The Relation Between Ejection Mechanism and Ion Abundance in the Electric Double Layer of Drops
Bibliographic record
Abstract
Charged droplets have been associated with distinct chemical reactivity. It is assumed that the composition of the surface layer plays a critical role in enhancing the reaction rates in the droplets relative to their bulk counterparts. We use atomistic modeling to relate the localization of the ions in the surface layer to their ejection propensity. We find thatthe ion ejection takes place via a two-stage process. Firstly, a conical protrusion emerges as a result of a global droplet deformation that is insensitive to the locations of single ions. The ions are subsequently ejected as they enter the conical regions. The study provides mechanistic insight into the ion-evaporation mechanism, which can be used to revise the commonly used ion-evaporation models. We argue that atomistic molecular dynamics simulations of minute nano-drops, do not sufficiently distinguish the ion-evaporation mechanism from a Rayleigh fission. We explain mass spectrometry data on the charge state of small globular proteins and the existence of super-charged droplet states (above the Rayleigh limit) that have been detected in experiments.
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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) | 0.001 | 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".