Probing the Influence of PAd-DalPhos Ancillary Ligand Structure on Nickel-Catalyzed Ammonia Cross-Coupling
Bibliographic record
Abstract
We report herein on the results of our combined experimental/computational study regarding the catalytic performance of PAd-DalPhos ( L1 ) in nickel-catalyzed ammonia arylation for primary aniline synthesis. Primary arylamine C–N reductive eliminations occurring from arylnickel(II) parent amido complexes of the type ( L )Ni(Ph)(NH 2 ) were modeled by use of density-functional theory (DFT) methods, for a series of L1 derivatives. The dual aims were to assess the effect of structural modifications to L1 on potentially rate-limiting C–N reductive elimination and to identify promising candidates for experimental inquiry. Increasing the steric demand of the P aryl groups from o -tolyl (in L1 ) to mesityl (in L16 ) resulted in a significant lowering of the barrier to C–N reductive elimination (Δ G ⧧ RE ), which can be attributed in part to interactions between the ligand P aryl groups and the nickel-bound amido ligand, as observed in noncovalent interaction (NCI) plots of the reductive elimination transition-state structures. Despite the favorability of L16 predicted on the basis of computational analysis focusing on C–N reductive elimination, this ancillary ligand performed poorly in experimental testing versus L1, suggesting that in practice the significant steric demands of L16 may discourage the formation of key catalytic intermediates. Modifications to the steric profile of the P aryl groups in L1 led to dramatic changes in catalytic performance, with the presence of an o -methyl proving to be important, among the L1 variants tested, in achieving useful catalytic performance in the Ni-catalyzed monoarylation of ammonia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".