Catalyzed β scission of a carbenium ion III — Scission observed in ab initio molecular dynamics simulations
Bibliographic record
Abstract
The β scission (cracking) of branched carbenium ions have been observed in molecular dynamics simulations, possibly for the first time. Simulations were performed with molecular dynamics based on PW91 density functional theory, and which included three-dimensional periodic boundary replication of the unit cell to mimic long-range bulk effects. A rising-temperature algorithm was used to encourage reaction within the narrow time windows (∼10 ps) of the simulations. Twenty-eight simulations were performed, featuring alkyl ions in three different catalytic systems: the ionic liquid, [(C 5 H 5 NH + ) 5 (Al 2 Cl 7 − ) 6 ] − , the chabazite zeolite, [AlSi 23 O 48 ] − , and the chabazite zeolite, [Al 4 Si 20 O 45 (OH) 3 ] − . Twenty-four runs began with unbranched sec-n-alkyl ions, but only one exhibited β scission, and only after branching to a tertiary ion and under extreme heating. In contrast, the four simulations that began with branched alkyl ions were all successful in demonstrating β scission at lower temperatures: 2,4,4-trimethyl-2-pentyl ion and 2,4-dimethyl-2-hexyl ion in each of the first two catalysts. The lifetimes of desorbed alkyl ions in the chabazite models were < 5 ps at 1000–1500 K. The β scission results support the classical Weitkamp et al. ( Appl. Catal. 1983, 8, 123 ) mechanism over the nonclassical Sie ( Ind. Eng. Chem. Res. 1992, 31, 1881 ) and the chemisorping Kazansky et al. ( J. Catal. 1989, 119, 108 ) mechanisms.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".