Bio-based green composites with high performance from poly(lactic acid) and surface-modified microcrystalline cellulose
Bibliographic record
Abstract
Bio-based green composites with high performance were prepared from poly(lactic acid) (PLA) and microcrystalline cellulose (MC) fibers grafted with L-lactic acid oligomers (g-MC). The chemical structure of g-MC was characterized by fourier transform infrared (FTIR) and NMR methods, which indicate that L-lactic acid oligomers were successfully grafted onto MC. The grafting percentage of L-lactic acid oligomers is ca. 3.4%, and the average degree of polymerization of grafted L-lactic acid oligomers is ca. 10%. The improved compatibility between g-MC and PLA, caused by the grafting, results in an excellent dispersion of g-MC in the composites, and consequently a considerably improved transparence of the g-MC/PLA composites compared with that of the MC/PLA composites. In addition, due to the improved compatibility between g-MC and PLA, the g-MC/PLA composites exhibit better mechanical properties than pure PLA, with a high tensile strength of 70 MPa and a higher elongation at breakage. The enhanced properties, coupled with the excellent biocompatibility and degradability, offer the bio-based composites potential applications in biomedical fields and the packaging 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".