Improved water resistance and air barrier performances of paper coated with polylactic acid/organoclay nanocomposites
Bibliographic record
Abstract
Abstract Paper packaging coated with synthetic materials raises major environmental and health concerns. As a response, new promising approaches consist of using sustainable coatings based on nano‐biocomposites. In this work, polylactic acid (PLA)/organoclays (OC) aqueous dispersions thickened by xanthan gum were applied on paper using the bar coating technique. Morphological and topographical analyses using scanning electron microscopy and laser confocal microscopy showed a smooth polymeric layer completely covering the fibrous and porous surface of the paper, resulting in a substantial improvement in the barrier properties. Water vapor transmission rates and water absorptivity had undergone a major decrease when coatings containing 3 and 5 wt% OC were used, while no significant difference was observed between the 1 wt% OC formulation and pure PLA. Moreover, coated paper showed no air porosity with 0 mL/min values recorded for all samples, thus confirming the morphology observations of the surfaces and cross‐sections. Additionally, the contact angle measurements indicated a slight decrease in the hydrophobicity of the base paper when coated with PLA and 1 wt% OC. However, this reduction was reversed with the addition of 3 and 5 wt% OC, restoring the hydrophobicity. Highlights Polylactic acid (PLA)/organoclay (OC) coatings sealed and covered completely the paper's surface. Water resistance of the base paper had a major improvement due to the coatings. The porous surface of the paper was successfully sealed, leading to no air porosity. Adding 3 and 5 wt% OC resulted in excellent barrier performances. PLA/OC coatings have the potential to replace synthetic paper coatings.
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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 | 0.001 |
| 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".