Recyclable luminescent carbon dots nanopaper for flexible electronics
Bibliographic record
Abstract
Abstract The use of sustainable materials in high-tech devices is one way to decrease the carbon footprint and tackle global climate change. We first synthesized blue-emissive carbon dots (CDs) from biocompatible onion inner epidermal cells using solvothermal method. Then, cellulose nanofiber was prepared by TEMPO oxidization, followed by homogenization from soft wood source. Finally, the blue emissive CDs-cellulose nanofibers-based nanopaper was fabricated by simple roller-coating approach, and its optical and morphological properties were investigated by transmittance, photoluminescence, fourier-transform infrared (FTIR) and scanning electron microscopy techniques. The results indicate that nanopapers have a high light emission, and that their transparency may be easily adjusted by varying the proportion of CDs content. These nanopapers can be incorporated into flexible and stretchable electronics and optical sensor platforms.
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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".