A Clean and Efficient Method for Recovery of Vanadium from Vanadium Slag: Nonsalt Roasting and Ammonium Carbonate Leaching Processes
Bibliographic record
Abstract
A cleaner method has been developed for the extraction of vanadium from vanadium slag. Compared to the traditional alkaline salts roasting followed by the water leaching process, in the nonsalt roasting process because no additives are added, the chromium spinel in the raw vanadium slag will not be converted to carcinogenic chromate salts and exhaust gas will not be produced. The ammonium metavanadate is precipitated from the water leach solution. The wastewater from the vanadate precipitation process can be recycled into the leaching process. The leaching residue can be comprehensively utilized in conjunction with an iron-making process using blast furnace. The nonsalt roasting mechanism was systematically investigated in a laboratory study. The XRD and morphology analysis of roasted vanadium slag showed that the oxidation of vanadium spinel occurred in the following steps: (1) the destruction of vanadium spinel and the formation of solid solution of Fe2O3·V2O3; (2) the oxidation of solid solution of Fe2O3·V2O3 to Fe2O3·V2O4 and a portion of the V(IV) in the Fe2O3·V2O4 was reacted with basic oxide such as MgO to generate the low-valence vanadate Mg2VO4; (3) the formation by further oxidation of highest-valence vanadates Mn2V2O7 and Mg2V2O7. The effects of particle size, oxygen concentration, gas flow rate, and temperature on vanadium recovery were investigated. Simultaneously, the effects of leaching variables, including ammonium carbonate concentration and temperature, were examined. The thermodynamics of the system are also reported.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".