Multiphase reactivity of polycyclic aromatic hydrocarbons is driven by phase separation and diffusion limitations
Bibliographic record
Abstract
Benzo[a]pyrene (BaP), a key polycyclic aromatic hydrocarbon (PAH) often associated with soot particles coated by organic compounds, is a known carcinogen and mutagen. When mixed with organics, the kinetics and mechanisms of chemical transformations of BaP by ozone in indoor and outdoor environments are still not fully elucidated. Using direct analysis in real-time mass spectrometry (DART-MS), kinetics studies of the ozonolysis of BaP in thin films exhibited fast initial loss of BaP followed by a slower decay at long exposure times. Kinetic multilayer modeling demonstrates that the slow decay of BaP over long times can be simulated if there is slow diffusion of BaP from the film interior to the surface, resolving long-standing unresolved observations of incomplete PAH decay upon prolonged ozone exposure. Phase separation drives the slow diffusion time scales in multicomponent systems. Specifically, thermodynamic modeling predicts that BaP phase separates from secondary organic aerosol material so that the BaP-rich layer at the surface shields the inner BaP from ozone. Also, BaP is miscible with organic oils such as squalane, linoleic acid, and cooking oil, but its oxidation products are virtually immiscible, resulting in the formation of a viscous surface crust that hinders diffusion of BaP from the film interior to the surface. These findings imply that phase separation and slow diffusion significantly prolong the chemical lifetime of PAHs, affecting long-range transport of PAHs in the atmosphere and their fates in 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 | 0.000 | 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 | 0.001 | 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".