Metallic Lead Formation in Perovskites: Mechanisms, Suppression, and Future Directions
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Lead halide perovskites APbX 3 (A = methylammonium, formamidinium, cesium; X = halogen) have advanced the field of optoelectronics, particularly in solar cells, photodetectors, and light-emitting diodes, due to their outstanding properties. However, a significant challenge remains unresolved: the formation of metallic lead (Pb 0 ), which introduces deep-level defects that trap charge carriers and degrade device performance. The formation of Pb 0 in perovskites can occur after their synthesis under various conditions, including high-energy radiation, light, heat, and moisture, and has also been observed during perovskite crystallization. Thus, it is crucial to understand the underlying mechanisms of Pb 0 formation and its suppression pathways. Recent studies have explored various strategies to suppress Pb 0 formation, including compositional engineering, additive incorporation, and protective passivation layers. In this review, we discuss the origins of Pb 0 formation in perovskites, focusing on the mechanisms driving this process under different environmental conditions, and then strategies for suppressing Pb 0 formation, including compositional engineering and passivation techniques. By addressing these aspects, we seek to identify pathways for enhancing the stability and performance of perovskite-based devices, enabling their widespread adoption in commercial applications.
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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) | 0.001 | 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".