Design and Synthesis of Thermoresponsive Ionic Liquid Polymer in Acetonitrile as a Reusable Extractant for Separation of Tocopherol Homologues
Bibliographic record
Abstract
We report the design and development of a series of novel ionic liquid polymers (PILs) which possess thermoresponsive properties in organic solvent. The PILs were synthesized via reversible addition–fragmentation chain transfer (RAFT) copolymerization of 1-vinyl-3-butylimidazolium bromide and N -isopropylacrylamide, followed by anion exchange of bromide to amino acid d -alanine. The PILs possessed 0.36–0.76 molar fraction of ionic liquid with number-average molecular weight of 2.70–8.17 kg/mol and polydispersity index ranging between 1.12 and 1.25. The copolymerizations followed first-order reaction kinetics, and they were well-controlled, as indicated by the linear increase of molecular weight with monomer conversion. The PILs were thermoresponsive in acetonitrile with upper critical solution temperatures (UCST) varying from 25.7 to 34.8 °C, owing to the introduction of anion of amino acid. The PILs could be completely precipitated out by lowering the solution temperature. The PIL/acetonitrile solutions were used as extract phase for separation of tocopherol homologues in hexane. The distribution coefficient of δ-tocopherol between the extract and raffinate phases ( D δ ) and the selectivity coefficient of δ-tocopherol to α-tocopherol ( S δ/α ) reached as high as 7.86 and 13.0, respectively, while D β&γ was 3.63 and S β&γ/α was 6.0. The mole ratio of α-tocopherol in the raffinate phase increased from 0.08 to 0.27 after one stage extraction. The PILs could be reused for multiple extraction cycles with negligible change in the tocopherol distribution and selectivity coefficients. The thermoresponsivity of the PILs is of great benefit by eliminating the normally required back extraction steps. This work demonstrates the potential of thermoresponsive polymers for use in high performance separation of natural products.
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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".