Vapor–Liquid Equilibria and Diffusion Coefficients of Difluoromethane, 1,1,1,2-Tetrafluoroethane, and 2,3,3,3-Tetrafluoropropene in Low-Viscosity Ionic Liquids
Why this work is in the frame
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Bibliographic record
Abstract
The phase-down of hydrofluorocarbons (HFCs) established by the Kigali Amendment to the Montreal Protocol is leading to the formulation and commercialization of new refrigerant blends containing hydrofluoroolefins (HFOs), such as 2,3,3,3-tetrafluoropropene (R1234yf), and HFCs with moderate global warming potential, namely, difluoromethane (R32) and 1,1,1,2-tetrafluoroethane (R134a). Moreover, the recycling of refrigerants is attracting attention as a means to reduce the amount of new HFCs produced and their release to the environment. To that end, the use of ionic liquids has been proposed as entrainers to separate refrigerants with close-boiling points or azeotropic blends. Thus, the vapor–liquid equilibria and diffusion coefficients of the refrigerant–ionic liquid pairs formed by R32 + [C2mim][BF4], R134a + [C2mim][BF4], R134a+ [C2mim][OTf], R1234yf + [C2mim][OTf], and R1234yf + [C2mim][Tf2N] are studied using an isochoric saturation method at temperatures ranging from 283.15 to 323.15 K and pressures up to 0.9 MPa. In addition, the solubility behavior is successfully modeled using the nonrandom two-liquid activity-coefficient method, and the Henry’s law constants at infinite dilution, solvation energies, and infinite dilution activity coefficients are calculated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it