Growth of $\varepsilon-\left(\text{In}_{\mathrm{x}} \text{Ga}_{1-\mathrm{x}}\right)_{2} \mathrm{O}_{3}$ on AlN via Pulsed Laser Deposition
Bibliographic record
Abstract
Ga2O3and its alloys are some of the most desirable ultra-wide bandgap semiconductors for high-power and harsh environment electronics, solar blind deep UV photodetectors, deep UV LEDs, toxic gas sensors, and highpower Schottky barrier diodes. In this research, hexagonal$\varepsilon$(In0.15$\left.\text{Ga}_{0.85}\right)_{2} \mathrm{O}_{3}$was successfully deposited on AIN for the very first time. The epitaxial${\varepsilon}$-(In0.15Ga0.85)2O3 was deposited on wurtzite c-plane (0002) AIN via pulsed laser deposition (PLD), using optimized PLD growth parameters, including the temperature and the oxygen partial pressure. It was observed that a moderate substrate temperature of 550 °C and a relatively high PLD oxygen partial pressure of$1.25 \times 10^{-2} \text{Torr}$, a laser energy density of ∼1.38 Jcm−2, and a laser repetition rate of 2 Hz were necessary to successfully grow${\varepsilon}$-(In0.15Ga0.85)2O3. The attained bandgap was 4.53 eV. X-ray photoelectron spectroscopy (XPS) high-resolution depth profile confirmed the uniform presence of indium throughout the${\varepsilon}$-(In0.15Ga0.85)2$\mathbf{O}_{3}$thin films. With$\sim 2500$laser pulses, the attained thickness of$\varepsilon \left(\text{In}_{0.15} \text{Ga}_{0.85}\right)_{2} \mathrm{O}_{3}$was ∼ 80 nm, confirmed by ellipsometry.
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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) | 0.003 | 0.001 |
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".