Characterization of Trilayer Antimicrobial Diffusion Films (ADFs) Based on Methylcellulose–Polycaprolactone Composites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Novel trilayer antimicrobial diffusion films (ADFs) were developed for food applications. ADFs were composed of two external layers of polycaprolactone and one internal layer of nanocrystalline cellulose (NCC)-reinforced methylcellulose (MC) matrix. Two antimicrobial mixtures (formulations A and B) were incorporated in the MC layer and compared via the evaluation of film properties. Resulting ADFs were inserted as diffusion devices into vegetable packages, and samples were stored at 4 °C for 14 days. Microbiological diffusion assays in the presence of ADFs were performed on pathogenic bacteria. From this, the study focused on characterizing the structural, physicochemical properties and total phenols (TP) release from ADFs. This TP release was determined by Folin-Ciocalteu's method and by FTIR analysis. Results indicated a controlled release of antimicrobials into the headspace (16.5% for formulation A and 13.4% for formulation B). Good correlations (≥90%) between both methods allowed validating an innovative, accurate, rapid FTIR procedure to quantify the diffusion of TP. SEM micrographs showed fibrillar structure due to NCC and a more compact network due to antimicrobials. Encapsulated antimicrobial formulations induced color changes without affecting visual attributes of films. ADFs containing formulation B exhibited the highest tensile strength (17.3 MPa) over storage.
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.
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) | 0.001 | 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 it