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Record W2354533270

Microstructure and properties of sub-nano ultra-fine beinite steel

2012· article· en· W2354533270 on OpenAlexaff
Xiang Wang

Bibliographic record

VenueCailiao rechuli xuebao · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBainiteMaterials scienceMicrostructureIsothermal transformation diagramIsothermal processMetallurgyUltimate tensile strengthContinuous cooling transformationMartensiteTRIP steelElongationComposite materialThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

In order to shorten transformation time of bainite and reduce the production cost,a new bainite steel was designed and refined.The CCT diagram of the tested steel was obtained by combining the thermal expansion curves measured on a Gleebe-1500 hot simulator and microstructure observation of the steel after simulation tests.According to the CCT diagram,isothermal heat treatment tests were carried out at a low bainite transformation temperature and tensile tests were performed to examine the mechanical properties.The results show that the tested steel is ultra-fine beinite steel consisting of sub-nano scale bainite and martensite.The ultimate strength of 1470 MPa and the total elongation of 15% are obtained for the steel after isothermal treatment at 340 ℃ for 2 h.It is found that the advanced beinitic steel with a good combination of strength and plasticity can be produced by normal heat treatment route and low-cost chemical composition design.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 head0.015
GPT teacher head0.191
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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