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Record W2886520910 · doi:10.1002/adma.201802902

Ionic Modulation of the Interfacial Magnetism in a Bilayer System Comprising a Heavy Metal and a Magnetic Insulator for Voltage‐Tunable Spintronic Devices

2018· article· en· W2886520910 on OpenAlexafffund
Mengmeng Guan, Lei Wang, Shishun Zhao, Ziyao Zhou, Guohua Dong, Wei Su, Tai Min, Jing Ma, Zhongqiang Hu, Wei Ren, Zuo‐Guang Ye, Ce‐Wen Nan, Ming Liu

Bibliographic record

VenueAdvanced Materials · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMultiferroics and related materials
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Shaanxi ProvinceNational Natural Science Foundation of China
KeywordsSpintronicsMaterials scienceYttrium iron garnetSpin pumpingMagnetismBilayerFerromagnetismCondensed matter physicsHeterojunctionIonic bondingOptoelectronicsSpin polarizationSpin Hall effectElectronPhysics

Abstract

fetched live from OpenAlex

The voltage modulation of yttrium iron garnet (YIG) is of practical and theoretical significance; due to its advantages of compactness, high-speed response, and energy efficiency, it can be used for various spintronic applications, including spin-Hall, spin-pumping, and spin-Seebeck effects. In this study, a significant ferromagnetic resonance change is achieved within the YIG/Pt bilayer heterostructures uisng ionic modulation, which is accomplished by modifying the interfacial magnetism in the deposited "capping" platinum layer. With a small voltage bias of 4.5 V, a large ferromagnetic field shift of 690 Oe is achieved in heterostructures of YIG (13 nm)/Pt (3 nm)/(ionic liquid, IL)/(Au capacitor). The remarkable magnetoelectric (ME) tunability comes from the additional and voltage-induced ferromagnetic ordering, caused by uncompensated d-orbital electrons in the Pt metal layer. Confirmed by first-principle calculations, this finding paves the way for novel voltage-tunable YIG-based 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 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 score0.000
Threshold uncertainty score0.002

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)0.0000.000

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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

Citations28
Published2018
Admission routes2
Has abstractyes

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