Long- and short-term antibacterial properties of low-density polyethylene-based films coated with zinc oxide nanoparticles for potential use in food packaging
Bibliographic record
Abstract
Concerns in food safety and the need for high-quality foods have increased the demand for extending the shelf life of packaged foods. Subsequently, promoting and investigating the development of antibacterial materials for food packaging has become inevitable. Zinc oxide nanoparticles have attracted attention lately owing to their multifunctional properties, especially antibacterial activity. For this study, antibacterial low-density polyethylene films were prepared by coating zinc oxide nanoparticles onto their surface. The low-density polyethylene film antibacterial activity was evaluated toward Gram-positive and Gram-negative bacteria. The scanning electron microscopy images showed that using anhydride-modified low-density polyethylene (LDPE-g-AM) resin permitted improved zinc oxide nanoparticle distribution on the low-density polyethylene film surface, reduced the agglomerate sizes, and reinforced the zinc oxide nanoparticle bonding to the low-density polyethylene film surface. We found that the coated low-density polyethylene films exhibited high antibacterial activity against both strains. The antibacterial tests also proved that the coated films retained their antibacterial efficiency toward Escherichia coli, even after eight months, with a reduction rate higher than 99.9%, whereas for Staphylococcus aureus the antibacterial properties for the linear low-density polyethylene (LLDPE) films decreased at eight months and improved for the LDPE-g-AM films. When the zinc oxide coated films were laminated with neat low-density polyethylene, only the LDPE-g-AM was still active against E. coli provided that the lamination thickness does not go beyond 8 µm. This research demonstrated that the coated low-density polyethylene films have excellent attributes when used as an active coating in the food packaging industry.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".