Direct-write fabrication of freestanding nanocomposite strain sensors
Bibliographic record
Abstract
This paper deals with the design and microfabrication of two three-dimensional (3D) freestanding patterned strain sensors made of single-walled carbon nanotube (SWCNT) nanocomposites with the ultraviolet-assisted direct-write (UV-DW) technique. The first sensor consisted of three nanocomposite microfibers suspended between two rectangular epoxy pads. The flexibility of the UV-DW technique enables the sensor and its housing to be manufactured in one monolithic structure. The second sensor was composed of a nanocomposite network consisting of four parallel microsprings, which demonstrates the high capability of the technique when compared to conventional photolithographic technologies. The performances of the sensors were assessed under tension and compression, respectively. The sensors' sensitivities were evaluated by correlating their measured resistivities to the applied displacements/strains. Electrical conductivity measurements revealed that the manufactured sensors are highly sensitive to small mechanical disturbances, especially for lower nanotube loadings when compared to traditional metallic or nanocomposite films. The present manufacturing method offers a new perspective for manufacturing highly sensitive 3D freestanding microstructured sensors.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".