Stabilization of iron arsenate solids by encapsulation with aluminum hydroxyl gels
Bibliographic record
Abstract
Abstract BACKGROUND Ferric arsenate solids in the form of scorodite (FeAsO4·2H2O) particles are suitable carriers for immobilization of arsenic‐rich wastes. The stability of scorodite is, however, highly pH dependent (typically at 4≤ pH ≤7) and satisfactory only under oxic disposal conditions. In this work a new stabilization technology based on the concept of encapsulation with aluminum hydroxyl gels is investigated to enhance the stability of arsenical solids over a wider range of disposal conditions. RESULTS The encapsulation system investigated involves blending and short‐term ageing of synthetic scorodite particles with amorphous aluminum hydroxyl gels derived from partial hydrolysis of aluminum chloride or aluminum sulfate salts. Of the two gel types, the Al(SO4)1.5‐derived gel proved to be the most effective, even at the very low Al(III)/As(V) molar ratio of 0.1, apparently due to in situ development of protective aluminum hydroxide matrix and not as a simple adsorption sink for soluble arsenate species. CONCLUSION Arsenic release from the scorodite–aluminum hydroxyl gel composites was found to be drastically reduced with respect to gel‐free scorodite, making this system a very interesting candidate for further development as an effective hazardous material encapsulating material. © 2014 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) | 0.000 | 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".