Data for: Superconductivity in twisted double bilayer graphene stabilized by WSe₂
Bibliographic record
Abstract
Abstract Identifying the essential components of superconductivity in graphene-based systems remains a critical problem in 2D materials research, connecting this field to the mysteries that underpin investigations of unconventional superconductivity throughout condensed-matter physics. Superconductivity has been previously observed in magic-angle twisted stacks of monolayer graphene but conspicuously not in twisted stacks of bilayer graphene, although both systems host topological flat bands and symmetry-broken states. Here, we report the discovery of superconductivity in twisted double bilayer graphene (TDBG) in proximity to WSe2. Samples with twist angles 1.24 and 1.37 degrees superconduct in small pockets of the gate-tuned phase diagram within the valence and conduction band, respectively. Superconductivity emerges from unpolarized phases near van Hove singularities and next to regions with broken isospin symmetry, showing the correlation between a high density of states and the emergence of superconductivity in TDBG while revealing a possible role for isospin fluctuations in the pairing.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.131 | 0.073 |
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".