Large spin-Hall effect in non-equilibrium binary copper alloys beyond the solubility limit
Bibliographic record
Abstract
Abstract Non-magnetic materials exhibiting large spin-Hall effect (SHE) are eagerly desired for high-performance spintronic devices. Here, we report that non-equilibrium Cu-Ir binary alloys with compositions beyond the solubility limit are candidates as spin-Hall materials, even though Cu and Ir do not exhibit remarkable SHE themselves. Thanks to non-equilibrium thin film fabrication, the Cu-Ir binary alloys are obtained over a wide composition range even though they are thermodynamically unstable in bulk form. We investigate the SHE of Cu-Ir by exploiting a combinatorial technique based on spin Peltier imaging, and find that the optimum Ir concentration for enhancing SHE is around 25 at.%. We achieve a large spin-Hall angle of 6.29 ± 0.19% for Cu76Ir24. In contrast to Cu-Ir, non-equilibrium Cu-Bi binary alloys do not show remarkable SHE. Our discovery opens a new direction for the exploration of spin-Hall materials.
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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 | 0.001 | 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".