Green Solvent-Processible N–H-Functionalized Perylene Diimide Materials for Scalable Organic Photovoltaics
Bibliographic record
Abstract
The growing demand for organic electronic devices warrants further development of the scalability and green solvent processibility of π-conjugated materials. Perylene diimide (PDI)-based materials have shown impressive performance as interlayers for electronic devices due to a low E LUMO energy and high charge mobility in films. The next step in the development of these materials is the transition toward scalable production and the fabrication of devices under ambient conditions. Here, we develop a green synthetic methodology to prepare a series of PDI-based electronically active materials ( X2–5 ), which can be slot-die-coated into uniform thin films from green solvents in air. Compounds X2–5 comprised a monomeric PDI core with a functional cyclic secondary amine appended to the bay region. Bromine or cyano moieties are incorporated into the molecular scaffold to systematically tune optoelectronic properties. The utility of these materials is demonstrated by slot-die coating them from ethanol to serve as cathode interlayers in prototype air-processed conventional organic photovoltaics. Using a PM6:Y6 active layer, device power conversion efficiencies reached 10%, among the best reported under these conditions.
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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) | 0.002 | 0.001 |
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".