Dry Spinning Based Spinneret Based Tunable Engineered Parameters (STEP) Technique for Controlled and Aligned Deposition of Polymeric Nanofibers
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Bibliographic record
Abstract
Polymeric nanofibers are finding increasing number of applications and hold the potential to revolutionize diverse fields such as tissue engineering, smart textiles, sensors, and actuators. Aligning and producing high aspect ratio fiber arrays (length/diameter > 2 000) in the sub-micron and nanoscale diameters has been challenging due to fragility of polymeric materials, thus making it difficult to deposit them as one dimensional structures functionally interfaced with other systems. Here, we present a pseudo dry spinning technique which allows precise control on fiber diameters and further allows deposition of fiber arrays in aligned configurations. Control on fiber diameters ranging from 50-500 nm and having lengths of several millimeters is achieved by altering the polymeric solution concentration. In the dilute and semi-dilute unentangled concentration domain droplets or beaded fibers are observed to form. Smooth uniform diameter fibers are observed to form at the onset of semi-dilute entangled concentration regime. For a given molecular weight, the increase in fiber diameter with increasing solution concentration is attributed to both the increase in the entanglement density and the decrease in the radius of gyration of solvated polymer molecules. Using this technique polymeric fiber arrays in single and multiple layers are demonstrated which can be used towards developing strong textiles, biological scaffolds, and sensor networks.
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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 | 0.000 |
| 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) | 0.000 | 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