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Thermal Stability and Nanocrystallization of Amorphous Ti-Ni Alloys Prepared by Cold Rolling and Post-Deformation Annealing

2007· article· en· W1972616333 on OpenAlexaff
Vladimir Braïlovski, С. Д. Прокошкин, Elena Bastarash, Vincent Demers, К. Inaekyan, I. Yu. Khmelevskaya

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceAnnealing (glass)SubstructureVolume fractionMetallurgyAmorphous solidWork hardeningAlloyAmorphous metalDiffusionless transformationThermal stabilityComposite materialThermomechanical processingMartensiteMicrostructureCrystallography

Abstract

fetched live from OpenAlex

The thermomechanical processing consisting in severe cold rolling (true strain 0.7–1.9) followed by a post-deformation annealing (200-700oC) is applied to Ti-50.0 and 50.7at%Ni alloys. The thermal stability of the amorphous phase as well as the influence of post-deformation annealing on the structure, substructure and temperature range of martensitic transformations are studied using TEM and DSC techniques. For a given level of cold work, the equiatomic alloy has a higher volume fraction of amorphous phase than the nickel-rich one. For both alloys, the higher the volume fraction of the amorphous phase, the higher the thermal stability. For a given post-deformation annealing temperature, the DSC martensitic transformation peaks from the material subjected to amorphization cold work are sharper and the hysteresis between the direct and reverse transformations is narrower than those for a material subjected to strain hardening cold work. This observation confirms the absence of the well-developed dislocation substructure in the severely deformed alloy subjected to nanocrystallization heat treatment, which is consistent with TEM results.

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 score0.009
Threshold uncertainty score0.476

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 communication0.0000.001
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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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