Molecular simulation methods of evaporating electrosprayed droplets
Bibliographic record
Abstract
A robust methodology for molecular simulations of evaporating droplets that enables comparison between the dynamics of the process of interest and the solvent evaporation rate has already been developed (Oh and Consta, 2017). The competition of these dynamics will determine the mass spectrum. However, the success of the approach depends on the accurate and effective treatment of electrostatic forces. Often, in droplet simulations, bulk solution parametrized force-fields are used where the Coulomb forces are directly taken into account with a cut-off distance longer than the droplet diameter. On the one hand this approach is inefficient for large droplets because the computational cost increases as the square of the number of the atomic sites, and on the other hand the force field is slightly different from that has been parametrized for the bulk solution. The effect of this new force field in the conformations of macromolecules is still unknown. Multilevel summation method (MSM) has been developed (Hardy et al. 2015) for the efficient treatment of electrostatic forces in non-periodic and semi-periodic systems, charged or neutral. MSM maintains the same force field in droplets as in the bulk solution. We compare MSM with direct electrostatic treatment in droplets. The comparison shows free energy differences between conformations of short peptides along the radius of gyration order parameter that indicate the need for validation of the direct method. We demonstrate the usage of MSM to study Rayleigh jet formation and charge emission from droplets. 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. • Robust atomistic modeling methods can capture competing dynamics that determine the mass spectrum. • Evaporating droplet simulation methods can be included in any MD software. • Direct treatment of electrostatic forces and MSM show small free energy differences between conformations of peptides along the radius of gyration order parameter that indicate that validation of the direct method may be needed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".