TPU/MOFs Electrospun Composite Film for Underwater Tactile Sensing and Finger Joint Bending Monitoring
Bibliographic record
Abstract
Abstract Most flexible tactile pressure sensors can hardly be used in deep sea due to the strict water sealing requirement on the soft material and the hardening effect due to high hydroSstatic pressure. To address these issues, a self‐powered and hydrostatic pressure‐balanced underwater flexible tactile sensor based on an electrospun nanofiber film composed of a thermoplastic polyurethane elastomer (TPU) and Metal Organic Frameworks (MOFs‐801) is presentedr. The sensor generates ionic current via different ion movement speeds under pressure, and can simultaneously achieve pressure and position sensing. Experimental results show the signal magnitude increases with the increase in the applied pressure, carboxyl group concentration, and stretching length. The direction and magnitude of the signal depend on the pressing or stretching position of the film, with bigger current magnitude closer to the film ends. The maximum sensitivity is 1.31 kPa −1 , with the response and recovery times of 0.16 and 0.51 s, respectively. The sensor remains operational after over 1400 cycles under 600 kPa external load. Furthermore, the signal magnitude decreased only by 10.38% under 100 m water depth. Proof of concept demonstration of object shape differentiation by monitoring the bending of finger joints is successfully achieved.
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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) | 0.000 | 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 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".