Modeling collision energy transfer in APCI/CID mass spectra of PAHs using thermal-like post-collision internal energy distributions
Bibliographic record
Abstract
The internal energy transferred when projectile molecular ions of naphthalene collide with argon gas atoms was extracted from the APCI-CID (atmospheric-pressure chemical ionization collision-induced dissociation) mass spectra acquired as a function of collision energy. Ion abundances were calculated by microcanonical integration of the differential rate equations using the Rice-Ramsperger-Kassel-Marcus rate constants derived from a UB3LYP/6-311G+(3df,2p)//UB3LYP/6-31G(d) fragmentation mechanism and thermal-like vibrational energy distributions pME,Tchar. The mean vibrational energy excess of the ions was characterized by the parameter Tchar (“characteristic temperature”), determined by fitting the theoretical ion abundances to the experimental breakdown graph (a plot of relative abundances of the ions as a function of kinetic energy) of activated naphthalene ions. According to these results, the APCI ion source produces species below Tchar = 1457 K, corresponding to 3.26 eV above the vibrational ground state. Subsequent collisions heat the ions up further, giving rise to a sigmoid curve of Tchar as a function of Ecom (center-of-mass-frame kinetic energy). The differential internal energy absorption per kinetic energy unit (dEvib/dEcom) changes with Ecom according to a symmetric bell-shaped function with a maximum at 6.38 ± 0.32 eV (corresponding to 6.51 ± 0.27 eV of vibrational energy excess), and a half-height full width of 6.30 ± 1.15 eV. This function imposes restrictions on the amount of energy that can be transferred by collisions, such that a maximum is reached as kinetic energy is increased. This behavior suggests that the collisional energy transfer exhibits a pronounced increase around some specific value of energy. Finally, the model is tested against the CID mass spectra of anthracene and pyrene ions and the corresponding results are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".