Engineering of CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> Perovskite Crystals by Alloying Large Organic Cations for Enhanced Thermal Stability and Transport Properties
Bibliographic record
Abstract
The number of studies on organic-inorganic hybrid perovskites has soared in recent years. However, the majority of hybrid perovskites under investigation are based on a limited number of organic cations of suitable sizes, such as methylammonium and formamidinium. These small cations easily fit into the perovskite's three-dimensional (3D) lead halide framework to produce semiconductors with excellent charge transport properties. Until now, larger cations, such as ethylammonium, have been found to form 2D crystals with lead halide. Here we show for the first time that ethylammonium can in fact be incorporated coordinately with methylammonium in the lattice of a 3D perovskite thanks to a balance of opposite lattice distortion strains. This inclusion results in higher crystal symmetry, improved material stability, and markedly enhanced charge carrier lifetime. This crystal engineering strategy of balancing opposite lattice distortion effects vastly increases the number of potential choices of organic cations for 3D perovskites, opening up new degrees of freedom to tailor their optoelectronic and environmental properties.
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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".