Application of Phosphonium Ionic Liquids as Ion Carriers in Polymer Inclusion Membranes (PIMs) for Separation of Cadmium(II) and Copper(II) from Aqueous Solutions
Bibliographic record
Abstract
Facilitated transport through polymer inclusion membranes (PIMs) is a promising method for simultaneous separation and removal of valuable and toxic metal ions from aqueous solutions. Recently, ionic liquids (ILs) have been used as extracting agents for metal ions due to their unique physicochemical properties. This paper presents research on the facilitated transport of cadmium(II) and copper(II) ions from aqueous chloride solutions through PIMs with phosphonium ILs as new selective ion carriers. Cellulose triacetate membranes containing o-nitrophenyl octyl ether (ONPOE) as a plasticizer and Cyphos IL 101 [trihexyl(tetradecyl)phosphonium chloride] or Cyphos IL 104 [trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate] as the ion carriers have been prepared and applied for investigations. Cd(II) ions were transported preferably from hydrochloric acid solutions containing Cu(II) ions through the PIMs. Higher selectivity coefficient of Cd(II) over Cu(II) (S Cd/Cu) from 0.1 mol·dm−3 hydrochloric acid was obtained for PIM with Cyphos IL 104 as the ion carrier. The influence of HCl and NaCl concentrations in the source phase on metal ion transport across PIM doped with Cyphos 104 was studied. It was found that the initial fluxes of Cd(II) and Cu(II) increase with increasing chloride ions concentration in the source phase. The selectivity coefficient for Cd(II) over Cu(II) decreases with increasing HCl concentration in the source phase. The results suggest that the separation system presented in this paper can be useful for the removal of Cd(II) from acidic chloride solutions in the presence of Cu(II).
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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) | 0.000 | 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".