Toward Enhancing Solar Cell Performance: An Effective and “Green” Additive
Bibliographic record
Abstract
Performance of bulk heterojunction polymer solar cells (PSCs) highly relies on the morphology of the photoactive layer involving conjugated polymers and fullerene derivatives as donors and acceptors, respectively. Herein, butylamine was found to be able to optimize the morphology of the donor/acceptor (D/A) film composed of a blend of poly(3-hexylthiophene-2,5-diyl) (P3HT) and phenyl-C 61 -butyric acid methyl ester (PCBM). Compared to the commonly used alkane dithiols and halogenated additives with high boiling points, butylamine has a much lower boiling point between 77 and 79 °C, and it is also much “greener”. A specific interaction between butylamine and PCBM was demonstrated to account for the morphology improvement. Essentially, butylamine can selectively dissolve PCBM in the P3HT:PCBM blend and facilitate the diffusion of PCBM in the film fabrication processes. Atomic force microscopy and X-ray photoelectron spectroscopy investigations confirmed the formation of the P3HT-enriched top surface and the abundance of PCBM at the bottom side, i.e., the formation of vertical phase segregation, as a consequence of the specific PCBM–butylamine interaction. The D/A film with inhomogeneously distributed D and A components in the vertical film direction, with more P3HT at the hole extraction side and more PCBM at the electron extraction side, enables more efficient charge extraction in the D/A film, reflected by the largely enhanced fill factor. The power conversion efficiency of devices reached 4.03 and 4.61%, respectively, depending on the thickness of the D/A film, and these are among the best values reported for P3HT:PCBM-based devices. As compared to the devices fabricated without the introduction of butylamine under otherwise the same processing conditions, they represented 19.6 and 21.6% improvement in the efficiency, respectively. The discovery of butylamine as a new, effective additive in enhancing the performance of PSCs strongly suggests that the differential affinity of additives toward donors and acceptors likely plays a more important role in morphology optimization than their boiling point, different from what was reported previously. The finding provides useful information for realizing large-area PSC fabrication, where a “greener” additive is always preferred.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".