Amphoteric Chelating Ultrasmall Colloids for FAPbI<sub>3</sub> Nanodomains Enable Efficient Near-Infrared Light-Emitting Diodes
Bibliographic record
Abstract
Perovskite light-emitting diodes (PeLEDs) are the next promising display technologies because of their high color purity and wide color gamut, while two classical emitter forms, i.e., polycrystalline domains and quantum dots, are encountering bottlenecks. Weak carrier confinement of large polycrystalline domains leads to inadequate radiative recombination, and surface ligands on quantum dots are the main annihilation sites for injected carriers. Here, pinpointing these issues, we screened out an amphoteric agent, namely, 2-(2-aminobenzoyl)benzoic acid (2-BA), to precisely control the in situ growth of FAPbI 3 (FA: formamidine) nanodomains with enhanced space confinement, preferred crystal orientation, and passivated trap states on the transport-layer substrate. The amphoteric 2-BA performs bidentate chelating functions on the formation of ultrasmall perovskite colloids (<1 nm) in the precursor, resulting in a smoother FAPbI 3 emitting layer. Based on monodispersed and homogeneous nanodomain films, a near-infrared PeLED device with a champion efficiency of >22% plus enhanced T 80 operational stability was achieved. The proposed perovskite nanodomain film tends to be a mainstream emitter toward the performance breakthrough of PeLED devices covering visible wavelengths beyond infrared.
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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".