Biodegradable polyhydroxybutyrate microfiber membranes decorated with photoactive <scp>Ag‐TiO<sub>2</sub></scp> nanoparticles for enhanced antibacterial and anti‐biofouling activities
Bibliographic record
Abstract
Abstract Developing advanced materials with antibacterial and antifouling activities offers an adequate protection solution against surface bacterial contamination—a common cause of infection threatening human health. The current work reports the preparation of polyhydroxybutyrate (PHB) microfiber membranes decorated with photoactive Ag‐TiO 2 nanoparticles using electrospinning coupled with dip‐coating methods. The decoration of Ag‐TiO 2 nanoparticles strongly enhances the antibacterial properties of prepared membranes, particularly under light illumination, thanks to their photocatalytic activity. The best‐performing sample exhibits potent antibacterial efficiency exceeding 99% against Escherichia coli and Staphylococcus epidermidis after 3 and 1 h of exposure to low‐power commercial LED light, respectively. The prepared samples also display excellent reusability with an insignificant antibacterial activity decrease after three cycles (<2% loss in antibacterial efficiency). Furthermore, these samples effectively prevent bacterial fouling due to their potent antibacterial properties. Notably, despite the strong antibacterial effect, decorated Ag‐TiO 2 nanoparticles promote the adhesion of microorganisms, accelerating the biodegradation of PHB microfibers. As a result, the prepared microfiber membranes with nanoparticle decoration exhibit biodegradability comparable to the non‐decorated membrane, with the soil degradation rates reaching almost 99% after only 6 weeks.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".