Effects of chain extension and clay reinforcement on PLA nanocomposite foams
Bibliographic record
Abstract
The effects of chain extension and nanoclay incorporation on the foamability of poly(lactic acid) (PLA) were investigated using supercritical CO 2 as the blowing agent in a batch setting. Multifunctional epoxide styrene-acrylic (Joncryl) chain extended PLA samples loaded with 0–3 wt% of nanoclay were prepared. Parallel plate rheology and differential scanning calorimetry verified the chain extension of the reactive process, indicating a 315 % increase in molecular weight and corresponding entanglement. Polarized optical microscopy showed the effect of chain extension and nanoclay incorporation on the crystallization and crystallization rate of the PLA. The batch foamed samples via supercritical CO 2 , showed a 304 % increase in the expansion ratio and corresponding to 76 % decrease in density after chain extension. Increasing nanoclay incorporation led to slight decreases in expansion, which eventually caused cell collapse at the higher loading levels. The mechanical and thermal insulation properties of the nanocomposite foams improved 64 % and 6 %, respectively upon chain extension, and improved by 27 % and 10 % again with nanoclay incorporation until a threshold loading where poor foamability caused a deterioration in properties. Results of the study indicated that chain extension and employment of nanofillers can be an effective way to generate effective PLA foams with sustainability benefits for a range of commodity and engineering applications. • Poly(lactic acid) (PLA) was chain extended with multifunctional epoxide styrene-acrylic. • Chain extension increased chain entanglement and hence melt-strength of PLA. • High melt-strength in conjunction with nanoparticle incorporation led to improved foamability of PLA. • PLA foams performance were comparable to polystyrene foams with sustainability attribute.
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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".