Unraveling the Unimolecular Ion Chemistry of Protonated Isoprene and Prenol
Bibliographic record
Abstract
The atmospheric chemistries of isoprene and prenol have been studied extensively; however, much of that research has focused on neutral or radical chemistry. Recent studies have demonstrated that under acidic conditions, isoprene and prenol can become protonated in the atmosphere, and we have explored the unimolecular chemistry of protonated isoprene and prenol with tandem mass spectrometry (using a triple-quadrupole mass spectrometer) and density functional theory. The collision-induced dissociation of protonated isoprene revealed two product ion channels: the neutral losses of C 2 H 4 and H 2, the former dominating over the latter. Protonated prenol dissociates by four product ion channels: the neutral losses of water, formaldehyde, methanol, and propene, with the former two being minor channels and the latter two being major channels. Density functional theory supplemented with CBS-QB3 single-point calculations revealed the underlying mechanisms to explain the breakdown behavior. The two competing channels from protonated isoprene could easily be rationalized due to the relative energy difference between key transition states along the reaction coordinates. However, in the case of protonated prenol, it was revealed that the minor products observed in the breakdown of protonated prenol had significantly lower reaction barriers when compared to the major products, an apparent contradiction. This could be rationalized if the initial ion population entering the collision cell is comproed of several isomeric species on the minimum energy reaction pathway, species populated by collisional excitation in the ion source region.
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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 | 0.000 | 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".