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Record W2767649148 · doi:10.1063/1.4995644

Driving higher magnetic field sensitivity of the martensitic transformation in MnCoGe ferromagnet

2017· article· en· W2767649148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Letters · 2017
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsDiffusionless transformationCondensed matter physicsMagnetic refrigerationFerromagnetismMetamagnetismMaterials scienceMagnetic shape-memory alloyMagnetizationMagnetic fieldMartensiteField (mathematics)Magnetic domainMetallurgyPhysicsMicrostructure

Abstract

fetched live from OpenAlex

The sharp metamagnetic martensitic transformation (MMT) triggered by a low critical field plays a pivotal role in magnetoresponsive effects for ferromagnetic shape memory alloys (FSMAs). Here, a sharper magnetic-field-induced metamagnetic martensitic transformation (MFIMMT) is realized in Mn1−xCo1+xGe systems with a giant magnetocaloric effect around room temperature, which represents the lowest magnetic driving and completion fields as well as the largest magnetization difference around MFIMMT reported heretofore in MnCoGe-based FSMAs. More interestingly, a reversible MFIMMT with field cycling is observed in the Mn0.965Co0.035Ge compound. These results indicate that the consensus would be broken that the magnetic field is difficult to trigger the MMT for MnCoGe-based systems. The origin of a higher degree of sensitivity of martensitic transformation to the magnetic field is discussed based on the X-ray absorption spectroscopic results.

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.

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 score0.158
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.224
Teacher spread0.210 · 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