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Record W4412101389 · doi:10.18280/rcma.350311

Characterization of Y2O3 and/or SiC Reinforced Al on Tribological Behaviour

2025· article· fr· W4412101389 on OpenAlexvenueno aff
Manar Assaf Al-Kinani, Saad Hameed Al-Shafaie

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2025
Typearticle
Languagefr
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTribologyCharacterization (materials science)Materials scienceComposite materialMetallurgyForensic engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

This study acknowledges the use of ceramics, such as SiC and/or Y2O3, in the stir casting technique for the producing AMMCs.Hardness, coefficient of friction and wear behavior of the prepared MMCs were evaluated.The results of the testing showed that the unreinforced matrix was not as hard as the reinforced matrix (16%).Wear resistance raised steadily due to the SiC and Y2O3 particle loading, both alone and in combination.Using Optical and scanning electron microscopes (SEM) to examine the microstructure and worn surface, it was discovered that mechanically mixed layers of SiC and Y2O3 had formed.These layers acted as an effective insulating surface, preventing the test sample surface from contacting the zirconia pins.weight loss decreased when the reinforcing materials were changed, and at 5% SiC, notable wear resistance was attained.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.036
GPT teacher head0.281
Teacher spread0.246 · 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.

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
Published2025
Admission routes1
Has abstractyes

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