Thermally Stable Charge Transport Materials for Vapor‐Phase Fabrication of Perovskite Devices
Bibliographic record
Abstract
Perovskite light‐emitting diodes (PeLEDs) have attracted tremendous research interest in recent years. Cesium lead bromide's (CsPbBr3) high color purity, intrinsically high photoluminescence quantum yield, and tunable emission wavelength make it a strong candidate as an emitter for light‐emitting applications. Organic charge transport materials and their impact on the growth mode of the perovskite layer have a pivotal influence on the device performance. Herein, it is reported that hole transport layers (HTLs) with higher glass transition temperatures (Tg) are critical to facilitate the growth of crystalline perovskites and thus the color purity. Second phase regions with higher Pb density are observed in films growing on HTLs with inadequate lower Tg. A minimum 100 °C glass transition is found to be essential to grow cesium lead bromides with sharp emission peaks. In addition to high glass transition temperature, high ionization energy (>5.6 eV) is also found to be important to remove the HTL/perovskite injection barrier. The optimal device in this study is fabricated with 3,5‐di(9H‐carbazol‐9‐yl)tetraphenylsilane (SimCP2) as the HTL and the device shows a very sharp 19 nm full‐width at half‐maximum emission.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".