Field-emission from carbon nanotube cones fabricated by micro-electro-discharge machining
Bibliographic record
Abstract
Field-emitters based on patterned carbon nanotube (CNT) arrays have promising properties. For example, they operate at low voltages and produce significant current. To pattern carbon nanotube arrays into various shapes, the typical approach consists of using lithography to pattern the catalyst prior to nanotube growth. However, this technique enables only two-dimensional patterning, where the height of the nanotubes remains unchanged. It is highly desirable to tailor the shape of CNT arrays in three dimensions (3D) in order to optimize the field emission performance of the arrays, including height control and creating angled surfaces. Here, we report on the polishing of the top surface of a CNT forest pillar and creation of cone-type structures in CNT arrays, similar in shape to the emitters in a conventional field-emitter array based on bulk metals. For this, we use dry micro-electro-discharge machining (μEDM) in oxygen ambient. We also report the results of field-emission experiments from them and show that the beam resulting from the CNT cone produces a sharp, uniform emission spot on the phosphor screen in field-emission microscopy.
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 | 0.000 | 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 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".