Thickness‐Dependent Microstructural Evolution of CsPbBr<sub>3</sub> Nanobricks Induced by Electron Beam Irradiation
Bibliographic record
Abstract
All‐inorganic halide perovskites exhibit exceptional optical properties and are promising photoactive materials for optoelectronics. However, their stability remains a key challenge, exacerbated by a limited understanding of degradation mechanisms. Herein, in situ transmission electron microscopy (TEM) is used to investigate the effect of thickness on the structural stability of CsPbBr3 nanobricks under electron beam irradiation. CsPbBr3 nanobricks with different thicknesses have been prepared using a traditional hot‐injection method, giving rise to a distinctive cubic structure. A modulated structure, caused by bromine vacancy ordering, has been observed in the thin nanobricks. The degradation behaviors of nanobricks are related to thickness‐dependent bromine vacancy formation in the CsPbBr3 lattice. More bromine vacancies exist in thin nanobricks than thick ones, resulting in a greater number of undercoordinated Pb atoms which accelerate irradiation‐induced degradation. Decomposition products include Pb nanoparticles, which also demonstrate thickness‐dependent characteristics. TEM images of Pb nanoparticles formed from thin nanobricks show evidence of irradiation‐induced amorphization. In thicker nanobricks, Pb nanoparticle size increases with the duration of electron beam irradiation, while the remaining Cs atoms bond with Br atoms to form relatively stable CsBr nanoparticles. These results contribute to understanding of degradation mechanisms in cesium lead halide perovskites under electron beam irradiation.
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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".