Collision-Induced Dissociation of Electrosprayed NaCl Clusters: Using Molecular Dynamics Simulations to Visualize Reaction Cascades in the Gas Phase
Bibliographic record
Abstract
Infusion of NaCl solutions into an electrospray ionization (ESI) source produces [Na ( n +1) Cl n ] + and other gaseous clusters. The n = 4, 13, 22 magic number species have cuboid ground state structures and exhibit elevated abundance in ESI mass spectra. Relatively few details are known regarding the mechanisms whereby these clusters undergo collision-induced dissociation (CID). The current study examines to what extent molecular dynamics (MD) simulations can be used to garner insights into the sequence of events taking place during CID. Experiments on singly charged clusters reveal that the loss of small neutrals is the dominant fragmentation pathway. MD simulations indicate that the clusters undergo extensive structural fluctuations prior to decomposition. Consistent with the experimentally observed behavior, most of the simulated dissociation events culminate in ejection of small neutrals ([NaCl] i, with i = 1, 2, 3). The MD data reveal that the prevalence of these dissociation channels is linked to the presence of short-lived intermediates where a relatively compact core structure carries a small [NaCl] i protrusion. The latter can separate from the parent cluster via cleavage of a single Na-Cl contact. Fragmentation events of this type are kinetically favored over other dissociation channels that would require the quasi-simultaneous rupture of multiple electrostatic contacts. The CID behavior of NaCl cluster ions bears interesting analogies to that of collisionally activated protein complexes. Overall, it appears that MD simulations represent a valuable tool for deciphering the dissociation of noncovalently bound systems in the gas phase.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".