Unravel the Effects of UV Light on the Lattice Stability of Perovskite via Numerical Simulation
Bibliographic record
Abstract
Abstract The light degradation of perovskite greatly hinders the commercialization of perovskite solar cells, which is yet to be resolved, despite the many attempts. A simulation method is applied here to illustrate the degradation kinetics, which reveals that under dark conditions, these perovskites show minimal degradation, suggesting that water and oxygen have little damaging effect without light. However, exposure to UV light significantly accelerates the degradation, which can be reduced by introducing self‐assembling from Zn 2+ and 1‐(triazol‐1‐ly)‐4‐(tetrazol‐5‐ylmethyl) benzene (Zn‐TTB) as an additive. This indicates that defect passivation via additives can significantly enhance the durability of perovskite materials. These findings not only provide insights into the kinetics of UV‐induced degradation of perovskites but also highlight the role of additives in improving the longevity of these materials, offering promising directions for their practical application under UV‐exposed conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".