Brazilin-Loaded Biodegradable Electrospun Membranes with Tunable Release for Active and Intelligent Food Packaging - Litke et al. (2026)
Bibliographic record
Abstract
This document contains the experimental data generated during the preparation of the manuscript "Brazilin-Loaded Biodegradable Electrospun Membranes with Tunable Release for Active and Intelligent Food Packaging". This study reports the fabrication and characterization of electrospun poly(lactic acid) (PLA) and poly(ethylene glycol) (PEG) membranes incorporating brazilin, a natural polyphenolic compound with antioxidant, antimicrobial, and pH-responsive dye properties. Monoaxial and coaxial electrospinning were employed to tailor fiber morphology and release kinetics, enabling modulation from rapid to sustained diffusion. The dataset documents the analysis of the fibers via SEM and fluorescent microscopy, the analysis of the swelling and release behaviour of the fibers, the antioxidant activity (ABTS and FRAP), the antibacterial behavior, as well as the colourimetric response to changes in pH. Collectively, these findings establish brazilin-loaded electrospun membranes as multifunctional, biodegradable packaging materials that integrate active protection with intelligent sensing. By uniting sustained antioxidant activity, targeted antimicrobial efficacy, and visible spoilage indication, this work advances the development of next-generation packaging technologies that enhance food quality, safety, and sustainability.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".