Moiré Valleytronics: Realizing Dense Arrays of Topological Helical Channels
Bibliographic record
Abstract
We propose a general and robust platform, the moiré valleytronics, to realize high-density arrays of 1D topological helical channels in real materials at room temperature. We demonstrate the idea using a long-period 1D moiré pattern of graphene on hBN by first-principles calculation. Through calculating the Berry curvature and topological charge of the electronic structure associated with various local graphene/hBN stackings in the moiré pattern, it is revealed that the helical channel arrays originate intrinsically from the periodic modulation of the local topological orders by the moiré pattern. For a freestanding wavelike moiré pattern, two groups of helical channel arrays are spatially separated out of plane, validating the structural robustness of the moiré topology. The generality and experimental feasibility of moiré valleytronics are demonstrated by investigating a broad range of moiré systems.
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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".