Competitive Ligand Exchange and Dissociation in Ru Indenyl Complexes
Bibliographic record
Abstract
Kinetic profiles obtained from monitoring the solution-phase substitution chemistry of [Ru(η 5 -indenyl)(NCPh)(PPh 3 ) 2 ] + ( 1 ) by both electrospray ionization mass spectrometry and 31 P{ 1 H} NMR are essentially identical, despite an enormous difference in sample concentrations for these complementary techniques. These studies demonstrate dissociative substitution of the NCPh ligand in 1 . Competition experiments using different secondary phosphine reagents provide a ranking of phosphine donor abilities at this relatively crowded half-sandwich complex: PEt 2 H > PPh 2 H ≫ PCy 2 H. The impact of steric congestion at Ru is evident also in reactions of 1 with tertiary phosphines; initial substitution products [Ru(η 5 -indenyl)(PR 3 )(PPh 3 ) 2 ] + rapidly lose PPh 3, enabling competitive re-coordination of NCPh. Further solution experiments, relevant to the use of 1 in catalytic hydrophosphination, show that PPh 2 H out-competes PPh 2 CH 2 CH 2 CO 2 Bu t (the product of hydrophosphination of tert -butyl acrylate by PPh 2 H) for coordination to Ru, even in the presence of a 10-fold excess of the tertiary phosphine. Additional information on relative phosphine binding strengths was obtained from gas-phase MS/MS experiments, including collision-induced dissociation experiments on the mixed phosphine complexes [Ru(η 5 -indenyl)PP′P″] +, which ultimately appear in solution during the secondary phosphine competition experiments. Unexpectedly, unsaturated complexes [Ru(η 5 -indenyl)(PR 2 H)(PPh 3 )] +, generated in the gas-phase, undergo preferential loss of PR 2 H. We propose that competing orthometallation of PPh 3 is responsible for the surprising stability of the [Ru(η 5 -indenyl)(PPh 3 )] + fragment under these conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".