Mechanical Improvement of Multi-Walled Carbon Nanotube/Poly (Methyl Methacrylate) Composites
Bibliographic record
Abstract
Multi-walled carbon nanotube (MWNT)/poly (methyl methacrylate) composites were fabricated with the variation of the concentration rate of nanotubes by the solution casting. SEM images showed that the nanotubes were dispersed well throughout PMMA. Assuming that MWNTs in MWNT/PMMA composites were randomly oriented, the Tsai-Pagano equation, which can give the moduli of short fiber reinforced composites, was used to evaluate that of the MWNT/PMMA composite. For investigating mechanical properties of the MWNT/PMMA composite, tensile loading tests were performed, varying the concentration rate of the MWNTs. For each concentration rate of the MWNTs, at least 5 specimens of MWNT/PMMA composites were made and tested. As the concentration rate of the MWNTs increased from 0 to 0.15wt%, tensile strength and modulus of the MWNT/PMMA composites were improved by about 20% and 32%, respectively. However, the experimental results were not in agreement with what we estimated. Here are two reasons supposed. First, the MWNTs used in this research were not stretched straightly but entangled. It means that MWNTs cannot be assumed to be short fibers. Second, the concentration rate of the MWNTs is too small to be considered as short fiber composites.
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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 | 0.000 | 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) | 0.002 | 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".