Field Emission Properties of Carbon Nanotube Arrays with Defects and Impurities
Bibliographic record
Abstract
It has been found experimentally that the results related to the collective field emission performance of carbon nanotube (CNT) arrays show variability. The emission performance depends on the electronic structure of CNTs (especially their tips). Due to limitations in the synthesis process, production of highly pure and defect free CNTs is very difficult. The presence of defects and impurities affects the electronic structure of CNTs. Therefore, it is essential to analyze the effect of defects on the electronic structure, and hence, the field emission current. In this paper, we develop a modeling approach for \nevaluating the effect of defects and impurities on the overall field emission performance of a CNT array. We employ a concept of effective stiffness degradation for segments of CNTs, which is due to structural defects. Then, we incorporate the vacancy defects and charge impurity effects in our Green's function based approach. Simulation results indicate decrease in average current due to the presence of such defects and impurities.
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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) | 0.000 | 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".