Aromatic Alkylammonium Spacer Cations for Efficient Two‐Dimensional Perovskite Solar Cells with Enhanced Moisture and Thermal Stability
Bibliographic record
Abstract
Three‐dimensional (3D) perovskite solar cells are prone to degradation in the presence of moisture, heat, and light. Recently, two‐dimensional (2D) perovskites are synthesized by isolating metal halide perovskite layers using aliphatic or aromatic alkylammonium spacer cation, which can retain their performance under ambient humidity levels due to the hydrophobic property of the spacer cation. However, the best 2D perovskite thus far, using aliphatic short butylammonium (BA) cation as spacer cation, shows only a modest tolerance against moisture and heat due to the inferior hydrophobicity as well as the relatively smaller size of the BA cation. Here, a bulkier aromatic phenylethylammonium (PEA) used as a spacer cation to synthesis 2D perovksite in order to achieve highly stable solar cells. By modifying the crystallization process, an average power conversion efficiency (PCE) of 5.50% is achieved, which is the highest reported PCE for aromatic alkylammonium‐based lower dimensional perovskite solar cells. Importantly, unencapsulated (PEA)2(MA)3Pb4I13 devices show enhanced moisture stability compared to other reported perovskite solar cells in harsh moisture environment (72 ± 2% relative humidity). Moreover, the use of organic materials in p‐i‐n type device, instead of metal oxides, as electron and hole extraction layers also paves the way toward constructing flexible 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 | 0.000 | 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".