Studies on why the heat deflection temperature of polylactide bioplastic cannot be improved by overcrosslinking
Bibliographic record
Abstract
The high temperature application of polylactide (PLA) has been greatly limited by its low heat deflection temperature (HDT). As a slow crystallizing material, the HDT of amorphous PLA is mainly determined by its low T g value, near 55°C. In this work, PLA was chemically crosslinked, and the HDT of the crosslinked PLA was evaluated from two aspects—crystallization ability improvement and chain mobility limitation at T g of the PLA. The crystallization rate is improved by crosslinking because of the increased nucleation efficiency, and reached the highest level at moderate crosslinking. The final crystallinity is, however, still far lower than the crystallinity threshold for enhancing HDT of PLA. More importantly, T g of the PLA is not influenced by the crosslinking, even the average molecular weight between the crosslink points reaches as low as 1654 g/mol. The experimental research and theoretical calculations indicate that, to improve the HDT of the PLA, conformational restriction on the PLA chains should be focused on the segments with less than, at least, 14 repeating units. The fundamental reason why the HDT of PLA cannot be improved by crosslinking is investigated to guide the future structure design for high HDT PLA products.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".