Soot Aggregate Restructuring Due to Coatings of Secondary Organic Aerosol Derived from Aromatic Precursors
Bibliographic record
Abstract
Restructuring of monodisperse soot aggregates due to coatings of secondary organic aerosol (SOA) derived from hydroxyl radical-initiated oxidation of toluene, p-xylene, ethylbenzene, and benzene was investigated in a series of photo-oxidation (smog) chamber experiments. Soot aggregates were generated by combustion of ethylene using a McKenna burner, treated by denuding, size-selected by a differential mobility analyzer, and injected into a smog chamber, where they were exposed to low vapor pressure products of aromatic hydrocarbon oxidation, which formed SOA coatings. Aggregate restructuring began once a threshold coating mass was reached, and the degree of the subsequent restructuring increased with mass growth factor. Although significantly compacted, fully processed aggregates were not spherical, with a mass-mobility exponent of 2.78, so additional SOA was required to fill indentations between collapsed branches of the restructured aggregates before the dynamic shape factor of coated particles approached 1. Trends in diameter growth factor, effective density, and dynamic shape factor with increasing mass growth factor indicate distinct stages in soot aggregate processing by SOA coatings. The final degree and coating mass dependence of soot restructuring were found to be the same for SOA coatings from all four aromatic precursors, indicating that the surface tensions of the SOA coatings are similar.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".