Self-, N<sub>2</sub>-, O<sub>2</sub>-broadening coefficients and line parameters of HFC-32 for <i>ν</i><sub>7</sub> band and ground state transitions from infrared and microwave spectroscopy
Bibliographic record
Abstract
Hydrofluorocarbons have been used as replacement gases of chlorofluorocarbons, since the latter have been phased out by the Montreal Protocol due to their environmental hazardous ozone-depleting effects. This is also the case of difluoromethane (CH2F2, HFC-32), which nowadays is widely used in refrigerant mixtures together with CF3CH3, CF3CH2F, and CF3CHF2. Due to its commercial use, in the last years, the atmospheric concentration of HFC-32 has increased significantly. However, this molecule presents strong absorptions within the 8–12 μm atmospheric window, and hence it is a greenhouse gas which contributes to global warming. Although over the years several experimental and theoretical investigations dealt with the spectroscopic properties of CH2F2, up to now pressure broadening coefficients have never been determined. In the present work, the line-by-line parameters of CH2F2 are retrieved for either ground state or ν7 band transitions by means of microwave (MW) and infrared (IR) absorption spectroscopy, respectively. In particular, laboratory experiments are carried out on 9 pure rotational transitions of the ground state and 26 ro-vibrational transitions belonging to the ν7 band lying around 8.2 μm within the atmospheric region. Measurements are carried out at room temperature on self-perturbed CH2F2 as well as on CH2F2 perturbed by N2 and O2. The line shape analysis leads to the first determination of self-, N2-, O2-, and air-broadening coefficients, and also of line intensities (IR). Upon comparison, broadening coefficients of ground state transitions are larger than those of the ν7 band, and no clear dependence on the rotational quantum numbers can be reported. The obtained results represent basic information for the atmospheric modelling of this compound as well as for remote sensing applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".