Evidence map›Paper›PMID 42188440›Full record

ArticleMembranes2026

Leveraging Electrical Network Models for Solving Fick's Second Law of Diffusion in Membrane Gas Permeation.

Zheng Cao, Boguslaw Kruczek, Jules Thibault

Abstract read
In one paragraph

Article in Membranes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zheng CaoDepartment of Chemical and Biological Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada.ORCID 0009-0001-2290-1913
Boguslaw KruczekDepartment of Chemical and Biological Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada.ORCID 0000-0001-8284-540X
Jules ThibaultDepartment of Chemical and Biological Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada.ORCID 0000-0001-6503-3688

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2021-04443 (BK) and RGPIN-2018-04433 (JT)
6 · The paper itself

Abstract

The permeation of gases through membranes is a fundamental process with wide-ranging applications, from gas separation and fuel cell technology to respiratory physiology. Governed by Fick's second law of diffusion, the mathematical modelling of such transport processes often becomes analytically and computationally challenging, especially in heterogeneous, mixed matrix, or multilayered systems. To navigate these complexities, this study revisits and expands upon the use of electrical analogies as an intuitive and powerful modelling approach rooted in mid-20th-century analog computing. By leveraging the mathematical equivalence between diffusion and electrical conduction, we construct an equivalent electrical network that mirrors the transient behaviour of gas permeation across membranes. In this framework, concentration gradients are represented as voltage differences, diffusive fluxes as electrical currents, and diffusional resistances as circuit resistances. While traditional applications of electrical analogies have largely focused on steady-state phenomena, our approach enables dynamic analysis, offering conceptual clarity and computational efficiency. This methodology not only simplifies the solution of Fick's second law but also reinforces the enduring relevance of analogical thinking in modern engineering practice. Comparative results demonstrate that the equivalent electrical circuit closely aligns with both analytical and finite difference solutions, validating its effectiveness and accuracy.

Indexed as

electrical analogyFick’s law of diffusionfinite differencesmembrane gas permeationMMMs

Identifiers

PMID42188440
PMCPMC13208332

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.