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Record W1621295472 · doi:10.1063/1.2829758

Magnetocaloric effect in Co-rich Er(Co1−xFex)2 Laves phase

2008· article· en· W1621295472 on OpenAlexaff
Xubo Liu, Z. Altounian

Bibliographic record

VenueJournal of Applied Physics · 2008
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsMagnetic refrigerationMagnetic momentCondensed matter physicsLaves phaseMagnetizationMetastabilityMaterials scienceMagnetic fieldFerromagnetismChemistryPhysicsIntermetallicMetallurgy

Abstract

fetched live from OpenAlex

Magnetic properties and magnetocaloric effect (MCE) in Co rich Er(Co1−xFex)2 have been studied by magnetic measurements and electronic structure calculations. With increasing x from 0 to 0.2, TC increases from 32to360K and the magnetization decreases from 6.8μB to 5.3μB per formula unit (5K), respectively. The peak value of the magnetic entropy change decreases rapidly from 23.0to4.5J∕kgK (under an external field change of 5T) with increasing x from 0 to 0.1. The addition of a small amount of Fe in ErCo2 drives the order of magnetic transition from first order to second order, as evidenced by the magnetothermal curves around TC, which is responsible for the decrease in MCE. The magnetic moment dependence of total energy Et(m) is studied by a fixed spin moment band structure calculation. Et(m) for x=0 has two minima at a low and a high Co magnetic moment, which correspond to a metastable and a stable magnetic state, respectively. On the other hand, Et(m) for x=0.125 shows only one minimum at a high Co (Fe) magnetic moment. These fixed spin moment calculation results explain the observed change in the order of magnetic transition by the addition of Fe in ErCo2.

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 categoriesnone
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 score0.011
Threshold uncertainty score0.913

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)0.0010.000

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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2008
Admission routes1
Has abstractyes

Explore more

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