A versatile hot melt centrifugal spinning apparatus for thermoplastic microfibres production
Bibliographic record
Abstract
The centrifugal spinning (CS) method could address common issues such as low production rate and high energy consumption in the industry of nonwoven textile fabrication. Similarly to cotton candy production, the high-speed rotating reservoir extrudes melt or solvent-based polymer from orifices to produce fibres. Using polymer melt avoids solvent elimination and toxicity, but the process is more difficult. Thus, a versatile lab-scale hot melt spinneret with the ability to pour pellets inside continuously to expand our knowledge of the CS method and investigating different extrusion geometries such as nozzlefree is developed. Among the controllable parameters are, the spinneret heating temperature (up to 300°C), its two interchangeable 3D printer nozzles. An Arduino code is used to stabilize the temperature. The system performance is investigated with polypropylene and polylactide. The results show that fibres under 15 μm in diameter are produced. This work is licensed under CC BY-NC 4.0. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc/4.0/.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".