Antifouling Polymer-Coated Anthocyanin-Loaded Cellulose Nanocrystals Demonstrate Reduced Bacterial Detection Capabilities
Bibliographic record
Abstract
Microbial contamination is a global concern with impacts on a variety of industries ranging from marine to biomedical applications. Recent research on hydrophilic polymer-based coatings is focused on combining antifouling polymers with nanomaterials to enhance mechanical, optical, and stimuli-responsive properties, yielding colour changing, self-healing, and super hydrophilic materials. This study combines the hydrophilic and antifouling properties of vitamin B5 analogous methacrylamide (B5AMA)-based polymers with stimuli-responsive anthocyanin-dye-loaded cellulose nanocrystals (CNCs) to develop antifouling materials with colour changing capabilities upon bacterial contamination. Poly(B5AMA)-grafted CNCs were prepared through surface-initiated photoiniferter reversible addition fragmentation chain transfer (SP-RAFT) polymerization and characterized through proton nuclear magnetic resonance (1H-NMR), transmission electron microscopy (SEM/TEM), and X-ray photon spectroscopy (XPS) to confirm the formation of surface-grafted polymer chains. The bare CNCs and poly(B5AMA)-grafted CNCs were loaded with anthocyanin dye and evaluated for pH-dependent colour changing capabilities. Interestingly, anthocyanin-loaded CNCs demonstrated vibrant colour changes in both solution and dried film form upon bacterial contamination; however, limited colour changing capabilities of the composites, specifically in dried film form, were attributed to the enhanced dispersibility and antifouling capabilities of the polymer-coated CNCs.
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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".