The variation of surface propensity of halides with droplet size and temperature
Bibliographic record
Abstract
Relative to a planar interface, nanodroplets are characterized by substantial mass density gradients between the interior and the surface regions and different forces when a sole ion is embedded within them. The radial number density of halide and alkali ions in aqueous clusters with equimolar radius up to approximately 1.4 nm, that corresponds to approximately 250 water molecules, has been extensively studied. However, the abundance of Cl-, Br- and I- on the surface relative to the bulk interior in these smaller clusters may not be representative of the larger systems. Indeed, here we show that the small droplet sizes with equimolar radius up to approximately 1.4 nm are significantly different in their structure and mass density and thus, in the relative surface abundance of halides from their larger counterparts composed of > 800 water molecules (equimolar radius > 1.75 nm). Starting from equimolar radius approximately 1.75 nm converging values in the ion location are observed. The chloride number density profile is the most sensitive to the droplet size and temperature and of the iodide least. The observed trend is that the larger the droplet is, the lower the relative surface abundance of chaotropic halides is. At elevated temperatures Cl- loses gradually its surface propensity, while I- still preserves it. The relative interfacial free energy of solvation of the ions is in the range of a few kJ/mol.
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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 | 0.000 | 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) | 0.002 | 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".