Homogenized contact in all- perovskite tandems using tailored 2D perovskite
Bibliographic record
Abstract
The fabrication of scalable all-perovskite tandem solar cells is considered an attractive route to commercialize perovskite photovoltaic modules1. However, The certified efficiency of 1-cm2 scale all-perovskite tandem solar cells lags behind their small-area (~0.1 cm2) counterparts. This performance deficit originates from inhomogeneity in wide-bandgap (WBG) perovskite solar cells (PSCs) at a large scale. The inhomogeneity is known to be introduced at the bottom interface and within the perovskite bulk itself. Here we uncover another crucial source for the inhomogeneity – the top interface formed during the deposition of the electron transport layer (ETL, C60). Meanwhile, the poor ETL interface is also a significant limitation of device performance. We address this issue by introducing a mixture of 4-fluorophenethylamine (F-PEA) and 4-trifluoromethyl phenylammonium (CF3-PA) to create a tailored two-dimensional perovskite layer (TTDL), in which F-PEA forms a two-dimensional perovskite at the surface reducing contact losses and inhomogeneity, CF3-PA enhances charge extraction and transport. As a result, we demonstrate a high open-circuit voltage of 1.35 V and an efficiency of 20.5% in 1.77-eV WBG PSCs at a square centimeter scale. By stacking with a narrow-bandgap perovskite sub-cell, we report 1.05 cm2 all perovskite tandem cells delivering 28.5% (certified 28.2%) efficiency, the highest among all reported so far. Our work showcases the importance of treating the top perovskite/ETL contact for upscaling perovskite solar cells.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".