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Record W4415152437 · doi:10.1063/5.0294721

Orbitronic terahertz emission from Mo-based nanolayers via the inverse orbital Hall and Rashba–Edelstein effects

2025· article· en· W4415152437 on OpenAlexafffund
Basem Y. Shahriar, A. Y. Elezzabi

Bibliographic record

VenueApplied Physics Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTerahertz radiationHeterojunctionSemiconductorSpin (aerodynamics)InverseSpin Hall effectFerromagnetism

Abstract

fetched live from OpenAlex

Rapid advancements in the communications and semiconductor industries have brought about the need to move to higher operating frequencies, with the terahertz (THz) frequency band being prospected as the next frontier for wireless communications and data transfer. Recent work has established that it is possible to harness orbital currents to generate THz radiation from metallic heterostructures comprised of ferromagnetic and transition metals. We demonstrate THz emission from Co/Mo/SiO2 and Co/Au/Mo/SiO2 orbitronic THz emitters (OTEs) via the inverse orbital Hall effect and the inverse orbital Rashba–Edelstein effect and measure the velocity of orbital carriers in Mo. Given the interplay between the various spin and orbital effects in OTEs that allow for interconversions between spin and orbital torque simply by the introduction of nm-thick metallic films, such devices hold significant potential in paving the way for the steady march away from conventional charge-based electronics in the decades to come.

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 score0.001
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)0.0010.000

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 head0.003
GPT teacher head0.182
Teacher spread0.179 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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