Cation–π Hydrogel Electrolyte for Flexible All‐Solid‐State Supercapacitors with Excellent Mechanical Deformation and Low‐Temperature Tolerance
Bibliographic record
Abstract
Abstract Flexible supercapacitors are promising power sources for new‐generation wearable electronics. However, their electrochemical performance often deteriorates under mechanical deformation and low‐temperature environments. Here, a flexible supercapacitor is developed by sandwiching a hydrogel electrolyte between two electrodes. To address performance challenges, cation−π crosslinking sites are incorporated into the hydrogel network. These dynamic crosslinking sites act as efficient ion‐hopping centers, imparting the hydrogel electrolyte with high fracture strength (1.8 MPa), strong ionic conductivity (3.9 S m −1 ), and excellent anti‐freezing properties. Furthermore, the hydrogel forms cation−π interactions with carbon nanotube‐based composite electrodes, facilitated by the reaction between the indole groups and Na + in the electrodes. This strong interfacial bonding minimizes electrode–electrolyte displacement during deformation, reducing interfacial resistance and enhancing charge transport efficiency. As a result, the cation−π hydrogel electrolyte enables the supercapacitor to achieve high energy storage, outstanding mechanical deformation tolerance, and robust performance at low temperatures. The device maintains 89.8% of its initial capacitance after 5000 bending cycles and retains 70.9% capacitance at −40 °C—significantly surpassing previously reported methods. This work presents an innovative strategy for designing high‐performance hydrogel electrolytes for advanced energy storage systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".