Analysis of multiaxial properties of carbon nanotubes/polypropylene and nanocrystalline cellulose/polypropylene composites
Bibliographic record
Abstract
Using the beam element to simulate single wall carbon nanotube (SWCNT) and nanocrystalline cellulose (NCC), finite element method is adopted to perform multi‐axial numerical tests to compare SWCNT and NCC reinforced polypropylene (PP). As a first step, SWCNT and NCC are assumed to be isotropic and linear elastic materials, while PP is assumed to be linear elastic or elastic–plastic. Using the same reinforcement volume fraction, the elastic and elastic–plastic properties of the nanocomposites are compared under biaxial and triaxial loading conditions. Then, the effect of particle volume fraction and particle size is presented. When NCC and SWCNT have equal particle length and number but different particle diameter, both can produce similar improvement on biaxial mechanical properties. Finally, NCC and SWCNT are compared from an economic point of view to get similar mechanical performance (biaxial properties). The results show that NCC is about 646 times cheaper than SWCNT and is an interesting prospect for future work. POLYM. COMPOS., 37:1180–1189, 2016. © 2014 Society of Plastics Engineers
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".