Ferrocene-Containing Polycarbosilazanes via the Alkaline-Earth-Catalyzed Dehydrocoupling of Silanes and Amines
Bibliographic record
Abstract
Abstract We report the use of the alkaline-earth (Ae) metal-catalyzed dehydrocoupling of silanes and amines for the synthesis of ferrocene-containing polycarbosilazanes. The barium complex [Ba(N(SiMe3)2)2·(THF)2] catalyzed the dehydrocoupling of the hydrosilane FeCp(CpSiPhH2) (1) with 1,4-(H2NCH2)2C6H4 under mild conditions to give a polycarbosilazane with pendant ferrocene groups. The polymer could be readily cross-linked by the addition of phenylsilane to the unquenched reaction mixture. Well-defined polycarbosilazanes with ferrocene in the main chain were also obtained from the dehydrocoupling of hydrosilanes Fe(Cp(SiPhH2))2 (3) and Fe(Cp(SiMe2H))2 (IX) with 1,4-(H(Me)NCH2)2C6H4 and 1,4-(H2NCH2)2C6H4, respectively. Crystalline monomeric analogues, FeCp(Cp(SiPh(NHBn)2)) (2, Bn = CH2(C6H5)), and Fe(Cp(SiPh(NHBn)2))2 (4), were also obtained via the dehydrocoupling benzylamine with 1 and 3, respectively. The barium-catalyzed dehydrocoupling of diaminoferrocene with Ph2SiH2 or Ph(Rc)SiH2 (6, Rc = (C5H4)Ru(C5H5)) did not result in polymer, but instead in the formation of the silazane-bridged ansa-[3]ferrocenophanes (Fe(η-C5H4NH)2SiPh2) (5) and (Fe(η-C5H4NH)2SiPh(Rc)) (7), respectively. Both polymeric and molecular products were electrochemically investigated, and the polymers proved to be promising precursors to magnetic iron-containing ceramics in yields of up to 64%.
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".