Strain‐Induced Large Anomalous Nernst Effect in Polycrystalline Co<sub>2</sub>MnGa/AlN Multilayers
Bibliographic record
Abstract
Abstract The anomalous Nernst effect (ANE), one of the thermoelectric effects in a magnet, is recently attracting growing interest with its potential for the next generation high‐efficiency energy‐harvesting applications. However, the reported thermoelectric conversion efficiencies with ANE are small compared to those with Seebeck effect, which hampers its practical application. Unlike the intensive effort of seeking novel materials with large intrinsic ANE, here a new pathway is proposed to enhance the ANE by exploiting the strain induced in a multilayer structure. A large anomalous Nernst coefficient of 4.9 µV K−1 is achieved for a polycrystalline Co2MnGa/AlN multilayer film deposited on an amorphous substrate, which is larger than 3.8 µV K−1 for a polycrystalline Co2MnGa single layer film. The enhanced ANE is attributed to the effect of interfacial strain on the Seebeck coefficient, which is barely discussed yet. Since the AlN layer is available on any substrate materials, even on a flexible polyimide substrate large ANE is successfully achieved for the Co2MnGa/AlN stack. The findings and demonstration have opened a way to develop the ANE‐based potential 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) | 0.000 | 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".