Extraction and separation studies of Ga(III), In(III) and Tl(III) using the neutral organophosphorous extractant, Cyanex-923
Bibliographic record
Abstract
The neutral extractant, Cyanes-923 has been used for the extraction and separation of gallium(III), indium(III) and thallium(III) from acidic solution. These metal ions were found to be quantitatively extracted with Cyanex-923 in toluene in the pH range 4.5?5.5, 5.0?6.5 and 1.5?3.0 respectively, and from the organic phase they can be stripped with 2.0 mol dm-3 HNO3, 3.0 mol dm-3 HNO3 and 3.0 mol dm-3 HCl, respectively. The effect of pH equilibration period, diluents, diverse ions and stripping agents on the extraction of Ga(III), In(III) and Tl(III) has been studied. The stroichiometry of the extracted species of these metal ions was determined on the basis of the slope analysis method. The reaction proceed by solvation and the probable extracted species found were [MCl3. 3Cyanex-923]?[where M = Ga(III) or In(III)]?and [HTlCl4. 3Cyanex-923]. Based on these results a sequential procedure for the separation of Ga(III), In(III) and Tl(III) from each other was developed.
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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".