Interface-controlled antiferromagnetic tunnel junctions
Bibliographic record
Abstract
Magnetic tunnel junctions (MTJs) are essential components of high-performance spintronic devices. While conventional MTJs use ferromagnetic materials, antiferromagnetic (AFM) compounds can significantly increase operation speed and packing density. Current AFM tunnel junctions (AFMTJs) exploit antiferromagnets as spin-filter barriers or metal electrodes with bulk spin-dependent currents. Here, we highlight a largely overlooked AFMTJ prototype with bulk-spin-degenerate electrodes exhibiting A-type AFM stacking, forming magnetically uncompensated interfaces that enable spin-polarized tunneling currents and a sizable tunneling magnetoresistance (TMR). Using first-principles quantum-transport calculations and van der Waals (vdW) metal Fe 4 GeTe 2 as an example, we demonstrate a large negative TMR from interfacial magnetic moment alignment. This prototype can also be realized with non-vdW A-type AFM metals featuring roughness-insensitive surface magnetization. Beyond TMR, these AFMTJs allow convenient switching of the Néel vector, opening new avenues for AFM spintronics based on interface-driven spin-dependent properties.
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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".