C(sp<sup>2</sup>)–H Borylation of Fluorinated Arenes Using an Air-Stable Cobalt Precatalyst: Electronically Enhanced Site Selectivity Enables Synthetic Opportunities
Bibliographic record
Abstract
Abstract Cobalt catalysts with electronically enhanced site selectivity have been developed, as evidenced by the high ortho-to-fluorine selectivity observed in the C(sp2)–H borylation of fluorinated arenes. Both the air-sensitive cobalt(III) dihydride boryl 4-Me-(iPrPNP)Co(H)2BPin (1) and the air-stable cobalt(II) bis(pivalate) 4-Me-(iPrPNP)Co(O2CtBu)2 (2) compounds were effective and exhibited broad functional group tolerance across a wide range of fluoroarenes containing electronically diverse functional groups, regardless of the substitution pattern on the arene. The electronically enhanced ortho-to-fluorine selectivity observed with the cobalt catalysts was maintained in the presence of a benzylic dimethylamine and hydrosilanes, overriding the established directing-group effects observed with precious-metal catalysts. The synthetically useful selectivity observed with cobalt was applied to an efficient synthesis of the anti-inflammatory drug flurbiprofen.
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".