Papaya peel waste carbon dots/reduced graphene oxide nanocomposite: From photocatalytic decomposition of methylene blue to antimicrobial activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Carbon dots (CDs) have gained unprecedented attention as a novel luminescent zero-dimensional carbon nanomaterial owing to their diverse industrial applications. Herein, we reported the sustainable synthesis of fluorescent CDs from papaya peel waste, acting as a natural carbon originator. As-prepared CDs and reduced graphene oxide (RGO) were fabricated in the composites through a facile one-step hydrothermal method. Synthesized RGO/CDs (RC) nanocomposites were characterized using spectroscopic, diffraction, and electron-microscopic techniques. Nanocomposites with variable RGO to CD mass ratios were tested for photodegradation of textile dye methylene blue (MB). The highest photocatalytic activity (degradation efficiency of 87% in 135 min) was obtained in the nanocomposite containing a 2꞉1 mass ratio (RC2). The RGO sheets in the nanocomposite acted as media for electron acceptors, promoting the fast transfer and separation of photoinduced electrons during CDs excitation, thus preventing the recombination of the electron and holes. Based on the agar well diffusion assay, the nanocomposites exhibited excellent antibacterial activity than other tested materials against Bacillus subtilis (Gram-positive) and Pseudomonas aeruginosa (Gram-negative) bacterium. The largest inhibition zone area (22 mm), i.e., the highest antimicrobial activity, was obtained in the nanocomposite tested against Gram-positive strains. Taken together, the synergistic effect of RGO and CDs enhanced the photocatalytic and antibacterial performance of synthesized nanocomposite material.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it