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Record W2166372321 · doi:10.1051/esomat/200905011

Microhardness of binary near-equiatomic Ti-Ni alloys after severe cold rolling and post-deformation annealing

2009· article· en· W2166372321 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueESOMAT 2009 - 8th European Symposium on Martensitic Transformations · 2009
Typearticle
Languageen
FieldMaterials Science
TopicTitanium Alloys Microstructure and Properties
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnnealing (glass)Indentation hardnessMaterials scienceMetallurgyDeformation (meteorology)Binary numberAccumulative roll bondingComposite materialMicrostructureMathematics

Abstract

fetched live from OpenAlex

Comparative HV-microhardness and TEM studies of Ti-50.0at%Ni and 50.26at%Ni alloys subjected to cold-rolling (e=0.3, 1 and 1.72) and post-deformation annealing at 100-700C (1 hour) are presented. Based on the TEM-measured grain size data for Ti-50.0at%Ni alloy as a function of an annealing temperature (T PDA ) higher than 250 o C, it was possible to evaluate the grain size (d) of the near-equiatomic Ti-Ni alloys at T PDA <250 o C, using exponential extrapolation distribution of the d-T PDA data. It was shown that below a critical grain size (d c = 10 nm), the smaller the grain size (as a result of the decrease in annealing temperature), the lower the microhardness. This softening phenomena can be described, with good correlation between the approximation and experimental data, by the normal-abnormal Hall-Petch transition caused by the influence of the intercrystalline regions and by the melting temperature grain-size dependence.

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 categoriesMeta-epidemiology (narrow)
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 score0.255
Threshold uncertainty score1.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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