Energy gap and orbital mixing in DNTT/PTCDI-C8 heterostructure
Bibliographic record
Abstract
Organic pn heterostructures are widely employed in emerging devices. However, charge carrier behavior in these structures is not well understood, posing a difficulty in designing and optimizing devices in a systematic manner. In this article, finite-element simulation is used to reproduce and rationalize transfer characteristics of a thin-film transistor fabricated with DNTT/PTCDI-C8 heterostructure. Introducing the concept of orbital mixing enables a fit to the experimental data, providing insights into the role of energetic, transport, and interface parameters. Spatial distribution of charge carriers and electric potential inside the semiconductor channel suggests that the device performance is strongly affected by energetic barriers formed at metal/organic and organic/organic interfaces. Finally, the importance of discretization is illustrated by creating different meshes and analyzing their impact on simulated transfer characteristics. • DNTT/PTCDI-C8 thin film heterojunction is analyzed through numerical simulation • Physical, electrical and energetic factors affecting charge transport are identified • Modeling reproduces anti-ambipolar switching observed in fabricated transistors
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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) | 0.001 | 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".