Apparent molar volumes of methanol, ethanol, and 2-propanol in dense phase CO2
Bibliographic record
Abstract
Despite the increasing importance of CO 2 processing and the use of aliphatic alcohols as cosolvents in supercritical fluid extraction, there is an apparent lack of densimetric or volumetric data for dilute alcohols in near-critical CO 2 within the literature. To this end, apparent molar volumes of binary solutions for methanol, ethanol, and 2-propanol in CO 2 were calculated from measured density differences ( δΔρ = 0.01–1.60 kg m −3 ) determined from T = 298–313 K and p = 8–13 MPa using a flow densimeter modified for high pressure measurement. This temperature and pressure range was chosen for the proximity to the critical point of pure CO 2 , where volumetric changes are very sensitive and allow for better calibration of binary parameters. The apparent molar volumes of the mixtures were then used to optimize mixing coefficients with reference quality pure component Helmholtz equations-of-state and Fluctuation Solution Theory. Apparent molar volumes of these alcohol solutes resulted in poorer fits of the binary mixing coefficients for reference quality reduced Helmholtz Equations of State when compared to Fluctuation Solution Theory; however, excess functions with more parameters may be developed by future researchers. With the Fluctuation Solution Theory equations, Krichevskii parameters were determined for each alcohol in CO 2 . These values were similar to a previous study of H 2 O in CO 2 ; however, variance was noted from literature values with different methods of extrapolation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".