Fruit Peel-Inspired Super-Stable Ionic Organohydrogel Electronics with Dense Hydrophobic Skin
Bibliographic record
Abstract
Hydrogels are easily dehydrated during use and storage, making it difficult to maintain structural and performance stability, which greatly reduces their application value as wearable devices. Inspired by the structure of fruit, an ionic organohydrogel core containing Ca2+ and glycerol was first fabricated, and then, stearic acid (STA) was rivetted on the organohydrogel surface through (3-aminopropyl) triethoxysilane to obtain a dense hydrophobic coating (100 μm). The organohydrogel with hydrophobic skin presented better water spreading resistance and mechanical strength. In addition to the moisturizing effect of Ca2+ and glycerol, the skin also further blocks the contact between the organohydrogel and the air, thereby significantly enhancing the anti-dryness of the organohydrogel. Therefore, this organohydrogel has extremely outstanding structural, strength, and electrical conductivity stability. The developed strain sensor based on this organohydrogel can realize human motion monitoring capability at ultra-low temperature. This design idea, which combines multiple anti-drying mechanisms, has great expansion value for other gels suitable for various application scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".