Small dop of comonomer, giant shift of dynamics: α-methyl-regulated viscoelasticity of poly(methacrylamide) hydrogels
Bibliographic record
Abstract
α -Methyl groups play significant roles in the regulation of water molecules within both small molecular systems and bio-macromolecular systems. Systematically studying the influence of α -methyl on the dynamics of water molecules within hydrogel systems is therefore worthwhile. In this study, we prepared a series of hydrogen-bonded (H-bonded) hydrogels with varying densities of α -methyl groups by copolymerizing methacrylamide (MAm) with its α -methyl-absent analogue, acrylamide (Am). Introducing a small amount of Am (≤6 mol%) into the polymer chain resulted in significant shifts in the viscoelasticity of the hydrogels. The hydrogels exhibit a “time-temperature- α -methyl equivalence”, meaning that introduction of α -methyl-absent monomer has effects similar to elevating temperature and prolonging observation time on the dynamic properties. Based on low-field nuclear magnetic resonance spectroscopy and Raman scattering, a “hydrophilic defects-assisted H-bonds dissociation” mechanism is proposed, depicting that the α -methyl-absent monomer can disturb the rearrangement of water molecules surrounding the polymer chain and accelerate chain dissociation. These findings enabled the copolymer hydrogels with functions such as fast self-healing and tunable interface adhesion.
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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".