Unlocking the Aromatic Cope Rearrangement with Gold(I) Catalysis
Bibliographic record
Abstract
The Aromatic Cope Rearrangement (ArCopeR) is a highly challenging chemical reaction under thermal conditions, pri-marily attributed to the loss of aromaticity during the initial [3,3]-sigmatropic step of the process. Such rare transfor-mation typically requires high temperatures and specially engineered 1,5-hexadiene scaffolds, making it impractical for straightforward synthesis of new molecules. Here, we demonstrated that gold(I) catalysts significantly lower the energet-ic barriers associated to ArCopeR, enabling the reaction to be carried out at low temperature (rt to 70°C) in dichloro-ethane or hexafluoroisopropanol with high yields. Specifically, phosphine gold(I) complex ((p-CF3Ph)3PAuOTf) permits for the diastereoselective and divergent aromatic Cope rearrangement from various α-allyl-α’-heteroaromatic γ-lactone or malonate derivatives, while N-heterocyclic carbene gold(I) (IPrAuNTf2) allows the selective dearomatization reaction. Extended quantum mechanics calculations, consistent with experimental observations, reveal that (i) an interweaved transformation occurs instead of the expected ArCope cascade made of formal [3,3]-sigmatropic rearrangement and [1,3]H-shift steps, and that (ii) van der Waals interactions between the catalyst and substrate contribute to the interrupt-ed ArCope process leading to dearomatize products. This study presents the first catalytic and synthetically useful proto-col to promote ArCopeR under mild conditions.
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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".