Scalable van der Waals epitaxy of tunable moiré heterostructures
Bibliographic record
Abstract
The unique physics found in moiré superlattices of twisted or lattice-mismatched atomic layers hold great promise for future quantum technologies. However, twisted configurations are typically thermodynamically unfavorable, making the accurate twist angle control in direct growth implausible. While rotationally aligned moiré superlattices based on lattice-mismatched layers such as WSe2/WS2 can be synthesized, they lack the critical tunability of the moiré period and the moiré formation mechanisms are not well-understood. Here, we report the scalable, thermodynamically driven van der Waals epitaxy of stable moirés with tunable period from 10 to 45 nanometers, based on lattice mismatch engineering in two WSSe layers with adjustable chalcogens ratios. Contrarily to conventional epitaxy, where lattice mismatch induced stress hinders high-quality growth, we reveal the key role of bulk stress in moiré formation, as well as its unique interplay with edge stress in shaping the moiré growth modes. Moreover, the synthesized superlattices display tunable interlayer, and moiré intralayer excitons. Our studies unveil the unique epitaxial science of moiré synthesis and lay the foundations for moiré-based technologies.
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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".