Exploring the Utility of Neutral Rhodium and Iridium κ<sup>2</sup>-<i>P</i>,<i>O</i>and κ<sup>2</sup>-P(<i>S</i>),<i>O</i>Complexes as Catalysts for Alkene Hydrogenation and Hydrosilylation
Bibliographic record
Abstract
Heating of [(COD)M(κ 2 -3- P i Pr 2 -2- N Me 2 -indene)] + X - (M = Rh or Ir; X = BF 4, PF 6; COD = η 4 -1,5-cyclooctadiene) in a mixture of water and THF (48 h, 60 °C) afforded the neutral (COD)M(κ 2 - P, O ) complexes (M = Rh, 5a, 80%; M = Ir, 5b, 74%). Similarly, thermolysis of [(COD)M(κ 2 -3-P( S ) i Pr 2 -2- N Me 2 -indene)] + BF 4 - (M = Rh or Ir) in a mixture of water and CH 2 Cl 2 (14 h, 60 °C) produced the neutral (COD)M(κ 2 -P( S ), O ) complexes (M = Rh, 13a, 91%; M = Ir, 13b, 90%). Subsequent preparation of 1-P i Pr 2 -2-indanone ( 8, 91%) enabled the non-hydrolytic synthesis of 5b in 70% isolated yield via treatment with 0.5[(COD)IrCl] 2 in the presence of NEt 3 . Lithiation of ( o -P i Pr 2 )phenol followed by quenching with 0.5[(COD)IrCl] 2 afforded the neutral (COD)Ir(κ 2 - P, O ) complex 10 (91%). Single-crystal X-ray diffraction data are provided for 5b, 10, 13a, and 13b . Whereas 5a, 13a, and 13b performed poorly as catalysts for the hydrogenation of alkenes, the known complex (COD)Ir(OPh)(PCy 3 ) 2 as well as 5b and 10 proved to be excellent catalysts for hydrogenation of mono-, di-, and trisubstituted alkene substrates under mild conditions (22 °C, ∼1 atm H 2 ). Complexes 13a,b were also shown to be competent catalysts for addition of triethylsilane to styrene.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".