Localized light induced thermionic emission from intercalated carbon nanotube forests
Bibliographic record
Abstract
In this work, we studied light induced thermionic emission from potassium intercalated carbon nanotube forests. Several recipes were developed for the intercalation process. The intercalated CNT forest was employed as the emitter of a light activated thermionic emission device. The resulting thermionic device was characterized by studying its current-voltage characteristics when illuminated by a focused laser beam. Based on the amount of current drop vs time, the value of workfunction reduction was estimated to be about 0.7 eV. Current-voltage characteristics were obtained at several incident light powers. Thermionic emission of potassium ions from the surface of the forest was observed at lower biases. In another set of experiments, in-situ intercalation of carbon nanotube forests was accomplished. The current-voltage characteristics were captured at different times during a period of 72 hours. It was observed that the workfunction has been reduced by 1.1 eV.
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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".