Large Bubbles Reduce the Surface Sorption Artifact of the Inert Gas Stripping Method
Bibliographic record
Abstract
Accurate Henry’s law constants between air and water ( H ) are crucial for understanding a chemical’s environmental behavior. During inert gas stripping (IGS) H is derived from the rate of a chemical’s disappearance from aqueous solution as a result of air bubbling through a water-filled column. While H of many semivolatile organic compounds has been measured by IGS, inconsistent results between different studies have been attributed to chemical adsorption to the bubble surface. This surface adsorption artifact is expected to increase with a chemical’s interface–air partition coefficient ( K IA ) and decreasing bubble size. Previous work with normal alkanols of variable chain length identified a K IA threshold of approximately 0.001 m, above which IGS is compromised by the surface sorption artifact. In this study, we repeated IGS measurements of H of normal alkanols at different temperatures of 298.15 K, 305.65 K, 323.15 K, and 343.15 K using a modified gas inlet mechanisms that results in the formation of large bubbles (diameter approximately 5.5 mm). The new H values agreed very well with those measured with a head space technique that is much less susceptible to surface adsorption. The method is judged suitable for measuring H of surface active chemicals with K IA values below 0.02 m .
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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 | 0.001 | 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".