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Record W2804057796 · doi:10.1103/physrevb.98.104434

Spin gaps in the ordered states of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>La</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mi>Li</mml:mi><mml:mi>X</mml:mi><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>6</mml:mn></mml:msub><mml:mspace width="0.28em"/><mml:mrow><mml:mo>(</mml:mo><mml:mi>X</mml:mi><mml:mo>=</mml:mo><mml:mi>Ru</mml:mi><mml:mo>,</mml:mo><mml:mi>Os</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math> and their relation to the distortion of the cubic double perovskite structure in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>4</mml:mn><mml:msup><mml:mi>d</mml:mi><mml:mn>3</mml:mn></mml:msup></mml:mrow></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>5</mml:mn><mml:msup><mml:mi>d</mml:mi><mml:mn>3</mml:mn></mml:msup></mml:mrow></mml:math> magnets

2018· article· lv· W2804057796 on OpenAlexafffund
Dalini Maharaj, Gabriele Sala, Casey Marjerrison, M. B. Stone, John E. Greedan, B. D. Gaulin

Bibliographic record

VenuePhysical review. B./Physical review. B · 2018
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsCanadian Institute for Advanced ResearchBrockhouse Institute for Materials ResearchMcMaster University
FundersOak Ridge National LaboratoryMcMaster UniversityNatural Sciences and Engineering Research Council of CanadaBasic Energy SciencesAspen Center for PhysicsU.S. Department of EnergyNational Science Foundation
KeywordsInelastic neutron scatteringPhysicsMonoclinic crystal systemCrystallographyCondensed matter physicsSpin (aerodynamics)Energy (signal processing)ScatteringInelastic scatteringCrystal structureChemistryQuantum mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Time-of-flight inelastic neutron scattering measurements have been carried out on polycrystalline samples of the $4{d}^{3}$ and $5{d}^{3}$ double pervoskite antiferromagnets ${\mathrm{La}}_{2}{\mathrm{LiRuO}}_{6}$ and ${\mathrm{La}}_{2}{\mathrm{LiOsO}}_{6}$. These reveal the development of an inelastic spin gap in ${\mathrm{La}}_{2}{\mathrm{LiRuO}}_{6}$ and ${\mathrm{La}}_{2}{\mathrm{LiOsO}}_{6}$ of $\ensuremath{\sim}1.8(8)$ and 6(1) meV, below their respective ordering temperatures ${T}_{N},\phantom{\rule{0.28em}{0ex}}\ensuremath{\sim}23.8$ and 30 K. The bandwidths of the spin excitations are shown to be $\ensuremath{\sim}5.7(9)\phantom{\rule{0.28em}{0ex}}\text{and}\phantom{\rule{0.28em}{0ex}}12(1)\phantom{\rule{0.28em}{0ex}}\mathrm{meV}$, respectively, at low temperatures. Spin gaps are surprising in such magnets as the ${t}_{2g}$ levels of ${\mathrm{Ru}}^{5+}$ or ${\mathrm{Os}}^{5+}$ are expected to be half-filled, resulting in an anticipated orbital singlet for both materials. We compare these results in monoclinic double perovskites ${\mathrm{La}}_{2}{\mathrm{LiRuO}}_{6}$ and ${\mathrm{La}}_{2}{\mathrm{LiOsO}}_{6}$ with those in cubic ${\mathrm{Ba}}_{2}{\mathrm{YRuO}}_{6}$ and ${\mathrm{Ba}}_{2}{\mathrm{YOsO}}_{6}$ as well as with those in other monoclinic ${\mathrm{La}}_{2}{\mathrm{NaRuO}}_{6},\phantom{\rule{0.28em}{0ex}}{\mathrm{La}}_{2}{\mathrm{NaOsO}}_{6}$, and ${\mathrm{Sr}}_{2}{\mathrm{ScOsO}}_{6}$ and model the inelastic magnetic scattering with linear spin-wave theory using minimal anisotropic exchange interactions. We discuss the possible role of the distortion of the face-centered-cubic double perovskite structure on the spin gap formation and geometric frustration in these materials and show that ${T}_{N}$ scales with the top of the spin-wave band in all members of these families that display long-range 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)0.009
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), 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 score0.879
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0060.010
Meta-epidemiology (broad)0.0020.011
Bibliometrics0.0030.008
Science and technology studies0.0080.010
Scholarly communication0.0070.008
Open science0.0120.012
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.4070.008

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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

Citations11
Published2018
Admission routes2
Has abstractyes

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