Ionic Liquid-Assisted MAPbI<sub>3</sub> Nanoparticle-Seeded Growth for Efficient and Stable Perovskite Solar Cells
Bibliographic record
Abstract
With the rapid improvement of perovskite solar cells (PSCs), long-life operational stability has become a major requirement for their commercialization. In this work, we devised a pristine cesium–formamidinium–methylammonium (termed as CsFAMA) triple-cation-based perovskite precursor solution into the ionic liquid (IL)-assisted MAPbI3 nanoparticles (NPs) through a seeded growth approach in which the host IL-assisted MAPbI3 NPs remarkably promote high-quality perovskite films with large single-crystal domains, enhancing the device performance and stability. The power conversion efficiency (PCE) of the MAPbI3 NP-seeded growth of MAPbI3 NPs/CsFAMA-based PSCs is as high as 19.44%, which is superior to those of MAPbI3 NPs and pristine CsFAMA films as the photoactive layer (9.52 and 17.33%, respectively). The long-term light-soaking and moisture stability of IL-aided MAPbI3 NPs/CsFAMA-based devices (non-encapsulated) remain above 90 and 80%, respectively, of their initial output after 2 h of light illumination (1 sun) and 6000 h storage at ambient with a relative humidity range of 30–40%. The use of the IL-assisted MAPbI3 NP-seeded growth for PSCs is a significant step toward developing stable and reliable perovskite photovoltaic devices.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".