Sensing of Halocarbons Using Femtosecond Laser-Induced Fluorescence
Bibliographic record
Abstract
A femtosecond laser-induced clean fluorescence technique was explored as a means to monitor halogenated alkanes in the atmosphere. Characteristic difluorocarbene radical (CF2) fluorescence in the UV-vis can be generated inside a femtosecond laser-induced filament for different halocarbons. We show that, due to different dissociation and excitation kinetics leading to fluorescence emission, it is possible to temporally resolve the characteristic fluorescence of CF2-containing halocarbons from that of background species, therefore enhancing the signal-to-noise ratio. Laboratory-scale experiments demonstrate the potential use of femtosecond laser-induced clean fluorescence for the remote sensing of halocarbons in the atmosphere. The combination of this detection strategy with LIDAR could allow the long-range monitoring of several atmospheric species with a single laser source, eventually leading to a better understanding of chemical and dynamic processes affecting global warming, ozone loss, tropospheric pollution, and weather prediction.
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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 | 0.000 |
| 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 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".