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Record W2165306314 · doi:10.1098/rspa.2014.0387

Magnetic phase transitions and magnetic entropy in the <i>XY</i> antiferromagnetic pyrochlores (Er <sub> 1− <i>x</i> </sub> Y <sub> <i>x</i> </sub> ) <sub>2</sub> Ti <sub>2</sub> O <sub>7</sub>

2014· article· en· W2165306314 on OpenAlexafffund
John Niven, Michel B. Johnson, Alex Bourque, Patrick Murray, David D. James, H. A. Dabkowska, B. D. Gaulin, Mary Anne White

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials ResearchDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityDivision of Materials ResearchMcMaster University
KeywordsHeat capacityAntiferromagnetismPhase transitionMaterials scienceMagnetic fieldPhysicsCondensed matter physicsThermodynamics

Abstract

fetched live from OpenAlex

We present the results of experimental determination of the heat capacity of the pyrochlore Er 2 Ti 2 O 7 as a function of temperature (0.35–300 K) and magnetic field (up to 9 T), and for magnetically diluted solid solutions of the general formula (Er 1− x Y x ) 2 Ti 2 O 7 ( x ≤0.471). On either doping or increase of magnetic field, or both, the Néel temperature first shifts to lower temperature until a critical point above which there is no well-defined transition but a Schottky-like anomaly associated with the splitting of the ground state Kramers doublet. By taking into account details of the lattice contribution to the heat capacity, we accurately isolate the magnetic contribution to the heat capacity and hence to the entropy. For pure Er 2 Ti 2 O 7 and for (Er 1− x Y x ) 2 Ti 2 O 7 , the magnetic entropy as a function of temperature evolves with two plateaus: the first at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>R</mml:mi> <mml:mi>ln</mml:mi> <mml:mo>⁡</mml:mo> <mml:mn>2</mml:mn> </mml:math> , and the other at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>R</mml:mi> <mml:mi>ln</mml:mi> <mml:mo>⁡</mml:mo> <mml:mn>16</mml:mn> </mml:math> . When a very high magnetic field is applied, the first plateau is washed out. The influence of dilution at low values is similar to the increase of magnetic field, as we show by examination of the critical temperature versus critical field curve in reduced terms.

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 categoriesMeta-epidemiology (narrow)
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 score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.201
Teacher spread0.195 · 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

Citations18
Published2014
Admission routes2
Has abstractyes

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