Determining the wettability of granular alumina by aluminum–magnesium alloys using the infiltration method
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".