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Record W2981618080 · doi:10.1063/1.5116549

Spin transport in an insulating ferrimagnetic-antiferromagnetic-ferrimagnetic trilayer as a function of temperature

2019· article· en· W2981618080 on OpenAlexfundno aff
Yizhang Chen, Egecan Cogulu, Debangsu Roy, Jinjun Ding, Jamileh Beik Mohammadi, Paul G. Kotula, Nancy A. Missert, Mingzhong Wu, Andrew D. Kent

Bibliographic record

VenueAIP Advances · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsnot available
FundersDivision of Materials ResearchDivision of Electrical, Communications and Cyber SystemsMaterials Research Science and Engineering Center, Harvard UniversitySandia National LaboratoriesU.S. Department of EnergyGordon and Betty Moore FoundationYork UniversityNational Nuclear Security AdministrationNational Science Foundation
KeywordsFerrimagnetismYttrium iron garnetCondensed matter physicsMaterials scienceAntiferromagnetismSpin Hall effectMagnetizationAtmospheric temperature rangeParamagnetismSpin (aerodynamics)Spin polarizationMagnetic fieldPhysicsElectron

Abstract

fetched live from OpenAlex

We present a study of the transport properties of thermally generated spin currents in an insulating ferrimagnetic-antiferromagnetic-ferrimagnetic trilayer over a wide range of temperature. Spin currents generated by the spin Seebeck effect (SSE) in a yttrium iron garnet (YIG) YIG/NiO/YIG trilayer on a gadolinium gallium garnet (GGG) substrate were detected using the inverse spin Hall effect (ISHE) in Pt. By studying samples with different NiO thicknesses, the spin diffusion length of NiO was determined to be ∼3.8 nm at room temperature. Surprisingly, a large increase of the SSE signal was observed below 30 K, and the field dependence of the signal closely follows a Brillouin function for an S=7/2 spin. The increase of the SSE signal at low temperatures could thus be associated with the paramagnetic SSE from the GGG substrate. Besides, a broad peak in the SSE response was observed around 100 K. These observations are important in understanding the generation and transport properties of spin currents through magnetic insulators and the role of a paramagnetic substrate in spin current generation.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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