Molecular Characterization of the Surface Excess Charge Layer in Droplets
Bibliographic record
Abstract
Charged droplets play a central role in native mass spectrometry, atmospheric aerosols and in serving as micro-reactors for accelerating chemical reactions. The surface excess charge layer in droplets has often been associated with distinct chemistry. Using molecular simulations we have found that this layer is ≈ 1.5−1.7 nm thick and depending on the droplet size it includes 33%-55% of the total number of ions. Here, we examine the effect of droplet size and sign of ions in the structure of the surface excess charge layer by using molecular dynamics. We find that the thickness of the surface excess charge layer is invariant not only with respect to droplet size but also with respect to the nature of the ions and it is not sensitive to fine details of different force fields used in our simulations. We also find that differences in the average water dipole orientation in the presence of positive and negative ions in this layer are reflected in the charge distributions. Within the surface charge layer, the number of hydrogen bonds reduces gradually relative to the droplet interior where the number of hydrogen bonds is on the average 2.9 for droplets of diameter <4 nm and 3.5 for larger droplets. The decrease in the number of hydrogen bonds from the interior to the surface is less pronounced in larger droplets. In droplets with diameter <4 nm and high concentration of ions the charge of the ions is not compensated only by the solvent polarization charge but by the total charge that also includes the other free charge. This finding shows exceptions to the commonly made assumption that the solvent “neutralizes” the charge of the ions in solvents with very high dielectric constant. The simulation findings provide molecular insight into the bi-layer droplet structure assumed in the equilibrium partitioning model of C. Enke.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".