A REVIEW OF ASSEMBLED POLYACRYLONITRILE-BASED CARBON NANOFIBER PREPARED ELECTROSPINNING PROCESS
Bibliographic record
Abstract
Electrospinning is a very simple and versatile process by which polymer nanofibers with diameters ranging from a few nanometers to several micrometers can be produced using an electrostatically driven jet of polymer solution (or polymer melt). Significant progress has been made in this process throughout the last decade and the resultant nanostructures have been exploited to a wide range of applications. An important feature of the electrospinning process is that electrospinning nanofibers are produced in atmospheric air and at room temperature. This paper reviews the assembled polyacrylonitrile (PAN)-based carbon nanofibers with various processing parameters such as electrical potential, distance between capillary and collector drum, solution flow rate (dope extrusion rate), and concentration of polymer solution. The average fiber diameter would increase with increasing concentration of the polymer solution and the flow rate. Therefore, the screen distance could also increase but the average electrical potential of the fibers diameter decreases. Electrospinning process can be conducted at higher electrical potentials, lower flow rate, nearer screen distance, and higher concentrations of dope.
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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 | 0.002 | 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".