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Record W2317537083 · doi:10.1103/physrevb.87.014427

Mapping the domain wall pinning profile by stochastic imaging reconstruction

2013· article· en· W2317537083 on OpenAlexaff
Wanjun Jiang, Yabin Fan, Pramey Upadhyaya, Murong Lang, Minsheng Wang, Li‐Te Chang, Kin Wong, Jianshi Tang, M. Lewis, Jing Zhao, Liang He, Xufeng Kou, Caifu Zeng, Xuezhi Zhou, Robert N. Schwartz, Kang L. Wang

Bibliographic record

VenuePhysical Review B · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSpintronicsCondensed matter physicsYttrium iron garnetMaterials scienceDomain wall (magnetism)MicroscopyPinning forceDomain (mathematical analysis)Field (mathematics)YttriumMagnetic domainFerromagnetismMagnetic fieldPhysicsOpticsMagnetizationCritical currentQuantum mechanics

Abstract

fetched live from OpenAlex

Polar magneto-optical Kerr effect microscopy and subsequent stochastic imaging reconstruction have been used to map out the distinct pinning profiles of randomly distributed intrinsic defects (pointlike/linelike), as well as their dependence on the external magnetic field in 2-\ensuremath{\mu}m-thick yttrium iron garnet films. A comparison of the pinning profiles produced by these intrinsic defects and the extrinsic defects (made by focused ion beam lithography) has also been made. In addition, we have found a linear dependence of the pinning potentials on the depths of the fabricated pointlike defects. Our observations should provide a fundamental understanding of the role of defects in domain wall spintronics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score1.000

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)0.0020.001

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 head0.011
GPT teacher head0.235
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations10
Published2013
Admission routes1
Has abstractyes

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