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Substructure and Nanocrystalline Structure Effects in Thermomechanically Treated Ti-Ni Alloys

2006· article· en· W2075994322 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials science forum · 2006
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsÉcole de Technologie Supérieure
FundersMinistry of Education and Science of the Russian FederationLady Tata Memorial Trust
KeywordsSubstructureMaterials scienceNanocrystalline materialAusteniteMetallurgyAnnealing (glass)Differential scanning calorimetryTransmission electron microscopyAlloyAtmospheric temperature rangeThermomechanical processingDislocationDeformation (meteorology)Composite materialCrystallographyMicrostructureThermodynamicsStructural engineeringNanotechnology

Abstract

fetched live from OpenAlex

Substructure and structure formation as well as functional properties of thermomechanically treated Ti-Ni wire have been studied using differential scanning calorimetry, X-ray diffraction, transmission electron microscopy and mechanical. The low- temperature themomechanical treatment (LTMT) was carried out by rolling at room temperature in a true strain range e = 0.3 to 1.9. It was shown that severe plastic deformation (e=1.9) of Ti-50.0at.%Ni alloy results in partial amorphization and formation of nanocrystalline austenite structure during post-deformation annealings up to 400 °C. As a result, the fully recoverable strain and recovery stress become much higher than the values reachable after traditional LTMT (e=0.3 to 0.88) with post-deformation annealing which creates a poligonized dislocation substructure.

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.

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 score0.037
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.210
Teacher spread0.206 · 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