Role of the Aerosol Substrate in the Heterogeneous Ozonation Reactions of Surface-Bound PAHs
Bibliographic record
Abstract
To probe how the aerosol substrate influences heterogeneous polycyclic aromatic hydrocarbon (PAH) oxidation, we investigated the reaction of surface-bound anthracene with gas-phase ozone on phenylsiloxane oil and azelaic acid aerosols under dry conditions in an aerosol flow tube with offline analysis of anthracene. The reaction exhibited pseudo-first-order kinetics for anthracene loss, and the pseudo-first-order rate coefficients displayed a Langmuir-Hinshelwood dependence on the gas-phase ozone concentration on both aerosol substrates. The following parameters were found: for the reaction on phenylsiloxane oil aerosols, K(O3) = (1.0 +/- 0.4) x 10(-13) cm(3) and k(I)(max) = (0.010 +/- 0.003) s(-1); for the reaction on azelaic acid aerosols, K(O3) = (2.2 +/- 0.9) x 10(-15) cm(3) and k(I)(max) = (0.057 +/- 0.009) s(-1), where K(O3) is a parameter that describes the partitioning of ozone to the surface and k(I)(max) is the maximum pseudo-first-order rate coefficient at high ozone concentrations. The K(O3) value for the reaction of surface-bound anthracene and ozone on azelaic acid aerosols is similar to the K(O3) value that we obtained in our previous study for the reaction of surface-bound benzo[a]pyrene and ozone on the same substrate. This finding supports our earlier hypothesis that the substrate influences the partitioning of ozone to the surface irrespective of the organic species (i.e., PAH) adsorbed to it. Preliminary ab initio calculations were performed to investigate whether there is a relationship between the relative binding energies of the ozone-substrate complex and the K(O3) values for the different substrates studied. A comparison between kinetic results obtained on aerosol substrates and thin films is presented.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".