Mass Production of Nanocomposites Using Electrospinning
Bibliographic record
Abstract
Many conventional polymer processing technologies for compounding micro-/nanocomposites are known in the field. These methods include the direct use of high shear mixers, roll mixers, Banbury mixers, and extruders. With recent interest in advanced composites with nanoscale fillers, efforts have been made to enhance conventional processing technologies as the imposed input energy is often ineffective at breaching the energy barrier to breakup agglomerated nanofiller structures. Electrospinning is a simple, inexpensive process that can be used to produce continuous fibers from submicron to nanometer diameter scale through an electrically charged polymer jet. In this paper, authors present a rotary electrospinning method developed to produce nanocomposites at mass scale by using simultaneously mechanical and electrical forces with a proprietary apparatus. A case study using silica nanoparticles and silicone rubber matrix is presented to demonstrate the capability of the above method of dispersing nanoparticles in highly viscous polymer matrix materials.
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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 | 0.001 | 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".