Mussel-Inspired Green Metallization of Silver Nanoparticles on Cellulose Nanocrystals and Their Enhanced Catalytic Reduction of 4-Nitrophenol in the Presence of β-Cyclodextrin
Bibliographic record
Abstract
A green approach to anchor silver nanoparticles (AgNPs) onto the surface of cellulose nanocrystals (CNCs) coated with mussel-inspired polydopamine (PDA) at room temperature in the absence of a stabilizer and a reducing agent is proposed. The resulting nanohybrids possessed a core–shell structure with numerous “satellites” of silver nanoparticles decorating the CNC surface. The nanocatalyst displayed superior dispersibility over pristine AgNPs and was six times more efficient in catalyzing the reduction of 4-nitrophenol. By associating the CNC hybrid with β-cyclodextrin to promote host–guest interactions, the catalytic process was accelerated. The associated physicochemical parameters associated with the catalytic process were investigated and compared.
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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) | 0.000 | 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 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".