A microcantilever of self-suspended carbon nanotube forest for material characterization and sensing applications
Bibliographic record
Abstract
This paper reports a laterally suspended microcantilever made entirely of a vertically aligned carbon nanotube (CNT) forest. The CNTs in a 1-mm-long cantilever, patterned using a post-growth microplasma technique, are preserved in their original alignment and structure, and are self-suspended only due to their entwined arrangement and internal interactions. This pure CNT forest cantilever is electrostatically actuated to characterize its resonance using a laser Doppler vibrometer, revealing a resonant frequency and quality factor of 7.95 kHz and 51.3, respectively, at room temperature. The measurement result fitted to a free vibrating microcantilever model indicates that the CNT forest, an anisotropic bulk material, has an in-plane Young's modulus of 3.8 MPa, which matches well with previously reported levels of the modulus. A preliminary test of the cantilever as a resonant-mode sensing device shows real-time temperature tracking, suggesting the device's potential for not only temperature sensing but also other sensing applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".