Structural, Thermal, Physical, Mechanical, and Barrier Properties of Chitosan Films with the Addition of Xanthan Gum
Bibliographic record
Abstract
Abstract Films based on chitosan and xanthan gum were prepared using casting technique aiming to investigate the potential of these polymers as packaging materials. Six formulations of films were studied varying the proportion of chitosan and xanthan gum: 100:0 (chitosan:xanthan gum, w/w, C100XG0 film); 90:10 (chitosan:xanthan gum, w/w, C90XG10 film); 80:20 (chitosan:xanthan gum, w/w, C80XG20 film); 70:30 (chitosan:xanthan gum, w/w, C70XG30 film); 60:40 (chitosan:xanthan gum, w/w, C60XG40 film); and 50:50 (chitosan:xanthan gum, w/w, C50XG50 film). The total quantity of solids (chitosan and xanthan gum) in the filmogenic solution was 1.5 g per 100 mL of aqueous solution for all treatments, according to the proportion of each polymer. The films were evaluated by their functional groups, structural, thermal, morphological, physical, mechanical, and barrier properties. All films have presented endothermic peaks in the range of 122 to 175 °C and broad exothermic peaks above 200 °C, which were assigned to the melting temperature and thermal decomposition, respectively. These results demonstrated that films with xanthan gum have the highest T m and Δ m H . The films containing higher content of xanthan gum show also the highest tensile strength and the lowest elongation. Xanthan gum addition did not affect the water vapor permeability, solubility, and moisture of films. This set of data suggests the formation of chitosan–xanthan complexes in the films.
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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) | 0.001 | 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; 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".