Epitaxial GaN using Ga(NMe2)3 and NH3 Plasma by Atomic Layer Deposition
Bibliographic record
Abstract
<div>Low temperature deposition of high-quality epitaxial GaN is crucial for its integration in</div><div>electronic applications. Chemical vapor deposition at approximately 800 °C using SiC with an</div><div>AlN buffer layer or nitridized sapphire as substrates is used to facilitate the GaN growth. Here,</div><div>we present a low temperature atomic layer deposition (ALD) process using</div><div>tris(dimethylamido)gallium(III) with NH3 plasma. The ALD process shows self-limiting</div><div>behaviour between 130-250 °C with a growth rate of 1.4 Å/cycle. The GaN films produced were</div><div>crystalline on Si(100) at all deposition temperatures with a near stochiometric Ga/N ratio with</div><div>low carbon and oxygen impurities. When GaN was deposited on 4H-SiC, the films grew</div><div>epitaxially without the need for an AlN buffer layer, which has never been reported before. The bandgap of the GaN films was measured to be ~3.42 eV and the fermi level showed that the GaN was unintentionally n-type doped. This study shows the potential of ALD for GaN-based</div><div>electronic devices.</div>
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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 | 0.000 | 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 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".