Product Energy and Angular Momentum Partitioning in the Unimolecular Dissociation Of Aluminum Clusters
Bibliographic record
Abstract
A previous classical trajectory simulation showed that the unimolecular decompositions of Al 6 and Al 13 are intrinsically RRKM. In the work presented here, this study is further analyzed to determine the Al 5 + Al and Al 12 + Al product energy distributions, which are compared with the predictions of statistical theories. Orbiting transition state/phase space theory (OTS/PST) gives distributions in excellent agreement with the trajectory results. Assuming a loose, product-like transition state gives a lower average product translational energy, 〈 E t 〉, than what is found with the orbiting transition state. Including anharmonicity, in the calculation of the product vibrational density of states, increases the energy partitioned to product vibration. The Engelking model for cluster decomposition overestimates 〈 E t 〉. One Klots model gives an inaccurate 〈 E t 〉, but a second model more firmly rooted in phase space theory performs quite well. The Engelking model, for deducing the cluster dissociation energy from the measured 〈 E t 〉, does not give accurate results for Al 6 and Al 13 dissociation.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".