Template-Assisted Assembly of DPP-TTT over a Hydrophilic Liquid Subphase toward Enhanced Charge Transport in Organic Field-Effect Transistors
Bibliographic record
Abstract
The progress in flexible electronics significantly benefits from improvements in charge transport within organic field-effect transistors (OFETs). The techniques used to incorporate organic conjugated polymers (CPs) into devices greatly influence their performance. In this study, we introduce an innovative method that utilizes the flexibility and solution-processing capabilities of donor–acceptor (D–A) type CPs, combined with the electrical conductivity and durability of two-dimensional (2D) organic materials in a composite mixture. Furthermore, during the production of thin films via the “unidirectional floating film transfer method (UFTM)”, it was observed that 2D organic C 3 N 5 nanosheets enhance the organization of the D–A polymer, poly[2,5-(2-octyl-dodecyl)-3,6-diketopyrrolopyrrole- alt -5,5-(2,5-di(thien-2-yl) thieno[3,2- b ] thiophene)] (DPP-TTT), on a hydrophilic liquid base, acting as a structural scaffold. This approach promotes the development of well-ordered DPP-TTT arrays, improving π–π stacking and intermolecular forces, which are essential for efficient charge transport. The OFETs crafted using this technique show a remarkable increase in charge carrier mobility, up to 0.41 cm 2 /(V s), with on/off ratios of 10 4 and superior operational durability. Our findings highlight the effectiveness of scaffold-assisted assembly on a liquid phase and the combined benefits of D–A polymers with 2D organic materials, offering a powerful approach for creating organic semiconductors with enhanced electrical characteristics. This opens promising pathways for advancing high-performance flexible electronic devices.
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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".