Unsymmetrical Diarylmethanes by Ferroceniumboronic Acid Catalyzed Direct Friedel–Crafts Reactions with Deactivated Benzylic Alcohols: Enhanced Reactivity due to Ion-Pairing Effects
Bibliographic record
Abstract
The development of general and more atom-economical catalytic processes for Friedel-Crafts alkylations of unactivated arenes is an important objective of interest for the production of pharmaceuticals and commodity chemicals. Ferroceniumboronic acid hexafluoroantimonate salt (1) was identified as a superior air- and moisture-tolerant catalyst for direct Friedel-Crafts alkylations of a variety of slightly activated and neutral arenes with stable and readily available primary and secondary benzylic alcohols. Compared to the use of classical metal-catalyzed alkylations with toxic benzylic halides, this methodology employs exceptionally mild conditions to provide a wide variety of unsymmetrical diarylmethanes and other 1,1-diarylalkane products in high yield with good to high regioselectivity. The optimal method, using the bench-stable ferroceniumboronic acid salt 1 in hexafluoroisopropanol as cosolvent, displays a broader scope compared to previously reported catalysts for similar Friedel-Crafts reactions of benzylic alcohols, including other boronic acids such as 2,3,4,5-tetrafluorophenylboronic acid. The efficacy of the new boronic acid catalyst was confirmed by its ability to activate primary benzylic alcohols functionalized with destabilizing electron-withdrawing groups like halides, carboxyesters, and nitro substituents. Arene benzylation was demonstrated on a gram scale at up to 1 M concentration with catalyst recovery. Mechanistic studies point toward the importance of the ionic nature of the catalyst and suggest that factors other than the Lewis acidity (pKa) of the boronic acid are at play. A SN1 mechanism is proposed where ion exchange within the initial boronate anion affords a more reactive carbocation paired with the non-nucleophilic hexafluoroantimonate counteranion.
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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) | 0.001 | 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".