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Crystallographic Relationships between FCC and BCC Crystals: A Study Using EBSD Techniques

2005· article· en· W1986876013 on OpenAlexaff
You Liang He, Stéphane Godet, Pascal Jacques, John J. Jonas

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2005
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectron backscatter diffractionAusteniteMaterials scienceFerrite (magnet)CrystallographyBainiteMeteoriteDiffractionTransformation (genetics)Shear matrixMetallurgyMicrostructureOpticsComposite materialChemistryAmorphous metalPhysics

Abstract

fetched live from OpenAlex

The mechanisms governing the formation of transformation textures during the austenite-to-ferrite transformation are the subject of major debate. In this study, two extreme cases were examined: those of undeformed and deformed austenite. The first involves the transformation of austenite into Widmanstätten ferrite under "equilibrium" conditions in the Gibeon iron-nickel meteorite. This meteorite passed through the transformation at the rate of a few degrees per million years. Such cooling rates cannot of course be reached under laboratory conditions. The second concerns the transformation of hot rolled austenite after a quench into the bainite temperature range. These two behaviors were investigated by means of optical microscopy and electron backscatter diffraction (EBSD) techniques. The orientations of both the parent and product phases were measured and the orientation relationships are represented in Rodrigues-Frank (R-F) space. From the orientation of a particular FCC crystal, the crystallographic orientations of the product BCC crystals can be predicted according to the Bain, Kurdjumov-Sachs (K-S) and Nishiyama- Wassermann (N-W) correspondence relationships. Comparison of the predicted and measured orientations reveals that the Bain rotation is never observed; the K-S and N-W relationships are both observed and there is a continuous distribution of orientations between the exact K-S and N-W positions. The formation of preferred orientations under non-equilibrium conditions is scrutinized. These results are compared to recent models accounting for variant selection.

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)0.001
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.300
Teacher spread0.232 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicMicrostructure and Mechanical Properties of SteelsFrench-language works237,207