Tuning charge density wave order and structure via uniaxial stress in a stripe-ordered cuprate superconductor
Bibliographic record
Abstract
Spin and charge density wave order in the cuprates are known to compete with superconductivity. In the stripe order ${(\text{La},M)}_{2}{\mathrm{CuO}}_{4}$ family of cuprates, spin and charge order occur as unidirectional order that can be stabilized by symmetry-breaking structural distortions, such as the low-temperature tetragonal (LTT) phase. Here we examine the interplay between structure and the formation of charge density wave (CDW) order in the LTT phase of ${\mathrm{La}}_{1.475}{\mathrm{Nd}}_{0.4}{\mathrm{Sr}}_{0.125}{\mathrm{CuO}}_{4}$ by applying uniaxial stress to distort the structure and influence the formation of CDW order. Using resonant soft x-ray scattering to measure both the CDW order and (0 0 1) structural-nematic Bragg peaks, we find that the application of uniaxial stress along the Cu-O bond direction suppresses the (0 0 1) peak and has the net effect of reducing CDW order, but does so only for CDW order propagating parallel to the applied stress. We connect these observations to previous work showing an enhanced superconducting transition temperature under uniaxial stress, providing insight into how CDW, superconductivity, nematicity, and structure are related and can be tuned relative to one another in cuprates.
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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".