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Record W4312445286 · doi:10.31399/asm.cp.itsc2009p1128

MMCs Coatings with High SiC Volume Fraction Retention by Pulsed-Gas Dynamic Spraying

2009· article· en· W4312445286 on OpenAlexaff
M. Yandouzi, P. Richer, B. Jodoin

Bibliographic record

VenueThermal spray · 2009
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceVolume fractionCoatingPorosityAluminiumComposite materialComposite numberRaw materialIndentation hardnessMass fractionMetallurgyMicrostructure

Abstract

fetched live from OpenAlex

Abstract Aluminum-based composite coatings reinforced with different volume fractions of SiC particles were deposited on aluminum substrates by means of pulsed gas dynamic spraying using a mechanically mixed composite feedstock powder. Microstructural features of the coatings are examined and their hardness is reported. The results show that the high fraction of SiC particles in the feedstock powder are retained in the coatings and that increasing SiC content in the aluminum matrix significantly improves coating hardness. The highest hardness value was obtained for a coating with 28 vol% SiC. Beyond that, coating hardness decreased, which is attributed to increasing porosity and decreasing cohesion between deposited aluminum-based particles.

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 score0.343
Threshold uncertainty score0.864

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)0.0000.000

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 head0.005
GPT teacher head0.177
Teacher spread0.173 · 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
Published2009
Admission routes1
Has abstractyes

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