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Resonant X-Ray Scattering Studies of Charge Order in Cuprates

2016· article· en· W2178637078 on OpenAlexafffund
Riccardo Comin, A. Damascelli

Bibliographic record

VenueAnnual Review of Condensed Matter Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersKillam TrustsNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanadian Institute for Advanced Research
KeywordsCuprateScatteringCharge (physics)Order (exchange)Condensed matter physicsX-rayPhysicsMaterials scienceOpticsQuantum mechanicsDoping

Abstract

fetched live from OpenAlex

X-ray techniques have been used for more than a century to study the atomic and electronic structure in practically any type of material. The advent of correlated electron systems, in particular complex oxides, brought about new scientific challenges and opportunities for the advancement of conventional X-ray methods. In this context, the need for new approaches capable of selectively sensing new forms of orders involving all degrees of freedom—charge, orbital, spin, and lattice—paved the way for the emergence and success of resonant X-ray scattering, which has become an increasingly popular and powerful tool for the study of electronic ordering phenomena in solids. We review the recent resonant X-ray scattering breakthroughs in the copper oxide high-temperature superconductors, in particular regarding the phenomenon of charge order, a broken-symmetry state occurring when valence electrons self-organize into periodic structures. After a brief historical perspective on charge order, we outline the milestones in the development of resonant X-ray scattering as well as the basic theoretical formalism underlying its unique capabilities. The rest of the review focuses on the recent contributions of resonant scattering to the advancements in our description and understanding of charge order. To conclude, we propose a series of present and upcoming challenges and discuss the future outlook for this technique.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.300
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations390
Published2016
Admission routes2
Has abstractyes

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