Effects of a Multifunctional Polymeric Chain Extender on the Properties of Polylactide and Polylactide/Clay Nanocomposites
Bibliographic record
Abstract
Abstract A multifunctional polymeric chain extender (Joncryl) was used in the melt processing of a neat polylactide and polylactide/clay nanocomposites. The effects of Joncryl on morphology, rheology, thermal and mechanical properties, barrier properties and biodegradability were investigated. Three Joncryl loadings (0.1, 0.3 and 0.5 wt%) were used in this study, and the 0.5 wt% loading induced a long-chain branched structure in the PLA matrix, as indicated by the melt rheology results. It is believed that the property variations are all related to the long-chain branched structure as well as on the molecular weight recovery. The use of Joncryl did not change the intercalated and partially exfoliated clay structures in the PLA/clay nanocomposites, as observed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The tensile modulus and maximum strength slightly increased with Joncryl loading. The oxygen barrier properties were also improved by adding Joncryl. However, the addition of Joncryl prevented the formation of large spherulitic crystals and decreased the creep resistance at low stress level. Joncryl could not only control the thermal degradation of PLA during processing, but also affected its biodegradation in compost: higher Joncryl loading led to slower biodegradation and less molecular weight reduction with time.
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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) | 0.001 | 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".