Orientation of Polylactic Acid–Chitin Nanocomposite Films via Combined Calendering and Uniaxial Drawing: Effect on Structure, Mechanical, and Thermal Properties
Bibliographic record
Abstract
The orientation of polymer composites is one way to increase the mechanical properties of the material in a desired direction. In this study, the aim was to orient chitin nanocrystal (ChNC)-reinforced poly(lactic acid) (PLA) nanocomposites by combining two techniques: calendering and solid-state drawing. The effect of orientation on thermal properties, crystallinity, degree of orientation, mechanical properties and microstructure was studied. The orientation affected the thermal and structural behavior of the nanocomposites. The degree of crystallinity increased from 8% for the isotropic compression-molded films to 53% for the nanocomposites drawn with the highest draw ratio. The wide-angle X-ray scattering results confirmed an orientation factor of 0.9 for the solid-state drawn nanocomposites. The mechanical properties of the oriented nanocomposite films were significantly improved by the orientation, and the pre-orientation achieved by film calendering showed very positive effects on solid-state drawn nanocomposites: The highest mechanical properties were achieved for pre-oriented nanocomposites. The stiffness increased from 2.3 to 4 GPa, the strength from 37 to 170 MPa, the elongation at break from 3 to 75%, and the work of fracture from 1 to 96 MJ/m3. This study demonstrates that the pre-orientation has positive effect on the orientation of the nanocomposites structure and that it is an extremely efficient means to produce films with high strength and toughness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".