Multifunctional Organohydrogel-Based Ionic Skin for Capacitance and Temperature Sensing toward Intelligent Skin-like Devices
Bibliographic record
Abstract
The ionic conducting hydrogel has attracted tremendous attention in fabricating flexible artificial skin-like devices. However, there are still unsolved challenges in hydrogel-based ionic skins, such as poor fulfillment of stretchability and compliance and weak interface interaction, as well as single sensory function. Herein, a high-performance organohydrogel-based ionic skin is facilely fabricated through one-step UV-initiated polymerization, in the presence of a polyacrylamide/cellulose nanofibril (PAAm/CNF) hybrid skeleton, a tannic acid (TA)-functionalized interface, and electrolytes (NaCl) dissolved in a glycerol–water binary solvent network. The design strategy demonstrates a profound synergistic effect of interpenetrating networks and interbonding structure in improving ultrastretchability (up to 1430%), suitable Young’s modulus (≈23 kPa), and high ionic conductivity (2.7 S m–1). Inspired by the adhesive mechanism of catechol groups in the mussel foot proteins, the TA component provides a durable interfacial contact (self-adhesiveness ≈ 103 N m–1) and unexpected UV-blocking capability (efficiency >99.9%). Moreover, by introducing a glycerol/water solvent system, the organohydrogel achieves desirable environmental stability. Furthermore, benefiting from the superior mechanical response and thermal perception capacities, our ionic skin can be assembled as capacitance sensors for real-life motion monitoring as well as thermistors for dynamic temperature detection.
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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".