Polymer‐Passivated Inorganic Cesium Lead Mixed‐Halide Perovskites for Stable and Efficient Solar Cells with High Open‐Circuit Voltage over 1.3 V
Bibliographic record
Abstract
Abstract Cesium‐based trihalide perovskites have been demonstrated as promising light absorbers for photovoltaic applications due to their superb composition stability. However, the large energy losses (Eloss) observed in inorganic perovskite solar cells has become a major hindrance impairing the ultimate efficiency. Here, an effective and reproducible method of modifying the interface between a CsPbI2Br absorber and polythiophene hole‐acceptor to minimize the Eloss is reported. It is demonstrated that polythiophene, deposited on the top of CsPbI2Br, can significantly reduce electron‐hole recombination within the perovskite, which is due to the electronic passivation of surface defect states. In addition, the interfacial properties are improved by a simple annealing process, leading to significantly reduced energy disorder in polythiophene and enhanced hole‐injection into the hole‐acceptor. Consequently, one of the highest power conversion efficiency (PCE) of 12.02% from a reverse scan in inorganic mixed‐halide perovskite solar cells is obtained. Modifying the perovskite films with annealing polythiophene enables an open‐circuit voltage (VOC) of up to 1.32 V and Eloss of down to 0.5 eV, which both are the optimal values reported among cesium‐lead mixed‐halide perovskite solar cells to date. This method provides a new route to further improve the efficiency of perovskite solar cells by minimizing the Eloss.
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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".