Anionic N‐Heterocyclic Carbenes with <i>N</i>,<i>N</i>′‐Bis(fluoroaryl) and <i>N</i>,<i>N</i>′‐Bis(perfluoroaryl) Substituents
Bibliographic record
Abstract
A series of rhodium complexes, [Rh(cod)(NHC-F(x))(OH(2))] (cod = 1,5-cyclooctadiene; NHC = N-heterocyclic carbene), incorporating anionic N-heterocyclic carbenes with 2-tert-butylmalonyl backbones and 2,6-dimethylphenyl (x = 0), 2,6-difluorophenyl (x = 4), 2,4,6-trifluorophenyl (x = 6), and pentafluorophenyl (x = 10) N,N'-substituents, respectively, has been prepared by deprotonation of the corresponding zwitterionic precursors with potassium hexamethyldisilazide, followed by immediate reaction of the resulting potassium salts with [{RhCl(cod)}(2)]. These complexes could be converted to the related carbonyl derivatives [Rh(CO)(2)(NHC-F(x))(OH(2))] by displacement of the COD ligand with CO. IR and NMR spectroscopy demonstrated that the degree of fluorination of the N-aryl substituents has a considerable influence on the σ-donating and π-accepting properties of the carbene ligands and could be effectively used to tune the electronic properties of the metal center. The carbonyl groups on the carbene ligand backbone provided a particularly sensitive probe for the assessment of the metal-to-ligand π donation. The ortho-fluorine substituents on the N-aryl groups in the carbene ligands interacted with the other ligands on rhodium, determining the conformation of the complexes and creating a pocket suitable for the coordination of water to the metal center. Computational studies were used to explain the influence of the fluorinated N-substituents on the electronic properties of the ligand and evaluate the relative contribution of the σ- and π-interactions to the ligand-metal interaction.
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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".