Tracking the evolution of materials and interfaces in perovskite solar cells under an electric field
Bibliographic record
Abstract
Abstract What causes the instability of perovskite solar cells has been a puzzling problem impeding the development of commercial panels. So far there is limited evidence on the link between device instability and the various materials in each of the stacked layers. Here, we study the chemistry and distribution of various species and the integrity of the functional layers in high-performance inverted perovskite solar cells, with and without an electric field. The distribution of the diffusion species and its impact on the chemical and electronic structures through the transporting layers are measured by photoemission spectroscopy combined with damage-free ion beam sputtering. We find that various species, such as I 2 and PbI 2 , are distributed throughout the organic transporting layers toward the electrode interface. These species are found to be charge neutral, have no impact on the Fermi level, and react little with copper. An electric field, however, can catalyze the electro-decomposition of the perovskite, causing chemical heterogeneity and degradation in device performance.
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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".