Application of Direct Analysis in Real Time-Mass Spectrometry (DART-MS) to the Study of Gas–Surface Heterogeneous Reactions: Focus on Ozone and PAHs
Bibliographic record
Abstract
A novel analytical method is presented whereby Direct Analysis in Real Time-Mass Spectrometry (DART-MS) is applied to the study of gas-surface heterogeneous reactions. To illustrate the capabilities of the approach, the kinetics of a well-studied reaction of surface-bound polycyclic aromatic hydrocarbons with ozone are presented. Specifically, using helium as the reagent gas and with the DART heater temperature of 500 °C, nanogram quantities of benzo[e]pyrene (BeP) deposited on the outside of glass melting point capillary tubes were analyzed in positive ion mode with a limit of detection of 40 pg. Using bis(2-ethylhexyl) sebacate as an internal standard, the kinetics of the ozone-BeP reaction were assessed by determining the surface-bound BeP decays, after oxidation in an off-line reaction cell. The reaction is demonstrated to follow the Langmuir-Hinshelwood mechanism, known to prevail for heterogeneous reactions of this type. In addition, a wide array of oxygenated, condensed-phase products has been observed. The present work demonstrates the capability of the DART-MS technique to investigate the heterogeneous chemistry taking place on a wide range of surfaces, such as those that form in both outdoor and indoor environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".