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Static recrystallization of pure titanium after cryo-deformation

2019· article· en· W2967881344 on OpenAlexaff
C. K. Yan, Guorong Cui, Shoujiang Qu, Aihan Feng, Jun Shen, D.L. Chen

Bibliographic record

VenueJournal of Physics Conference Series · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsToronto Metropolitan University
FundersNational Science Foundation
KeywordsMaterials scienceAlgorithmComputer science

Abstract

fetched live from OpenAlex

Abstract Commercially-pure (CP) titanium was first processed via cryogenic deformation to activate high-density deformation twins, and was subsequently annealed at 500°C to induce static recrystallization (SRX). Two types of twins were mainly activated during cryogenic deformation, i.e. , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>11</mml:mn> <mml:mover accent="true"> <mml:mn>2</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> contraction twins and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>10</mml:mn> <mml:mover accent="true"> <mml:mn>1</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> extension twins. Multiple point-like twins were also present because the growth of twins was remarkably impeded at the low temperature. During annealing the recrystallization mechanisms were identified to be <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>11</mml:mn> <mml:mover accent="true"> <mml:mn>2</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>10</mml:mn> <mml:mover accent="true"> <mml:mn>1</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> twinning induced SRX. The point-like twins could effectively promote the occurrence of SRX. The grains were significantly refined from ∼40 to ∼2.7 μm while a few <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>11</mml:mn> <mml:mover accent="true"> <mml:mn>2</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block" overflow="scroll"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>10</mml:mn> <mml:mover accent="true"> <mml:mn>1</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> TBs still retained with the same twinning angle/axis relationship during annealing.

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)0.000
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 score0.022
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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