Comparative molecular characterization of aluminum hydroxy‐gels derived from chloride and sulphate salts
Bibliographic record
Abstract
Abstract Background Aluminum (III) hydroxy‐gels find important applications in areas such as paint pigments, pharmaceuticals and water treatment or toxic metal sequestration. Since the method of preparation may affect their properties and performance, in this work we prepare aluminum hydroxy‐gels from either chloride or sulphate salts and subject them to comparative characterization. Results Aluminum (III) hydroxy‐gels were produced by partial quick neutralization of 2 mol L−1 AlCl3 or Al(SO4)1.5 salt solutions with 5 N NaOH at room temperature. The gels were found, following ageing and water washing, to consist of 60–70 wt% Al(OH)3, 5–18 wt% Cl or SO4 and ∼20 wt% water. Both gel materials upon drying were seen to be highly porous formed from aggregates of very fine particles nucleated during the fast neutralization process. The Al(SO4)1.5‐derived gel was found to differ significantly from the AlCl3‐derived gel both in terms of surface area (38 m2 g−1 vs. 18 m2 g−1) and chemical features. The aluminum chloride gel material is probably composed of chains of aluminum octahedra (Aln(OH)2.5Cl0.5n(H2O)3n) while the aluminum sulphate gel of SO4‐stabilized Keggin Al13 structure: AlO4Al12(OH)24(SO4)3.5(H2O)12. Conclusion The distinct molecular structure of the aluminum sulphate‐derived gel may provide an effective matrix for hazardous metal containment. © 2013 Society of Chemical Industry
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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) | 0.001 | 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".