A Water-Stable Organic-Inorganic Hybrid Perovskite for Solar Cells by Inorganic Passivation
Bibliographic record
Abstract
Organic-inorganic hybrid halide perovskite solar cells (PSCs) have been a trending topic in recent years. Significant progress has been made to increase their power conversion efficiency (PCE) to more than 20%. However, the poor stability of PSCs in both working and non-working conditions results in rapid degradation through multiple environmental erosions such as water, heat, and UV light. Attempts have been made to resolve the rapid-degradation problems, including formula changes, transport layer improvements, and encapsulations, but none of these have effectively resolved the dilemma. This paper reports our findings on adding inorganic films as surface-passivation layers on top of the hybrid perovskite materials, which not only enhance stability by eliminating weak sites but also prevent water penetration by using a water-stable layer. The surface-passivated hybrid perovskite layer indicates a slight increase of bandgap energy (Eg = 1.76 eV), compared to the original methylammonium lead iodide (MAPbI3, Eg = 1.61 eV) layer, allowing for more stable perovskite layer with a small sacrifice in the photoluminescence property, which represents a lower charge diffusion rate and higher bandgap energy. Our finding offers an alternative approach to resolving the low stability issue for PSC fabrication.
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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".