Mechanism of the Addition of Nonenolizable Aldehydes and Ketones to (Di)metallenes (R<sub>2</sub>XYR<sub>2</sub>, X = Si, Ge Y = C, Si, Ge): A Density Functional and Multiconfigurational Perturbation Theory Study
Bibliographic record
Abstract
The mechanism of the addition of nonenolizable aldehydes and ketones to group 14 (di)metallenes has been examined through a theoretical study of the addition of formaldehyde to Si=C, Ge=C, Si=Si, Si=Ge, and Ge=Ge bonds at the B3LYP/6-311++G(d,p) and CAS-MCQDPT2/6-31++G(d,p) levels of theory. The reaction pathways located can be grouped as either involving the formation of singlet diradical or zwitterionic intermediates or as concerted processes. Within each group of reaction pathways, several different mechanisms have been located, with not all mechanisms being available to all of the (di)metallenes. It was found that for reactions in which a Si-O bond results (i.e., addition to Si=C, Si=Si, and Si=Ge) both diradical and zwitterionic intermediates are possible; however, the formation of diradical intermediates was not found for reactions that result in the formation of a Ge-O bond (addition to Ge=C and Ge=Ge). The underlying cause of this pathway selectivity is examined, as well as the effect of solvent on the relative energies of the pathways. The results of the study shed light on the cause of experimentally obtained results regarding the mechanism of the reaction of (di)metallenes with nonenolizable ketones and aldehydes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".