Toughening hydrogels through a multiscale hydrogen bonding network enabled by saccharides for a bio-machine interface
Bibliographic record
Abstract
Hydrogels have considerably emerged in a variety of fields, but their weak mechanical properties severely restrict the wide range of implementation. Herein, we propose a multiscale hydrogen bonding toughening strategy using saccharide-based materials to optimize the hydrogel network. The monosaccharide (glucose) at the molecular scale and polysaccharide (cellulose nanofibrils) at the nano/micro scale can effectively form hydrogen bonds across varied scales within the hydrogel network, leading to significantly enhanced mechanical properties. Besides, the toughened hydrogels present excellent environmental resilience and bad solvent resistance, allowing them to retain their performance in various severe environments. Notably, after being exchanged with a bad solvent such as ethanol, the alcogel exhibits strain-depended vivid interference color, allowing it to function as a mechano-optical sensor. Finally, this strategy has been shown to be adaptable across multiple material systems, and the resulting hydrogels have potential as a bioelectronic interface for long-term stable recording of physiological signals, highlighting the potential of sustainable biomaterials in designing high-quality hydrogels for advanced applications.
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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) | 0.000 | 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 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".