Giant anomalous Nernst effect in polycrystalline thin films of the Weyl ferromagnet Co2MnGa
Bibliographic record
Abstract
Recent discoveries of topological magnets have opened up diverse spintronic applications of large responses due to their unique band structures. A prominent example is the anomalous Nernst effect (ANE), a transverse magneto-thermoelectric phenomenon that produces an electromotive force orthogonal to the heat flux and magnetization. Unlike the Seebeck effect generating an electromotive force parallel to the heat flux, transverse thermoelectric properties of ANE well fit in the lateral configurations of devices fabricated through conventional thin-film fabrication processes. This feature enables distinct device applications through a simplified fabrication process, reduced production cost, extensive area coverage, and enhanced flexibility. In this study, we report the highest ANE ever recorded among all reported polycrystalline films to date by using a topological ferromagnet. In particular, we have fabricated high-quality polycrystalline thin films of the Weyl ferromagnet Co2MnGa that exhibit a large ANE of − 5.4 μV/K. By retaining a high film density, we demonstrate the sizable ANE in the films obtained using a simple fabrication process well suited for device developments. Establishing a thin-film fabrication technique capable of producing a giant ANE facilitates spintronic applications of the Weyl ferromagnet, including diverse ANE-based device applications.
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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".