An overview of organic molecule soft ionization using vacuum ultraviolet laser radiation
Bibliographic record
Abstract
The utility of coherent vacuum ultraviolet (VUV) single-photon ionization (SPI) combined with time-of-flight mass spectrometry (TOF-MS) for organic molecule detection by parent mass is explored in this short review. Nonresonant tripling in phase-matched XeAr gas mixtures was used to generate photons at a fixed energy of 10.5 eV. Representative organic molecules with different functional groups were examined, including aliphatic and aromatic alkanes, alkenes, alkynes, alkanols, ethers, amines, aldehydes, ketones, carboxylic acids, and esters. In almost every case, the intensity of the resultant parent molecular ion peak detected by TOF-MS was found to be superior to that obtained using 70 eV electron impact (EI), and comparable to that obtained with 12 eV EI. In those instances when fragmentation reactions did occur, the resultant ions were similar to those found using EI but with significantly reduced mass spectral intensities. It was still possible to establish one dominant fragmentation pathway that could be used for molecular identification even if the parent molecular ion was not the strongest feature in the spectrum, for example, in the case of alcohols, alcohol clusters, and alcoholether adducts. Several of the fragment ions were metastably broadened. Not surprisingly, their known appearance energies or estimated reaction enthalpies were very similar to the fixed photon energy used. The success of using VUV for organic molecule soft ionization is attributed to the low photon energy that removes predominantly a π- or non-bonding electron from the functionalized species. As most organic compounds have ionization potentials in the 10.5 eV region, this approach is expected to be near universal.Key words: vacuum ultraviolet laser, single photon ionization, organic molecule detection, soft-ionization, mass spectrometry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".