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Record W3024211941 · doi:10.1103/physrevb.101.174508

<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi mathvariant="normal">La</mml:mi><mml:mprescripts/><mml:none/><mml:mn>139</mml:mn></mml:mmultiscripts></mml:math> NMR investigation of the interplay between lattice, charge, and spin dynamics in the charge-ordered high-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>T</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:math> cuprate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>La</mml:mi><mml:mrow><mml:mn>1.875</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mi>Ba</mml:mi><mml:mrow><mml:mn>0.125</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mi>CuO</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:mrow></mml:math>

2020· article· lv· W3024211941 on OpenAlexafffund
Philip M. Singer, A. Larry Arsenault, Takashi Imai, M. Fujita

Bibliographic record

VenuePhysical review. B./Physical review. B · 2020
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsCharge (physics)InverseLattice (music)Condensed matter physicsCrystallographyCombinatoricsQuantum mechanicsChemistryMathematicsGeometry

Abstract

fetched live from OpenAlex

We investigate the interplay between the lattice, charge, and spin dynamics in charge-ordered high ${T}_{c}$ cuprate ${\mathrm{La}}_{1.875}{\mathrm{Ba}}_{0.125}{\mathrm{CuO}}_{4}\phantom{\rule{4pt}{0ex}}({T}_{c}=4\phantom{\rule{0.16em}{0ex}}\mathrm{K})$ based on the inverse Laplace transform (ILT) analysis of the $^{139}\mathrm{La}$ nuclear spin-lattice relaxation rate $1/{T}_{1}$ (dubbed ${\mathrm{ILTT}}_{1}$ analysis hereafter). A major thrust of the ${\mathrm{ILTT}}_{1}$ analysis is that one can deduce the probability density function $P(1/{T}_{1})$ of distributed $1/{T}_{1}$. We demonstrate that $1/{T}_{1}^{\text{lm}}$, defined as the log mean (i.e., the center of gravity on a logarithmic scale) of $P(1/{T}_{1})$, can be well approximated by $1/{T}_{1}^{\text{str}}$ deduced from the phenomenological stretched fit; however, $P(1/{T}_{1})$ can provide much richer insight into how the lattice, charge, and spin fluctuations and their distribution develop near and below the long-range charge order at ${T}_{\text{charge}}\ensuremath{\sim}54\phantom{\rule{0.16em}{0ex}}\mathrm{K}$. Upon entering the charge-ordered state, a divergent increase of $1/{T}_{1}^{\text{lm}}$ toward the spin ordering at ${T}_{\text{spin}}^{\ensuremath{\mu}\text{SR}}\ensuremath{\simeq}35\phantom{\rule{0.16em}{0ex}}\mathrm{K}$ is accompanied by an asymmetric broadening of $P(1/{T}_{1})$. Even deep inside the charge-ordered state, $1/{T}_{1}$ at a gradually diminishing fraction of $^{139}\mathrm{La}$ sites continues to slow down as temperature is lowered, as expected for canonical superconducting ${\mathrm{CuO}}_{2}$ planes without enhanced spin fluctuations. The fraction of such canonical $^{139}\mathrm{La}$ sites almost disappears by $\ensuremath{\simeq}40\phantom{\rule{0.16em}{0ex}}\mathrm{K}$. In contrast, nearly half of the $^{139}\mathrm{La}$ sites in ${\mathrm{La}}_{1.885}{\mathrm{Sr}}_{0.115}{\mathrm{CuO}}_{4}\phantom{\rule{4pt}{0ex}}({T}_{\text{charge}}\ensuremath{\simeq}80\phantom{\rule{0.16em}{0ex}}\mathrm{K})$ still exhibit the canonical behavior without enhanced spin fluctuations even near its ${T}_{c}=31\phantom{\rule{0.16em}{0ex}}\mathrm{K}$. These contrasting behaviors explain why superconductivity in ${\mathrm{La}}_{1.875}{\mathrm{Ba}}_{0.125}{\mathrm{CuO}}_{4}$ is more strongly suppressed than in ${\mathrm{La}}_{1.885}{\mathrm{Sr}}_{0.115}{\mathrm{CuO}}_{4}$ despite the lower onset temperature of the charge order.

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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0040.008
Meta-epidemiology (broad)0.0020.009
Bibliometrics0.0020.006
Science and technology studies0.0060.008
Scholarly communication0.0060.008
Open science0.0110.010
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.4190.009

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 head0.022
GPT teacher head0.265
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

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

Citations34
Published2020
Admission routes2
Has abstractyes

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