Characterization and environmental footprint of crosslinked faba bean starch-based ecofilms reinforced with tunicate cellulose nanocrystals
Bibliographic record
Abstract
The growing demand for sustainable materials has intensified efforts to valorize by-products such as faba bean starch (FBS), a co-product of seed fractionation currently lacking high-value applications. This study investigates the development of ecofilms from crosslinked air classified (65 % starch content) and isolated (95 % starch content) FBS, reinforced with tunicate cellulose nanocrystals (t-CNCs, 0–6 wt% relative to starch dry weight). Isolated FBS films exhibited superior moisture resistance, with an 8.13 % reduction in water vapor permeability (WVP) at 6 wt% t-CNC, while air classified films showed increased WVP upon t-CNC inclusion. Water solubility ranged from 34.35 % to 53.92 %, and the water contact angle decreased slightly due to hydrogen bonding facilitated by surface hydroxyl groups of the starch and t-CNC. Tensile strength (TS) improved to 3.41 MPa in isolated FBS films at 4 wt% t-CNC threshold compared to 2.95 MPa at 4 wt% t-CNC for air FBS classified films, with elongation at break maintained between 20 and 40 % in all the films. SEM analysis revealed increased surface roughness at higher t-CNC concentrations, FTIR confirmed successful component blending, and XRD indicated amorphous film structures. Antimicrobial activity showed efficacy against food spoilage pathogen ( E. coli ), while thermal stability (97 % weight retention at 150 °C), and a low carbon footprint underscore the films' suitability for sustainable food packaging. These results position crosslinked FBS/t-CNC ecofilms as high-performance, sustainable alternatives to conventional plastics, advancing the development of eco-friendly materials for diverse applications.
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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) | 0.000 | 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".