Encapsulation of Cinnamon Essential Oil for Active Food Packaging Film with Synergistic Antimicrobial Activity
Bibliographic record
Abstract
Porous adsorption, a less powerful adsorptive force than chemical bonds, is based on the physical adsorption of small molecules onto a solid surface that is capable of adsorbing gas or liquid molecules. Antimicrobial permutite composite (containing Ag+, Zn2+ and Ag+/Zn2+), starting from Linde Type A-permutite (LTA), was obtained in this research. The permutite samples were characterized by field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), colorimeter and nitrogen adsorption technique. Cinnamon essential oil (CEO) was encapsulated into Ag+/Zn2+-permutite. The FT-IR and differential scanning calorimetry (DSC) confirmed that no chemical bond existed between CEO and Ag+/Zn2+-permutite. The loading capacity of Ag+/Zn2+-permutite/CEO was 313.07 µL/g, and it had a sustained release effect. The Ag+/Zn2+-permutite/CEO showed stronger efficacy against Aspergillus niger and Penicillium sp. than Ag+/Zn2+-permutite. Ethyl cellulose pads modified by composite antimicrobial particles were applied in the preservation of Chinese bayberry. Compared to the control group, treatment with the Ag+/Zn2+-permutite/CEO antimicrobial pads resulted in a significantly lower decay incidence. In addition, the amount of migrated silver, zinc and aluminum from LTA was below the legal limit. These results confirmed that the ethyl cellulose pads modified by the Ag+/Zn2+-permutite/CEO provided an active packaging to control decay of fresh Chinese bayberry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".