Carbon Nanotube and Graphene Based Polyamide Electrospun Nanocomposites: A Review
Bibliographic record
Abstract
Electrospinning is a unique and versatile technique to produce nanofibres; the facility to incorporate fillers has expanded its range of applications. This review gives a brief description of the process and the different polymers employed for obtaining nanofibres. Owing to the ability of fibrillation of polyamides, these polymers have resulted in a wide variety of interesting results obtained when using this technique; therefore these features are summarised. Additionally, because of the feasibility of incorporating carbon nanotubes and graphene in these nanofibres and the growing interest on these nanomaterials, this review focuses in the most common methods employed for their incorporation in electrospun polyamides. Several equipment setups used for the electrospinning of the nanofibres are explained. The outstanding electrical, optical, crystallinity, and mechanical properties obtained by a number of research groups are discussed. The potential applications of the resulting nanocomposites have also been explored.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".