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Record W2013289273 · doi:10.1016/j.pmatsci.2013.09.002

Dynamic and post-dynamic recrystallization under hot, cold and severe plastic deformation conditions

2013· article· en· W2013289273 on OpenAlexaff
Taku Sakai, Andrey Belyakov, Rustam Kaibyshev, Hiromi Miura, John J. Jonas

Bibliographic record

VenueProgress in Materials Science · 2013
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMcGill University
Fundersnot available
KeywordsDynamic recrystallizationMaterials scienceRecrystallization (geology)NucleationAnnealing (glass)MicrostructurePlasticityMetallurgyGrain boundaryComposite materialHot workingThermodynamicsGeology

Abstract

fetched live from OpenAlex

The evolution of the new microstructures produced by two types of dynamic recrystallization is reviewed, including those brought about by severe plastic deformation (SPD). The microstructural changes taking place under these conditions and the associated mechanical behaviors are described. During the conventional discontinuous dynamic recrystallization (dDRX) that takes place at elevated temperatures, the new grains evolve by nucleation and growth in materials with low to medium stacking fault energies (SFE). On the other hand, new ultrafine grains can be produced in any material irrespective of the SFE by means of SPD at relatively low temperatures. These result from the gradual transformation of the dislocation sub-boundaries produced at low strains into ultrafine grains with high angle boundaries at large strains. This process, termed in situ or continuous dynamic recrystallization (cDRX), is still not perfectly understood. This is because many SPD methods provide data concerning the microstructural changes that take place but little information regarding the flow stress behavior. By contrast, multi-directional forging (MDF) provides both types of data concurrently. Recent studies of the deformation behavior of metals and alloys under SPD conditions, carried out using MDF as well as other SPD methods, are synthesized and the links between the microstructural and mechanical observations are examined carefully. Some models for grain formation under SPD conditions are discussed. Next, the post-dynamic recrystallization behavior, i.e. that of annealing after both dDRX and cDRX, is described. The differing annealing behaviors result from the differences in the natures of the deformed microstructures. Finally, an integrated recrystallization model for these phenomena, i.e. dynamic and static recrystallization of both the continuous and discontinuous types, is presented and discussed.

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: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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
GenreReview

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

Citations2,698
Published2013
Admission routes1
Has abstractyes

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