Controlling threshold voltage and leakage currents in vertical organic field-effect transistors by inversion mode operation
Bibliographic record
Abstract
The interest in vertical organic transistors as a means to overcome the limitations of conventional organic field-effect transistors (OFETs) has been growing steadily in recent years. Current vertical architectures, however, often suffer from a lack of parameter control, as they are limited to certain materials and processing techniques, making a controlled shift of, e.g., the transistor threshold voltage difficult. In this contribution, we present a vertical OFET (VOFET) operating in the inversion regime. By varying the thickness or doping concentration of a p-doped layer in an otherwise n-type VOFET, we are able to shift the threshold voltage in a controlled manner from 1.61 V (for a normal n-type VOFET) to 4.83 V (for the highest doping concentration of 50 mol. %). Furthermore, it is found that low doping concentrations of 20 mol. % can improve the Off state of the VOFET through reduction of the source-drain leakage current.
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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".