A Dicopper Nitrenoid by Oxidation of a Cu<sup>I</sup>Cu<sup>I</sup> Core: Synthesis, Electronic Structure, and Reactivity
Bibliographic record
Abstract
A dicopper nitrenoid complex was prepared by formal oxidative addition of the nitrenoid fragment to a dicopper(I) center by reaction with the iminoiodinane PhINTs (Ts = tosylate). This nitrenoid complex, (DPFN)Cu 2 (μ-NTs)[NTf 2 ] 2 (DPFN = 2,7-bis(fluorodi(2-pyridyl)methyl)-1,8-naphthyridine), is a powerful H atom abstractor that reacts with a range of strong C–H bonds to form a mixed-valence Cu(I)/Cu(II) μ-NHTs amido complex in the first example of a clean H atom transfer to a dicopper nitrenoid core. In line with this reactivity, DFT calculations reveal that the nitrenoid is best described as an iminyl (NR radical anion) complex. The nitrenoid was trapped by the addition of water to form a mixed-donor hydroxo/amido dicopper(II) complex, which was independently obtained by reaction of a Cu 2 (μ-OH) 2 complex with an amine through a protonolysis pathway. This mixed-donor complex is an analogue for the proposed intermediate in copper-catalyzed Chan–Evans–Lam coupling, which proceeds via C–X (X = N or O) bond formation. Treatment of the dicopper(II) mixed donor complex with MgPh 2 (THF) 2 resulted in generation of a mixture that includes both phenol and a previously reported dicopper(I) bridging phenyl complex, illustrating that both reduction of dicopper(II) to dicopper(I) and concomitant C–X bond formation are feasible.
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".