C–O and C–N Functionalization of Cationic, NCN-Type Pincer Complexes of Trivalent Nickel: Mechanism, Selectivity, and Kinetic Isotope Effect
Bibliographic record
Abstract
This report presents the synthesis of new mono- and dicationic NCN-Ni III complexes and describes their reactivities with protic substrates. (NCN is the pincer-type ligand κ N, κ C, κ N - 2,6-(CH 2 NMe 2 ) 2 -C 6 H 3 .) Treating van Koten’s trivalent complex (NCN)Ni III Br 2 with AgSbF 6 in acetonitrile gives the dicationic complex [(NCN)Ni III (MeCN) 3 ] 2+, whereas the latter complex undergoes a ligand-exchange reaction with (NCN)Ni III Br 2 to furnish the related monocationic complex [(NCN)Ni III (Br)(MeCN)] + . These trivalent complexes have been characterized by X-ray diffraction analysis and EPR spectroscopy. Treating these trivalent complexes with methanol and methylamine led, respectively, to C-OCH 3 or C-NH(CH 3 ) functionalization of the Ni-aryl moiety in these complexes, C-heteroatom bond formation taking place at the ipso -C. These reactions also generate the cationic divalent complex [(NCN)Ni II (NCMe)] +, which was prepared independently and characterized fully. The unanticipated formation of the latter divalent species suggested a comproportionation side reaction between the cationic trivalent precursors and a monovalent species generated at the C–O and C–N bond formation steps; this scenario was supported by direct reaction of the trivalent complexes with the monovalent compound (PPh 3 ) 3 Ni I Cl. Kinetic measurements and density functional theory analysis have been used to investigate the mechanism of these C–O and C–N functionalization reactions and to rationalize the observed inverse kinetic isotope effect in the reaction of [(NCN)Ni III (Br)(MeCN)] + with CH 3 OH/CD 3 OD.
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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 | 0.001 | 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".