Micro glow plasma for localized nanostructural modification of carbon nanotube forest
Bibliographic record
Abstract
This paper reports the localized selective treatment of vertically aligned carbon nanotubes, or CNT forests, for radial size modification of the nanotubes through a micro-scale glow plasma established on the material. An atmospheric-pressure DC glow plasma is shown to be stably sustained on the surface of the CNT forest in argon using micromachined tungsten electrodes with diameters down to 100 μm. Experiments reveal thinning or thickening of the nanotubes under the micro glow depending on the process conditions including discharge current and process time. These thinning and thickening effects in the treated nanotubes are measured to be up to ∼30% and ∼300% in their diameter, respectively, under the tested conditions. The elemental and Raman analyses suggest that the treated region of the CNT forest is pure carbon and maintains a degree of crystallinity. The local plasma treatment process investigated may allow modification of material characteristics in different domains for targeted regions or patterns, potentially aiding custom design of micro-electro-mechanical systems and other emerging devices enabled by the CNT forest.
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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".