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Record W2006349383 · doi:10.1103/physrevb.90.214433

Nonmonotonic residual entropy in diluted spin ice: A comparison between Monte Carlo simulations of diluted dipolar spin ice models and experimental results

2014· article· en· W2006349383 on OpenAlexafffund
T. Lin, Xianglin Ke, Mischa Thesberg, P. Schiffer, Roger G. Melko, Michel J. P. Gingras

Bibliographic record

VenuePhysical Review B · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsCanadian Institute for Advanced ResearchPerimeter InstituteMcMaster UniversityUniversity of Waterloo
FundersOak Ridge National LaboratoryNatural Sciences and Engineering Research Council of CanadaIndustry CanadaCanada Foundation for InnovationOntario Ministry of Economic Development and InnovationCanada Research ChairsGovernment of CanadaNational Science Foundation
KeywordsSpin iceResidual entropyMonte Carlo methodStatistical physicsResidualDipolePhysicsMaterials scienceCondensed matter physicsConfiguration entropyMathematicsStatisticsQuantum mechanics

Abstract

fetched live from OpenAlex

Spin ice materials, such as ${\mathrm{Dy}}_{2}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$ and ${\mathrm{Ho}}_{2}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$, are highly frustrated magnetic systems. Their low-temperature strongly correlated state can be mapped onto the proton disordered state of common water ice. As a result, spin ices display the same low-temperature residual Pauling entropy as water ice, at least in calorimetric experiments that are equilibrated over moderately long-time scales. It was found in a previous study [X. Ke et al., Phys. Rev. Lett. 99, 137203 (2007)] that, upon dilution of the magnetic rare-earth ions (${\mathrm{Dy}}^{3+}$ and ${\mathrm{Ho}}^{3+}$) by nonmagnetic yttrium (${\mathrm{Y}}^{3+}$) ions, the residual entropy depends nonmonotonically on the concentration of ${\mathrm{Y}}^{3+}$ ions. A quantitative description of the magnetic specific heat of site-diluted spin ice materials can be viewed as a further test aimed at validating the microscopic Hamiltonian description of these systems. In this work, we report results from Monte Carlo simulations of site-diluted microscopic dipolar spin ice models (DSIM) that account quantitatively for the experimental specific-heat measurements, and thus also for the residual entropy, as a function of dilution, for both ${\mathrm{Dy}}_{2\ensuremath{-}x}{\mathrm{Y}}_{x}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$ and ${\mathrm{Ho}}_{2\ensuremath{-}x}{\mathrm{Y}}_{x}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$. The main features of the dilution physics displayed by the magnetic specific-heat data are quantitatively captured by the diluted DSIM up to 85% of the magnetic ions diluted ($x=1.7$). The previously reported departures in the residual entropy between ${\mathrm{Dy}}_{2\ensuremath{-}x}{\mathrm{Y}}_{x}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$ versus ${\mathrm{Ho}}_{2\ensuremath{-}x}{\mathrm{Y}}_{x}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$, as well as with a site-dilution variant of Pauling's approximation, are thus rationalized through the site-diluted DSIM. We find for 90% ($x=1.8$) and 95% ($x=1.9$) of the magnetic ions diluted in ${\mathrm{Dy}}_{2\ensuremath{-}x}{\mathrm{Y}}_{x}{\mathrm{Ti}}_{2}{\mathrm{O}}_{7}$ a significant discrepancy between the experimental and Monte Carlo specific-heat results. We discuss possible reasons for this disagreement.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.350
Teacher spread0.324 · 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 designSimulation or modeling
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

Citations20
Published2014
Admission routes2
Has abstractyes

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