Effect of Indium Doping on the Growth and Physical Properties of Ultrathin Nanosheets of GaInN/ZnO Solid Solution
Bibliographic record
Abstract
We have prepared single-crystal, thin GaInN/ZnO solid-solution nanosheets by nitration of a single source Ga−In−Zn−O gel-like homogeneous precursor. The thickness of these nanosheets can be as low as about 2 nm. The In doping ratio typically was 1−2%. It is found that while indium plays an important role in the formation of the nanosheets and contributes to their narrow bandgap energy of about 2.55 eV, the impact of Zn doping on the bandgap shrinkage is higher than that of indium. An X-ray absorption near-edge structures (XANES) study confirms the validity of In doping in the solid solution, revealing that it increases chemical disorder, which is evident by the corresponding distortion of the Ga L 3,2 -edge and the N K-edge spectra. From the XANES, we observe that Zn atoms are displaced from the GaN lattice as In is incorporated into the solid solution. X-ray excited optical luminescence measurements show that indium doping reduces zinc acceptors in the GaN lattice, resulting in a blue shift and narrowing of the material’s emission band.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".