Enhanced Organic Thin-Film Transistor Stability by Preventing MoO<sub>3</sub> Diffusion with Metal/MoO<sub>3</sub>/Organic Multilayered Interface Source-Drain Contact
Bibliographic record
Abstract
The source-drain electrode with a MoO3 interfacial modification layer (IML) is considered the most promising method to solve electrical contact issues impeding organic thin-film transistors (OTFTs) from commercialization. However, this method raises many concerns because MoO3 might diffuse into organic materials, which causes device instability. In this work, we observed a significant device stability degradation by damaging on/off switching performance caused by MoO3 diffusion. To prevent the MoO3 diffusion, a source-drain electrode with a multilayered interface contact (MIC) consisting of a top-down stack of metal, MoO3 IML, and organic buffer layer (OBL) is proposed. In the MIC device, the MoO3 IML serves well for its intended functions of reducing contact resistance and suppressing minority carrier injection to the OTFT channel. The inclusion of OBL to the MIC helps block MoO3 diffusion and thereby leads to better device stability and an increased on/off ratio. Through combinations with several organic compounds as a buffer layer, the MoO3 diffusion related electrical behaviors of OTFTs are systematically studied. Key parameters related to MoO3 diffusion such as the Fick coefficient and bias-stress stability such as carrier trapping time are extracted from numerical device analysis. Finally, we summarize a general rule of material selection for making robust source-drain contact.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".