Effect of viscosity on photodegradation rates in complex secondary organic aerosol materials
Bibliographic record
Abstract
This work explores the effect of environmental conditions on the photodegradation rates of atmospherically relevant, photolabile, organic molecules embedded in a film of secondary organic material (SOM). Three types of SOM were studied: α-pinene/O3 SOM (PSOM), limonene/O3 SOM (LSOM), and aged limonene/O3 obtained by exposure of LSOM to ammonia (brown LSOM). PSOM and LSOM were impregnated with 2,4-dinitrophenol (2,4-DNP), an atmospherically relevant molecule that photodegrades faster than either PSOM or LSOM alone, to serve as a probe of SOM matrix effects on photochemistry. Brown LSOM contains an unidentified chromophore that absorbs strongly at 510 nm and photobleaches upon irradiation. This chromophore served as a probe molecule for the brown LSOM experiments. In all experiments, either the temperature or relative humidity (RH) surrounding the SOM films was varied. The extent of photochemical reaction in the samples was monitored using UV-vis absorption spectroscopy. For all three model systems examined, the observed photodegradation rates were slower at lower temperatures and lower RH, conditions that make SOM more viscous. Additionally, the activation energies for photodegradation of each system were positively correlated with the viscosity of the SOM matrix as measured in poke-flow experiments. These activation energies were calculated to be 50, 24, and 17 kJ mol(-1) for 2,4-DNP in PSOM, 2,4-DNP in LSOM, and the chromophore in brown LSOM, respectively, and PSOM was found to be the most viscous of the three. These results suggest that the increased viscosity is hindering the motion of the molecules in SOM and is slowing down their respective photochemical reactions.
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 | 0.001 | 0.000 |
| 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".