Chitin nano-whiskers (CNWs) as a bio-based bio-degradable reinforcement for epoxy: evaluation of the impact of CNWs on the morphological, fracture, mechanical, dynamic mechanical, and thermal characteristics of DGEBA epoxy resin
Bibliographic record
Abstract
Chitin nano-whiskers (CNWs) are high performance nanomaterials that can be extracted from chitin, which is one of the most widely available bio-resources. Herein we investigate the effect of CNWs on the morphological, mechanical, dynamic mechanical and thermal properties of DGEBA epoxy. Optically transparent, bulk epoxy nano-composites with 0.25 wt%, 0.5 wt% and 0.75 wt% CNWs were evaluated in addition to neat epoxy. The composites were prepared based on a modified slurry compounding method. CNWs appear to be well dispersed within the epoxy matrix with increasing tendency for clustering as the CNW content is increased. The addition of 0.25 wt% CNWs to neat epoxy results in a decrease in the glass transition temperature and an increase in the tensile strength, modulus, damping and thermal degradation temperature. All the composites evaluated with CNWs showed distinct crack arrest events upon initiation of the first major crack growth during fracture toughness testing. Composites with 0.75 wt% CNWs showed the highest damping and an increase in the fracture toughness and resilience over neat epoxy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".