Effective amino-functionalization of carbon nanotubes for reinforcing epoxy polymer composites
Bibliographic record
Abstract
An effective functionalization method was investigated to take full advantage of the exceptional performance of both carbon nanotubes and epoxy polymer for composite application. Epoxy polymer curing agent, EPI-W, was grafted to the single-walled carbon nanotubes through diazotization. Fourier transformed infrared spectroscopy, Raman spectroscopy, differential scanning calorimetry, dynamical mechanical analysis and thermo-gravimetric analysis were performed to characterize the functionalization effect. The degree of functionalization was estimated to be 1 in 50 carbons in the nanotube framework. The elastic modulus of the nanocomposite was enhanced 24.6% with only 0.5 wt% loading of functionalized carbon nanotubes, in contrast to the 3.2% increase of un-functionalized carbon nanotube reinforced composite. This significant improvement suggested an effective way to realize an industrial application of nanotubes reinforcing epoxy composite.
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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) | 0.001 | 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".