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Record W2972978304 · doi:10.1115/1.4044530

Oxidation Behavior of Alumina-Forming Austenitic Steels in Superheated Steam at 700 °C

2019· article· en· W2972978304 on OpenAlexafffund
Bingjie Xiao, Nick Tepylo, Xiao Huang, Zhangjian Zhou, Sami Penttilä

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2019
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsCarleton University
FundersNatural Resources CanadaOffice of Energy Research and DevelopmentNatural Sciences and Engineering Research Council of CanadaAcademy of Finland
KeywordsMaterials scienceSpallationOxideAusteniteAlloyMetallurgySuperheated steamLayer (electronics)Internal oxidationSuperheatingComposite materialMicrostructureNeutron

Abstract

fetched live from OpenAlex

Abstract In this study, three alumina-forming austenitic (AFA) steels (Fe-18Ni-12Cr-AlNbC, Fe-18Ni-12Cr-Al, and Fe-18Ni-16Cr-AlNbC) were exposed to superheated steam (SHS) at 700 °C for 1000 h to study their oxidation behavior. The Fe-18Ni-16Cr-AlNbC alloy showed the best performance as it had the least weight gain due to a denser surface oxide layer and the lack of internal oxidation. The Fe-18Ni-12Cr-AlNbC alloy suffered from internal oxidation and had a greater weight gain than Fe-18Ni-16Cr-AlNbC, while Fe-18Ni-12Cr-Al experienced weight loss due to perhaps external oxide spallation, leaving a less protective Fe-oxide on the external surface.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.367

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 communication0.0000.001
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 head0.005
GPT teacher head0.212
Teacher spread0.206 · 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
Published2019
Admission routes2
Has abstractyes

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