Hydrophilic solvent recovery from switched‐on microdroplet dissolution
Bibliographic record
Abstract
Abstract Switchable hydrophilicity solvents (SHSs) are a unique class of chemical compounds that can be switched between their hydrophobic and hydrophilic forms. The switchable characteristics allow SHSs to be used as emerging, green solvents for sustainable extraction and separation technology. In the production of polymeric microparticles from recycled plastics, SHSs are used to dissolve the polymer and then are switched to the hydrophilic form for separation from the generated polymeric microparticles. However, it is extremely difficult to fully recover the SHS residue from the mixtures. In this work, we will identify the key parameters that determine the level of the solvent residue during the switched‐on dissolution of emulsion microdroplets. The SHS N,N ‐dimethylcyclohexylamine from solvent–polymer binary emulsion droplets was switched to the hydrophilic, water‐soluble form, triggered by addition of an acid in the surrounding aqueous phase. By applying a sensitive detection method developed in this work, we compared the levels of SHS residue in polymer microparticles obtained under 30 different dynamical and chemical conditions for the switching processes. The quantitative analysis revealed that residue levels remained constant at varied addition rates and concentration of the trigger solution, but decreased with the increase in organic phase fractions or the decrease in the emulsion temperature. Trapped water in the drops during switched‐on dissolution may have contributed to the high level of solvent residue. The understanding of the new possible mechanism for residual solvent reported in this work may help develop effective approaches for the recovery of switchable solvents in environmentally friendly separation processes.
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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".