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Record W2588422802 · doi:10.1021/acs.inorgchem.6b02912

Synthetic Approach for (Mn,Fe)<sub>2</sub>(Si,P) Magnetocaloric Materials: Purity, Structural, Magnetic, and Magnetocaloric Properties

2017· article· en· W2588422802 on OpenAlexafffund
Allan He, Volodymyr Svitlyk, Yurij Mozharivskyj

Bibliographic record

VenueInorganic Chemistry · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMagnetic refrigerationChemistryCurie temperatureMagnetizationAnnealing (glass)SynchrotronDiffractionMagnetic hysteresisCondensed matter physicsCrystallographyAnalytical Chemistry (journal)ThermodynamicsMetallurgyFerromagnetismMaterials scienceMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

A conventional solid-state approach has been developed for the synthesis of phase-pure magnetocaloric Mn 2– x Fe x Si 0.5 P 0.5 materials ( x = 0.6, 0.7, 0.8, 0.9). Annealing at high temperatures followed by dwelling at lower temperatures is essential to obtain pure samples with x = 0.7, 0.8, and 0.9. Structural features of the samples with x = 0.6 and 0.9 were analyzed as a function of temperature via synchrotron powder diffraction. The Curie temperature, temperature hysteresis, and magnetic entropy change were established from the magnetic measurements. According to the diffraction and magnetization data, all samples undergo a first-order magnetostructural transition, but the first-order nature becomes less pronounced for samples that are more Mn rich.

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), Scholarly communication, Insufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.201
Teacher spread0.188 · 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 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

Citations41
Published2017
Admission routes2
Has abstractyes

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