Gold N‐Heterocyclic Carbene Catalysts for the Hydrofluorination of Alkynes Using Hydrofluoric Acid: Reaction Scope, Mechanistic Studies and the Tracking of Elusive Intermediates
Bibliographic record
Abstract
An efficient and chemoselective methodology deploying gold-N-heterocyclic carbene (NHC) complexes as catalysts in the hydrofluorination of terminal alkynes using aqueous HF has been developed. Mechanistic studies shed light on an in situ generated catalyst, formed by the reaction of Brønsted basic gold pre-catalysts with HF in water, which exhibits the highest reactivity and chemoselectivity. The catalytic system has a wide alkyl substituted-substrate scope, and stoichiometric as well as catalytic reactions with tailor-designed gold pre-catalysts enable the identification of various gold species involved along the catalytic cycle. Computational studies aid in understanding the chemoselectivity observed through examination of key mechanistic steps for phosphine- and NHC-coordinated gold species bearing the triflate counterion and the elusive key complex bearing a bifluoride counterion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".