Understanding and Mitigating the Degradation of Perovskite Solar Cells Based on a Nickel Oxide Hole Transport Material during Damp Heat Testing
Bibliographic record
Abstract
The development of stable materials, processable on a large area, is a prerequisite for perovskite industrialization. Beyond the perovskite absorber itself, this should also guide the development of all other layers in the solar cell. In this regard, the use of NiO x as a hole transport material (HTM) offers several advantages, as it can be deposited with high throughput on large areas and on flat or textured surfaces via sputtering, a well-established industrial method. However, NiO x may trigger the degradation of perovskite solar cells (PSCs) when exposed to environmental stressors. Already after 100 h of damp heat stressing, a strong fill factor (FF) loss appears in conjunction with a characteristic S-shaped J–V curve. By performing a wide range of analysis on cells and materials, completed by device simulation, the cause of the degradation is pinpointed and mitigation strategies are proposed. When NiO x is heated in an air-tight environment, its free charge carrier density drops, resulting in a band misalignment at the NiO x /perovskite interface and in the formation of a barrier impeding hole extraction. Adding an organic layer between the NiO x and the perovskite enables higher performances but not long-term thermal stability, for which reducing the NiO x thickness is necessary.
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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".