Ferrocenyl Functionalized Silver-Chalcogenide Nanoclusters
Bibliographic record
Abstract
New (chalcogenoethyl)ferrocenylcarboxalate functionalized silver chalcogenide nanoclusters were synthesized using a combination of silylated chalcogen reagents at low temperatures. The addition of E(SiMe(3))(2) to reaction mixtures of FcC{O}OCH(2)CH(2)ESiMe(3) (E = S, Se) and (Ph(3)P)(2)·AgOAc affords nanoclusters with approximate molecular formulas [Ag(36)S(9)(SCH(2)CH(2)O{O}CFc)(18)(PPh(3))(3)] (1), [Ag(100)Se(17)(SeCH(2)CH(2)O{O}CFc)(66)(PPh(3))(10)] (2), and [Ag(180)Se(54)(SeCH(2)CH(2)O{O}CFc)(72)(PPh(3))(14)] (3) as noncrystalline solids. Compositions were formulated on the basis of elemental analysis, high resolution transmission electron microscopy, and dynamic light scattering experiments. Solutions of these polyferrocenyl assemblies display a single quasi-reversible redox wave with some adsorption to the electrode surface as studied by cyclic voltammetry. With the smaller clusters 1, the addition of [Bu(4)N][HSO(4)] results in a shift of the reduction wave to less positive potentials than those of the complex in the absence of these oxoanions. No further shift is observed after the addition of approximately 1 equivalent of HSO(4)(-)/ferrocene branch. Cyclic voltammograms of the larger clusters 2 and 3 show the appearance of a new, irreversible wave at less positive potentials than the initial wave upon the addition of HSO(4)(-). The appearance of this new wave together with the disappearance of the reduction wave indicates a stronger interaction between the nanoclusters and the hydrogen sulfate anion.
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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".