An Elastic Autonomous Self‐Healing Capacitive Sensor Based on a Dynamic Dual Crosslinked Chemical System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Adopting self-healing, robust, and stretchable materials is a promising method to enable next-generation wearable electronic devices, touch screens, and soft robotics. Both elasticity and self-healing are important qualities for substrate materials as they comprise the majority of device components. However, most autonomous self-healing materials reported to date have poor elastic properties, i.e., they possess only modest mechanical strength and recoverability. Here, a substrate material designed is reported based on a combination of dynamic metal-coordinated bonds (β-diketone-europium interaction) and hydrogen bonds together in a multiphase separated network. Importantly, this material is able to undergo self-healing and exhibits excellent elasticity. The polymer network forms a microphase-separated structure and exhibits a high stress at break (≈1.8 MPa) and high fracture strain (≈900%). Additionally, it is observed that the substrate can achieve up to 98% self-healing efficiency after 48 h at 25 °C, without the need of any external stimuli. A stretchable and self-healable dielectric layer is fabricated with a dual-dynamic bonding polymer system and self-healable conductive layers are created using polymer as a matrix for a silver composite. These materials are employed to prepare capacitive sensors to demonstrate a stretchable and self-healable touch pad.
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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) | 0.001 | 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) | 0.000 | 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