Comparison of Headspace and Gas-Stripping Techniques for Measuring the Air−Water Partititioning of Normal Alkanols (C4 to C10): Effect of Temperature, Chain Length, and Adsorption to the Water Surface
Bibliographic record
Abstract
The air−water partition coefficients of normal alkanols (C4 to C10) were determined as a function of temperature using both the phase ratio variation headspace (PRV−HS) method and the inert gas-stripping (IGS) method. Whereas the results of the PRV−HS experiments conducted at (50 to 90) °C were in good agreement with previous measurements for butan-1-ol, penta-1-ol, and heptan-1-ol, the values obtained from the IGS experiments performed at (25, 31, 51, and 69) °C were too high when compared to the PRV−HS results, literature values, and predictions based on vapor pressure and water solubility. For the short-chain alkanols and for the at higher temperatures, this discrepancy is likely due to evaporation from the stripping vessel. For the longer chain alkanols at lower temperatures, it is additionally due to adsorption to the air−water interface of the gas bubbles. The magnitude and dependence of the latter artifact on chain length and temperature is consistent with predictions based on interfacial adsorption coefficients ( K IA ) and bubble radius. The evaporation effect leads to an overestimation of the temperature dependence of air−water partitioning, whereas the surface adsorption effect can cause the opposite for substances with strong adsorption to the water surface. The validity of previously published air−water partitioning data that have been generated for substances with relatively high K IA (>10 mm) using the IGS method should be re-evaluated.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".