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Record W2392158882 · doi:10.5006/1982

Stability of Chromia (Cr2O3)-Based Scales Formed During Corrosion of Austenitic Fe-Cr-Ni Alloys in Flowing Oxygenated Supercritical Water

2016· article· en· W2392158882 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.

Bibliographic record

VenueCORROSION · 2016
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsCanadian Nuclear LaboratoriesHamilton Health SciencesUniversity of New BrunswickMcMaster University
Fundersnot available
KeywordsChromiaCorrosionAusteniteMaterials scienceSupercritical fluidMetallurgyIntergranular corrosionAustenitic stainless steelAlloyChemistryMicrostructure

Abstract

fetched live from OpenAlex

The comparative corrosion resistance of two high-chromium austenitic Fe-Cr-Ni alloys, namely Type 310S stainless steel (UNS S31008) and Alloy 33 (UNS R20033), was examined after exposure in supercritical water (25 MPa and 550°C), using a flow-loop autoclave testing facility operated at a flow rate of 200 mL/min. Electron microscopy techniques were used to determine links between the composition and structure of the Cr2O3-based oxide scale formed on both alloys and the difference in corrosion resistance observed. The weight change kinetics was distinctly different: progressively positive (weight gain) for Type 310S stainless steel and progressively negative (weight loss) for Alloy 33. The descaled weight loss was lower for Alloy 33, indicating improved corrosion resistance. This improved corrosion resistance was attributed to the improved stability of the Cr2O3-based scale that formed on Alloy 33 despite the negative weight change kinetics. The suitability of these alloys as candidate fuel cladding for the Generation IV supercritical water-cooled reactor concept is discussed in light of the findings presented.

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)0.000
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 score0.011
Threshold uncertainty score0.816

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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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