Value adding to acid mine drainage: Synthesis of high purity alumina and recovery of gypsum
Bibliographic record
Abstract
With the depletion of natural resources, research into the recovery of valuable materials from various mine wastes is increasing. Reprocessing of mine waste provides an avenue to generate new revenue streams while alleviating pressure on storage requirements and reducing the environmental impact of the mining operation. The presented research demonstrates the recovery and synthesis high purity gypsum and high purity alumina (HPA) from acid mine drainage via lime precipitation, acid extraction and crystallisation. Acid mine drainage (pH 3.62) was neutralised using lime to two different pH targets of 6.5 and 8.5, the upper and lower limits of the ANZECC guidelines for agricultural and livestock water. The lime precipitation residue was washed using 20% hydrochloric acid (HCl), followed by water, to produce a gypsum product with a purity of 99.9 wt.%. Leachates produced from this stage were sparged with gaseous hydrogen chloride to precipitate aluminium chloride hexahydrate (ACH). To improve the purity of ACH the crystals were redissolved and recrystallised a further two times prior to thermal decomposition at 1200 o C to produce an α-alumina with a purity of 99.99 wt%.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
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".