Versatile Two‐Step Process for Perovskite‐Based Tandem Photovoltaics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perovskite photovoltaics promise high power conversion efficiencies (PCEs) and cost‐effective fabrication, making them a transformative solar technology. Among deposition methods, the solution‐based two‐step process has emerged as a promising approach for integrating high‐quality perovskite layers onto silicon (Si) bottom cells, enabling dense and pinhole‐free films. However, achieving both high efficiency and long‐term stability remains underexplored for solution‐based two‐step‐processed perovskite solar cells (PSCs). This study introduces a versatile solution‐based two‐step method, demonstrating a seamless transition from a triple‐cation (CsMAFA) to a more stable double‐cation (CsFA) perovskite composition. Implementing a novel dual bimolecular passivation strategy with propane‐1,3‐diammonium iodide (PDAI 2 ) and n‐butylammonium iodide (BAI) for both bulk and surface passivation effectively addresses defects at grain boundaries and interfaces. This approach minimizes nonradiative recombination, enhances film crystallization, and promotes efficient charge extraction. The resulting PSCs demonstrate a stable power output of 20.9%, representing the highest reported efficiency for a solution‐based two‐step processed PSC with a bandgap of 1.67 eV. Laboratory‐scale monolithic perovskite/Si tandem solar cells (1 cm 2 active area) achieve PCEs exceeding 26% on small‐textured Si bottom cells (<2 μm). This emphasizes the potential of the solution‐based two‐step process for practical implementation in high‐performance photovoltaic systems.
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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