New magnesium based half-metallic ferromagnetic chalcogenide MgFe <sub>2</sub> Z <sub>4</sub> (Z = S, Se) spinels; a promising materials for spintronic applications
Bibliographic record
Abstract
Abstract This article focuses on the physical properties of MgFe 2 Z 4 (Z = S, Se) spinels investigated by employing density functional theory calculations. To explore the magnetic and electronic properties, WIEN2k code was executed whereas thermoelectric properties were studied using the BoltzTraP. The determined negative formation energies and positive phonon frequencies show that the system under investigation is stable. The lowest possible ground state energies clearly indicate that spinels lie in ferromagnetic state. Studied spinels illustrated half-metallic nature upon employing the calculations of density of states (DOS) and spin-polarized band structures (BS). Ferromagnetic (FM) state was found to be stable ground state. Observation of ferromagnetism in these compounds was ensured by exchange energies, Jahn-Teller energy and hybridization and is attributed to electron spin in place of Fe 2+ clustering. Curie temperature and spin polarization of these compounds is also comprehensively investigated in this study. Analysis of the thermoelectric properties showed a good fit between the ratio of electrical ( σ / τ ) and thermal conductivity ( κ e / τ ). Thermoelectric efficiency of studied compounds is found to be appropriate as demonstrated by the thermoelectric power factors.
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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".