The Effect of Aligned Porous Nanofibers on Filter Efficiency and Pressure Drop
Bibliographic record
Abstract
Masks, vital for submicron filtration, face a trade-off between enhanced when increasing filter efficiency and, an increased pressure drop, impacting user comfort during physical activities leading to difficulty breathing. Polycaprolactone (PCL) and Nylon masks electrospun with humidity control, was investigated. Optimal conditions emerged with a 10% PCL solution by weight in a chloroform and dimethylformamide mix (8:2 ratio), collected at 500 RPM, producing highly efficient aligned porous fibers. Conversely, Nylon failed to yield porous fibers under any tested combination of parameters. Our findings reveal a filtration efficiency range for porous aligned PCL fibers from 6% for 0.3 μm particles up to 42% at 5 μm, accompanied by a minimal pressure drop of 7 Pa. Introducing humidity proved effective in manufacturing porous nanofibers within a conventional electrospinning setup, offering promise for exploring diverse materials. The material’s distinct behavior suggests a broad avenue for the development of oriented multilayered mask application.
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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 | 0.001 |
| 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) | 0.001 | 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".