Surface Tension of Two Near-Ideal Binary Liquid Mixtures and the Influence of Adjacent Vapors
Bibliographic record
Abstract
The measured surface tension of a binary liquid is found to depend strongly on the constituents of the adjacent vapor and on whether equilibrium has been achieved, giving insight into the complex interfacial configuration. This dependence is quantified by three techniques that offer complementary insights: surface tension measurements with a constrained sessile drop surrounded by different vapors, surface tension measurements by surface light scattering spectroscopy in a sealed cell at equilibrium, and molecular dynamics simulations of the equilibrium surface tension and excess surface concentration. Ensuring homogeneity of the binary liquid, which is essential for surface light scattering, was found to be nontrivial and was assured by high-sensitivity Schlieren imaging. Two pairs of liquids, n -pentane with 2-methylpentane and n -pentane with n -hexane, were investigated. The first pair was motivated by the observed improvement in the effectiveness of binary fluids versus a single constituent in wickless heat pipes studied in microgravity. The second pair was used for comparison. Experimental evaluation of different volume fractions of the two liquids showed strong dependence of surface tension on the relative concentration of different molecules near the interfacial region. For the above pairs of liquids, which appear to form ideal mixtures in bulk, we present sufficiently precise surface tension measurements to indicate unexpectedly complex behaviors at interfaces.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".