Mechanistic Investigation of Zirconium-Catalyzed Hydroaminoalkylation of Alkynes: Substrate and Ligand Effects
Bibliographic record
Abstract
The mechanism of zirconium-catalyzed hydroaminoalkylation of diphenylacetylene, and the origin of the contrasting reactivity with N -benzylaniline or N -(trimethylsilyl)benzylamine substrates, have been investigated. Isolated intermediates have revealed that the nature of the C–H activation and C–C bond-forming steps in alkyne hydroaminoalkylation are analogous to those of the alkene variant, regardless of the amine substrate. In the zirconium-catalyzed hydroaminoalkylation of alkynes, the open coordination sphere at the zirconium center, supported by the bis(ureate) ligand, enables the coordination of neutral protic donors. This is essential for promoting catalytic turnover in these reactions. Under catalytic conditions, dimethylamine acts as a proton source for releasing the allylic amine products while minimizing the formation of side products. Additionally, we identified the formation of a homoleptic tetra(ureate) zirconium complex as the main catalyst decomposition pathway in catalytic alkyne hydroaminoalkylation. The formation of similar homoleptic structures is further favored when employing smaller bis(urea) proligands, thus explaining the poor performance of some ligands in catalysis. However, further increasing the bis(urea) proligand size to minimize such catalyst decomposition favors isomerization side-products resulting in reduced yields of the desired product. This study provides ligand design principles that guide the development of coordinatively flexible catalysts to achieve catalytic turnover in systems that rely upon protonolysis steps, as in hydroaminoalkylation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".