Synthesis and Elaboration of the Dinuclear Iron-Imide Cluster Core [Fe<sub>2</sub>(μ-NR)<sub>2</sub>]<sup>2+</sup>
Bibliographic record
Abstract
The protolysis of mononuclear ferric amide precursors FeCl[N(SiMe3)2]2(THF) (1) or [FeCl2{N(SiMe3)2}2]- (2) by primary amines provides, under suitable conditions, an effective route to dinuclear weak-field ferric-imide clusters with [Fe2(mu-NR)2]2+ cores. In the synthesis of known arylimide clusters [Fe2(mu-NAr)2Cl4]2- (Ar = Ph, p-Tol, Mes) from 2, the counterion has a major effect on selectivity and yield, and the use of quaternary ammonium salts affords a substantial improvement over earlier, Li+-based chemistry. The new tert-butylimide core is obtained by protolysis of 1 with excess tBuNH2 to give crystalline cis-Fe2(mu-NtBu)2Cl2(NH2tBu)2 (9). Complex 9 can be transformed to other dinuclear species through substitution of the terminal amines by pyridines, PEt3, or chloride, or through protolysis of bridging alkylimides by arylamines, allowing isolation of trans-Fe2(mu-NtBu)2Cl2(DMAP)2 (DMAP = 4-dimethylaminopyridine), cis-Fe2(mu-NtBu)2Cl2(PEt3)2, [Fe2(mu-NtBu)2Cl4]-, and trans-Fe2(mu-NPh)2Cl2(NH2tBu)2. The susceptibility of alkyl substituents to beta-elimination appears to limit the general applicability of protolytic cluster assembly using alkylamines. The dinuclear clusters have been characterized by X-ray, spectroscopic, and electrochemical analyses.
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 | 0.001 |
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".