Dispersion of Multi-Walled Carbon Nanotubes in Biodegradable Poly(butylene succinate) Matrix
Bibliographic record
Abstract
This communication describes the preparation, characterization and properties of biodegradable poly(butylene succinate) (PBS)/multi-walled carbon nanotubes (MWCNTs) nanocomposite. Nanocomposite was prepared by melt-blending in a batch mixer and the amount of MWCNTs loading was 3 wt%. State of dispersion-distribution of the MWCNTs in the PBS matrix was examined by scanning and transmission electron microscopic observations that revealed homogeneous distribution of stacked MWCNTs in PBS matrix. The investigation of the thermomechanical behavior was performed by dynamic mechanical thermal analysis. Results demonstrated substantial enhancement in the mechanical properties of PBS, for example, at room temperature, storage flexural modulus increased from 0.64 GPa for pure PBS to 1.2 GPa for the nanocomposite, an increase of about 88% in the value of the elastic modulus. The tensile modulus and thermal stability of PBS were moderately improved after nanocomposite preparation with 3 wt% of MWCNTs, while electrical conductivity of neat PBS dramatically increased after nanocomposite formation. For example, the in plane conductivity increased from 5.8 x 10(-9) S/cm for neat PBS to 4.4 x 10(-3) for nanocomposite, an increase of 10(6) fold in value of the electrical conductivity.
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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) | 0.000 | 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 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".