Au(I) Complexes Supported by Donor-Functionalized Indene Ligands: Synthesis, Characterization, and Catalytic Behavior in Aldehyde Hydrosilylation
Bibliographic record
Abstract
New Au(I) complexes featuring ligands of the type κ 1 -3-R 2 P -indene (κ 1 - 1a, R = i Pr; κ 1 - 1b, R = Ph) and κ 1 -1-R 2 P -2-Me 2 N -indene (κ 1 - 1c, R = i Pr; κ 1 - 1d, R = Ph) were prepared and structurally characterized. Dicoordinate neutral complexes (κ 1 - 1 )AuCl ( 2 − 5 ) were prepared by reacting 1 with Me 2 SAuCl, with isolated yields ranging from 56 to 88%. Addition of a second equivalent of 1a to 2 resulted in formation of the tricoordinate neutral species (κ 1 - 1a ) 2 AuCl ( 6; 69%). By treating 6 with AgOTf, the corresponding cationic complex [(κ 1 - 1a ) 2 Au] + OTf - ([ 7 ] + OTf -; 72%) was obtained. The catalytic performance of these new Au(I) compounds in the hydrosilylation of various aldehydes was compared to that of catalyst systems derived from a combination of R 3 P (R = Et, n Bu, t Bu, Cy, or Ph) or N -heterocyclic carbene ligands and Me 2 SAuCl. While for the phosphine-substituted indene complexes, a catalyst mixture of 3 mol % 2 and 20 mol % 1a was found to be optimal, a catalyst derived from 3 mol % Me 2 SAuCl and 20 mol % Et 3 P, n Bu 3 P, or t Bu 3 P proved to be the most effective overall, especially for reactions conducted at 24 °C. Single-crystal X-ray diffraction data are provided for 2, 4, 6, and [ 7 ] + OTf - .
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".