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Record W2754692642 · doi:10.3390/met7090374

Investigation of the Frozen Bath Layer under Cold Anodes

2017· article· en· W2754692642 on OpenAlexafffund
Donald Picard, Jayson Tessier, Guillaume Gauvin, Donald Ziegler, Houshang Alamdari, Mario Fafard

Bibliographic record

VenueMetals · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicMolten salt chemistry and electrochemical processes
Canadian institutionsAlcoa (Canada)Université Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaAlcoa
KeywordsCryoliteAnodeMicrostructureScanning electron microscopeMaterials scienceLayer (electronics)MetallurgyAnalytical Chemistry (journal)Composite materialMineralogyChemical engineeringAluminiumChemistryElectrodeChromatography

Abstract

fetched live from OpenAlex

Hall-Héroult cell stability is highly affected by anode changing operations. Upon the insertion of a cold anode in the cell, a layer of molten cryolite freezes under the anode. The thickness, microstructure, and chemical composition of this layer vary as a function of time and its location in the cell. To better understand the evolution of the frozen layer, mandatory for the validation of numerical models, a measurement campaign was conducted on the anodes having a few hours of operation in the cell. The macrostructure of the selected frozen bath samples has been investigated using computed tomography while scanning electron microscope (SEM) has been used to qualify its microstructure. An energy-dispersive X-ray spectroscope (EDS) coupled to the SEM has revealed the chemical content. The results showed not only very different macrostructures between samples, but also significantly heterogeneous structure within the same sample. Nevertheless, for all samples, there is a clear distinction between the frozen cryolite and alumina/dusting phases, with the latter surrounding the cryolite matrix.

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 score0.006
Threshold uncertainty score0.242

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 head0.039
GPT teacher head0.259
Teacher spread0.219 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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