Effectiveness study of Cellulose Nanocrystal (CNC) filler usage on polylactic acid (PLA) properties through plasticizer addition optimization: Application in paper-coated tableware
Notice bibliographique
Résumé
Polylactic acid (PLA) represents a bioplastic imbued with biocompatibility, biodegradability , and potential as a synthetic plastic substitute. However, PLA's brittleness and inferior toughness present limitations to its broader utility. To combat this, plasticizers are incorporated to lower the glass transition temperature (Tg), enhance ductility, and refine processability . Yet, while enhancing film elongation, plasticizer use may reduce tensile strength . An alternative solution involves incorporating reinforcements or fillers such as Cellulose Nanocrystal (CNC). This study aims to scrutinize the impact of additive incorporation on resulting film characteristics. The methodology involves solvent blending via stirring at 250 rpm for 6 hours at ambient temperature, followed by 24-h film evaporation under enclosed conditions. Optimization utilizing Response Surface Methodology (RSM) via the Face Centered Composite Design (FCCD) method is also conducted. Evaluation of additive influence on the film includes X-ray diffraction (XRD) analysis to ascertain crystallinity values through characteristic peaks at 2θ ≈ 16.7°, 19.2°, and 30°, Fourier Transform Infrared (FTIR) for identifying organic and inorganic chemical compounds, and Dynamic Mechanical Analysis (DMA) to analyze tensile strength , Young's modulus , and elongation at break . While higher crystallinity is traditionally associated with increased rigidity and brittleness in polymeric materials, the results from this study reveal an interesting relationship between crystallinity and elongation in the context of PLA-based films. The addition of CNC as a filler and PEG200 as a plasticizer facilitates a unique interplay between crystalline and amorphous regions within the composite structure. CNC acts as a nucleating agent , promoting uniform crystallization and creating a finer microstructure that enhances stress distribution, while PEG200 improves the flexibility of the matrix by increasing chain mobility in the amorphous regions. This balance allows the films to stretch further before breaking, resulting in higher elongation values without significant brittleness. Furthermore, the homogeneity of CNC dispersion within the PLA matrix, as confirmed by SEM and FTIR analyses, reduces the formation of stress concentrators that typically lead to brittle failure . Through elongation at break optimization, optimal outcomes are achieved with a composition of 90 % PLA: 10 % Additive – 66 % CNC: 34 % PEG200, yielding 14.49 % elongation at break, tensile strength of 4.26 MPa, and Young's modulus of 22.95. Similar testing at the optimal point using glycerol and sorbitol plasticizers results in elongation at break values of 10 % and 91.25 %, respectively, with tensile strength values of 4.71 and 5.12 MPa, and Young's modulus values of 46.74 and 36.44 MPa, respectively. Additive inclusion in the composite also increases the crystallinity value, and morphological analysis reveals increased porosity compared to unmodified samples, indicating dispersion within the composite. The crystallinity index values exhibit linearity with elongation at break test outcomes, suggesting that higher elongation at break leads to higher crystallinity index values. This highlights how controlled crystallinity, paired with effective plasticization , can yield films that defy conventional expectations by achieving both higher crystallinity and improved elongation.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».