Regioselective formation of fluorinated metallacycles from fluoroalkenes and an electron-rich Ni(0) difluorocarbene
Bibliographic record
Abstract
The reactivity of an electron-rich Ni-difluorocarbene complex, Ni=CF2(dppe)[P(OMe)3] (1), with a variety of fluorinated alkenes was investigated (dppe = 1,2-bis(diphenylphosphino)ethane). Reactions of 1 with perfluoro(methyl vinyl ether) and chlorotrifluoroethylene (CTFE) give regiospecific formation of metallacyclobutanes, in which the carbene C attacks the most electron-rich carbon of the fluoroalkene. Further reaction of the CTFE-derived metallacycle in the presence of tetrahydrofuran affords a single isomer of NiCl(σ-CF2CF=CFH) (dppe), 8, proposed to be formed by Ni-mediated Cα-Cl activation followed by hydride abstraction and loss of HF. Although 1 also undergoes a cyclization reaction with trifluoroethylene (TrFE), instability of the presumed nickelacyclobutane affords the C3 fluoroalkene, F2C=CH(CF3), and subsequent formation of isomeric metallacyclopentanes from two additional TrFEs. Alternatively, reaction of 1 with hexafluoropropene forms an unexpected Ni–CF3 σ-perfluoroallyl complex.
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) | 0.002 | 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".