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Record W3206453972 · doi:10.1016/j.jmrt.2021.10.021

A steel-like unalloyed multiphase ductile iron

2021· article· en· W3206453972 on OpenAlexaff
Wentao Zhou, Derek O. Northwood, Cheng Liu

Bibliographic record

VenueJournal of Materials Research and Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceUltimate tensile strengthBainiteAusteniteMetallurgyFerrite (magnet)AlloyToughnessDuctile ironQuenching (fluorescence)ElongationMartensiteDuctility (Earth science)Cast ironComposite materialMicrostructureCreep

Abstract

fetched live from OpenAlex

This work highlights a new process for direct manufacturing of ductile iron that is based on the innovative combined technology of quenching and partitioning, and low-temperature-transformation of nano bainite as used for high strength steels. In this process, a commercial unalloyed ductile iron is austenitized at 890 °C for 20 min, then rapidly quenched to 180 °C for 5 s, and finally partitioned at 220 °C for 240 min. A maximum tensile strength of more than 1600 MPa, a hardness of 55 HRC at an elongation in excess of 5%, and the number of repeat tensile fatigue failure of 2.5 × 104 cycles at a stress amplitude of 600 MPa, are achieved. This is comparable to those of a high strength carbon alloy steel. These properties are due to the synergistic strengthening and toughening effects of a multiphase structure comprising tempered martensite, bainitic ferrite and retained austenite in the matrix, and a spherical graphite morphology. This work provides a guidance on how to produce unique steel-like ductile iron with a high level of strength and acceptable toughness.

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 score0.033
Threshold uncertainty score0.315

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 head0.025
GPT teacher head0.281
Teacher spread0.256 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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