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Record W2098021773 · doi:10.1149/1.3482156

Electrolytic Production of Aluminum Using Mechanically Alloyed Cu–Al–Ni–Fe-Based Materials as Inert Anodes

2010· article· en· W2098021773 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of The Electrochemical Society · 2010
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsKingston Process Metallurgy (Canada)Institut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAlloyElectrolysisInertAnodeMetallurgyElectrolyteHomogeneity (statistics)AluminiumOxideElectrodeChemical engineeringChemistry

Abstract

fetched live from OpenAlex

materials with varying from 0 to 20 (wt %) were prepared by mechanical alloying. For , the as-milled was made of an α-phase, whereas was formed at . Upon consolidation, a small amount of κ Ni/Fe-rich Al phase with a B2 structure is formed for and 10, whereas no new phase is formed in the other compounds. Aluminum electrolysis tests conducted at an anode current density of for 20 h in a low temperature electrolyte showed that the electrode stability and aluminum purity are strongly dependent on the alloy composition. The lowest values of cell voltage (4.1 V) and Cu contamination (0.8 wt %) were obtained for . This relatively lower contamination is due to the formation of a dense and adherent oxide scale between the outermost oxide layer and the substrate. In comparison, a hot-rolled C63000 commercially available alloy with the same composition but lower chemical/microstructural homogeneity gave a higher Cu contamination level (1.4 wt %).

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)0.001
metaresearch head score (Gemma)0.001
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 score0.017
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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