Controlled Morphological Growth and Photonic Lasing in Cesium Lead Bromide Microcrystals
Bibliographic record
Abstract
Morphology plays a crucial role in defining the optical, electronic, and mechanical properties of halide perovskite microcrystals. Therefore, developing strategies that offer precise control over crystal morphology during the growth process is highly desirable. This work presents a simple scheme to simultaneously grow distinct geometries of cesium lead bromide (CsPbBr3) microcrystals, including microrods (MR), microplates (MP), and microspheres (MS), in a single chemical vapor deposition (CVD) experiment. By strategically adjusting precursor evaporation temperatures, flux density, and the substrate temperature, we surpass previous techniques by achieving simultaneous yet selective growth of multiple CsPbBr3 geometries at distinct positions on the same substrate. This fine growth control is attributed to the synergistic variation in fluid flow dynamics, precursor substrate distance, and temperature across the substrate, offering regions suitable for the growth of different morphologies. Pertinently, perovskite MR are grown at the top, while MP and MS are observed at the center and bottom regions of the substrate, respectively. Structural analysis reveals high crystallinity and an orthorhombic phase of the as-grown perovskite microcrystals, while persistent photonic lasing manifests their nonlinear optical characteristics, underpinning their potential application for next-generation photonic and optoelectronic devices.
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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) | 0.000 | 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) | 0.000 | 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".