Magnetism, half-metallicity and electrical transport properties of V- and Cr-doped semiconductor SnTe: A theoretical study
Bibliographic record
Abstract
This work presents results for the electronic structure, magnetic properties, and electrical resistivity of the semiconductor SnTe doped with 3d transition metals V and Cr. From the standpoint of potential application in spintronics, we look for half-metallic states and analyze their properties in both rock salt and zinc blende structures using ab initio electronic structure methods. In both cases, it is the Sn-sublattice that is doped with the transition metals, as has been the case with experiments performed so far. We find four half-metallic compounds at their optimized cell volumes. Results of exchange interactions and the Curie temperature are presented and analyzed for all the relevant cases. Resistivity calculation based on Kubo-Greenwood formalism shows that the resistivities of these alloys due to transition metal doping of the Sn-sublattice may vary, in most cases, from typical liquid metal or metallic glass value to 2–3 times higher. 25% V-doping of the Sn-sublattice in the rock salt structure gives a very high resistivity, which can be traced to high values of the lattice parameter resulting in drastically reduced hopping or diffusivity of the states at the Fermi level.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".