A mechanistic analysis of the tetrasilyl-substituted trimetallaallenes, >EEE< (E = C, Si, Ge, Sn, and Pb)
Bibliographic record
Abstract
The potential energy surfaces for the chemical reactions of tetrasilyl-substituted trimetallaallenes containing two cumulative E-E double bonds, where E = C, Si, Ge, Sn, and Pb, are studied using density functional theory (B3LYP/LANL2DZ). Two types of chemical reactions, methanol addition and intramolecular 1,2-silyl migration, are used to study the reactivity of these allene analogues. The theoretical investigations suggest that the relative reactivity increases in the order: >C-C-C< << >Si-Si-Si< < >Ge-Ge-Ge< < >Sn-Sn-Sn< < >Pb-Pb-Pb<. That is, the heavier the atomic weight of the group 14 atom (E), the more reactive is the >E-E-E< towards chemical reactions. Electronic (due to the group 14 element E) and steric (due to four bulky t-Bu2MeSi groups) factors play a key role in determining both the geometrical structures and the reactivity of the tetrasilyl-substituted trimetallaallenes, from both kinetic and thermodynamic viewpoints. A configuration mixing model, based on the work of Pross and Shaik, is used to rationalize the computational results. The results obtained allow a number of predictions, such as the reactivities and the reaction mechanisms of heavy allenes, to be made.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".