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Record W4410596990 · doi:10.5006/4723

Selective Oxidation of Fe-Cr-Mn Stainless Steel in Supercritical Water

2025· article· en· W4410596990 on OpenAlexaff
S. Mahboubi, Yinan Jiao, J.R. Kish

Bibliographic record

VenueCORROSION · 2025
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSupercritical fluidMetallurgyMaterials scienceManganeseCorrosionSupercritical water oxidationChemistry

Abstract

fetched live from OpenAlex

Oxidation of austenitic Fe-Cr-Mn stainless steel (Nitronic® 32) in supercritical water (25 MPa) was assessed to determine the (i) ability to form a ferrite surface layer from selective oxidation of Mn and (ii) protection provided by the oxide scale. X-ray diffraction and electron microscopy techniques revealed a layered oxide scale forms, complete with a ferrite surface layer within a zone depleted of alloying elements after 500 h at 550°C. While intact during immersion, the oxide spalled during cooling, indicating a sensitivity to thermal stresses. The suitability of Fe-Cr-Mn alloy fuel claddings for the supercritical water-cooled reactor concept is discussed.

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 score0.017
Threshold uncertainty score0.373

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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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