The femtochemistry of nitrobenzene following excitation at 240 nm
Bibliographic record
Abstract
Abstract Although the photochemistry of nitrobenzene has been extensively studied, the assignment of fragmentation channels and their specific dynamics remains challenging. Here the photochemistry of nitrobenzene following 240 nm excitation into its S4 excited singlet state is investigated by femtosecond laser-induced ionization using an intense 800 nm pulse, coupled with time-resolved Coulomb explosion imaging and covariance mapping. We assign photochemical channels by observing correlations between the molecular fragment ions of the associated product pairs, enabling the time-resolved dynamics of channels leading to NO, NO2, and C6H5NO to be fully characterized. NO is produced via two distinct pathways, leading to translationally cold and hot photofragments with risetimes of ~ 8 ps and ~ 14 ps, respectively. NO2 photofragments are characterised by a bimodal risetime of ~ 8 ps and ≳ 2 ns, and can be detected within the first picosecond following ultra-violet photon absorption. C6H5NO is formed with a risetime of 17 ps. Kinetic energy disposals determined for the three chemical channels agree well with previous work. The techniques employed offer new opportunities to study the time-resolved photochemistry of relatively complex molecules 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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".