Real-time monitoring of benzene, toluene, and p-xylene in a photoreaction chamber with a tunable mid-infrared laser and ultraviolet differential optical absorption spectroscopy
Bibliographic record
Abstract
We describe the implementation of a mid-infrared laser-based trace gas sensor with a photoreaction chamber, used for reproducing chemical transformations of benzene, toluene, and p-xylene (BTX) gases that may occur in the atmosphere. The system performance was assessed in the presence of photoreaction products including aerosol particles. A mid-infrared external cavity quantum cascade laser (EC-QCL)-tunable from 9.41-9.88 μm (1012-1063 cm(-1))-was used to monitor gas phase concentrations of BTX simultaneously and in real time during chemical processing of these compounds with hydroxyl radicals in a photoreaction chamber. Results are compared to concurrent measurements using ultraviolet differential optical absorption spectroscopy (UV DOAS). The EC-QCL based system provides quantitation limits of approximately 200, 200, and 600 parts in 10(9) (ppb) for benzene, toluene, and p-xylene, respectively, which represents a significant improvement over our previous work with this laser system. Correspondingly, we observe the best agreement between the EC-QCL measurements and the UV DOAS measurements with benzene, followed by toluene, then p-xylene. Although BTX gas-detection limits are not as low for the EC-QCL system as for UV DOAS, an unidentified by-product of the photoreactions was observed with the EC-QCL, but not with the UV DOAS system.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".