Super‐Assembled Hierarchical Cellulose Aerogel‐Gelatin Solid Electrolyte for Implantable and Biodegradable Zinc Ion Battery
Bibliographic record
Abstract
Abstract Transient devices represent an emerging type of electronics whose main characteristic is the constituent materials that could fully or partially dissolute or disintegrate by chemical or physical processes after completing the mission, and are considered as new research directions for implantable devices. However, research on transient devices is still in its infancy and there are many challenges to overcome, especially the development of transient energy devices is relatively slow. Here, an implantable, biodegradable transient zinc ion battery (TZIB) that assembles a carefully designed cellulose aerogel‐gelatin (CAG) solid electrolyte. The new fully degradable CAG solid electrolyte allows TZIB to achieve controlled degradation and stable electrochemical performance, at the same time maintaining excellent mechanical properties. The entire battery device can be completely degraded within 30 days in the buffered proteinase K solution. More importantly, TZIB has excellent electrochemical performance while meeting controlled degradation, providing a specific capacity of 211.5 mAh g −1 at a current of 61.6 mA g −1 and a wide voltage range (0.85–1.9 V). These results demonstrate the potential of TZIB in future clinical applications and provide a new platform for transient electronic technology.
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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) | 0.001 | 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".