Switchable Water: Microfluidic Investigation of Liquid–Liquid Phase Separation Mediated by Carbon Dioxide
Bibliographic record
Abstract
Increase in the ionic strength of water that is mediated by the reaction of carbon dioxide (CO2) with nitrogenous bases is a promising approach toward phase separation in mixtures of water with organic solvents and potentially water purification. Conventional macroscale studies of this complicated process are challenging, due to its occurrence via several consecutive and concurrent steps, mass transfer limitation, and lack of control over gas-liquid interfaces. We report a new microfluidic strategy for fundamental studies of liquid-liquid phase separation mediated by CO2 as well as screening of the efficiency of nitrogenous agents. A single set of microfluidic experiments provided qualitative and quantitative information on the kinetics and completeness of water-tetrahydrofuran phase separation, the minimum amount of CO2 required to complete phase separation, the total CO2 uptake, and the rate of CO2 consumption by the liquid mixture. The efficiency of tertiary diamines with different lengths of alkyl chain was examined in a time- and labor-efficient manner and characterized with the proposed efficiency parameter. A wealth of information obtained using the MF methodology can facilitate the development of new additives for switchable solvents in green chemistry applications.
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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".