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Record W2020474023 · doi:10.1149/1.1509068

CO[sub 2] Corrosion of Bare Steel under an Aqueous Boundary Layer with Oxygen

2002· article· en· W2020474023 on OpenAlexafffund
F.M. Song, Donald W. Kirk, J. W. Graydon, D. E. Cormack

Bibliographic record

VenueJournal of The Electrochemical Society · 2002
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsCorrosionOxygenCarbon dioxideCarbon steelPartial pressureMaterials scienceDiffusionAnaerobic corrosionElectrochemistryCarbon fibersChemistryInorganic chemistryMetallurgyComposite materialElectrodeThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

The effect of dissolved carbon dioxide on steel corrosion in aerated solutions has been variously reported, ranging from "no effect" to "catalytic enhancement of corrosion." A corrosion model was developed, verified with published experimental data, and then used to interpret the role of carbon dioxide in the presence of oxygen. Carbon dioxide has little effect on the corrosion rate when its pressure is less than the oxygen pressure. The model reveals that the effect becomes significant only when the carbon dioxide pressure is substantially higher than the oxygen pressure. The results also show that for a thick boundary layer, carbon dioxide hydration controls the corrosion rate at low oxygen pressures. As oxygen pressure is increased, oxygen dominates corrosion with oxygen diffusion contributing to and then controlling the corrosion rate. For a thin boundary layer, charge transfer of oxygen reduction controls the corrosion rate. © 2002 The Electrochemical Society. All rights reserved.

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 score0.004
Threshold uncertainty score0.493

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

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