Effect of surface acetylated‐chitin nanocrystals on structure and mechanical properties of poly(lactic acid)
Bibliographic record
Abstract
ABSTRACT In this work, the miscibility between chitin nanocrystals (ChNs) and poly(lactic acid) (PLA) was expected to be improved by surface acetylation of ChN. The reaction of acetic anhydride onto the ChN surface was confirmed by FTIR and 13C NMR, while XRD and TEM proved the crystalline structure and rod‐like morphology were maintained. The acetylated ChN (AChN) was incorporated into a PLA matrix by solution blending, and resulted in an increase of tensile strength and Young's modulus and they reached to the maximum value as 45 and 37% higher than neat PLA film, respectively, with the loading level of AChN reaching to 4 wt %. The enhancement could be attributed to that acetylation improved dispersion of AChN in the PLA matrix and interfacial adhesion between AChN and PLA. The performances of the nanocomposites based on PLA and chitin nanocrystals derived from renewable resources have good potential for industrial applications. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 39809.
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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".