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Record W2996540673 · doi:10.1021/acsanm.9b02055

Stacking-Dependent Interlayer Magnetic Coupling in 2D CrI <sub>3</sub> /CrGeTe <sub>3</sub> Nanostructures for Spintronics

2019· article· en· W2996540673 on OpenAlexaff
Jing Shang, Xiao Tang, Aijun Du, Ting Liao, Sean C. Smith, Yuantong Gu, Chun Li, Liangzhi Kou

Bibliographic record

VenueACS Applied Nano Materials · 2019
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Manitoba
FundersNational Cancer InstituteAustralian Research CouncilQueensland University of TechnologyNational Computational Infrastructure
KeywordsSpintronicsCondensed matter physicsStackingHeterojunctionMaterials scienceFerromagnetismFerrimagnetismCoupling (piping)Inductive couplingMagnetic domainMagnetic fieldPhysicsMagnetizationNuclear magnetic resonanceQuantum mechanics

Abstract

fetched live from OpenAlex

The recent emergence of two-dimensional (2D) materials with intrinsic long-range magnetic order opens the avenue of fundamental physics studies and the spintronics application; however, the mechanism of interlayer magnetic coupling and the feasible way to control magnetic states are yet to be fully investigated. In the present study, from first-principle calculations, we studied the interlayer magnetic coupling of 2D CrI3/CrGeTe3 heterostructures and revealed the stacking-dependent magnetic states. It is found that AB and AB1 stacking are prefer ferromagnetic interlayer coupling, while the other two stacked configurations are in the ferrimagnetic state. The underlying mechanism has contributed to the competition between nearest-neighbor (NN) and second-nearest-neighbor (SNN) Cr–Cr atoms interaction between layers. Meanwhile, it is also found that the electronic properties are stacking dependent, while the band edge states are separated to the different layers. The magnetic and electronic states can be effectively tuned by the external strain. Based on these findings, the magnetic domain devices are proposed in the twisted magnetic heterostructures with the domain size and interlayer coupling being controlled by the rotation angle. Our study thus provides an approach to achieve the controllable magnetic/electronic properties which is not only important for fundamental research but also useful for the practical applications in 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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.

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

Citations64
Published2019
Admission routes1
Has abstractyes

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