Revised Mechanism for a Ruthenium-Catalyzed Coupling of Aldehyde and Terminal Alkyne
Bibliographic record
Abstract
Ruthenium catalysts have been found to be of great use for many kinds of reactions. Understanding the details of the catalytic cycle allows to not only rationalize experimental results but also to improve upon reactions. Herein, we present a detailed computational study of a ruthenium-catalyzed coupling between a terminal alkyne and an aldehyde. The reaction under examination facilitates novel access to olefins with the concurrent loss of a single carbon as carbon monoxide. The reaction was first developed in 2009, but the tentative mechanism initially proposed was proven to be contradictory to some experimental data obtained since then. Using a combination of computational investigations and isotope-labeling experiments, several potential mechanisms have been studied. In contrast to the [2+2] cycloaddition mechanism suggested for similar catalysts, we propose a new consensus pathway that proceeds through the formation of a ruthenium-vinylidene complex that undergoes an aldol-type reaction with the aldehyde to yield the product olefins. Computational insights into the influence of different reagents used to optimize reaction conditions and the intricacies of decarbonylation of a Ru-CO complex affecting catalyst turnover are highlighted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".