Highly Stretchable Strain Sensor based on Polyurethane-modified Carbon Nanotube Buckypaper
Bibliographic record
Abstract
This work focuses on the development of flexible strain sensors based on nanocomposites of thermoplastic polyurethane (TPU) and carbon nanotube (CNT) buckypaper (BP). A one-step filtration process is used to fabricate the TPU-CNT BP sensors, providing tailorability of CNT:TPU ratio. The developed sensors retain the porous morphology of buckypaper even at relatively high TPU content. Characterization of morphology, electrical conductivity, and mechanical properties is reported. In addition, electromechanical response was investigated for both quasistatic loads (strains up to 125%) and cyclic loads (1% and 5% strains). Cyclic tests show a repeatable response that becomes predictable after a few cycles. The combination of mechanical strength, electrical conductivity, and constant and high gauge factor makes this material promising as a free-standing sensing material.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".