Atmospheric OH Oxidation Chemistry of Particulate Liquid Crystal Monomers: An Emerging Persistent Organic Pollutant in Air
Bibliographic record
Abstract
Liquid crystal monomers (LCMs) are synthetic chemicals widely used in liquid crystal displays such as televisions and smartphones and have recently been detected in indoor dust. Despite extensive use, the atmospheric fate of LCMs is unknown. Here, the heterogeneous OH oxidation of LCMs was studied by exploring the kinetics and mechanisms of 1-ethyl-4-(4-(4-propylcyclohexyl)phenyl)benzene (EPPB) and 4′′-ethyl-2′-fluoro-4-propyl-1,1′:4′,1′′-terphenyl (EFPT) coated onto ammonium sulfate particles. The measured heterogeneous rate constants for EPPB and EFPT were (7.05 ± 0.46) × 10 –13 and (4.67 ± 0.25) × 10 –13 cm 3 molecule –1 s –1,respectively, equivalent to atmospheric lifetimes of up to 25 and 38 days. These lifetimes are significantly longer than previously predicted values (<1 day) for these LCMs, indicating that they are much more persistent in air than predicted, with the potential to undergo long-range transport. Furthermore, 66 transformation products from the heterogeneous photooxidation of these LCMs were identified for the first time. Given the known toxicity of the parent LCMs, their measured persistence in the atmosphere, and the demonstrated complexity of their products, the present results not only underscore the need to quantify the levels of LCMs in ambient air, but also suggest that the presence of their transformation products should not be ignored when assessing the risks of airborne LCMs.
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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 | 0.000 | 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".