Band Engineering via Gradient Molecular Dopants for CsFA Perovskite Solar Cells
Bibliographic record
Abstract
Abstract Perovskites with the multi‐cation composition of cesium (Cs), methylammonium (MA), and formamidinium (FA) (CsMAFA) are pursued for their high power conversion efficiencies, but they are limited by their thermal stability. To withstand damp‐heat accelerated aging MA‐free compositions such as CsFA are of interest, but these exhibit lower carrier diffusion lengths and thus lesser performance in photovoltaic devices. A band engineering strategy that overcomes limited carrier diffusion within inverted perovskite solar cells based on CsFA is reported. A joint experimental‐computational study shows that treating the perovskite with an n‐type molecular dopant increases band bending, shaping the electric field across the active layer to overcome limited diffusive transport. Using this strategy, CsFA solar cell devices with stabilized power conversion efficiencies of 20.3%, a high value for devices using CsFA active layers, are fabricated.
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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".