An interlocked flexible piezoresistive sensor with 3D micropyramidal structures for electronic skin applications
Bibliographic record
Abstract
The development of flexible pressure sensors with human-like sensing capabilities is an emerging field due to their wide range of applications from human robot interactions to wearable electronics. Piezoresistive sensors respond to externally induced mechanical stimuli through changes in their electrical resistance. The current state-of-the-art piezoresistive sensors are mainly constructed via dispersion of conductive nanofillers in an elastomer matrix making their performance strongly reliable on the degree of dispersion. Alternatively, changes in the contact area of conductive elastomers result in higher sensitivity and more tunable variables. Herein, an interlocked sensor comprising two flexible layers of 3D pyramidal microstructures is fabricated with a thin layer of carbon nanotubes deposited onto the micropatterns. The introduced array of micropyramids with varying height and pitch sizes allows for higher changes in the contact area upon applying an external load. The results indicate that the height and pitch of the structures together with a newly defined variable, the critical dimension, affect the sensor's sensitivity. An optimal performance is observed for minimized values of the critical dimension. Furthermore, to verify the obtained results, a finite-element-assisted analytical constriction-resistance model is used to capture the piezoresistive response of the sensor. The theoretical results show the high tracking ability of their experimental counterparts.
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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".