On the structure and dynamics of secondary n-alkyl cations
Bibliographic record
Abstract
A variety of computational studies was undertaken to examine and establish the relative importance of open versus closed structures for unbranched secondary n-alkyl cations. First, the PW91 level of density functional theory was used to optimize over 20 minimum-energy structures of sec-pentyl, sec-hexyl, and sec-heptyl ions, demonstrating that closed structures are more stable than open ones on the potential energy surface (PES). Second, PW91 was used with a theoretical Andersen thermostat to perform a molecular dynamics simulation (150 ps) of C9H19+ at a typical catalytic temperature of 800 K, demonstrating that the structure preference is inverted on the free-energy surface. Third, both quantum (rigid-rotor/harmonic oscillator) and classical partition functions were used to demonstrate that the simulated structure-opening at catalytic temperatures is due to the floppiness of the open forms, which improves its free energy by both lowering its zero-point vibrational energy and increasing its molecular entropy. The particular conformer of the preferred open form (at 800 K) is dependent on length of alkyl ion, with pentyl ions preferring syn/anti structures but longer ions preferring open-clinal ones. These results, plus an additional set of PES optimized structures from an alternative level of theory (MP2/6-31G(d,p)), are used to discuss the likely nature of secondary n-alkyl ions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".