Generation of Hydrofluoronickelacycles from Trifluoroethylene and Ni(0): Ligand Effects on Regio-/Stereoselectivity and Reactivity
Bibliographic record
Abstract
Treatment of Ni(0) complexes 1a – e with sub-atmospheric pressures of trifluoroethylene (TrFE) affords hydrofluoronickelacyclopentanes L 2 Ni(C 4 F 6 H 2 ) 2a – e (L = PPh 3, P(O- o -tol) 3, PPh 2 Me, PPhMe 2, PMe 3 ). Fluorine NMR analysis of 2a – e demonstrates predominant formation of three (of the possible six) isomers upon oxidative cycloaddition of TrFE: the cis and trans head–tail isomers and the trans head–head isomer, where the CHF group is defined as the TrFE “head”. The respective ratios of L 2 Ni(C 4 F 6 H 2 ) isomers are influenced by the nature of L, with smaller phosphines favoring the thermodynamically preferred (from DFT calculations) trans head–head isomer (cf. 50% with PMe 3 ) and the largest affording small amounts of the tail–tail isomers. Lewis and Brønsted acids induce a surprising double C–F bond activation in 2c – d, affording small functionalized hydrofluoroalkenes. Interestingly, varying the acid employed dictates the organic product obtained from the head–tail isomers: BF 3 ·OEt 2 is selective for 1,1,2,3-tetrafluorocyclobutene, whereas Me 3 SiOTf and N,N -dimethylanilinium bromide yield ( Z,E )-1,1,3,4-tetrafluorobutadiene as the major fluorinated product. Reaction intermediates were isolated, and possible pathways are discussed.
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) | 0.003 | 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".