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Record W2000164062 · doi:10.1002/sia.2926

Determining the wettability of granular alumina by aluminum–magnesium alloys using the infiltration method

2008· article· en· W2000164062 on OpenAlexafffund
Duygu Kocaefe, Guvenc Ergin, Yaşar Kocaefe

Bibliographic record

VenueSurface and Interface Analysis · 2008
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaCentre québécois de recherche et de développement de l’aluminium
KeywordsWettingMagnesiumInfiltration (HVAC)Materials scienceAluminiumCapillary actionContact angleFiltration (mathematics)Composite materialMetallurgyMathematics

Abstract

fetched live from OpenAlex

Abstract Wettability of the granular bed media influences the efficiency of aluminum filtration. This project was undertaken to develop a method for determining the wettability of the granular media in order to evaluate its suitability for filtration. The wetting characteristics of different granular alumina particles by aluminum–magnesium alloys were studied using the infiltration method. The contact angles for rough as well as smooth surfaces were determined, and alumina particles were classified according to their wetting characteristics. The results were consistent and showed that it is possible to differentiate the wetting characteristics of different alumina samples with the infiltration method. A capillary model based on the energy balance was developed to analyze the experimental data. The model uses an average capillary pore size. For one type of alumina, this model was extended to carry out the analysis using a capillary pore size distribution. Similar results were found in both cases. This paper describes the experimental and modeling work, and the results are presented and discussed. Copyright © 2008 John Wiley & Sons, Ltd.

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)0.002
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 score0.073
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.034
GPT teacher head0.301
Teacher spread0.267 · 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

Citations6
Published2008
Admission routes2
Has abstractyes

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