Silver metal nanoparticles: Facile dendrimer‐assisted size‐controlled synthesis and selective catalytic reduction of chloronitrobenzenes
Bibliographic record
Abstract
Abstract A simple and versatile synthetic methodology to silver metal nanoparticles that utilizes 3,5‐dihydroxybenzyl alcohol‐based dendrimers as templates and does not necessitate the addition of any external reducing agent is reported. An evaluation of the role of addition rate of the silver acetate solution, and the dendrimer to silver acetate molar ratio, as well as the dendritic effect on nanoparticle growth, suggests that the size of these metal nanoparticles can be controlled by simple variations of these parameters. A probe of the mechanism of the nanoparticle formation and growth indicates that the terminal hydroxyl groups of the dendrimers play a major role in metal ion isolation and reduction, in addition to providing stabilization to the growing metal particles. These silver metal nanoparticles are highly active catalysts for the selective reduction of chloronitrobenzenes to chloroanilines. © 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 47: 4482–4493, 2009
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".