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Record W4318406320 · doi:10.1002/srin.202200810

Measurements by SKPFM and Finite‐Element Modeling of Hydrogen Atom Diffusion and Distribution in Ferrite and Bainite Contained in X80 Steel

2023· article· en· W4318406320 on OpenAlexafffund
Qing Hu, Y. Frank Cheng

Bibliographic record

Venuesteel research international · 2023
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBainiteFerrite (magnet)Atom probeMaterials scienceHydrogenMetallurgyDissolutionKelvin probe force microscopeCrystallographyAnalytical Chemistry (journal)MicrostructureComposite materialChemistryAusteniteNanotechnologyAtomic force microscopyPhysical chemistry

Abstract

fetched live from OpenAlex

Herein, the diffusion and distribution of hydrogen (H) atoms in ferrite and bainite contained in an X80 pipeline steel is studied by both scanning Kelvin probe force microscopy and finite‐element modeling. The effect of metallurgical microphases on H‐atom accumulation in the steel is analyzed. The results show that H‐charging elevates the electrochemical dissolution activity of both ferrite and bainite contained in the steel, as indicated by the increased Volta potential and thus the decreased work function. The H atoms tend to accumulate at ferrite, making the local H‐atom concentration much greater than the concentration at bainite. The results imply that, compared with bainite, ferrite is the location to accumulate more H atoms initiating hydrogen‐induced cracks once the local H‐atom concentration reaches a threshold value.

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)0.004
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 score0.749
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.107
GPT teacher head0.375
Teacher spread0.268 · 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

Citations11
Published2023
Admission routes2
Has abstractyes

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