Transparent and Conducting Graphene–RNA‐Based Nanocomposites
Bibliographic record
Abstract
Ribonucleic acid (RNA) is proposed as a nonionic surfactant for the efficient exfoliation of graphite in thin flakes of few-layer graphene and the subsequent preparation of transparent and conducting thin films. Parameters such as the type of RNA used and the size of starting graphite flakes are demonstrated to be essential for obtaining RNA-graphene thin films of good quality. A model explaining the exfoliation of graphene by RNA in water is suggested. A number of post- and predeposition treatments (including thermal annealing, functionalization of the films, and the preoxidation of graphite) are critical to improve the performance of graphene-RNA nanocomposites as transparent conductors. The study establishes an ideal link between RNA and graphene, the fundamental building blocks for nanobiology and carbon-based nanotechnology.
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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".