Energy Transfer between Conjugated Colloidal Ga2O3 and CdSe/CdS Core/Shell Nanocrystals for White Light Emitting Applications
Bibliographic record
Abstract
Developing solid state materials capable of generating homogeneous white light in an energy efficient and resource-sustainable way is central to the design of new and improved devices for various lighting applications. Most currently-used phosphors depend on strategically important rare earth elements, and rely on a multicomponent approach, which produces sub-optimal quality white light. Here, we report the design and preparation of a colloidal white-light emitting nanocrystal conjugate. This conjugate is obtained by linking colloidal Ga₂O₃ and II-VI nanocrystals in the solution phase with a short bifunctional organic molecule (thioglycolic acid). The two types of nanocrystals are electronically coupled by Förster resonance energy transfer owing to the short separation between Ga₂O₃ (energy donor) and core/shell CdSe/CdS (energy acceptor) nanocrystals, and the spectral overlap between the photoluminescence of the donor and the absorption of the acceptor. Using steady state and time-resolved photoluminescence spectroscopies, we quantified the contribution of the energy transfer to the photoluminescence spectral power distribution and the corresponding chromaticity of this nanocrystal conjugate. Quantitative understanding of this new system allows for tuning of the emission color and the design of quasi-single white light emitting inorganic phosphors without the use of rare-earth elements.
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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".