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Record W2038672301 · doi:10.1063/1.4795627

Enhancement of ferromagnetism by Cr doping in Ni-Mn-Cr-Sb Heusler alloys

2013· article· en· W2038672301 on OpenAlexaff
Mahmud Khan, Igor Dubenko, Shane Stadler, Jieun Jung, Stanislav S. Stoyko, Arthur Mar, Abdiel Quetz, Tapas Samanta, Naushad Ali, K. H. Chow

Bibliographic record

VenueApplied Physics Letters · 2013
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsUniversity of Alberta
FundersU.S. Department of Energy
KeywordsFerromagnetismCondensed matter physicsMaterials scienceMagnetoresistanceMagnetizationElectrical resistivity and conductivityDopingMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

A series of Mn rich Ni50Mn37−xCrxSb13 Heusler alloys have been investigated by dc magnetization and electrical resistivity measurements. Due to the weakening of the Ni-Mn hybridization, the martensitic transition shifts to lower temperatures with increasing Cr concentration, while the saturation magnetization at 5 K increases. The magnetoresistance and exchange bias properties are dramatically suppressed with increasing Cr concentration. The observed behaviors suggest that substitution of Cr for Mn in Ni50Mn37−xCrxSb13 Heusler alloys not only destabilizes the martensitic phase but also enhances ferromagnetism in the system. The possible mechanisms responsible for the observed behavior are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.216
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations50
Published2013
Admission routes1
Has abstractyes

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