In situ studies of the degradation mechanisms of perovskite solar cells
Bibliographic record
Abstract
Abstract The last decade has seen an extraordinary rise in the performance of perovskite solar cells (PSCs). State‐of‐the‐art devices now have efficiencies of over 25%, putting them on par with the best silicon solar cells. Yet despite their impressive performance, their longevity lags behind that of conventional silicon technology. Environmental factors like moisture, heat, and light can all adversely affect PSC performance and limit device lifetime. Systematically elucidating and eliminating PSC degradation pathways will be critical to the success of this technology. In situ techniques provide powerful tools to this end, as they allow structural, compositional, morphological, and optoelectronic changes to be tracked in real‐time. Because they follow a single film or device over the course of the degradation process, they can help eliminate the statistical variation that negatively affects many studies. Here we provide an overview of perovskite degradation processes, with an emphasis on in situ studies. image
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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".