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Record W4293054155 · doi:10.1002/srin.202200232

Microstructure and Mechanical Properties of a Novel Ultra‐High Strength Hot‐Stamped Steel with High Hardenability

2022· article· en· W4293054155 on OpenAlexaff
Weijian Chen, Xiaohong Chu, Feng Li, Jie Liu, Hongzhou Lu, Shuang Kuang, Yu Zou, Zhengzhi Zhao

Bibliographic record

Venuesteel research international · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceHardenabilityUltimate tensile strengthMicrostructureMetallurgyFerrite (magnet)MartensiteElongationIntergranular corrosionQuenching (fluorescence)CarbideComposite material

Abstract

fetched live from OpenAlex

Herein, it is shown that the hot‐stamped steel exhibits high hardenability with a critical cooling rate of about 0.7 °C s −1 due to its unique chemical composition. The microstructure of the annealed sheet consists of ferrite, spherical carbides, and intergranular martensite. Thereinto, the generation of intergranular martensite can eliminate the yield point elongation and reduce the ratio of yield strength to ultimate tensile strength. Furthermore, compared with commercial 30MnB5 steel, the experimental steel (40Mn2CrNbV) quenched sheet shows excellent mechanical properties: yield strength (YS) = 1361 MPa, ultimate tensile strength (UTS) = 2422 MPa, and total elongation (TE) = 6.1%. Additionally, it is found that the Cr 7 C 3 with a mean diameter of 240 ± 50 nm in the annealed quenching sheet can hinder dislocation movement to increase the yield strength. The coherent Nb‐rich (Nb, V)C precipitate (a mean diameter is <50 nm) in the cold‐rolled quenched sheet can improve the mechanical properties of the hot‐stamped steel.

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)0.001
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 score0.027
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.264
Teacher spread0.231 · 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
Published2022
Admission routes1
Has abstractyes

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