High‐Throughput Production of Gelatin‐Based Touch‐Spun Nanofiber for Biomedical Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nanofiber production techniques have become increasingly important due to their wide range of applications. However, the complex design of the setup and difficulty in scaling up to high production rate have limited the industrial applicability of some of the conventional fiber generation techniques such as electrospinning. Herein, the touch spinning method is scaled up for nanofiber production using a simple rotating drawing setup with polymers that are relevant for biomedical applications such as polyethylene oxide and gelatin. The process is amenable to use of benign solvent such as water and production of a wide variety of submicron‐scale gelatin‐based nanofibers at a high throughput (≈2.45 g hr −1 with the single channel flow), which is an order of magnitude higher than those produced by other fiber generation methods is shown. The parametric study indicates that the fiber production process can be tuned at a desired rate without sacrificing the fiber quality by simply altering the number of drawing rods, the size of the rotating disk, and the number of solution flow supply channels. The utility of this technique for different biomedical applications such as cell culture and air filtration applications is also demonstrated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it