Nitrogen incorporation into GaAsN and InGaAsN layers grown by liquid‐phase epitaxy
Bibliographic record
Abstract
Abstract This paper presents the comparison of nitrogen incorporation in GaAsN and InGaAsN layers grown on GaAs substrate from Ga‐ and In‐rich solution, respectively, by liquid‐phase epitaxy. Polycrystalline GaN has been used as a source of nitrogen in two cases. The initial epitaxy temperature has been varied in the temperature range 600‐550 °C. Nitrogen content in Ga1‐xAsNx grown layers has been determined to be in the range 0.1‐0.5%. Higher nitrogen incorporation efficiency has been found for quaternary InGaAsN layers grown under carefully chosen lattice matched conditions. The incorporation of nitrogen into GaAsN and InGaAsN layers has been study by vibrational mode absorption spectroscopy. Nitrogen‐induced vibration mode near 472 cm‐1 has been registered in GaAsN samples. Preferential In‐N bonds and the formation of N‐centred In3Ga1 clusters have been identified for lattice matched to GaAs epitaxial InGaAsN layers. Electrical properties of the samples have been characterized by temperature‐dependent Hall effect measurements. Nominally undoped GaAsN and InGaAsN grown layers are n‐type with Hall concentration about one order of magnitude higher in comparison to layers not containing nitrogen. Thermally activated increase in the free carrier concentration at temperatures higher than 150 K is observed which indicates the presence of N‐related deep donor levels below dilute nitride conduction band edge. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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".