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Record W2736632413 · doi:10.1021/acssuschemeng.7b00945

Characterization of Carbon Anode Protected by Low Boron Level: An Attempt To Understand Carbon–Boron Inhibitor Mechanism

2017· article· en· W2736632413 on OpenAlexafffund
Ramzi Ishak, Gaétan Laroche, Jean‐François Lamonier, Donald Ziegler, Houshang Alamdari

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversité LavalAlcoa (Canada)Natural Sciences and Engineering Research Council of Canada
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaAlcoa
KeywordsBoronAnodeCarbon fibersThermogravimetric analysisX-ray photoelectron spectroscopyMaterials scienceInorganic chemistrySecondary ion mass spectrometryRaman spectroscopyBoron oxideChemical engineeringChemistryOrganic chemistryIonElectrodeComposite numberPhysical chemistry

Abstract

fetched live from OpenAlex

Several chemical reactions occur during the electrolysis of alumina in the Hall–Héroult process resulting in a significant overconsumption of the carbon anode. Carbon oxidation with oxygen is one of these reactions. The inhibition of this reaction by the application of protective layers on the anode can be an effective technique to reduce carbon consumption. Boron impregnation was shown to suppress this reaction. In this study, very low boron content has been impregnated on the anode, and several characterization methods have been performed to understand the protection mechanism of such a low boron concentration during the oxidation reaction of anodes. An air reactivity test of boron-impregnated anodes has been performed at temperatures between 400 and 600 °C. The samples were characterized using XPS, Raman spectroscopy, XRD, XRF, porosimetry, and thermogravimetric analysis (TGA). TGA revealed that the total number of interactions between oxygen atoms and carbon active sites was reduced, decreasing the pre-exponential factor. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS) has been employed as a highly sensitive surface characterization method to identify chemical forms of boron on the anode. It has been confirmed that boron blocks active sites of carbon by creating boron–carbon bonds, thus reducing the interaction of carbon active sites with oxygen.

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 categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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.

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

Citations33
Published2017
Admission routes2
Has abstractyes

Explore more

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