Ni‐Catalyzed Borylation of Aryl Sulfoxides
Bibliographic record
Abstract
Abstract A nickel/N‐heterocyclic carbene (NHC) catalytic system has been developed for the borylation of aryl sulfoxides with B2(neop)2 (neop=neopentyl glycolato). A wide range of aryl sulfoxides with different electronic and steric properties were converted into the corresponding arylboronic esters in good yields. The regioselective borylation of unsymmetric diaryl sulfoxides was also feasible leading to borylation of the sterically less encumbered aryl substituent. Competition experiments demonstrated that an electron‐deficient aryl moiety reacts preferentially. The origin of the selectivity in the Ni‐catalyzed borylation of electronically biased unsymmetrical diaryl sulfoxide lies in the oxidative addition step of the catalytic cycle, as oxidative addition of methoxyphenyl 4‐(trifluoromethyl)phenyl sulfoxide to the Ni(0) complex occurs selectively to give the structurally characterized complex trans‐[Ni(ICy)2(4‐CF3‐C6H4){(SO)‐4‐MeO‐C6H4}] 4. For complex 5, the isomer trans‐[Ni(ICy)2(C6H5)(OSC6H5)] 5‐I was structurally characterized in which the phenyl sulfinyl ligand is bound via the oxygen atom to nickel. In solution, the complex trans‐[Ni(ICy)2(C6H5)(OSC6H5)] 5‐I is in equilibrium with the S‐bonded isomer trans‐[Ni(ICy)2(C6H5)(SOC6H5)] 5, as shown by NMR spectroscopy. DFT calculations reveal that these isomers are separated by a mere 0.3 kJ/mol (M06/def2‐TZVP‐level of theory) and connected via a transition state trans‐[Ni(ICy)2(C6H5)(η2‐{SO}‐C6H5)], which lies only 10.8 kcal/mol above 5.
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".