Possible mechanism in dry micro-electro-discharge machining of carbon-nanotube forests: A study of the effect of oxygen
Bibliographic record
Abstract
The working principle of dry micro-electro-discharge machining of vertically aligned carbon-nanotube forests is investigated by evaluating the effect of oxygen on the process. The machining experiments with controlled oxygen/nitrogen ratios indicate a correlation between the peak current of discharge pulses and the oxygen concentration, suggesting not only a vital role for oxygen in the process, but also a removal mechanism fundamentally different from that in typical electro-discharge machining based on direct melting and evaporation of the sample material. The highest surface quality and uniformity in the machined forest microstructures as well as smooth machining without short circuiting are achieved at an approximate oxygen concentration of 20% under the discharge condition of 30 V and 10 pF, revealing that air is an optimal medium for the removal process. Elemental and molecular analyses show no evidence of significant crystalline deterioration or contamination in the nanotubes processed with the technique.
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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 | 0.001 | 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".