Perylene Diimide Based Organic Photovoltaics with Slot-Die Coated Active Layers from Halogen-Free Solvents in Air at Room Temperature
Bibliographic record
Abstract
Herein, we investigate the role of processing solvent additives on the formation of polymer–perylene diimide bulk-heterojunction active layers for organic photovoltaics using both spin-coating and slot-die coating methods. We compare the effect of 1,8-diiodooctane (DIO) and diphenyl ether (DPE) as solvent additives on the aggregation behavior of the non-fullerene acceptor, N-annulated perylene diimide dimer (tPDI 2 N-EH), in neat films and blended films with the benzodithiophene-quinoxaline (BDT-QX, QX-3) donor polymer, processed from toluene in air. DIO processing crystallizes the tPDI 2 N-EH acceptor and leads to the decreased solar cell performance. DPE processing has a more subtle effect on the bulk-heterojunction morphology and leads to an improved solar cell performance. A comparison of the spin-coating vs slot-die coating methods shows that the effect of DPE is prominent for the slot-die coated active layers. While similar device power conversion efficiencies are achieved with active layers coated with both methods (ca. 7.3% vs 6.5%), the use of DPE improves the film quality when the slot-die coating method is employed.
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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".