Selective Tuning of Benzothiadiazole Functionality Enables High Crystallinity and Mobility in Regiorandom <i>n</i>-Type Polymers for Organic Field-Effect Transistors
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide We report three novel donor–acceptor (D–A) copolymers sharing a common fused donor unit (CDTT) but differing in the functionalization of the benzothiadiazole (BT) acceptor unit. Acceptors bearing two cyano groups (DCNBT) are compared to novel acceptors bearing one cyano and one fluorine group (FCNBT) or one nitro and one fluoro group (NO 2 FBT). The choice of the acceptor has a significant effect on the optoelectronic properties of the resulting polymers. In organic field-effect transistor (OFET) devices, PCDTT-DCNBT exhibited moderate performance with an electron mobility of 0.031 cm 2 V –1 s –1, whereas PCDTT-FCNBT demonstrated significantly improved electron mobility (0.4 cm 2 V –1 s –1 ). The improved performance is attributed to increased backbone linearity combined with a more coplanar backbone and high thin-film crystallinity. In comparison, the presence of the nitro group is shown to have a detrimental impact, with a blue-shifted absorption and a 0.2 eV increase in band gap compared to the cyanated polymers. Steric effects are shown to limit the nitro group’s π-accepting capability and result in reduced device performance, with an electron mobility of 0.024 cm 2 V –1 s –1 . This study introduces a new BT building block and highlights that substituent tuning via cyano and fluorine groups is an effective approach for modulating polymer morphology and electron transport.
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".