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Record W4377141655 · doi:10.1016/j.corsci.2023.111284

A mechanistic study on dealloying-induced stress corrosion cracking of Alloy 800 in boiling caustic solutions

2023· article· en· W4377141655 on OpenAlex
Hooman Gholamzadeh, Adil Shaik, Kevin Daub, Matthew Topping, Mark R. Daymond, S.Y. Persaud

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCorrosion Science · 2023
Typearticle
Languageen
FieldMaterials Science
TopicNanoporous metals and alloys
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity Network of Excellence in Nuclear EngineeringMcMaster University
KeywordsStress corrosion crackingMaterials scienceAlloyBoilingCorrosionMetallurgyCrackingCaustic (mathematics)PorosityCleavage (geology)Boiling water reactorComposite materialChemistryFracture (geology)

Abstract

fetched live from OpenAlex

Alloy 800 (Fe-30Ni-20Cr) is used in steam generators of some nuclear power plants . In-service performance has been excellent, but stress corrosion cracking (SCC) can occur in certain off-chemistry environments. In this study, the SCC mechanism for Alloy 800 in boiling caustic solution is investigated. After exposure, a Ni-rich porous surface film is formed with a large density of cracks. Complementary electron microscopy techniques are applied to study the SCC mechanism at the nanoscale from chemical and mechanical perspectives. Results suggest SCC initiation occurs by transmission of a micro-crack from the Ni-rich layer into the substrate material via a cleavage mechanism.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.046
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.076
GPT teacher head0.332
Teacher spread0.255 · 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