The Use of Green‐Solvent Processable Molecules with Large Dipole Moments in the Electron Extraction Layer of Inverted Organic Solar Cells as a Universal Route for Enhancing Stability
Bibliographic record
Abstract
Abstract Employing a large dipole interlayer has recently been one of the most captivating interfacial engineering approaches in organic solar cells (OSCs). In this work, the effect of using green‐solvent processable molecules with large dipole moments as electron extraction layers (DM‐EELs) on OSCs’ stability is investigated. The inverted OSCs are based on two donor–acceptor systems, with histidine and sarcosine as representative DM‐EELs and with ZnO as a control EEL. Stability results illustrate that while the dominant degradation mechanism depends on the donor–acceptor system (photoinduced degradation vs temporal degradation), using DM‐EELs substantially suppresses degradation and enhances stability in both cases. The voltage‐dependent ideality factor characteristics show that the DM‐EEL OSCs exhibit minimal recombination mechanism changes even after UV exposure. By contrast, ZnO cells are limited by significant shunt formation and UV‐induced surface recombination. Low‐temperature measurements verify that unlike the indium tin oxide (ITO)/ZnO contact, the ITO/DM‐EEL contact is not affected by trap states or work function variations. As a result, the ITO/DM‐EEL contact maintains its electron‐selectivity and resists UV‐induced surface recombination observed in the ZnO cells. The results show that using green‐solvent processable materials with large dipole moments as EELs can provide a universal route for enhancing the stability of inverted OSCs.
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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".