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Record W3128438128 · doi:10.7566/jpsj.90.034705

Revisiting the <sup>63</sup>Cu NMR Signature of Charge Order in La<sub>1.875</sub>Ba<sub>0.125</sub>CuO<sub>4</sub>

2021· article· en· W3128438128 on OpenAlexafffund
Takashi Imai, Philip M. Singer, A. Larry Arsenault, M. Fujita

Bibliographic record

VenueJournal of the Physical Society of Japan · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsMcMaster University
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsCharge orderingCharge (physics)Condensed matter physicsOrder (exchange)Lattice (music)Relaxation (psychology)Spin–lattice relaxationSpin (aerodynamics)Nuclear magnetic resonanceQuantum mechanicsNuclear quadrupole resonanceThermodynamics

Abstract

fetched live from OpenAlex

We use single crystal $^{63}$Cu NMR techniques to revisit the early $^{63}$Cu NQR signature of charge order observed for La$_{1.875}$Ba$_{0.125}$CuO$_{4}$ ($T_{\text{c}} =4$~K) [A. W. Hunt et al., Phys. Rev. Lett. {\bf 82}, 4300 (1999)]. We show that the growth of spin correlations is accelerated below $\sim 80$~K, where the inverse Laplace transform (ILT) T$_{1}$ analysis of the $^{139}$La NMR spin-lattice relaxation curve recently uncovered emergence of the slow components in the lattice and/or charge fluctuations [P. M. Singer et al., {\bf 101}, 174508 (2020)]. From the accurate measurements of the $^{63}$Cu NMR signal intensity, spin echo decay $M(2\tau)$, spin-lattice relaxation rate $^{63}1/T_1$, and its density distribution function $P(^{63}1/T_{1})$, we also demonstrate that charge order at $T_{\text{charge}}\simeq 54$~K turns on strong enhancement of spin fluctuations {\it within charge ordered domains}, thereby making the CuO$_2$ planes extremely inhomogeneous. The charge ordered domains grow quickly below $T_{\text{charge}}$, and the volume fraction $F_{\text{CA}}$ of the canonical domains unaffected by charge order gradually diminishes by $\sim 35$~K. This finding agrees with our independent estimations of $F_{\text{CA}}$ based entirely on the $^{139}$La ILTT$_{1}$ analyses, but is in a stark contrast with much slower growth of charge ordered domains observed for La$_{1.885}$Sr$_{0.115}$CuO$_{4}$ from its $T_{\text{charge}}\simeq 80$~K to $T_{\text{c}}\simeq 30$~K.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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 teacher head, not a consensus.

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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

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