Computational study of the rovibrational spectrum of CO<sub>2</sub>–N<sub>2</sub>
Bibliographic record
Abstract
The CO2-N2 complex is formed from two key components of Earth's atmosphere, and as such, has received some attention from both experimental and theoretical studies. On the theory side, a potential energy surface (PES) based on high level ab initio data was reported [Nasri et al., J. Chem. Phys., 2015, 142, 174301] and then used in more recently reported rovibrational calculations [Lara-Moreno et al., Phys. Chem. Chem. Phys., 2019, 21, 3550]. Accuracy of about 1 percent was achieved for calculated rotational transitions of the ground vibrational state of the complex, compared with previously reported microwave spectra. However, a very recent measurement of the geared bending mode frequency [Barclay et al., J. Chem. Phys., 2020, 153, 014303] recorded a value of 21.4 cm-1, which is wildly different from the corresponding calculated value of 45.9 cm-1. To provide some insight into this discrepancy, we have constructed a new more accurate PES, and used it to perform highly converged variational rovibrational calculations. Our new results yield a value of 21.1 cm-1 for that bending frequency, in close agreement with the experiment. We also obtain significantly improved predicted rotational transitions. Finally, we note that a very shallow well, previously reported as a distinct second isomer, is not found on our new PES, but rather a transition structure is seen in that location.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".