Palladium Complexes of N‐Heterocyclic Carbenes as Catalysts for Cross‐Coupling Reactions—A Synthetic Chemist's Perspective
Bibliographic record
Abstract
Palladium-catalyzed C-C and C-N bond-forming reactions are among the most versatile and powerful synthetic methods. For the last 15 years, N-heterocyclic carbenes (NHCs) have enjoyed increasing popularity as ligands in Pd-mediated cross-coupling and related transformations because of their superior performance compared to the more traditional tertiary phosphanes. The strong sigma-electron-donating ability of NHCs renders oxidative insertion even in challenging substrates facile, while their steric bulk and particular topology is responsible for fast reductive elimination. The strong Pd-NHC bonds contribute to the high stability of the active species, even at low ligand/Pd ratios and high temperatures. With a number of commercially available, stable, user-friendly, and powerful NHC-Pd precatalysts, the goal of a universal cross-coupling catalyst is within reach. This Review discusses the basics of Pd-NHC chemistry to understand the peculiarities of these catalysts and then gives a critical discussion on their application in C-C and C-N cross-coupling as well as carbopalladation reactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".