Exploring Regioselective Bond Cleavage and Cross‐Coupling Reactions using a Low‐Valent Nickel Complex
Bibliographic record
Abstract
Recently, esters have received much attention as transmetalation partners for cross-coupling reactions. Herein, we report a systematic study of the reactivity of a series of esters and thioesters with [{(dtbpe)Ni}2(μ-η(2):η(2)-C6H6)] (dtbpe=1,2-bis(di-tert-butyl)phosphinoethane), which is a source of (dtbpe)nickel(0). Trifluoromethylthioesters were found to form η(2)-carbonyl complexes. In contrast, acetylthioesters underwent rapid Cacyl-S bond cleavage followed by decarbonylation to generate methylnickel complexes. This decarbonylation could be pushed backwards by the addition of CO, allowing for regeneration of the thioester. Most of the thioester complexes were found to undergo stoichiometric cross-coupling with phenylboronic acid to yield sulfides. While ethyl trifluoroacetate was also found to form an η(2)-carbonyl complex, phenyl esters were found to predominantly undergo Caryl-O bond cleavage to yield arylnickel complexes. These could also undergo transmetalation to yield biaryls. Attempts to render the reactions catalytic were hindered by ligand scrambling to yield nickel bis(acetate) complexes, the formation of which was supported by independent syntheses. Finally, 2-naphthyl acetate was also found to undergo clean Caryl-O bond cleavage, and although stoichiometric cross-coupling with phenylboronic acid proceeded with good yield, catalytic turnover has so far proven elusive.
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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 | 0.001 |
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".