A User‐Friendly, All‐Purpose Pd–NHC (NHC=N‐Heterocyclic Carbene) Precatalyst for the Negishi Reaction: A Step Towards a Universal Cross‐Coupling Catalyst
Bibliographic record
Abstract
We have developed the first user-friendly Negishi protocol capable of routinely cross-coupling all combinations of alkyl and aryl centers. The use of an easily synthesized, air stable, highly active, well-defined precatalyst PEPPSI-IPr (1; PEPPSI=pyridine-enhanced precatalyst preparation, stabilization and initiation; IPr=diisopropylphenylimidazolium derivative) substantially increases the scope, reliability, and ease-of-use of the Negishi reaction. All organohalides and routinely used pseudohalides were excellent coupling partners, with the use of chlorides, bromides, iodides, triflates, tosylates, and mesylates resulting in high yield of the coupled product. Furthermore, all reactions were performed by using general laboratory techniques, with no glove-box necessary as the precatalyst was weighed and stored in air. Utilization of this methodology allowed for the easy synthesis of an assortment of sterically encumbered biaryls and druglike heteroaromatics, demonstrating the value of the PEPPSI-IPr system. Furthermore, this is also the first time Pd-NHC (NHC=N-heterocyclic carbene) methodology has surpassed the related phosphine-ligated Negishi processes both in activity and use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".