Feature Article: Macromolecules Containing Pendent Cationic Cyclopentadienyliron Moieties
Bibliographic record
Abstract
This feature article describes the synthesis of various classes of monomers and polymers incorporating organoiron moieties. Polyethers incorporating η6-substituted-arene-η5-cyclopentadienyliron moieties were synthesized via metal-mediated nucleophilic aromatic substitution reactions. Linear polymers incorporating both cationic and neutral organoiron units were prepared; these polymers underwent two electrochemical processes, oxidation of the neutral iron species occurred between 0.89 and 1.0 V and reduction of the cationic iron groups occurred between −1.10 and −1.45 V. Polynorbornenes, polymethacrylates, and polystyrenes were prepared via radical and condensation polymerization of organoiron functionalized monomers. The incorporation of azo dyes into the polymers gave rise to a variety of colored materials that could be photobleached in the presence of hydrogen peroxide. The incorporation of benzothiazole-based dyes resulted in colored polymers with higher λmax values than azobenzene-based dyes. Photolytic decoordination of the cationic cyclopentadienyliron moieties resulted in the formation of organic analogs or neutral polyferrocenes depending on the nature of the starting polymers. A number of 3-arm star-shaped molecules were also prepared; electrochemical studies showed that the inner and outer iron moieties are reduced at different potentials.
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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) | 0.004 | 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".