Dependence of the magnetic properties of MnGaN epitaxial layers on external electrical field
Bibliographic record
Abstract
Abstract Investigation of the magnetic properties of MnGaN epitaxial layers as a function of external electrical field was performed on the basis of field effect structure. The structure included substrate of n-type GaN, epitaxial layer of n-type MnxGa1-xN, dielectric layer and metal layer acting as field effect device gate. Each Mn atom in MnxGa1-xN contributes 4 net spins due to the electrons occupying energy levels 4F, 4D, 4P and 4G belonging to 3d orbital, and these levels are in the energy band gap and in the top of the valence band of MnxGa1-xN. The position of the Fermi level is determined to be in the energy band gap of the layer of GaN and to be above the level 4F in the layer of MnxGa1-xN. In this way application of external negative voltage on the gate causes change in the number of electrons contributing net spins and the saturation magnetization Msat of MnxGa1-xN changes as well. It was found that Msat changes in the range 1.15 × 10−3–0.7 × 10−3 A μm−1 if the external voltage changes in the interval 0–−5V. The application of this structure for the design of spintronic devices is discussed in this paper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".