Robust Guar Gum/Cellulose Nanofibrils Multilayer Films with Good Barrier Properties
Bibliographic record
Abstract
The pursuit of sustainable functional materials requires development of materials based on renewable resources and efficient fabrication methods. Hereby, we fabricated all-polysaccharides multilayer films using cationic guar gum (CGG) and anionic cellulose nanofibrils (i.e., TEMPO-oxidized cellulose nanofibrils, TOCNs) through a layer-by-layer casting method. This technique is based on alternate depositions of oppositely charged water-based CGG and TOCNs onto laminated films. The resultant polyelectrolyte multilayer films were transparent, ductile, and strong. More importantly, the self-standing films exhibited excellent gas (water vapor and oxygen) and oil barrier performances. Another outstanding feature of these resultant films was their resistance to various organic solvents including methanol, acetone, N,N-dimethylacetamide (DMAc) and tetrahydrofuran (THF). The proposed film fabrication process is environmentally benign, cost-effective, and easy to scale-up. The developed CGG/TOCNs multilayer films can be used as a renewable material for industrial applications such as packaging.
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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".