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 (SECL) in droplets has often been associated with distinct chemistry. Using molecular simulations for droplets with Na+ and Cl- ions 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 nature of ions in the structure of SECL by using molecular dynamics. We find that in the presence of simple ions 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 simple ions and it is not sensitive to fine details of different force fields used in our simulations. In the presence of macroions the SECL may extend to 2.0. nm. For the same droplet size, iodide and model H3O+ ions show considerably higher concentration than the sodium and chloride ions. In nano-drops, the SECL does not have the highest concentration of ions. We identify the maximum ion concentration region that may overlap with SECL in nano-drops. We also find that the differences in the average water dipole orientation in the presence of cations and anions 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 compensates the charge of the ions in solvents with very high dielectric constant. The study provides molecular insight into the bi-layer droplet structure assumed in the equilibrium partitioning model (EPM) of C. Enke and assesses critical assumptions of the Iribarne-Thomson model for the ion-evaporation mechanism. We suggest the extension of the bi-layer droplet structure in EPM to include the maximum ion concentration region that may not coincide with SECL in nanodrops. We compute the ion concentrations in SECL, which are those that should enter the kinetic equation in the ion-evaporation mechanism, instead of the overall drop ion concentration that has been used thus far.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".