Modeling the ionization mechanism of amorphous solid particles without an external energy source coupled to mass spectrometry
Bibliographic record
Abstract
desorption of charged analytes from the surface of solid amorphous glutaric acid particles, without the assistance of an external energy source, has been shown to be a promising method that can be coupled to mass spectrometry. We conduct mechanistic studies of the later stages of this ionization process using atomistic molecular dynamics. Our analysis focuses on the hydrogen bonding, diffusion, and ion desorption from nano-aggregates of glutaric acid. These nano-aggregates exhibit an extended H-bonded network, often comprising H-bonded chains, linear dimeric assemblies, and occasionally cyclic trimeric assemblies. These local structures serve as centers for proton transfer reactions. The intermediate hydrocarbon chain between the proton-carrying oxygen sites prevents proton diffusion over a long distance unless there is significant translational or rotational movement of the proton-carrying diacid molecule. Our calculations show that diffusion on the surface is an order of magnitude faster than in the core of the nano-aggregate, which aids effective proton transfer on the particle's exterior. We find that ionic species desorb from the aggregate's surface through independent evaporation events of small clusters, where the ion is coordinated by only a few glutaric acid molecules. Near the nano-aggregate's Rayleigh limit, jets capable of releasing multiple ions were not observed. These observations suggest a more general ion-evaporation mechanism that applies to low-dielectric particles of various sizes, complementing the original ion-evaporation mechanism proposed for aqueous droplets with an approximate radius of 10-15 nm. The combined evidence from molecular modeling presented here and the thermodynamic properties of solid and supercooled liquid glutaric acid indicates that the stronger signals of glutaric acid observed in the mass spectra, relative to other experimentally tested diacids, can be attributed to its significantly lower melting point and the reduced enthalpy of vaporization of its amorphous state compared to other tested diacids.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".