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Record W2468854705 · doi:10.31399/asm.cp.itsc2015p0015

Cold Spray and Reaction Sintering of Ti-TiAl3 Composite Coatings

2015· article· en· W2468854705 on OpenAlexaff
Volf Leshchynsky, Oleksandra Bielousova, Anatoli Papyrin

Bibliographic record

VenueThermal spray · 2015
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceComposite numberIntermetallicSinteringGas dynamic cold sprayIndentation hardnessDiffusion bondingComposite materialCoatingAluminiumTitaniumMetallurgyScanning electron microscopeTitanium powderMicrostructure

Abstract

fetched live from OpenAlex

Abstract Recently a Ti–TiAl3 metal–intermetallic laminate (MIL) composite attracts growing attention because they have potential application in honeycomb or sandwich components of airplanes and as biomaterial with good bio-compatibility. Of the available processing techniques, diffusion bonding of elemental titanium and aluminum foils is an effective low-temperature method to synthesize the composite, allowing growth of the intermetallic layer. However, application of assembling and multi-pass cold rolling operations leads to fact that this technology is complex and expensive. The use of Cold Spray technology instead of aluminum foils utilization and multi-pass cold rolling to produce the Ti–TiAl3 MIL composites is believed to be more effective. However, reaction diffusion kinetics of Ti-Al particulate composite differs from that of classical MIL composite and needs to be studied. The task of this paper is to define microstructural changes of Tl-TiAl3 composite coating during cold spraying and reaction sintering. The optical microscopy, SEM, EDS, X-ray and microhardness examinations are 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 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 score0.012
Threshold uncertainty score0.345

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 communication0.0000.000
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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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