Effects of starch nanocrystal‐<i>graft</i>‐polycaprolactone on mechanical properties of waterborne polyurethane‐based nanocomposites
Bibliographic record
Abstract
Abstract Based on a “graft from” strategy, the surface of starch nanocrystals (StN) were functionalized by grafting with polycaprolactone (PCL) chains via microwave assisted ring‐opening polymerization (ROP). The modified natural nanoparticles were then compounded into a PCL‐based waterborne polyurethane as matrix. The structural and mechanical properties of the WPU/StN‐g‐PCL nanocomposites were characterized by XRD, FTIR, SEM, DSC, DMA, and tensile testing. It was interesting to note that a loading‐level of 5 wt % StN‐g‐PCL resulted in a simultaneous enhancement of tensile strength and elongation at break, both of which were higher than those of neat WPU. This enhancement was attributed to the uniform dispersion of StN‐g‐PCL because of its nano‐scale size, the increased entanglements mediated with grafted PCL chains, and the reinforcing function of rigid StN. Increasing the StN‐g‐PCL content however caused the StN‐g‐PCL to self‐aggregate as crystalline domains, which impeded improvement in tensile strength and elongation at break, but significantly enhanced Young's modulus. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
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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".