Effect of Droplet Size and Counterions on the Spatial Distribution of Ions
Bibliographic record
Abstract
Charged droplets have become a new environment for accelerating chemical reactions by orders of magnitude relative to their bulk analogues. Nevertheless the reaction mechanisms still remain unknown. Here we investigate the ion spatial distributions and surface charge in aqueous droplets with diameters in the range of 5 nm to 16 nm with and without counterions using molecular dynamics. The charge carriers are Na, Cl, I, ions and model hydronium ions. We demonstrate the convergence of ion spatial distributions. Scaling of the ion distributions reveals underlying universal behavior. The convergence allows one to extrapolate the simulation results from nanoscopic dimensions to larger ones, which are still inaccessible to atomistic modeling. The surface excess charge and electric field are also computed. We find that the surface excess charge layer is approximately 1.5 nm-1.7 nm thick and that approximately 55%-33 % (from smaller to larger droplets) of the total number of ions reside in this layer. For the first time droplet sizes that are accessible to experimental scrutiny are modeled atomistically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".