Evaluation of the subtle trade-off between physical stability and thermo-responsiveness in crosslinked methylcellulose hydrogels
Bibliographic record
Abstract
Methylcellulose (MC) hydrogels, undergoing sol-gel reversible transition upon temperature changes, lend themselves to smart system applications. However, their reduced stability in aqueous environment and unsatisfactory mechanical properties limit the breadth of their possible applications. Here, a crosslinking strategy based on citric acid (CA) was developed: exploiting three crosslinking parameters (CA concentration, crosslinking time, and crosslinking temperature) by a design of experiment approach, optimized crosslinked MC hydrogels (MC-L, MC-M, MC-H) were obtained and characterized. Swelling tests in water revealed the effectiveness of CA crosslinking in modulating the water uptake of MC hydrogels. Both theoretical and experimental analyses showed an increase in the crosslinking density by the rationale selection of process parameters. The extent of sol-gel transition was assessed by swelling tests, Raman spectroscopy and rheological analyses. MC-M samples demonstrated to preserve their thermo-responsive behavior around their lower critical solution temperature (LCST), while showing increased stability and enhanced mechanical properties when compared to pristine MC hydrogels.
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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) | 0.000 | 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".