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Record W2507189418 · doi:10.1149/07537.0037ecst

Investigation of the Optimum Operative Conditions for a Parallel Plate Electrochemical Reactor

2017· article· en· W2507189418 on OpenAlexaff
Giuliana Litrico, Camila Braga Vieira, Ehsan Askari, Pierre Proulx

Bibliographic record

VenueECS Transactions · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSolverTurbulenceComputational fluid dynamicsElectrochemistryMechanicsFlexibility (engineering)ElectrodeDeposition (geology)Materials scienceCurrent densityCurrent (fluid)IonNuclear engineeringChemistryComputer sciencePhysicsThermodynamicsEngineeringMathematicsPhysical chemistry

Abstract

fetched live from OpenAlex

A new solver named POTisoFOAM is presented to predict and investigate the performance of electrochemical reactors. Its mathematicalmodel is developed and implemented through finite volume methodsand exploits the flexibility of the open source package OpenFOAM. The solver consists of two consecutive predictor-corrector loops. The first solves the pressure and velocity fields accounting for turbulence, while the second handles the ions transport and current conserva-tion. The equations' system is further complicated by means of thenon linear Buttler-Volmer boundary conditions. Despite the strong coupling between the charged ions and the electric potential, the reconstruction of the tertiary current density distribution is achieved. This study simulates the electrodeposition of copper, where changes in the electrodes geometry due to material deposition and corrosion are taken into account with the intent to predict the electrodes' replacements and the productivity of the reactor.

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 score0.452
Threshold uncertainty score0.338

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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