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Record W4410883776 · doi:10.1016/j.matlet.2025.138857

Embrittlement of 1Cr-1/2Mo pressure vessel steel during long-term service

2025· article· en· W4410883776 on OpenAlex
Nitin Saini, Zhe Lyu, Leijun Li

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

VenueMaterials Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials sciencePressure vesselEmbrittlementTerm (time)MetallurgyReactor pressure vesselForensic engineeringComposite materialNuclear engineeringEngineering

Abstract

fetched live from OpenAlex

Assessing the mechanical properties of in-service pressure vessels is essential to ensure their safe and continued operation. 1Cr-1/2Mo steel samples are collected from pressure vessels with different years of service exposure. Sub-size flat tensile specimens are tested, and the results show that with an increasing service exposure time, samples exhibited an increased strength, but a decreased ductility compared to the original material. Precipitation of nanoscale carbides within the ferrite/bainite grains has contributed to strengthening the material while the decrease in ductility is believed to be caused by larger size discontinuous carbide particles on the grain boundaries.

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 score0.054
Threshold uncertainty score0.496

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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