Unveiling Photovoltaic Performance Enhancement Mechanism of Polymer Solar Cells via Synergistic Effect of Binary Solvent Additives
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Bibliographic record
Abstract
Binary solvent additive engineering is an effective strategy to optimize photoactive films for high‐efficiency organic solar cells, however, the effect of single components on device performance and the combination principle of binary solvent additives remain unclear. Herein, synchrotron‐based grazing incident X‐ray diffraction, Derjaguin–Muller–Toporov modulus imaging, and plasmon energy shift imaging acquired by scanning transmission electron microscopy to investigate the effect of new binary solvent additive of 1,8‐diiodooctane (DIO) and less‐toxic and p‐anisaldehyde (AA) on device performance of solar cells based on poly[(5,6‐difluoro‐2,1,3‐benzothiadiazol‐4,7‐diyl)‐alt‐(3,3‴‐di(2‐octyldodecyl)2,2′;5′,2″;5″,2‴‐quaterthio‐phen‐5,5‴‐diyl)] (PffBT4T‐2OD) and [6,6]‐phenyl‐C61‐butyric acid methyl ester (PC61BM) are used. It is found that AA mainly favors polymer order and high crystallinity of PffBT4T‐2OD. Differently, DIO mainly enables PC61BM diffusing into PffBT4T‐2OD polymer matrix, leading to enlarged donor–acceptor (D–A) interface. As expected, by combining AA and DIO, the composite film provides large D–A interface and more balanced charge carrier transport. Consequently, their beneficial synergistic effect results in enhanced short circuit current and fill factor, and thereby increased power conversion efficiency of 10.64%, improved by 16% with respect to the control device. Herein, a general mechanism of enhancing device performance via the combination of solvent additives with different contributions to photoactive film is unveiled.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it