Green Development of Biodegradable Films Based on Native Yam (Dioscoreaceae) Starch Mixtures
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
Mixtures of starch comprising starches from different botanical origins and species can improve the mechanical properties of films and coatings. Here, the aim is to develop a sustainable process of starch modification to obtain enhanced starch films through mixing three Dioscoreaceae starches and to study the films resultant mechanical (tensile strength and elongation at break), thermal (glass transition and melting temperature), and physicochemical (moisture, solubility, thickness, color, transparency, light transmission, water vapor permeability, crystallinity, and surface uniformity) properties. The films obtained after the mixing process show low moisture content and high transparency, high solubility desirable for biodegradability, and significantly different thickness. An improved light barrier is achieved and water vapor permeability barrier properties are obtained. Using differential scanning calorimetry, it is observed that the glass transition temperature of the films decreased. The starch mixture improves the mechanical characteristics of the films by 200% for tensile strength and 232% for elongation at break. After mixing, the films show increased crystallinity and no crack or pinholes in their surface. These findings demonstrate that the yam‐starch mixtures form strong and flexible films suitable for various industrial products through a simple green process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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