MétaCan
Menu
Back to cohort
Record W4310806129 · doi:10.18280/rcma.320502

Preparation of an Aluminum Titania /Mullite Composite from the Raw Materials Alumina, Titania and Silica Fume

2022· article· en· W4310806129 on OpenAlexvenueno aff
Al-Saudi Sarah Kareem Mohammed, Emese Kurovics, Jamal Eldin F. M. Ibrahim, Mohammed Tihtih, Andrea Simon, Róbert Géber

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2022
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsnot available
Fundersnot available
KeywordsCristobaliteMaterials scienceMulliteSilica fumeMicrostructureScanning electron microscopeTitanatePhase (matter)CeramicPorosityComposite numberChemical engineeringAmorphous solidComposite materialCompressive strengthChemistry

Abstract

fetched live from OpenAlex

The present work deals with the preparation of ceramic composites and the study of phase transformation. Three mixtures were prepared, the main mixture containing (80 wt%) alumina and (20 wt%) titania and the other two mixtures to which two amounts of silica fume were added at (5 and 10 wt%). The phase transformation was studied at two temperatures: 1200℃ and 1400℃. The X-ray diffraction results at 1200℃ show that the amorphous silica (silica fume) transformed into the crystalline phase cristobalite. At 1400℃, aluminum titanate formed by the reaction of alumina with titania, and mullite formed by the reaction of alumina with silica. The result of scanning electron microscopy shows that the addition of (5 wt%) silica leads to a microstructure with smaller grain size up to (500 nm), a lower porosity (20 vol%), a lower water absorption (7 wt%) and a thermal conductivity (1.514W/m.k).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.031
GPT teacher head0.291
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicAdvanced ceramic materials synthesisFrench-language works237,207