Polymeric Micro/Nanofiber Manufacturing and Mechanical Characterization
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 long smooth, uniform and defect-free fibers with control on fiber dimensions at the submicron and nanoscale has been challenging due to fragility of polymeric materials. Besides fabrication, the other challenge lies in the ability to characterize these fibers for mechanical properties, as they are widely believed to have improved properties than bulk due to minimization of defects. In this study we present an overall strategy for fabrication and mechanical characterization of polymeric fibers with diameters ranging from sub-50 nm to sub-microns. In the proposed fabrication strategy, polymeric solution is continuously pumped through a glass micropipette which is collected in the form of aligned fiber arrays on a rotating substrate. Polymer molecular weight and polymer solution concentration play dominant roles in controlling the fiber dimensions, which can be used to deposit fibers of different diameters in the same layer or successively built up multi-layer structures. Using this approach, we demonstrate single and multi-layer architectures of several polymeric systems such as Polystyrene (PS), Poly(methyl methacrylate) (PMMA), Poly lactic acid (PLA), and poly(lactic-co-glycolic acid) (PLGA). Further, we demonstrate the ability to manufacture PMMA fixed-free boundary condition cantilevers by breaking the fixed-fixed boundary condition PMMA fibers using Atomic Force Microscope (AFM) in the lateral mode. An integrated approach for mechanical characterization of polymeric fibers is developed. In this approach, the fibers are first deposited on commercially available Transmission Electron Microscopy (TEM) grids in aligned configurations and are mapped for accurate locations under the TEM. Subsequently, the fibers are carefully placed under the AFM and mechanically characterized for flexural modulus using lateral force microscopy (LFM). Finally, accurate fiber dimensions are determined under the Scanning Electron Microscope (SEM). The unique advantage of this approach lies in the ability to deposit a large number of fibers with tunable diameters in aligned configurations with fixed-fixed boundary conditions and requires no external manipulation. Finally, we present a novel methodology to study the resonance characteristics of fixed-fixed boundary condition suspended fibers using a commercially available Laser Doppler Vibrometer (LDV) for sensor applications. The methods developed in this study will greatly aid in increasing our fundamental knowledge of polymeric materials at reduced lengthscales and allow integration of these one-dimensional building blocks in bottom-up assembly environments.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".