Insights into Bulk‐Heterojunction Organic Solar Cells Processed from Green Solvent
Bibliographic record
Abstract
The environmental impact of solution processed organic solar cells (OSCs) can be mitigated by introducing so‐called green solvents during the fabrication processes. However, the effects of such green solvents on the molecular‐level structures and optoelectronic properties lack in‐depth characterization. Here, insights into the structure–processing–property correlation of a PPDT2FBT:PC 61 BM bulk‐heterojunction (BHJ) system processed from a green solvent, ortho ‐xylene ( o ‐XY), is investigated in comparison with the same blend processed from a traditional halogenated solvent, chlorobenzene (CB). The BHJ blends are characterized with various techniques probing at difference length scales, and an increased donor:acceptor (D:A) interfacial area as well as well‐mixed features in the bulk morphologies of the active layer are observed for the o ‐XY processed BHJ blend. Furthermore, molecular‐level differences in the D–A intermolecular interactions at the BHJ interfaces in o ‐XY and CB cast films are elucidated by 2‐dimensional solid‐state nuclear magnetic resonance (ssNMR) measurements and analysis. These results are consistent with the device properties, suggesting that the green‐solvent‐processed devices have longer charge carrier lifetimes and faster charge carrier extraction. The optimized PPDT2FBT:PC 61 BM devices processed from o ‐XY can achieve a noteworthy higher power conversion efficiency (PCE) owing to a higher short‐circuit current density and fill factor.
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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".