Compatibility, crystallinity and mechanical properties of poly(lactic acid)‐poly(ether‐ <i>block</i> ‐amide) based copper nanocomposites
Bibliographic record
Abstract
Abstract Binary and ternary composites of poly(lactic acid) (PLA), poly(ether‐ block ‐amide) (PEBAX) and copper nanoparticles were prepared by melt blending in an internal mixer. Compatibility and molecular interactions between the three components of the nanocomposites were evaluated using scanning electron microscopy and Fourier transform infrared spectroscopy. It was found that the carbonyl groups of the PLA and copper nanoparticles interact. Also, PLA and PEBAX are compatible and develop molecular interactions between the C=O of PLA and the C=O and NH of PEBAX, forming dipole–dipole bonds and hydrogen bonds. The compatibility and molecular interaction between PLA and PEBAX are reduced by copper nanoparticles. The reduction of compatibility between PLA and PEBAX produced a lower storage modulus and lower strain at break in the ternary systems than in the blend PLA‐PEBAX. Copper nanoparticles enhanced the crystallinity of PLA. PLA responded more strongly to the nucleating effect of copper when PEBAX was added indicating a synergistic effect. The strain at break of PLA was enhanced by the addition of PEBAX but was severely reduced by the presence of nanoparticles. © 2020 Society of Chemical Industry
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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) | 0.000 | 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".