Planar-integrated single-crystalline perovskite photodetectors
Bibliographic record
Abstract
Hybrid perovskites are promising semiconductors for optoelectronic applications. However, they suffer from morphological disorder that limits their optoelectronic properties and, ultimately, device performance. Recently, perovskite single crystals have been shown to overcome this problem and exhibit impressive improvements: low trap density, low intrinsic carrier concentration, high mobility, and long diffusion length that outperform perovskite-based thin films. These characteristics make the material ideal for realizing photodetection that is simultaneously fast and sensitive; unfortunately, these macroscopic single crystals cannot be grown on a planar substrate, curtailing their potential for optoelectronic integration. Here we produce large-area planar-integrated films made up of large perovskite single crystals. These crystalline films exhibit mobility and diffusion length comparable with those of single crystals. Using this technique, we produced a high-performance light detector showing high gain (above 10(4) electrons per photon) and high gain-bandwidth product (above 10(8) Hz) relative to other perovskite-based optical sensors.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".