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Record W4389109629 · doi:10.1149/1945-7111/ad1067

A Mathematical Model for the Membrane Electrode Assembly of a Bicarbonate Electrolyzer

2023· article· en· W4389109629 on OpenAlexaff
Datong Song, Qianpu Wang, Parisa Karimi Amirkiasar, Darren Jang

Bibliographic record

VenueJournal of The Electrochemical Society · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsElectrolysisCathodeAnodeElectrolyteBicarbonateChemistryElectrolysis of waterFaraday efficiencyChemical engineeringMembraneElectrodeConcentration polarizationInorganic chemistryPolarization (electrochemistry)Analytical Chemistry (journal)ChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Bicarbonate electrolyzers are devices designed to convert CO2 released in situ from bicarbonate ions into chemicals and fuels without an external source of CO2 gas. A one-dimensional steady-state isothermal model is developed for the membrane electrode assembly of a bicarbonate CO2 electrolyzer with a bipolar membrane design. The model incorporates species transport in both the anode and cathode electrodes due to convection, diffusion, and migration, and accounts for the catalyzed water splitting reaction at the interface of the anion exchange layer and the cation exchange layer of the bipolar membrane. A direct comparison of model simulations with available experimental data shows that the model can accurately simulate measured Faradaic efficiency and CO yield for all operating current densities. The model can also accurately simulate most of the polarization curve, with the only limitation being in the range dominated by mass transport. Compared to the other parameters studied in this paper, numerical results show that the performance of the bicarbonate CO2 electrolyzer is more sensitive to both aqueous electrolyte saturation in the cathode catalyst layer and the catalyzed water splitting efficiency of the bipolar membrane.

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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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