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Record W3044964321 · doi:10.1002/maco.202011902

New insights into the stress corrosion cracking of carbon steel in ethanolic media

2020· article· en· W3044964321 on OpenAlexaff
Ali Riahi, Amir Forrozan Ebrahimy, V.S. Ramsundar, Andreas Korinek, Roger Newman

Bibliographic record

VenueMaterials and Corrosion · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceScanning electron microscopeTransgranular fractureIntergranular corrosionStress corrosion crackingMetallurgyCrackingCorrosionGrain boundaryFracture mechanicsHydrogen embrittlementComposite materialIntergranular fracture

Abstract

fetched live from OpenAlex

Abstract Potentiostatic slow strain rate testing was conducted on stress corrosion cracking (SCC) test specimens exposed to ethanolic environments prepared from pure dehydrated ethanol. The mechanism of SCC in such environments is not well‐understood. Cracks of various types—intergranular and transgranular open cracks, and sharp closed transgranular cracks—were found by altering several testing parameters. The presence of chloride was found to be essential for crack initiation. A scanning electron microscope examination indicated that an “anodic” cracking mechanism, not necessarily slip dissolution, was most likely operating at high elongations. Sharp, closed transgranular cracks, with a maximum depth of 4 µm, were detected at elongations below 3% in ethanol solutions containing 2.5‐mM LiCl. A focused ion beam was used to extract such a transgranular crack tip for analytical transmission electron microscopy using electron energy loss spectroscopy, which confirmed that the crack was in a ferrite grain. The sharp closed transgranular cracks seem to ally with the cracks observed in CO–CO 2 –H 2 O and anhydrous ammonia environments, which are proposed to grow by unique cleavage mechanisms. The possibility of embrittlement by carbon interstitials produced by ethanol electro‐oxidation within the crack 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 score0.007
Threshold uncertainty score0.521

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 head0.021
GPT teacher head0.242
Teacher spread0.222 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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