Improvement of Water Barrier Property of Paperboard by Coating Application with Biodegradable Polymers
Bibliographic record
Abstract
Biopolymeric coatings were prepared and applied onto paperboard to improve its water barrier property. To prepare whey protein isolate (WPI)/cellulose-based films, WPI and glycerol were dissolved in water with glutaraldehyde (cross-linking agent) and cellulose xanthate. The solution was cast, dried, and insolubilized by entrapment of WPI in regenerated cellulose. Films were combined with beeswax (BW) into a bilayer coating system and then applied onto paperboard by heating compression. Another coating solution consisting of poly(vinyl butyral) (PVB)/zein was prepared by dissolving poly(vinyl alcohol) (PVA) and zein in 70% ethanol with glutaraldehyde and butyraldehyde (functionalization agent). The PVB/zein solution was applied onto paperboard after BW was sprayed. The structure of the PVB/zein-based coatings was analyzed by Fourier transform infrared spectroscopy (FTIR). The water vapor barrier property of coated paperboards was evaluated by water vapor transmission rate (WVTR) measurements. From the FTIR spectra, PVA functionalization after cross-linking and efficient acetalization into PVB were confirmed. WPI/cellulose and PVB/zein coating treatments improved the water barrier properties of paperboard by decreasing the WVTR by 77-78%. Although the BW coating was more efficient (decrease of WVTR by 89%), bilayer coatings composed of BW and polymer coatings had a stronger barrier effect with a decrease of WVTR to 92-95%, hence approaching commercial attributes required to ensure water vapor barrier in paperboard-based food containers (10 g/m(2).day). These results suggest that surface coating by biodegradable polymers may be utilized for the manufacture of paperboard containers in industrial applications.
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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 | 0.000 | 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 teacher head, 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".