Topological magnets for innovating quantum electronics
Bibliographic record
Abstract
Abstract Macroscopic responses of magnets are often governed by magnetization and thus have been restricted to ferromagnets. However, such responses are found strikingly large in the newly developed topological magnets, breaking the conventional scaling with magnetization. Taking the antiferromagnetic Weyl semimetals as a prime example, we highlight the two central ingredients driving the significant macroscopic responses: the Berry curvature enhanced due to nontrivial band topology in momentum space, and the cluster magnetic multipoles in real space and we show our recent results on the electrical switching of the chiral antiferromagnetic state in its heterostructure using heavy metals and the tunneling magnetoresistance effect using all antiferromagnetic tunnel junctions. Besides, recent studies have indicated that topological magnets exhibit a gigantic anomalous Nernst effect that is a few orders of magnitude larger than previously thought according to its linear relationship to magnetization. Topological electronic structures such as nodal points, lines, and planes are found to generate large Berry curvature and enhance the transverse responses in magnetic states. The discoveries of the novel thermoelectric properties of thin films of recently developed topological magnets pave the path for their application of these effects for the fabrication of heat current sensors.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".