Field-emission-assisted approach to dry micro-electro-discharge machining of carbon-nanotube forests
Bibliographic record
Abstract
This work investigates dry micro-electro-discharge machining (μEDM) of vertically aligned carbon nanotube (CNT) forests that are used as cathodes in the process, as opposed to conventional μEDM where the material to be machined forms the anode, toward achieving higher precision in the patterned microstructures. The new configuration with the reversed polarity is observed to generate higher discharge currents in the process, presumably due to effective field-emission from CNTs. This effect allows the process to be performed at very low discharge energies, approximately 80× smaller than in the conventional normal-polarity case, with the machining voltage and tolerance down to 10 V and 2.5 μm, respectively, enabling high-precision high-aspect-ratio micropatterning in the forests. The new approach is also demonstrated to make the process faster, cleaner, and more stable than conventional processing. Spectroscopic analyses of the forests processed by reverse μEDM show no evidence of significant crystalline deterioration or contamination in the CNTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".