Fundamental crystal field excitations in magnetic semiconductor SnO<sub>2</sub>: Mn, Fe, Co, Ni
Bibliographic record
Abstract
Directly measuring elementary electronic excitations in dopant 3d metals is essential to understanding how they function as part of their host material. Through calculated crystal field splittings of the 3d electron band it is shown how transition metals Mn, Fe, Co, and Ni are incorporated into SnO2. The crystal field splittings are compared to resonant inelastic X-ray scattering (RIXS) experiments, which measure precisely these elementary dd excitations. The origin of spectral features can be determined and identified via this comparison, leading to an increased understanding of how such dopant metals situate themselves in, and modify the host's electronic and magnetic properties; and also how each element differs when incorporated into other semiconducting materials. We found that oxygen vacancy formation must not occur at nearest neighbour sites to metal atoms, but instead must reside at least two coordination spheres beyond. The coordination of the dopants within the host can then be explicitly related to the d-electron configurations and energies. This approach facilitates an understanding of the essential link between local crystal coordination and electronic/magnetic properties.
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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".