Facile nucleation of gold nanoparticles on graphene-based thin films from Au<sub>144</sub>molecular precursors
Bibliographic record
Abstract
We demonstrate a facile and cost effective method to obtain gold nanoparticles on graphene by dispersing Au₁₄₄ molecular nanoclusters by spin coating them in thin layers on graphene-based films and subsequent annealing in a controlled atmosphere. The graphene-based thin films used for these experiments are prepared by solvent-assisted exfoliation of graphite in water in the presence of ribonucleic acid as a surfactant and by subsequent vacuum filtration of the resulting graphene-containing suspensions. Not only is this method easily reproducible, but it leads to gold nanoparticles that are not dependent in size on the number of graphene layers beneath them. This is a distinct advantage over other methods. Plasmonic effects have been detected in our gold nanoparticle-decorated graphene layers, indicating that these thin films may be useful in applications such as plasmonic solar cells and optical memory devices.
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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 | 0.000 | 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) | 0.000 | 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".