Classical analysis of intermolecular potentials for ArCO<sub>2</sub> rotational collisions
Bibliographic record
Abstract
Classical trajectory calculations have been performed for four potential energy functions to describe ArCO2 collisions. A comparison is given between classical cross sections calculated using the two most recent potential surfaces and two older intermolecular potential surfaces based on the electron gas model. The two-dimensional atom ellipsoid model has also been applied for the study of multiple collisions. The model was able to predict such a phenomenon in agreement with quantum scattering results previously published for an ab initio potential surface in the region of very low collision energy. On the other hand, the two older potentials showed multiple collision effects at very high energies. The comparison of the cross sections showed some deviations from the experimental data. By introducing two parameters, a modified surface is proposed by changing the most recent intermolecular potential. In this case the agreement with experimental measurements and theoretical scattering cross sections was considerably improved. It is concluded that global potential surfaces for describing ArCO2 interaction are not well established. To achieve the requirement of reproducing all properties of this system, the present work suggests that one needs further experimental and theoretical investigations. Key words: classical trajectories, dynamics, cross sections, ArCO2 collisions, potentials.
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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 | 0.001 | 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) | 0.004 | 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".