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Record W4405322374 · doi:10.1080/13873954.2024.2433502

Modeling electrolytic transport for systems with concentration gradients, Ohmic resistance and electrochemical reactions

2024· article· en· W4405322374 on OpenAlexaff
Glyn Kennell, Richard W. Evitts

Bibliographic record

VenueMathematical and Computer Modelling of Dynamical Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOhmic contactElectrolyteElectrochemistryMaterials scienceComputer scienceChemistryElectrodeNanotechnology

Abstract

fetched live from OpenAlex

This paper describes a two-dimensional multi-component electrolytic transport model that calculates the electric field by applying electroneutrality as an upper bound. This approach avoids directly enforcing electroneutrality in mass transport calculations or using Poisson’s equation. The two coupled equations of this model were numerically solved for cases with no convection. The transport equation was solved using a modified Control Volume method and a Peclet number. The electric field equation was discretized using the finite difference method and solved using the Alternating Direction Implicit method. The model’s results were compared with free-diffusion liquid junction data. Comparisons were also made with one-dimensional transport models. The model was then used to simulate two-dimensional scenarios without prescribed current distributions. The simulations agreed with the comparison data. Hence, the model shows promise in its ability to simulate two-dimensional multi-component electrolytic transport with concentration gradients, Ohmic resistance, and electrochemical reactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.178
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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