Nonlinear Fowler–Nordheim plots of the field electron emission from graphitic nanocones: influence of non-uniform field enhancement factors
Bibliographic record
Abstract
Well-aligned graphitic nanocones were synthesized on polished pristine p-type (100) silicon wafers through plasma enhanced hot filament chemical vapour deposition. The field electron emission properties were investigated using anode probes of different diameters. Non-linearity was observed in the field electron emission (FEE) Fowler–Nordheim (FN) plots at high electric field. The numerical calculations based on the superposition of two types of characteristic emission sites are consistent with the experimental data. The non-linearity in the FN plot may be attributed to the non-uniform field enhancement factor (FEF) of the graphitic nanocones. At low electric field, electrons are emitted mainly from nanocones with large FEF, corresponding to a small slope magnitude in the FN plots. With the increasing electric field, the nanocones with small FEFs also contribute to the emission current, which results in a reduced average FEF and so a larger slope magnitude. If the difference in FEFs of the two types of emission sites is large, the emission sites with smaller FEF may not be able to participate in emission even at the highest electric field tested in the experiments and the FN plot remains a straight line determined presumably by the emission sites with larger FEF.
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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 | 0.000 | 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".