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Record W4319078009 · doi:10.1063/9.0000408

Constituent contribution to the magnetocrystalline anisotropy in Mn(Al1−xGax)

2023· article· en· W4319078009 on OpenAlexafffund
Xubo Liu, D. H. Ryan, Z. Altounian

Bibliographic record

VenueAIP Advances · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties of Alloys
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsMagnetocrystalline anisotropyTetragonal crystal systemMagnetic anisotropyCondensed matter physicsMaterials scienceCoercivityThermal stabilityMagnetic momentFormula unitAnisotropyAnisotropy energyPhase (matter)Nuclear magnetic resonanceChemistryCrystallographyMagnetic fieldMagnetizationCrystal structurePhysics

Abstract

fetched live from OpenAlex

The phase stability and magnetocrystalline anisotropy (MCA) of tetragonal Mn(Al1−xGax) with the L10-type structure (P4/mmm) has been studied using first-principles density functional calculations. The calculated decomposition energy indicates that partial replacement of Al by Ga suppresses the formation of Mn5(Al,Ga)8 and enhances the thermal stability of the L10 phase while the total magnetic moment per formula unit (f.u.) remains almost unchanged. The site- and atomic-resolved MCA calculations show that the MCA energy (MAE) comes mainly from the Mn atoms, and the total MAE increases from 0.25 meV/f.u. (x = 0) to 0.34 meV/f.u (x = 1). Spin resolved MCA and band structure calculations indicate that the high MCA is mainly due to spin flipping behavior near Fermi level. The derived effective magnetic anisotropy field increases from 37 kOe (x = 0) to 46 kOe (x = 1), in agreement with experiments. Doping with Ga improves the thermal stability of the L10 structure and enhances the magnetic anisotropy field, which facilitates developing high coercivity Mn-Al magnets.

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 score0.003
Threshold uncertainty score0.006

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)0.0020.000

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 head0.253
Teacher spread0.243 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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Same venueAIP AdvancesSame topicMagnetic Properties of AlloysFrench-language works237,207