Enantioselective Palladium-Catalyzed Hydrosilylation of Styrene: Detailed Reaction Mechanism from First-Principles and Hybrid QM/MM Molecular Dynamics Simulations
Bibliographic record
Abstract
The mechanism of the enantioselective hydrosilylation of styrene catalyzed by Pd 0 species generated in situ from dichloro{1-{( R )-1-[( S )-2(diphenylphosphino-κ P )ferrocenyl]ethyl}-3-trimethylphenyl-5-1 H -pyrazole-κ N }palladium, 1, has been investigated in detail through ab initio molecular dynamics and hybrid ab initio molecular dynamics/molecular mechanics (QM/MM) calculations. Different QM/MM models have been adopted in order to probe the specific steric and electronic contributions of different substituents. The catalytic cycle is initiated by the formation of a weakly bound π-complex (Δ E ≈ −5.4 kcal/mol) under simultaneous detachment of the pyrazole ligand. In agreement with a Chalk−Harrod mechanism, this is followed by the migratory insertion of the hydride, which leads to a η 3 -coordination mode of the benzylic fragment. The significant stabilization of the allylic intermediate (Δ E ≈ −11 kcal/mol) is responsible for the high regioselectivity of the reaction (as well as for its enantioselectivity). The rate-determining step with an activation barrier of 16 kcal/mol is the migration of the silyl ligand to the α-carbon of the substrate with concomitant closure of the ligand chelate ring. This step leads to the formation of an intermediate in which the phenyl moiety of the product remains coordinated in an η 2 -mode to the palladium. The addition of trichlorosilane leads to product formation and hence to the regeneration of the catalyst. A unimolecular reaction pathway on the other hand, in which the transfer of the silyl ligand to the benzylic fragment is concerted with the addition of a molecule of HSiCl 3 to the catalyst, is disfavored by an activation barrier of ∼30 kcal/mol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".