Investigating the Properties of Novel Poly(2-hydroxyethyl methacrylate-co-methyl methacrylate) Hydrogel Hollow Fiber Membranes
Bibliographic record
Abstract
Poly(2-hydroxyethyl methacrylate-co-methyl methacrylate) hydrogel hollow fiber membranes were synthesized by a novel centrifugal-spinning methodology that resulted in new asymmetric wall morphologies, which in turn affected the mechanical and transport properties. Hollow fiber membranes were formed after polymerizing the comonomers, 2-hydroxyethyl methacrylate and methyl methacrylate, in an aqueous system under centrifugal forces. The concentration of methyl methacrylate in the comonomer and the concentration of redox initiators were investigated for their effects on membrane morphology, water content, Young's modulus, and diffusive transport. Both monomer composition and initiator concentration impacted the resulting asymmetric membrane morphology, which varied from a macroporous sponge to a microporous gel to a homogeneous gel. The hollow fiber membranes synthesized herein had equilibrium water contents between 42 and 57%, elastic moduli between 22 and 400 kPa, and effective diffusion coefficients between 10 - 7 and 10 - 9 cm 2 s - 1 for vitamin B12 and 10 kD dextran. The significant differences in both the moduli and the diffusion coefficients exhibited by these hydrogel membranes reflect differences in their intrinsic microstructures. Synthesis of hydrogel hollow fiber membranes using centrifugal force is a highly dynamic process; the membrane properties can be effectively tailored by controlling phase separation kinetics. These hydrogel hollow fibers are particularly attractive for soft tissue applications, such as nerve guidance channels, where biocompatibility, mechanical strength, and transport properties are determinants of device performance in vivo.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".