DFT-guided Development of New Hemilabile (P^N) Ligands for Gold-(I/III) RedOx Catalysis : Application to the Thiotosylation of Aryl Iodides
Bibliographic record
Abstract
Ligand-enabled oxidative addition of Csp2-X bonds to Au(I) centers has recently appeared as a valuable strategy for the development of catalytic RedOx processes. Several cross-coupling reactions that were previously considered difficult to achieve were reported lately, thus expanding the synthetic potential of gold(I) complexes beyond the traditional nucleophilic functionalization of pi-systems. MeDalPhos has played an important role in this development and, despite several studies on alternative structures, remains so far, the only general ligand for such process. We report herein the discovery and the DFT-guided structural optimization of a new family of hemilabile (P^N) ligands that can promote oxidative addition of aryl iodides to gold(I). These flexible ligands, which possess a common 2-methylamino heteroaromatic N-donor motif, are structurally and electronically tunable, beyond being easily accessible and affordable. The corresponding Au(I) complexes were shown to outperform the reactivity of (MeDalPhos)Au(I) in a series of alkoxy- and amidoarylation of alkenes. Their synthetic potential and comparatively higher reactivity were further highlighted in the thiotosylation of aryl iodides, a challenging unreported C-S cross-coupling reaction that could not be achieved under classical Pd(0/II) catalysis and that allows a general and divergent access to aryl sulfur derivatives.
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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) | 0.000 | 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) | 0.002 | 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".