Enhancing and Tuning the Response of Environmentally Sensitive Hydrogels With Embedded and Interconnected Pore Networks
Bibliographic record
Abstract
Abstract Porous and temperature-sensitive poly(N-isopropylacrylamide) (PNIPAam) hydrogels with tunable and enhanced response properties were prepared by using porous poly(ε-caprolactone) (PCL) molds. The molds were obtained from melt-processed cocontinuous polymer blends of ethylene propylene diene monomer (EPDM) and PCL. Quiescent annealing of the blends resulted in microstructure coarsening, and subsequent extraction of the EPDM phase yielded the molds. Ultimately, it allowed control over the average gel pore size from 20 to 300 μm. The gelling solution was injected within the molds, which were subsequently extracted, yielding hydrogels with fully interconnected pores. The porous gels display enhanced thermoresponsive properties in water: tunable, fully reversible and significantly faster swelling and deswelling responses following a temperature change across the PNIPAam lower critical solution temperature, as compared to nonporous gels. The fabrication process is compatible with a broad choice of gel chemistries, and allows the fabrication of complex 3D shapes of various sizes.
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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 | 0.000 |
| 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) | 0.001 | 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".