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Record W2025986893 · doi:10.1143/jjap.50.028001

Preparation of Highly-Oriented Co<sub>2</sub>MnSi Films on a Non-Single-Crystalline Substrate Using a Titanium–Nitride Buffer Layer

2011· article· en· W2025986893 on OpenAlexfundno aff
Atsushi Sugihara, Yuya Sakuraba, Kay Yakushiji, Shinji Yuasa, Kōki Takanashi

Bibliographic record

VenueJapanese Journal of Applied Physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicHeusler alloys: electronic and magnetic properties
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDefence Research and Development Canada
KeywordsMaterials scienceCoercivityBuffer (optical fiber)NitrideLayer (electronics)Titanium nitrideTitaniumSubstrate (aquarium)Iron nitrideMagnetizationAnalytical Chemistry (journal)Composite materialMetallurgyChemistryCondensed matter physicsMagnetic field

Abstract

fetched live from OpenAlex

Highly-oriented titanium–nitride films were prepared on a non-single-crystalline substrate as a buffer layer of a Co2MnSi film. Co2MnSi films prepared on the titanium–nitride buffer layer showed a high (001)-orientation and at least a B2-ordered phase even for room temperature preparation. The magnetization curve of the Co2MnSi film annealed at 600 °C showed an extremely low coercivity of 1.4 Oe in addition to a high saturation magnetization, which indicated no interdiffusion between a Co2MnSi layer and a buffer layer. These results indicate that titanium nitride is a potential material for applications based on Co2MnSi.

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 head0.033
GPT teacher head0.252
Teacher spread0.219 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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Same venueJapanese Journal of Applied PhysicsSame topicHeusler alloys: electronic and magnetic propertiesFrench-language works237,207