Stepwise recovery of metal element from blast-furnace magnesium slag by hydrometallurgy
Bibliographic record
Abstract
A route for selective recovery of magnesium (Mg), iron (Fe), and silicon (Si) from blast-furnace magnesium slag was studied in this paper. The experimental results demonstrated that under favourable conditions, such as sulfuric acid concentrations of 6% weight in weight (w/w), solid-liquid ratio (S/L) of 1:30, temperatures of 80°C, and a time of 30 min, the leaching rates of Mg, Si, and Fe can be reached up to 85.86%, 63.80%, and 17.04%, respectively. Flocculation desilication was used to remove Si up to 85.7% from the filtrate, and amorphous SiO2 was obtained with a purity of 95.8%. A significant level of effectiveness has been achieved in utilising ammonia neutralisation to eliminate iron (Fe) from the filtrate, with an impressive removal rate of 99.73%. Finally, a filtrate with a high concentration of magnesium (Mg) was obtained.
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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".