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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.761
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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