Spatially correlated incommensurate lattice modulations in an atomically thin high-temperature <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Bi</mml:mi><mml:mrow><mml:mn>2.1</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mi>Sr</mml:mi><mml:mrow><mml:mn>1.9</mml:mn></mml:mrow></mml:msub><mml:mi>Ca</mml:mi><mml:msub><mml:mi>Cu</mml:mi><mml:mrow><mml:mn>2.0</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mrow><mml:mn>8</mml:mn><mml:mo>+</mml:mo><mml:mi>y</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> superconductor
Bibliographic record
Abstract
The authors present the first nanoscale imaging of X-ray diffraction in atomically thin superconducting Bi${}_{2.1}$Sr${}_{1.9}$CaCu${}_{2.0}$O${}_{8+\ensuremath{\delta}}$ single crystals, employing the scanning X-ray nanobeam 100 nanometers wide. By simultaneously mapping the lattice and superlattice peaks over the crystal, they find that while the lattice peak position remains constant over the scan area, the superlattices peaks vary in position, reflecting mesoscale inhomogeneities. Remarkably, while the two types of superlattice peaks are correlated in k-space position in the bulk, they become anti-correlated when the crystals become two-unit cells thick. Reducing dimensionality towards atomic limit changes the lattice strain locally allowing raising of the new mesoscopic patterns, which controls charge distribution and material electronic 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".