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Record W4415965432 · doi:10.1021/acsomega.5c09258

3D Modeling Study of Bubble-Driven Flow and Its Interaction with Cell Operation

2025· article· en· W4415965432 on OpenAlexafffund
Samuel Théberge, Lukas Dion, László I. Kiss, Thomas Roger, Simon‐Olivier Tremblay, Sébastien Guérard, Jean‐François Bilodeau

Bibliographic record

VenueACS Omega · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicMolten salt chemistry and electrochemical processes
Canadian institutionsRio Tinto (Canada)Université du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaRio Tinto
KeywordsBubbleFlow (mathematics)AnodeCurrent (fluid)Transient (computer programming)Heat transferChannel (broadcasting)MagnetohydrodynamicsThermalCathode

Abstract

fetched live from OpenAlex

A detailed three-dimensional model of carbon dioxide generation and movement beneath the anode in an aluminum electrolysis cell has been developed. By incorporation of localized current density and multiple nucleation sites, the model captures the transient behavior of the anode-cathode distance (ACD) and the deformation of the bath-metal interface (BMI) caused by bubble dynamics. It also evaluates the pot's response in terms of turbulent kinetic energy, providing insights into alumina dissolution efficiency and heat transfer mechanisms. The model further investigates how the MHD-induced flow direction and evacuation channel geometries impact bubble behavior, voltage fluctuations, and thermal distribution. The results not only align with existing experimental data but also shed light on subtle interplays within the cell environment. Notably, the orientation of the MHD flow emerges as a decisive factor in the local bubble overvoltage and the heterogeneity of alumina mixing. This study provides industry with actionable insights into optimizing cell design parameters by taking into consideration the impact caused by their operational ACD range, the evacuation channel width, and the relative MHD flow direction.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.341

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2025
Admission routes2
Has abstractyes

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