Quantifying the hole distribution in cuprates: Atomic‐resolution near‐edge fine‐structures of the superconductor <scp>Sr3Ca11Cu24O41</scp>
Bibliographic record
Abstract
Sr 14‐x Ca x Cu 24 O 41 is a fascinating member in the family of cuprates, not only because of its peculiar crystal structure where two distinct units, corner‐shared CuO 2 chains and edge‐shared Cu 2 O 3 ladders, coexist within the unit cell but also because it is the only known superconductor with a non two‐dimensional CuO 2 plane structure. Indeed, the superconducting state theoretically predicted by E. Dagotto and T.M. Rice [1] was first observed experimentally in Sr 0.4 Ca 13.6 Cu 24 O 41.84 below T c = 12 K and for pressures starting from 3 GPa [2]. Independently of the Ca composition, Sr 14‐x Ca x Cu 24 O 41 is an intrinsically hole‐doped compound with 6 holes per formula unit, leading to an average Cu valence of +2.25. A central issue for understanding the mechanisms leading to superconductivity in this compound is therefore to measure accurately the carrier distribution among CuO 2 chains and Cu 2 O 3 ladders. This task has been undertaken shortly after the discovery of superconductivity in this system [3] but is still a matter of intense debate due to the very scattered nature of the results. For instance, depending on the technique, reported hole concentrations in the ladder layers of Sr 3 Ca 11 Cu 24 O 41 vary from ~1 to ~4.5 holes/formula unit [4,5]. All these results have been obtained with techniques that have a relatively poor spatial resolution ranging from several hundred nanometers to a few micrometers. In this work, we exploit the unmatched spatial‐resolution of STEM‐EELS to measure local hole concentration in superconducting Sr 3 Ca 11 Cu 24 O 41 at the atomic scale and provide, for the first time, a real‐space measurement where spatial separation between chains and ladders is achieved [6]. As shown by F.C. Zhang and T.M. Rice [7], in doped cuprates, the hole strongly binds to the four O atoms surrounding the central Cu through Cu 3d ‐O 2p in‐plane sigma hybridization within the CuO 4 plaquettes. As such, the local hole concentration can be monitored very efficiently through the O‐K pre‐edge structures as shown in Figure 1. These experimental results, combined with inelastic scattering calculations, demonstrate unambiguously that holes lie preferentially within the CuO 2 chains of the structure. In summary, this work illustrates how the combination of near‐edge fine‐structure analyses with atomic resolution in the aberration corrected STEM can improve the understanding of the electronic properties of complex oxides, such as Cu‐based superconductors [8].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".