Ruthenium Carbene–Diether Ligand Complexes: Catalysts for Hydrogenation of Olefins
Bibliographic record
Abstract
A series of carbene–diether ligands were prepared and the corresponding Ag salts used to prepare the complexes RuHCl(PPh 3 ) 2 (Im(OR) 2 ) (Im(OR) 2 = C 3 H 2 (NCH 2 CH 2 OR) 2; R = Me ( 4a ), t- Bu ( 4b ), tert- hexyl ( 4c ), Ph ( 4d ), 2,6- i- Pr 2 C 6 H 3 ( 4e )). In an analogous fashion the species RuHCl(PPh 3 ) 2 (Y 2 Im(OMe) 2 ) (Y 2 Im(OMe) 2 = Y 2 C 3 (NCH 2 CH 2 OMe) 2; Y 2 = C 6 H 4 ( 4f ), Y = Cl ( 4g ), Me ( 4h )) were also synthesized. Similarly RuHCl(CO)(PPh 3 ) 2 (Im(OMe) 2 ) ( 5 ) was prepared and readily converted to RuHCl(CO)(SIMes)(Im(OMe) 2 ) ( 6 ) via treatment with SIMes. The reaction of 4a with SIMes afforded RuHCl(SIMes)(Im(OMe) 2 )(PPh 3 ) ( 7 ), which reacts subsequently with Na[BPh 4 ] to give [RuH(Im(OMe) 2 )(SIMes)][(η 6 -Ph)BPh 3 ] ( 8 ). In a series of tests, the species 4a – h, 5, 6, and 8 were shown to catalyze the hydrogenations of 1-hexene, cyclohexene, and dimethyl itaconate. From the activity of 4a – h it is clear that the capability of the carbene–ether substituents to coordinate to the metal as well as electron-donating substituents on the carbene fragment enhances catalytic activity. Other variations such as in 5, 6, and 8 resulted in terminal-olefin-selective hydrogenation catalysts, although the zwitterionic species 8 showed significantly enhanced activity.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".