Mapping Electrophile Chemoselectivity in DalPhos/Nickel <i>N</i>‐Arylation Catalysis: The Unusual Influence of Remote Sterics
Bibliographic record
Abstract
We disclose herein our evaluation of competitive (hetero)aryl-X (X: Br>Cl>OTf) reactivity preferences in bisphosphine/Ni-catalyzed C-N cross-coupling catalysis, using furfurylamine as a prototypical nucleophile, and employing DalPhos and DPPF as representative ancillary ligands with established efficacy. Beyond this general (pseudo)halide ranking, other intriguing structure-reactivity trends were noted experimentally, including the unexpected observation that bulky alkyl (e. g., R=tBu) substitution in para-R-aryl-X electrophiles strongly discourages (pseudo)halide reactivity relative to smaller substituents (e. g., nBu, Et, Me), despite being both remote from, and having a similar electronic influence on, the reacting C-X bond; such effects on nickel oxidative addition have not been documented previously and were not observed in our comparator reactions presented herein involving palladium. Density functional theory modeling of such PhPAd-DalPhos/Ni-catalyzed C-N cross-couplings revealed the origins of competitive turnover of C-Br over C-Cl, and possible ways in which bulky para-alkyl substitution might discourage net electrophile uptake/turnover, leading to inversion of halide selectivity.
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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".