Iron-Mediated Hydrazine Reduction and the Formation of Iron-Arylimide Heterocubanes
Bibliographic record
Abstract
The reaction of Fe(N{SiMe(3)}(2))(2) (1) with 1 equiv of arylthiol (ArSH) results in material of notional composition Fe(SAr)(N{SiMe(3)}(2)) (2), from which crystalline Fe(2)(μ-SAr)(2)(N{SiMe(3)}(2))(2)(THF)(2) (Ar = Mes) can be isolated from tetrahydrofuran (THF) solvent. Treatment of 2 with 0.5 equiv of 1,2-diarylhydrazine (Ar'NH-NHAr', Ar' = Ph, p-Tol) yields ferric-imide-thiolate cubanes Fe(4)(μ(3)-NAr')(4)(SAr)(4) (3). The site-differentiated, 1-electron reduced iron-imide cubane derivative [Fe(THF)(6)][Fe(4)(μ(3)-N-p-Tol)(4)(SDMP)(3)(N{SiMe(3)}(2))](2) ([Fe(THF)(6)][4](2); DMP = 2,6-dimethylphenyl) can be isolated by adjusting the reaction stoichiometry of 1/ArSH/Ar'NHNHAr' to 9:6:5. The isolated compounds were characterized by a combination of structural (X-ray diffraction), spectroscopic (NMR, UV-vis, Mössbauer, EPR), and magnetochemical methods. Reactions with a range of hydrazines reveal complex chemical behavior that includes not only N-N bond reduction for 1,2-di- and trisubstituted arylhydrazines, but also catalytic disproportionation for 1,2-diarylhydrazines, N-C bond cleavage for 1,2-diisopropylhydrazine, and no reaction for hindered and tetrasubstituted hydrazines.
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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".