Colloidal Gallium Indium Oxide Nanocrystals: A Multifunctional Light-Emitting Phosphor Broadly Tunable by Alloy Composition
Bibliographic record
Abstract
We demonstrate compositionally tunable photoluminescence in complex transparent conducting oxide nanocrystals. Alloyed gallium indium oxide (GIO) nanocrystals with variable crystal structures are prepared by a colloidal method throughout the full composition range and studied by different structural and spectroscopic methods, including photoluminescence and X-ray absorption. The structures and sizes of the GIO nanocrystals can be simultaneously controlled, owing to the difference in the growth kinetics of In(2)O(3) and Ga(2)O(3) nanocrystals and the polymorphic nature of both materials. Using the synthesized nanocrystal series, we demonstrate the structural and compositional dependences of the photoluminescence of GIO nanocrystals. These dependences, induced by the interactions between specific defect sites acting as electron donors and acceptors, are used to achieve broad emission tunability in the visible spectral range at room temperature. The nature of the photoluminescence is identified as donor-acceptor pair recombination and changes with increasing indium content owing to the changes in the energy states of, and interactions between, donors and acceptors. Structural analysis of GIO nanocrystals by extended X-ray absorption fine structure spectroscopy reveals that In(3+) occupies only octahedral, rather than tetrahedral, sites in the spinel-type γ-Ga(2)O(3) nanocrystal host lattice, until reaching the substitutional incorporation limit of ca. 25%. The emission decay dynamics is also strongly influenced by the nanocrystal structure and composition. The oxygen vacancy defects, responsible for the observed photoluminescence properties, are also implicated in other functional properties, particularly conductivity, enabling the application of colloidal GIO nanocrystals as integrated optoelectronic materials.
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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) | 0.000 | 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".