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Record W2055201801 · doi:10.1073/pnas.1200743109

Magnetostriction and magnetic texture to 100.75 Tesla in frustrated SrCu <sub>2</sub> (BO <sub>3</sub> ) <sub>2</sub>

2012· article· en· W2055201801 on OpenAlexaff
M. Jaime, Ramzy Daou, S. A. Crooker, Franziska Weickert, Atsuko Uchida, Adrian Feiguin, Cristian D. Batista, H. A. Dabkowska, B. D. Gaulin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
Fundersnot available
KeywordsFrustrationCondensed matter physicsAntiferromagnetismMagnetostrictionMagnetic fieldSaturation (graph theory)Plateau (mathematics)MagnetizationPhysicsDensity matrix renormalization groupMagnetMagnetic refrigerationMagnetic structureRenormalization groupQuantum mechanics

Abstract

fetched live from OpenAlex

Strong geometrical frustration in magnets leads to exotic states such as spin liquids, spin supersolids, and complex magnetic textures. SrCu 2 (BO 3 ) 2 , a spin-1/2 Heisenberg antiferromagnet in the archetypical Shastry–Sutherland lattice, exhibits a rich spectrum of magnetization plateaus and stripe-like magnetic textures in applied fields. The structure of these plateaus is still highly controversial due to the intrinsic complexity associated with frustration and competing length scales. We discover magnetic textures in SrCu 2 (BO 3 ) 2 via magnetostriction and magnetocaloric measurements in fields up to 100.75 T. In addition to observing low-field fine structure with unprecedented resolution, the data also reveal lattice responses at 73.6 T and at 82 T that we attribute, using a controlled density matrix renormalization group approach, to a unanticipated 2/5 plateau and to the long-predicted 1/2 plateau.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.256
Teacher spread0.233 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations147
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPhysics of Superconductivity and MagnetismFrench-language works237,207