A green synthesis route of <scp>ZnO</scp> /polyhydroxybutyrate composites with antibacterial and biodegradable properties
Bibliographic record
Abstract
Abstract The development of environmentally friendly polymer‐based materials with antibacterial and biodegradable properties is bringing significant benefits to the packaging industry. In the present work, green‐synthesized zinc oxide microporous particles (ZnO MPs) are dispersed in the poly(3‐hydroxybutyrate) (PHB) matrix using a simple casting method to prepare bioactive films with improved antibacterial and anti‐biofouling properties. The resultant films display a microporous morphology with a uniform dispersion of ZnO MPs within the polymeric matrix. The incorporation of green‐synthesized ZnO MPs (3% wt) into PHB films leads to potent antibacterial activity, notably under LED light, with bacterial inactivation efficiencies of 97.5% and 76.2% against Escherichia coli and Staphylococcus epidermidis , respectively, after 90 min of light irradiation. This antibacterial activity is superior to that induced by films loaded with the same amount of commercial ZnO nanoparticles. Furthermore, the potent antibacterial activity gives rise to improved anti‐biofouling for prepared films, in which the biofilm formation on their surface is effectively eliminated. Notably, the ZnO MP incorporation improves the microbe adhesion, accelerating the biodegradation of developed films, with soil biodegradation rates reaching 99% in 10 weeks. The present work offers a simple and cost‐effective approach to producing promising composites with prolonged shelf‐life and the capability of reducing bacterial contamination for packaging industry applications. Highlights 99% bacterial inhibition for Escherichia coli and 95% for Staphylococcus epidermidis . Microfiltration efficiency >99% achieved in one filtration cycle. Mechanical strength is enhanced by 2.2 times with the addition of gelatin. Biofouling resistance by preventing bacterial attachment. Sustainable membranes with fast biodegradation in soil.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".