Versatile sensing devices for self-driven designated therapy based on robust breathable composite films
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
Flexible wearable electronics were developed for applications such as electronic skins, human-machine interactions, healthcare monitoring, and anti-infection therapy. But conventional materials showed impermeability, single sensing ability, and no designated therapy, which hindered their applications. Thus it was still a great challenge to develop electronic devices with multifunctional sensing properties and self-driven anti-infection therapy. Herein, flexible and breathable on-skin electronic devices for multifunctional fabric based sensing and self-driven designated anti-infection therapy were prepared successfully with cellulose nanocrystals/iron(III) ion/polyvinyl alcohol (CNC/Fe 3+ /PVA) composite. The resultant composite films possessed robust mechanical performances, outstanding conductivity, and distinguished breathability (3.03 kg/(m 2 ·d)), which benefited from the multiple interactions of weak hydrogen bonds and Fe 3+ chelation and synergistic effects among CNC, polyaniline (PANI), and PVA. Surprisingly, the film could be assembled as a multifunctional sensor to actively monitor real-time physical and infection related signals such as temperature, moisture, pH, NH 3 , and human movements even at sweat states. More importantly, this multifunctional device could act as a self-driven therapist to eliminate bacterial by the release of Fe 3+ , which was driven by the damage of metal coordination Fe-O bonds due to the high temperature caused by infection at wound sites. Thus, the composite films had potential versatile applications in electronic skins, smart wound dressings, human-machine interactions, and self-driven anti-infection therapy.
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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) | 0.000 | 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 it