Influence of Chitin Nanocrystals on the Crystallinity and Mechanical Properties of Poly(hydroxybutyrate) Biopolymer
Bibliographic record
Abstract
This study focuses on the use of pilot-scale produced polyhydroxy butyrate (PHB) biopolymer and chitin nanocrystals (ChNCs) in two different concentrated (1 and 5 wt.%) nanocomposites. The nanocomposites were compounded using a twin-screw extruder and calendered into sheets. The crystallization was studied using polarized optical microscopy and differential scanning calorimetry, the thermal properties were studied using thermogravimetric analysis, the viscosity was studied using a shear rheometer, the mechanical properties were studied using conventional tensile testing, and the morphology of the prepared material was studied using optical microscopy and scanning electron microscopy. The results showed that the addition of ChNCs significantly affected the crystallization of PHB, resulting in slower crystallization, lower overall crystallinity, and smaller crystal size. Furthermore, the addition of ChNCs resulted in increased viscosity in the final formulations. The calendering process resulted in slightly aligned sheets and the nanocomposites with 5 wt.% ChNCs evaluated along the machine direction showed the highest mechanical properties, the strength increased from 24 to 33 MPa, while the transversal direction with lower initial strength at 14 MPa was improved to 21 MPa.
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 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".