Surface-Enabled Energy Transfer in Ga<sub>2</sub>O<sub>3</sub>–CdSe/CdS Nanocrystal Composite Films: Tunable All-Inorganic Rare Earth Element-Free White-Emitting Phosphor
Bibliographic record
Abstract
Development of inorganic phosphors capable of generating white light in a homogeneous and reproducible fashion without the use of rare earth elements can lead to an efficient, long-lasting, and sustainable solid state lighting. The design of such phosphors requires that different inorganic components emitting in complementary spectral ranges are electronically coupled to avoid the challenges associated with a multicomponent approach, such as inhomogeneity, poor chromaticity control, and low color rendering index. Here we demonstrate coupling between electronically excited blue-emitting Ga 2 O 3 and orange-red-emitting CdSe/CdS core/shell nanocrystals by surface-enabled Förster resonance energy transfer. This energy transfer process is evident from quenching of Ga 2 O 3 (donor) and an enhancement of CdSe/CdS (acceptor) nanocrystal emission and is further confirmed through the diminished lifetime of Ga 2 O 3 and significantly extended lifetime of CdSe/CdS nanocrystals in the composite films. Controlling the energy transfer efficiency by adjusting the separation and distribution of codeposited CdSe/CdS and Ga 2 O 3 nanocrystals allows for tuning of the emission color. White light is reproducibly generated for [CdSe/CdS]:[Ga 2 O 3 ] ≈ 0.5 by tuning energy transfer efficiency to be ca. 25% using 4.5 ± 0.3 nm Ga 2 O 3 and 6.4 ± 0.3 nm CdSe/CdS nanocrystals. The main goal of this work is to quantitatively explore the energy transfer coupling between heterogeneous nanocrystals having complementary optical properties, anchored without the application of organic linkers. These broadly relevant results are applied to demonstrate a path to all-inorganic rare earth element-free nanocrystal phosphors for potential application in white light-emitting diodes and other light-emitting devices.
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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".