Short Alkyl Chain Engineering Modulation on Naphthalene Flanked Diketopyrrolopyrrole toward High‐Performance Single Crystal Transistors and Organic Thin Film Displays
Bibliographic record
Abstract
Abstract Studying multi‐purpose applications of a specific material is a challenging topic in the organic electronics community. In this work, through molecular engineering and smart device structure design strategy, high performance in transistors and thin film display devices is simultaneously achieved by applying a simple new dye molecule, naphthalene flanked diketopyrrolopyrrole (DPPN), as the active layer material. Short alkyl chains (hexyl or octyl side groups for H‐DPPN and O‐DPPN, respectively) are adapted to improve the hole mobility in organic thin film transistors (OTFTs) and single crystal transistors (SCTs). Specifically, H‐DPPN shows a similar hole mobility in either OTFTs or SCTs, while O‐DPPN exhibits a dramatically enhanced mobility, reaching 0.125 cm2 V−1 s−1 in SCTs. Additionally, a smart organic light emitting diode (OLED) device is designed by using DPPN molecule as the dopant with a host matrix. The promising external quantum efficiencies of 4.0% and 2.3% are achieved for H‐DPPN and O‐DPPN fabricated OLEDs. Overall, in this work, it is reported that DPP‐based small molecules can simultaneously function well in both transistors and thin film displays with high device performance through molecular and smart device engineering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".