Micro-mechanical bending (M<sup>2</sup>B) method for carbon nanotube (CNT) based sensor fabrication
Bibliographic record
Abstract
Vertically aligned carbon nanotubes (VACNTs forest) array is known to be the darkest material on earth. However, post processing of VACNTs array by micro mechanical bending (M2B) causes the individual CNT to be bent, flattened and reflective. This interesting change in the optical property of CNT forest opens the gateway, to use it as displacement sensor both for linear and angular motion. This paper investigates experimentally how different parameters of M2B process affect the morphology of the patterned zone which is very important in fabricating this type of sensor. Micro-mechanical bending is locally applied to the targeted area in order to change the physical property of carbon nanotube. The factors that govern the resultant have been first identified; rotation spindle rate, bending speed rate, step size and total depth of bend. The resultant has been analyzed using Field Emission Scanning Electron Microscopy (FE-SEM) technique to observe the differences in surface roughness and structural integrity, revealing their dependence on the machining parameters.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".