Synergistic Polymer Coatings with Antibacterial and Antiviral Properties for Healthcare Applications
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The role of frequently touched surfaces in the transmission of infectious diseases is well-documented, and the urgent need for effective surface technologies with antipathogen activity has been highlighted by the recent global pandemic and rise in antimicrobial resistance. Here, we have explored combinations of up to 3 different classes of compounds within a polymeric matrix to enable the fabrication of coatings with broad-spectrum activity. Compounds were either based on metals or metal oxides, namely, copper, silver, and copper oxide, essential oils, namely, cinnamaldehyde, tea tree oil, and carvacrol oil, or cationic polymers, namely, poly(ε-lysine) and poly(hexamethylene biguanide). These compounds were mixed into a polymer matrix, coated, and dried to yield durable coatings. Coatings containing up to 7.5% (w/w) of the compounds were assessed in the zone of inhibition and biofilm assays using Staphylococcus aureus and Pseudomonas aeruginosa, as well as infectivity assays using human coronavirus OC43. Our data demonstrate that a selected combination of additives was able to provide a 5-log reduction in the colony-forming units of both bacteria and a 4-log reduction in viral infectivity. This simple but highly effective technology is expected to find applications in environments such as hospitals, aged care facilities, or public transport.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".