Key Factors Impacting the Decomposition Rate of REE Silicates During Sulfuric Acid Treatment
Bibliographic record
Abstract
The decomposition of silicates in sulfuric acid to extract rare earth elements (REE) is typically characterized by the formation of an amorphous silica layer surrounding the receding crystal that may act as a passivation barrier limiting the rate of mineral dissolution. In this context, sulfuric acid treatment experiments coupled with detailed characterization of the evolution of the decomposition reaction were performed on natural allanite (CaREEAl2Fe2+Si3O11O[OH]), as well as synthetic neodymium disilicate (Nd2Si2O7), orthosilicate (Ca2Nd8(SiO4)6O2), and orthophosphate (NdPO4) phases in order to investigate if there are key factors, operating on a wide range of silicates, that negatively impact REE recovery. While, as expected, the acid strength is the driver in promoting the decomposition of the orthophosphate, for the silicates investigated, no matter their crystalline structure and chemical resistance, there is a severe passivation mechanism at play in concentrated H2SO4. However, in all cases, this effect can be minimized by water dilution, which strongly enhances sulfate-forming cation transfer across the produced amorphous silica layer. Taking into consideration this distinct characteristic of the mode of decomposition of silicates in sulfuric acid should help in defining optimal extraction strategies.
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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 | 0.001 |
| 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".