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Record W2010731592 · doi:10.1063/1.4794132

Using different Mn-oxides to influence the magnetic anisotropy of FePt in bilayers with little change of the exchange bias field

2013· article· en· W2010731592 on OpenAlexaff
Ko‐Wei Lin, Chin Shueh, C.-H. Liu, Elizabeth Skoropata, Teresa Wu, J. van Lierop

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsExchange biasBilayerMagnetizationMaterials scienceCondensed matter physicsOxideLayer (electronics)CoercivityCoupling (piping)Magnetic anisotropyFerromagnetismAnisotropyAnalytical Chemistry (journal)Magnetic fieldChemistryMetallurgyNanotechnologyMembrane

Abstract

fetched live from OpenAlex

We have investigated the exchange coupling between a bottom FePt thin film layer capped with different Mn-oxides. Results have shown that the magnetization reversal of the soft FePt layer is influenced strongly by the capped Mn-oxide layer (Mn, MnO, and Mn3O4), as revealed by the enhanced coercivities. Typical temperature dependent magnetization between zero-field cooled (ZFC) and field cooled (FC) scans was observed in the Mn-oxide (8%O2/Ar)/FePt bilayer that exhibited a blocking temperature (TB ∼ 120 K) close to the Nèel temperature, TN, of MnO. However, the Mn/FePt bilayer exhibited unusual temperature dependent of M vs. T, implying that intermixing between Mn and FePt interfaces formed an AF FeMn that may have enabled a high irreversibility temperature (Tirr. ∼ 400 K) compared to almost identical ZFC and FC curves from weaker exchange coupling between FePt and the Mn3O4 created with 21 and 30%O2/Ar deposition conditions.

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)0.000
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 score0.100
Threshold uncertainty score0.295

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 head0.034
GPT teacher head0.234
Teacher spread0.200 · 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.

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
Published2013
Admission routes1
Has abstractyes

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