Engineering the Template Layer for Silicon Phthalocyanine‐Based Organic Thin Film Transistors
Bibliographic record
Abstract
Abstract Multi‐phenyl and multi‐thiophene rod‐like molecules are typically used for weak epitaxial growth (WEG) of highly ordered organic semiconductor films enabling controllable microstructure properties and improved device performance. However, very few templating molecules have been reported, making it challenging to establish structure‐property relationships. As semiconductors are integrated into organic thin film transistors (OTFTs), the impact of templating layers on semiconductor microstructure and device performance must be established. Herein, four aromatic molecules with similar structure to para‐sexiphenyl ( p ‐6P) are synthesized and incorporated as the template layer in bis (pentafluoro phenoxy) silicon phthalocyanine (F 10 ‐SiPc) OTFTs. The use of fluorinated p ‐6P ( p ‐6PF) yields devices with the highest electron field‐effect mobility of 0.14 cm 2 V −1 s −1 while a partially fluorinated p ‐6P ( p ‐6PF 4 ) results in improved threshold voltage. X‐ray diffraction (XRD) demonstrates varying F 10 ‐SiPc crystallinity with choice of templating layer with the most crystalline films resulting from the use of p ‐6PF. By grazing incidence wide angle X‐ray scattering (GIWAXS) and polarized Raman microscopy, all templating layers yield films with F 10 ‐SiPc molecules predominantly aligned face‐on to the substrate. However, rod‐like p ‐6P derivatives increased the face‐on orientation of F 10 ‐SiPc. This study highlights the importance of template layer selection and deposition optimization in WEG‐based OTFTs.
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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) | 0.000 | 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 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".