Activation of Aryl and Heteroaryl Halides by an Iron(I) Complex Generated in the Reduction of [Fe(acac)<sub>3</sub>] by PhMgBr: Electron Transfer versus Oxidative Addition
Bibliographic record
Abstract
The mechanism of the reactions of aryl/heteroaryl halides with aryl Grignard reagents catalyzed by [Fe(III)(acac)3] (acac=acetylacetonate) has been investigated. It is shown that in the presence of excess PhMgBr, [Fe(III)(acac)3] affords two reduced complexes: [PhFe(II)(acac)(thf)n] (n=1 or 2) (characterized by (1)H NMR and cyclic voltammetry) and [PhFe(I)(acac)(thf)](-) (characterized by cyclic voltammetry, (1)H NMR, EPR and DFT). Whereas [PhFe(II)(acac)(thf)n] does not react with any of the investigated aryl or heteroaryl halides, the Fe(I) complex [PhFe(I)(acac)(thf)](-) reacts with ArX (Ar=Ph, 4-tolyl; X=I, Br) through an inner-sphere monoelectronic reduction (promoted by halogen bonding) to afford the corresponding arene ArH together with the Grignard homocoupling product PhPh. In contrast, [PhFe(I)(acac)(thf)](-) reacts with a heteroaryl chloride (2-chloropyridine) to afford the cross-coupling product (2-phenylpyridine) through an oxidative addition/reductive elimination sequence. The mechanism of the reaction of [PhFe(I)(acac)(thf)](-) with the aryl and heteroaryl halides has been explored on the basis of DFT calculations.
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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 | 0.000 | 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".