Lignin derived hydrogel with highly adhesive for flexible strain sensors
Why this work is in the frame
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Bibliographic record
Abstract
The application of natural polymers to hydrogel materials with stretchable and compressible properties has attracted more and more attention. However, hydrogel materials made of pure natural polymers are not only poor in mechanical properties, but also lack in stability and sensitivity in strain sensors. Herein, the ionic conductive lignin hydrogels with highly stretchable (tensile strain ∼525.1%) and compressible (compression strain ∼95%) performance were formulated by a simple solution blending method. The lignin-based hydrogel with ultra-self-adhesive properties was able to adhere to various hydrophobic or hydrophilic surfaces. The adhesion measured on stainless steel, plexiglass, and paper reached 307 kPa, 301 kPa, and 174 kPa, respectively. Moreover, lignin-based hydrogels can be used as reliable and stable strain sensors to respond to environmental stimuli. Good adhesion can make hydrogels closer to the skin, so as to more accurately detect human signals, and excellent ion conduction ability can meet the needs of monitoring wrist bending activities. Significantly, the various properties of lignin-based hydrogel can be controlled through rationally adjusting the chemical composition of the hydrogel. It was proved that lignin-based hydrogel with natural-based formulation, high mechanical properties, and adhesion performance has great application potential in flexible equipment.
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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 it