An Innovative Process for the Recovery of Consumed Acid in Rare-Earth Elements Leaching from Phosphogypsum
Bibliographic record
Abstract
Many technologies relied upon by modern society, such as portable electronics and renewable energy systems, require the use of rare-earth elements (REEs). The global demand for REEs is increasing rapidly, and new developments for their recovery from secondary sources have been sparked. Phosphogypsum (PG), the byproduct of phosphoric acid production, is considered a secondary source for REEs. This research builds upon previous studies investigating the hydrometallurgical recovery of REEs from PG via acid leaching. The current study put the emphasis on developing processes to recover consumed acid in the leaching process. Here we propose an innovative process that relies upon the addition of calcium sulfate anhydrite seeds to the leached solution. Anhydrite seeding results in the rejection of calcium sulfate from the leached solution and reduced calcium concentration. Because the REE leaching efficiency is controlled by the solubility limit of PG, which is correlated to the calcium concentration, the drop increases the potential of the solution to leach more REEs. Thus, the solution can be recycled and reused as the leachant in subsequent leaching steps. This novel process is a promising technique to recycle consumed acid, lowering the operating costs and improving the efficiency.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".