Separation of vanadium(V) using N235 by three-phase system in concentrated HCl media
Bibliographic record
Abstract
The third phase formed in the process of extracting vanadium in a N235/HCl system was usually regarded as a limit to the throughput of the plant. To have a deep insight on this problem, the formation of the third phase in the extraction of vanadium by tertiary amine N235 in the concentrated HCl system was studied. The optimum parameters of three-phase system extraction were determined, and FTIR analysis was carried out to characterize the structure of extracted complexes and analyze the mechanism of formation and elimination of the third phase. The results showed that vanadium extraction efficiency was 86.5% with 20% v/v N235 and a phase ratio (O:A) of 1:2 in 2 min at 25 °C, though an obvious third phase was found within the experimental HCl concentration range. Cl− is the participant in the process of increasing the vanadium extraction efficiency, whereas H+ has an inhibitory effect on vanadium extraction. Meanwhile, the structure of the extracted complex was confirmed as (R3N)m(HCl)m+x·([Formula: see text])·(H2O)n through a solvation mechanism with molecular association, which was further proved by FTIR spectral analysis. Furthermore, the limited solubility of the ion-extracted complexes in the nonpolar solvent kerosene made the third-phase form. The third phase disappeared when phase modifier (about 5% v/v TBP) was added into the organic phase, as the polarity of the organic phase increased.
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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) | 0.000 | 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 | 0.001 |
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".