Effect of Chitin Nanocrystals on Crystallization and Properties of Poly(lactic acid)-Based Nanocomposites
Bibliographic record
Abstract
The crystalline phase of poly(lactic acid) (PLA) has crucial effects on its own properties and nanocomposites. In this study, the isothermal crystallization of PLA, triethyl citrate-plasticized PLA (PLA-TEC), and its nanocomposite with chitin nanocrystals (PLA-TEC-ChNC) at different temperatures and times was investigated, and the resulting properties of the materials were characterized. Both PLA and PLA-TEC showed extremely low crystallinity at isothermal temperatures of 135, 130, 125 °C and times of 5 or 15 min. In contrast, the addition of 1 wt % of ChNCs significantly improved the crystallinity of PLA under the same conditions owing to the nucleation effect of the ChNCs. The samples were also crystallized at 110 °C to reach their maximal crystallinity, and PLA-TEC-ChNC achieved 48% crystallinity within 5 min, while PLA and PLA-TEC required 40 min to reach a similar level. Moreover, X-ray diffraction analysis showed that the addition of ChNCs resulted in smaller crystallite sizes, which further influenced the barrier properties and hydrolytic degradation of the PLA. The nanocomposites had considerably lower barrier properties and underwent faster degradation compared to PLA-TEC110. These results confirm that the addition of ChNCs in PLA leads to promising properties for packaging 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) | 0.001 | 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 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".