Extraction of Aluminium from Kaolin: a Comparative Study of Hydrometallurgical Processes
Bibliographic record
Abstract
The increase of aluminium demand globally, raises the interest of developing alternative technologies to produce alumina from non-bauxitic sources, especially clays. This paper studies the extraction of aluminium from kaolin through leaching process, using aqueous solutions of acids and bases, as leaching agents. For this study, crude kaolin excavated in Milos Island, Greece, was used. Before leaching, crude kaolin was calcined; calcination achieves the dehydroxylation of kaolinite, which is the main mineralogical phase of kaolin and its transformation to metakaolin, an amorphous Al-Si phase from which aluminium is easily leached. Calcination of the crude kaolin used in this work was taken place at 850 o C for 2 h, given that these conditions revealed as optimum in the relevant experimental investigation. Leaching of aluminium from the calcined kaolin was performed with aqueous solutions of mineral acids (HCl, HNO 3 and H 2 SO 4 ), organic acids (C 2 H 2 O 4 , C 2 H 4 O 2 and C 6 H 8 O 7 ) and bases (NaOH, KOH and NH 4 OH). All leaching experiments were performed under constant conditions, regardless the leaching agent used. According to the experimental results, acids were proved more effective in aluminium extraction, than bases. However, aluminum extraction was accompanied by simultaneous extraction of Si which comprises an important impurity for the production of alumina from the pregnant liquor. Based on this consideration, oxalic acid was revealed as the most effective leaching agent, yielding more than 75% extraction of Al and less than 5% Si extraction.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".