A study of oleic acid and 2,4-DHB acid aerosols using an IR-VUV-ITMS: insights into the strengths and weaknesses of the technique
Bibliographic record
Abstract
An investigation of oleic acid and 2,4-dihydroxybenzoic (DHB) acid aerosols was carried out using an aerosol mass spectrometer with pulsed lasers for vaporization and ionization and an ion trap for mass analysis. The extent of ion fragmentation was studied as a function of both vaporization energy and ionization wavelength. Low CO2 laser energies in the vaporization stage and near-threshold single photon ionization resulted in the least fragmented mass spectra. For DHB, only the molecular ion was observed, but for oleic acid fragmentation could not be eliminated. Tandem MS of the main fragment peak from oleic acid was carried out and provided a tool for compound identification. Photoionization efficiency curves were also collected for both DHB and oleic acid and the appearance energies of both parent and fragment ions were measured. Evidence for fragmentation occurring post-ionization is given by the similar appearance energies for both the parent and fragment ions. The results from this study were compared with those from similar experiments undertaken with time-of-flight (TOF) mass analyzers. The degree of fragmentation in the ion trap was considerably higher than that seen with TOF systems, particularly for oleic acid. This was attributed to the long storage interval in the ion trap which allows time for metastable ions to decay. Differences in the degree of fragmentation between the ion trap and TOF studies also provided further evidence for fragmentation occurring post-ionization. For 2,4-dihydroxybenzoic acid, the long delay prior to mass analysis also allowed time for reactions with background gases, in this case water, to occur.
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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 | 0.000 |
| Open science | 0.000 | 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".