Large-scale production and metrology of vertically aligned carbon nanotube films
Bibliographic record
Abstract
The authors have produced carbon nanotube (CNT) films on a large scale in a commercial chemical vapor deposition (CVD) reactor. The reactor (built by Tystar, Inc) is the first of its kind and is capable of handling up to 50 150mm wafers simultaneously with industry standard process control. Electron microscopy reveals that the CNT films consist of densely packed and vertically aligned multiwalled CNTs. A variety of catalysts and reaction conditions were systematically tested. Both Fe films and Cr∕Ni∕Fe film stacks have been found favorable for the growth of aligned CNT films. While electron microscopy provides invaluable information, it is qualitative and unsuitable for process optimization and industrial quality control. A quantitative metrology standard is required for these purposes, but has to date not been explicitly defined. They report on their initial developments toward this metrology standard, considering such factors as film thickness (or CNT length), CNT wall number and diameter, amorphous carbon content, and uniformity. Various measurement techniques have been investigated and are discussed. The developed metrology will facilitate quality control and process optimization necessary for industry applications of CNT films.
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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 | 0.001 |
| 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".