Self‐Powered Wearable Electronics Based on Moisture Enabled Electricity Generation
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
Abstract Most state‐of‐the‐art electronic wearable sensors are powered by batteries that require regular charging and eventual replacement, which would cause environmental issues and complex management problems. Here, a device concept is reported that can break this paradigm in ambient moisture monitoring—a new class of simple sensors themselves can generate moisture‐dependent voltage that can be used to determine the ambient humidity level directly. It is demonstrated that a moisture‐driven electrical generator, based on the diffusive flow of water in titanium dioxide (TiO 2 ) nanowire networks, can yield an output power density of up to 4 µW cm −2 when exposed to a highly moist environment. This performance is two orders of magnitude better than that reported for carbon‐black generators. The output voltage is strongly dependent on humidity of ambient environment. As a big breakthrough, this new type of device is successfully used as self‐powered wearable human‐breathing monitors and touch pads, which is not achievable by any existing moisture‐induced‐electricity technology. The availability of high‐output self‐powered electrical generators will facilitate the design and application of a wide range of new innovative flexible electronic devices.
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.
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