Enhanced colloidal stability and antibacterial performance of silver nanoparticles/cellulose nanocrystal hybrids
Bibliographic record
Abstract
The aggregation of nanoparticles has been shown to significantly reduce the activity of nanomaterials, resulting in inferior performance. As an alternative to the use of traditional capping agents, stabilization of unstable nanoparticles with water-dispersible and biocompatible carriers is a promising strategy. A bioinspired coating strategy was developed and the hybrid nanoparticles displayed excellent colloidal stability that significantly improved antibacterial activity when silver nanoparticles (AgNPs) were used as a model. Cellulose nanocrystals (CNCs) were first modified with dopamine, followed by in situ generation and anchoring of AgNPs on the surface of CNCs through the reduction of silver ions by polydopamine coated CNCs. The results indicated that the dispersion stability of AgNPs was significantly enhanced by the CNC, which in turn resulted in more than fourfold increase in antibacterial activity based on antibacterial studies using Escherichia coli and Bacillus subtilis.
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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".