Observation of Pure-Spin-Current Diodelike Effect at the Au/Pt Interface
Bibliographic record
Abstract
Asymmetric charge transport at the interface of two materials with dissimilar electrical properties, such as metal-semiconductor and p-n junctions, is the fundamental feature behind modern diode and transistor technology. Spin pumping from a ferromagnet into an adjacent nonmagnetic material is a powerful technique to generate pure-spin currents, wherein spin transport is unaccompanied by net charge transport. It is therefore interesting to study pure-spin transport at the interface of two materials with different spin transport properties. Here we demonstrate asymmetric transport of pure-spin currents across an interface of dissimilar nonmagnetic materials Au/Pt. We exploit Py/Au/Pt/Co structures where spin pumping can generate pure-spin current from either Py or Co independently. We find that the transmission of pure-spin current from Au into Pt is twice as efficient as transmission from Pt into Au. Experimental results are interpreted by extending conventional spin-pumping, spin-diffusion theory to include boundary conditions of reflected and transmitted spin current at the Au/Pt interface that are proportional to the established spin chemical potentials on either side of the interface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".