases where the periodicity is only approximate is more challenging. Here, we generalise a method by Bruna and Chapman (2015) for upscaling a non-periodic diffusion equation to the PNP equations. After upscaling, we find a rational derivation of the swelling pressure closely resembling the classical, though phenomenological, use of Donnan membrane theory predictions for the swelling pressure in cartilage, together with a novel contribution driven by heterogeneous fixed (surface) charges. The resulting macroscale model is also shown to be thermodynamically consistent, though its comparison with a recent upscaled models for swelling pressure in cartilage mechanics emphasises the need to understand how macroscale models depend on differing upscaling techniques, especially in the absence of perfect periodicity.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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页数:8
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