Towards upscaling of organic photovoltaics using non-fullerene acceptors
Bibliographic record
Abstract
Herein, we present our current efforts on fundamental research towards large area organic photovoltaic devices using nonfullerene acceptors (NFAs). First, we present a short review of the main highlights of the state-of-the art in large-area organic solar cells (OSCs) coating. We then present our guidelines to prepare OSCs in an environmentally friendly way from the synthesis of the organic compounds to the choice of the solvent for the coating solutions and the actual OSCs coating. As a starting point, we paired a perylene diimide (PDI) acceptor, PDI2-EH, to the donor polymer PBDB-T to compare spin-coated and slot-die coated OSC devices. Considering the poor solubility of this bulk-heterojunction system in non-halogenated solvents, we focused our efforts to slot-die coat the soluble PDI2-EH acceptor on glass and polyethylene terephthalate (PET) substrates from non-halogenated solvents such as toluene, o-xylenes and anisole. We also explored the influence of different UV/ozone treatments for cleaning the PET substrates. Overall, this study presents practical considerations for laying foundations to proceed with an environmentally responsible upscale of OSC coatings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".