Molecular Simulation Methods of Evaporating Electrosprayed Droplets
Bibliographic record
Abstract
Molecular simulations provide significant insights into the relationship between the release of a macromolecule from charged droplets and its charge state. These simulations also help determine the possible location of the charge in macroions detected by mass spectrometry. However, several significant challenges must be considered in the modeling process. These challenges include the effect of the droplet-size-dependent chemistry on the charge state of a macroion, limitations in force fields, efficient droplet evaporation at any temperature, and effective treatment of electrostatic interactions. Here, we present a robust methodology for molecular simulations that enables the study of the chemistry and interactions of macromolecules within a droplet, and the relationship between the dynamics of the process of interest and the solvent evaporation rate. The competition of these dynamic processes will determine the mass spectrum. The success of the approach depends on the accurate and effective treatment of electostatic interactions in combination with the efficient use of spherical boundary conditions. Multilevel summation method (MSM) has been developed [Hardy et al. ``Multilevel summation method for electrostatic force evaluation'' J. Chem. Theory Comput. {\bf 11}, 766 (2015)] for the efficient treatment of electrostatics in non-periodic and semi-periodic systems, charged and neutral. We present comparison of MSM with particle-mesh Ewald (PME) method in order to show MSM's ability to study conformational changes of macromolecules in droplets. We find that MSM produces the same conformations of macromolecules (within one standard deviation) as PME. We demonstrate the capability of spherical boundary condition and MSM to study physical and chemical processes in droplets by using the example of the Rayleigh jet formation and charge emission from it. We conclude that robust approaches for droplet simulations that can be used with a force field of any complexity are available and can be implemented within many of the available open-source molecular modeling softwares. In the near future, the presented approach may provide reliable reference mass spectra for experiments, where the deviations from the experimental data may reveal valuable information about the processes that take place within the instrument.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".