The impact of the Fermi–Dirac distribution on charge injection at metal/organic interfaces
Bibliographic record
Abstract
The Fermi level has historically been assumed to be the only energy-level from which carriers are injected at metal/semiconductor interfaces. In traditional semiconductor device physics, this approximation is reasonable as the thermal distribution of delocalized states in the semiconductor tends to dominate device characteristics. However, in the case of organic semiconductors the weak intermolecular interactions results in highly localized electronic states, such that the thermal distribution of carriers in the metal may also influence device characteristics. In this work we demonstrate that the Fermi-Dirac distribution of carriers in the metal has a much more significant impact on charge injection at metal/organic interfaces than has previously been assumed. An injection model which includes the effect of the Fermi-Dirac electron distribution was proposed. This model has been tested against experimental data and was found to provide a better physical description of charge injection. This finding indicates that the thermal distribution of electronic states in the metal should, in general, be considered in the study of metal/organic interfaces.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".